6 Commits

Author SHA1 Message Date
chihlasm
0bda590537 fix: use get_admin_db for all new admin account endpoints
All admin endpoints query across tenants without a tenant context.
get_db (app-role, subject to RLS) was never imported and would crash
at runtime — replace all 6 occurrences with get_admin_db (BYPASSRLS).

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-13 07:47:42 +00:00
chihlasm
2dbb8b6abf refactor: design critique fixes for account pages
- Admin accounts: replace dense card grid with compact DataTable
- Account settings: remove redundant hero card, stat grid, header pills
- Fix bg-accent (orange) misuse on decorative elements across 7 files
- Add ConfirmButton for destructive actions (deactivate, remove member)
- Replace single-field modals with inline editing (plan, trial)
- Add contextual help: display code tooltip, improved empty states
- Non-owner aside explanation for hidden owner-only sections
- Admin sidebar: group 11 items into 5 labeled sections
- Rename UsersPage.tsx → AccountsPage.tsx to match route
- Fix border radius consistency, hide zero-count badges

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-12 04:54:26 +00:00
chihlasm
9452e5d408 fix: remove unused admin account icon import 2026-04-12 04:54:26 +00:00
chihlasm
e002fe4969 feat: add admin account detail management 2026-04-12 04:54:26 +00:00
chihlasm
7cbc9fe224 feat: expand admin customer account controls 2026-04-12 04:54:26 +00:00
chihlasm
70242ad037 feat: reorganize admin panel around accounts 2026-04-12 04:54:26 +00:00
222 changed files with 1297 additions and 44936 deletions

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# CURRENT_TASK.md
**Task:** none — replace this file when starting the next real task.
**Status:** not-started
**Definition of Done:** n/a
**Assumptions:** n/a
**Out of scope:** n/a
---
<!-- When you start a real task, replace the block above with:
**Task:** One-sentence goal.
**Status:** not-started | in-progress | blocked | ready-for-review | complete
**Definition of Done:**
- [ ] Testable criterion 1
- [ ] Testable criterion 2
- [ ] Tests added or updated
- [ ] `npm run build` passes (frontend) / `pytest` passes (backend)
**Assumptions:**
- What we're treating as given
**Out of scope:**
- What this task explicitly does NOT cover
-->

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# DECISIONS.md
> Append-only architectural decision log. Newest entries at the top.
> Entry format:
>
> ```
> ## YYYY-MM-DD — <short title>
> **Context:** why this came up
> **Decision:** what we chose
> **Rejected:** what we didn't choose and why
> **Consequences:** what this means going forward
> ```
---
## 2026-04-24 — Adopt dual-agent handoff system (`.ai/` + `CLAUDE.md` + `AGENTS.md`)
**Context:** Claude Code hits session and weekly usage limits. Work stalls when the primary agent is locked out. Needed a structured way for OpenAI Codex to resume where Claude left off without losing architectural truth or drifting across sessions.
**Decision:** Split the old CLAUDE.md into `.ai/PROJECT_CONTEXT.md` (stable repo truth), agent-specific root files (`CLAUDE.md`, `AGENTS.md`) with a shared protocol block, and a small handoff toolkit (`CURRENT_TASK.md`, `HANDOFF.md`, `TODO.md`, `DECISIONS.md`, `SESSION_LOG.md`, `README.md`). Previous CLAUDE.md snapshotted in commit `e110fed` before the migration.
**Rejected:**
- Single symlinked CLAUDE.md/AGENTS.md — diverges silently, hides agent-specific tooling differences.
- Putting GitNexus/gstack content in AGENTS.md — Codex doesn't have those tools; would mislead the resume agent.
- Keeping the old CLAUDE.md as-is and adding AGENTS.md alongside it — duplicated truth, drift guaranteed.
**Consequences:**
- First read for either agent: `.ai/PROJECT_CONTEXT.md` + `.ai/CURRENT_TASK.md` + `.ai/HANDOFF.md`.
- Architectural changes in the repo require updating PROJECT_CONTEXT.md, not the root agent files.
- Git trailers differ per agent (`Claude Opus 4.7` vs `Codex`) — preserved in each root file.
- Legacy `SESSION-HANDOFF.md` deleted in the same commit; superseded by `.ai/HANDOFF.md`.

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<!-- Keep under ~2K tokens. Old handoffs live in SESSION_LOG.md. Do not let this file accumulate history. -->
# HANDOFF.md
**Last updated:** 2026-04-24 (America/New_York)
**Active task:** None — see [CURRENT_TASK.md](CURRENT_TASK.md). Replace it when picking up the next real task.
**Branch:** `feat/flowpilot-migration` — a long-running FlowPilot Phase 9 feature branch. The recent AI-handoff migration commits ride on this branch (not on their own branch); they'll merge to `main` whenever Phase 9 does.
**Branch state:** 3 commits ahead of `origin/feat/flowpilot-migration`:
- `b3be1e0 chore: ignore .remember/ skill runtime state`
- `b3506b5 docs(pilot): phase 9 review issues`
- `b14a16a chore(tests): gate RLS tests behind RUN_RLS_TESTS flag`
Earlier in this session (already pushed to origin):
- `9c8ba29 fix(ai): correct stale role-hierarchy and file-listing claims`
- `bee8690 chore(ai): migrate to dual-agent handoff system`
- `e110fed chore: snapshot CLAUDE.md before ai-handoff migration` (tag: `pre-ai-handoff`)
**Where I left off:**
- File: n/a — nothing mid-edit.
- Next intended action: push the 3 unpushed commits when ready (`git push`), then start the next real task (replace `CURRENT_TASK.md`, update this file).
**Uncommitted state:**
- Working tree is clean.
**Immediate next steps:**
1. `git push` to publish the 3 local commits (cleanup batch).
2. When starting the next real feature task: replace `CURRENT_TASK.md` with actual goal/DoD, rewrite this file's resume section.
**Open questions / blockers:**
- None. The dual-agent handoff system is live and has survived one Codex review round (see DECISIONS.md 2026-04-24 entry; corrections in `9c8ba29`).

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# PROJECT_CONTEXT.md — ResolutionFlow
> SaaS troubleshooting platform for MSPs. Stable architectural truth. Updated only when the repo's shape changes.
---
## Product & naming
Canonical product name is **ResolutionFlow**. `patherly` is the legacy internal name — still present in DB name (`patherly` on Railway, `resolutionflow` locally), some Railway service names, and historical paths. Treat as aliases, not canonical. Docker containers are `resolutionflow_*`.
**User terminology:** "Flows" (not Trees), "Projects" (not Procedures), "Solutions Library" (not Step Library). Maintenance flows hidden from pilot UI (backend retains them). DB column `tree_type` values unchanged.
---
## SaaS shape
Multi-tenant by account. Primary role hierarchy: `super_admin` > `owner` > `engineer` > `viewer` — driven by `is_super_admin` + `account_role`. Never `role=='admin'` — use `is_super_admin`. Separate team-scoped admin gate exists orthogonally to the role hierarchy: `is_team_admin=True` + valid `team_id`, enforced by `require_team_admin`. Backend deps in `app/api/deps.py`: `get_current_active_user`, `require_engineer_or_admin`, `require_admin`, `require_account_owner`, `require_team_admin`. Frontend: `usePermissions()` hook. Central logic in `backend/app/core/permissions.py` + `frontend/src/hooks/usePermissions.ts`.
---
## Status
Go-to-Market Validation (pre-PMF). Backend feature-complete (55+ endpoints, 100+ tests). Phase 0.5 FlowPilot telemetry baseline accruing. See [CURRENT-STATE.md](../CURRENT-STATE.md) for live status, [03-DEVELOPMENT-ROADMAP.md](../03-DEVELOPMENT-ROADMAP.md) for phases.
---
## Tech stack
- **Backend:** Python 3.11 + FastAPI, SQLAlchemy 2.0 async (asyncpg), Alembic, Pydantic v2, JWT (python-jose + bcrypt, JTI refresh rotation), APScheduler (in-process with FastAPI lifespan).
- **Frontend:** React 19 + Vite + TypeScript, Tailwind v4 (CSS-only config in `index.css`), Zustand (immer + zundo), React Router v7, Axios (token-refresh interceptor), Lucide.
- **DB:** PostgreSQL 16 (RLS enabled Phase 4, pgvector).
---
## Project structure
```
resolutionflow/
├── backend/
│ ├── app/
│ │ ├── main.py # FastAPI entry
│ │ ├── api/endpoints/ # 50+ routers registered in api/router.py — auth/admin, trees/sessions, AI/chat, scripts, integrations, uploads, accounts, FlowPilot, etc.
│ │ ├── api/deps.py # auth deps (incl. require_team_admin)
│ │ ├── api/router.py # registration
│ │ ├── core/ # config, database, permissions, security, audit, rate_limit
│ │ ├── models/ # SQLAlchemy (incl. FlowProposal)
│ │ ├── schemas/ # Pydantic
│ │ ├── services/psa/ # PSA provider pattern (base, connectwise/, autotask/, halopsa/, cache, encryption, exceptions, registry, ticket_context, types)
│ │ ├── services/knowledge_flywheel.py + _scheduler.py
│ │ └── services/knowledge_gap_service.py
│ ├── alembic/versions/ # 001-070 sequential, then hex hash
│ ├── scripts/ # seed_data, seed_trees, seed_test_users
│ └── tests/ # pytest integration
├── frontend/
│ ├── src/
│ │ ├── api/ # Axios client + endpoint modules
│ │ ├── components/ # common, layout, dashboard, tree-editor, session, procedural, procedural-editor, library, step-library, ui, flowpilot
│ │ ├── hooks/ # usePermissions, useSessionTimer, useKeyboardShortcuts
│ │ ├── pages/
│ │ ├── store/ # Zustand (auth, treeEditor, proceduralEditor, userPreferences, scriptGeneratorStore)
│ │ └── types/
│ └── (Tailwind v4 CSS-only config in src/index.css)
├── docs/plans/archive/ # pre-March 2026 plans
├── docs/connectwise/ # CW API reference + best-practices guides
├── docs/LESSONS-ARCHIVE.md # archived lessons (fixes in code)
├── .ai/ # dual-agent handoff system (see .ai/README.md)
├── CLAUDE.md · AGENTS.md · CURRENT-STATE.md · DESIGN-SYSTEM.md · DEV-ENV.md
```
---
## Dev commands
Full setup in [DEV-ENV.md](../DEV-ENV.md) (host-agnostic, with homelab Proxmox reference topology). Day-to-day:
```bash
docker compose -f docker-compose.dev.yml up -d # start stack
cd backend && source venv/bin/activate && uvicorn app.main:app --reload
cd frontend && npm run dev
pytest --override-ini="addopts=" # tests (first time: CREATE DATABASE resolutionflow_test)
cd backend && alembic upgrade head # migrate
cd backend && alembic revision -m "desc" # manual migration (preferred per Lesson 77)
cd backend && alembic revision --autogenerate -m "desc" # picks up drift; review carefully
cd frontend && npm run build # stricter than tsc --noEmit — final check
cd frontend && npx tsc -b # TS-only check when dist/ has EACCES
docker exec -it resolutionflow_postgres psql -U postgres -d resolutionflow
python -m scripts.seed_trees # seed (from backend/)
```
**Never pass `--rev-id`** to alembic — let it generate the hex hash.
---
## URLs & test users
**URLs:** Frontend <http://localhost:5173>, backend <http://localhost:8000>, API docs <http://localhost:8000/api/docs>.
**Test users** (all password `TestPass123!`): `admin@resolutionflow.example.com` (super_admin), `teamadmin@resolutionflow.example.com`, `engineer@resolutionflow.example.com`, `pro@resolutionflow.example.com`.
---
## CI
Gitea (`gitea.resolutionflow.com/chihlasm/resolutionflow/actions`). `gh` CLI works for issues/PRs on the GitHub mirror, but not CI runs.
---
## Deployment (Railway)
- **Prod:** `resolutionflow.com` (frontend), `api.resolutionflow.com` (backend).
- Auto-deploy: Gitea push → GitHub mirror → Railway follows GitHub `main`.
- PR environments auto-created; need manual domain generation + `VITE_API_URL` with `https://` prefix.
- `ALLOW_RAILWAY_ORIGINS=true` for `*.up.railway.app` CORS.
- Shared Variables (Railway project-level) auto-propagate to PR envs — use for secrets like `ANTHROPIC_API_KEY`.
- Super admin utility: `backend/make_superadmin_simple.py list|<email>`.
---
## ConnectWise PSA
Reference: `docs/connectwise/` — start with `CONNECTWISE-API-REFERENCE.md`, then the `best-practices/` guides. Extracted OpenAPI spec in `connectwise-psa-resolutionflow-reference.json` (670 endpoints, v2025.16); full spec in `connectwise-psa-openapi-full.json`.
- **Auth:** API Key (Base64 `companyId+publicKey:privateKey`) + `clientId` header every request. `clientId` is server-side (`CW_CLIENT_ID` in `config.py`) — identifies ResolutionFlow, not per-tenant. Per-connection: `company_id`, `public_key`, `private_key`, `server_url`.
- **Architecture:** `services/psa/` provider pattern — `PSAProvider` base, `ConnectWiseProvider` impl, `PsaProviderRegistry` for multi-PSA dispatch. Credentials encrypted at rest via `services/psa/encryption.py` (Fernet). Per-team credentials, never per-user. Endpoints in `api/endpoints/integrations.py`. In-memory TTL cache in `services/psa/cache.py`.
- **Integration flows:** session docs → ticket notes (`POST /service/tickets/{id}/notes`, markdown supported); ticket context → FlowPilot; callbacks via `/system/callbacks` with HMAC verification.
- **API rules:** pin version via Accept header `application/vnd.connectwise.com+json; version=2025.16`. Paginate ≤1000/page. Dynamic base URL via `/login/companyinfo/{companyId}`. Request minimal permissions (MY, not ALL).
---
## Coding standards
- **Python:** type hints everywhere, async/await for DB, Pydantic v2, `DateTime(timezone=True)` always.
- **TypeScript:** interfaces for all data, `const` over `let`, functional components + hooks, shared logic in custom hooks.
- **Git:** feature branch before committing (`git checkout -b feat/feature-name`). Commit format: `type: description` (feat/fix/refactor/docs/test/chore). Large features: commit per phase with `npm run build` validation. Push to Gitea — auto-mirrors to GitHub (`.gitea/workflows/mirror-to-github.yml`); never push GitHub directly. (Agent-specific `Co-Authored-By` trailers live in CLAUDE.md / AGENTS.md.)
**After shipping:** update [CURRENT-STATE.md](../CURRENT-STATE.md) + [03-DEVELOPMENT-ROADMAP.md](../03-DEVELOPMENT-ROADMAP.md), `gh issue close #N` for resolved issues, add lessons only for non-obvious traps (otherwise let the code speak).
---
## Common tasks
- **New endpoint:** `endpoints/``router.py``schemas/` → tests → frontend API client.
- **New page:** `pages/` → route in `router.tsx` → nav in `AppLayout.tsx`.
- **New public route:** top-level in `router.tsx` alongside `/login`, not inside `ProtectedRoute`.
- **New frontend API module:** types in `types/` → export from `types/index.ts` → client in `api/` → export from `api/index.ts`.
- **Schema change:** update model → `alembic revision -m "desc"` → review → `alembic upgrade head`.
- **New `VITE_*` env var:** add as `ARG` + `ENV` in `frontend/Dockerfile` for Railway builds (Lesson 60 — Railway env vars are runtime-only, Vite bakes at build time).
- **Account sub-page:** add route in `router.tsx` under `account` children + add link card in `AccountSettingsPage.tsx``AccountLayout` has NO sidebar nav.
---
## Design system
**Source of truth: [DESIGN-SYSTEM.md](../DESIGN-SYSTEM.md).** Read before any visual change.
- Flat high-contrast dark theme, Sentry/PostHog-inspired. **No** glass, backdrop blur, ambient orbs, gradient surfaces.
- Accent **electric blue** (#60a5fa dark / #2563eb light) — ≤5% of UI, interactive elements only. Warning amber (#fbbf24), info cyan (#67e8f9), success green (#34d399), danger red (#f87171). Each with `-dim` at 10% opacity.
- Backgrounds: `bg-sidebar` (#0e1016) → `bg-page` (#16181f) → `bg-card` (#1e2028) → `bg-elevated` (#2a2d38). Borders `border-default` / `border-hover`.
- Text: `text-heading``text-primary``text-muted-foreground``text-muted`.
- Fonts: IBM Plex Sans (body), Bricolage Grotesque (heading, 700 weight for logo), JetBrains Mono (code).
- Logo: 30px gradient square (ember orange) + "ResolutionFlow" in Bricolage Grotesque. Assets in `brand-assets/`, `frontend/src/assets/brand/`, `frontend/public/icons/`.
- Mockups: `docs/mockups/` (HTML).
- **Deprecated — do not use:** glass-card, glass-stat, `bg-gradient-brand`, `backdrop-filter: blur()`, ambient orbs, purple gradients, ember orange as accent, cyan as accent (cyan is info only).
---
## Frontend patterns
- **Component basics:** `cn()` from `@/lib/utils`, Lucide icons, `Modal.tsx` for modals (mobile-responsive `items-end sm:items-center` + `max-w-full sm:max-w-lg`).
- **Types:** Create in `types/`, export from `types/index.ts`, `import type { T } from '@/types'`.
- **Routing:** `getTreeNavigatePath()` / `getTreeEditorPath()` from `@/lib/routing`. Tree editor is `/trees/new`. All dashboard session clicks → `/pilot/:id` regardless of `session_type`.
- **Lazy routes:** `lazyWithRetry` from `@/lib/lazyWithRetry.ts`, not `React.lazy` (auto-reload on stale chunks).
- **Public pages:** raw `fetch()` with full URL, NOT `apiClient` (which requires auth tokens).
- **Toast:** `toast.warning()` not `toast.warn()`. Import from `@/lib/toast` — methods: `success`, `error`, `warning`, `info`.
- **Assistant chat:** uses local React `useState`, not Zustand. All three send paths (`handleSend`, `sendPrefill`, `handleResumeNew`) must call `setShowTaskLane(true)` when response has actions/questions.
- **Chat backend wiring:** `aiSessionsApi.sendChatMessage``/ai-sessions/{id}/chat``unified_chat_service.py`. NOT `assistant_chat_service.py` (removed except retention settings).
- **FlowPilot:** Actions live in page header (Resolve/Escalate/Share Update + overflow). `useBlocker` for active-session nav guard. "Pause & Leave" auto-pauses.
- **AI markers:** `[QUESTIONS]`, `[ACTIONS]`, `[FORK]`, `[DELTA]...[/DELTA]` (editor), `[TREE_UPDATE]` (troubleshooting builder), `[STEPS_UPDATE]` (procedural builder), `[METADATA]`. Parsed in `unified_chat_service.py`; conversation history stores stripped `display_content`. If markers disappear: check system-prompt final reminder + per-user-message `[SYSTEM: ...]` injection in `_call_anthropic_cached()`.
- **Image uploads:** paste/attach → Railway S3 via `uploadsApi.upload()` → resized by `storage_service.resize_image_for_vision()` (Pillow, 1568px max, PNG→JPEG) → base64 → Claude multimodal blocks. Max 3/msg. Images NOT stored in history.
- **Async select-load-apply:** guard with a ref (pattern in `AssistantChatPage` `currentChatRef`). Update synchronously on every selection change; after every `await`, bail out if `ref.current !== thisId`.
- **Editor-Embedded Flow Assist:** `EditorAIPanel` (320px side panel) + `useEditorAI`. Ghost nodes via `_suggestion: true`. Route actions via `settings.get_model_for_action()`.
- **Script Builder:** `/script-builder`, chat-style. Backend `ScriptBuilderSession`, `script_builder_service.py`, endpoints `/scripts/builder/`. FlowPilot handoff via `action_type: "open_script_builder"` + `sessionStorage`.
- **Intake form field schema:** `variable_name` + `field_type` (NOT `name` / `type`).
- **Node field priority** (copilot, summaries): `title``question``description``content``label`.
- **Procedural sessions auto-start** on page load (no intake/Start screen). Troubleshooting flows DO have a start screen.
---
## Critical lessons
> Lessons 1-40 archived to [docs/LESSONS-ARCHIVE.md](../docs/LESSONS-ARCHIVE.md) — fixes baked into the codebase. **Grep the archive when an error message or symptom is unfamiliar, or after two failed attempts at resolving an issue.** Don't pre-load for routine work.
### Backend / data
- **APScheduler interval jobs always `max_instances=1`** — without it, overlapping runs reprocess records (TOCTOU).
- **`get_db` rolls back on exception** — never remove the `await session.rollback()`, or one failed request poisons the connection with `InFailedSQLTransaction` cascading.
- **Startup routines on tenant-isolated tables must use `_admin_session_factory()`, not `get_db()`.** Phase 4 RLS has no `app.current_account_id` set at startup. `get_service_account_id` is safe (reads cached `app.state`).
- **Backfill migrations adding `account_id`:** grep ALL `ModelClass(` sites in service code to verify `account_id=` is passed. SQLAlchemy accepts `None` silently — Phase 4 RLS WITH CHECK surfaces the problem at runtime as `InsufficientPrivilegeError: new row violates row-level security policy`.
- **`tree_shares.account_id = tree.account_id`**, never `current_user.account_id`. A super_admin sharing another tenant's tree must produce the share in the tree owner's tenant, or it becomes invisible post-RLS.
- **Global tables (no `account_id`, never in RLS migrations):** `script_categories`, `platform_steps`, `template_trees`, `plan_feature_defaults`, `accounts`. Scan at class level — one `.py` file can hold multiple classes with different columns (e.g. `ScriptCategory` vs `ScriptTemplate`).
- **`ai_sessions.status` is VARCHAR(30)** — fits `requesting_escalation` (23 chars). Migration `f0aad74ea51b` widened from 20.
- **PostgreSQL `func.sum(case(...))` returns `Decimal` via asyncpg** — cast to `int()` before Pydantic `dict[str, Any]`.
- **Enhancement / branch_addition proposals need `modified_flow_data` via "Edit & Publish"** — backend 400 on direct approve. Only `new_flow` supports direct approve.
- **Adding email types:** static async method on `EmailService` in `core/email.py`. Fire-and-forget from endpoints (log errors, don't fail the request).
### AI / FlowPilot
- **Anthropic SDK `max_retries=1`** — default of 2 can take 3× the timeout.
- **Model tier routing:** `settings.get_model_for_action(action_type)`. Always alias form (`claude-sonnet-4-6`).
- **FlowPilot must ask GUI-vs-script before suggesting either** when both are viable — see `FLOWPILOT_SYSTEM_PROMPT` in `flowpilot_engine.py`.
- **Telemetry events to grep:** `anthropic.cache` (prompt-cache hit/create), `mcp.turn` (per-turn MCP availability), `mcp.fallback` (MCP silent-retry fired).
- **Don't put literal payloads in system prompts.** Bit us twice in one day: a worked `[QUESTIONS]` example with literal "Outlook + jsmith" content, and a full DNS troubleshooting tree, both caused Claude to recite that content on unrelated tickets — the symptom looked like task-lane state leaking across chats. The fix is structural: every output example in a system prompt uses `<placeholder>` syntax (`{"text": "<one short, specific question>"}`), never literal field values. Real-looking format examples live in few-shot messages (separate file, separate code path), not system prompts. Guardrail: `tests/test_prompt_anti_parrot.py` scans every `*_PROMPT`/`*_SCHEMA`/`*_PROTOCOL`/`*_FORMAT` constant in `app/services/` and `app/core/`; CI fails when a marker block contains a literal JSON value or when a known leaked token (jsmith, DC01, ADSync, Dnscache, etc.) appears anywhere in a prompt.
### Frontend / UI
- **Flex height chain:** every ancestor from `app-shell` grid to React Flow canvas needs `flex` + `flex-1` + `min-h-0` or `h-full`. Missing `flex` collapses to 0. Same rule for FlowPilot action bar and any tall scroller.
- **React Flow CSS in Tailwind v4:** import in `index.css`, not component JS. Override dark theme via `--xy-*` CSS vars.
- **`text-secondary` renders invisible on dark** — Tailwind v4 maps it to `--color-secondary` (a surface color). Use `text-muted-foreground` for readable secondary text. Avoid `text-muted` for body — labels only.
- **`bg-accent` is electric blue — never for code/kbd.** Use `bg-white/[0.12] border border-white/[0.06]` for inline code, `bg-white/[0.08]` for kbd. Accent reserved for interactive elements.
- **`landing.css` uses self-contained `--lp-*` vars** — never `var(--color-*)` theme tokens (they resolve incorrectly outside the app shell).
- **Never `transition: all`** — list properties explicitly, or layout props animate and jank.
- **Date range filter end dates:** `setHours(23, 59, 59, 999)` before sending, or the day's items are excluded. For string-based date inputs, append `T23:59:59.999Z`.
- **TopBar search:** full bar `hidden sm:block`, icon button `sm:hidden` — both open CommandPalette.
- **Hover pop-out cards:** scrim `pointer-events-none`, expanded card has its own click handler at `z-50`, dismiss via `onMouseLeave` on wrapper. Never put handlers on the scrim.
- **`tsc -b` in Dockerfile is stricter than `tsc --noEmit`** — enforces `noUnusedLocals` / `noUnusedParameters` as hard errors. Check IDE yellow squiggles before pushing.
- **Dashboard prefill auto-submits** via `useEffect` + `prefillHandledRef` guard — no double-enter.
- **Global Axios 5xx interceptor fires before component `.catch()`** — fix optional-data endpoints at the source (return `[]` / `{}` on provider failure), not in the component.
- **Playwright strict mode:** scope selectors to avoid sidebar/main ambiguity. Use `getByRole('heading', { name })` or `.animate-scale-in` locators, not bare `getByText()`.
### Env / infra
- **Node 20.19+ required** (Vite 7). `nvm use 20` or `PATH="$HOME/.nvm/versions/node/v20.19.0/bin:$PATH"`.
- **Railway backend service is `patherly`, DB name `railway`.** Public Postgres proxy: `interchange.proxy.rlwy.net:45797`.
- **Railway Object Storage bucket `resolutionflow-uploads`.** Env vars `STORAGE_*`. boto3 in `storage_service.py`. Dockerfile needs Pillow + `libjpeg-dev` / `zlib1g-dev`.
- **PostHog:** `PostHogProvider` + `posthog.init()` in `main.tsx`. Helpers in `lib/analytics.ts`. Env: `VITE_PUBLIC_POSTHOG_KEY`, `VITE_PUBLIC_POSTHOG_HOST`. `identifyUser()` in `authStore.fetchUser()`, `resetAnalytics()` on logout.
- **bun PATH on devserver01:** `BUN_INSTALL="$HOME/.bun"`, `PATH="$BUN_INSTALL/bin:$PATH"`. Playwright Chromium needs `libatk1.0-0 libatk-bridge2.0-0 libcups2 libxkbcommon0 libatspi2.0-0 libxcomposite1 libxdamage1 libxfixes3 libxrandr2 libgbm1 libasound2`.
- **Full-stack change:** trace schema → endpoint → API client → hook → store → UI. Don't assume one end proves the other.
- **Dev env** — see [DEV-ENV.md](../DEV-ENV.md) for current topology, `REPO_ROOT` requirement when compose runs inside a container, Vite `allowedHosts`, linuxserver.io `group_add` + custom-cont-init.d workaround, `docker compose up` no-op-on-unchanged-hash gotcha.
---
## Quick reference
| What | Where |
|---|---|
| Detailed status | [CURRENT-STATE.md](../CURRENT-STATE.md) |
| Roadmap | [03-DEVELOPMENT-ROADMAP.md](../03-DEVELOPMENT-ROADMAP.md) |
| Design system | [DESIGN-SYSTEM.md](../DESIGN-SYSTEM.md) |
| Dev env | [DEV-ENV.md](../DEV-ENV.md) |
| Archived lessons | [docs/LESSONS-ARCHIVE.md](../docs/LESSONS-ARCHIVE.md) |
| ConnectWise API | `docs/connectwise/` |
| GitHub issues | `gh issue list --state open` |
| Local API docs | <http://localhost:8000/api/docs> |
| Handoff system | [.ai/README.md](README.md) |

View File

@@ -1,42 +0,0 @@
# .ai/ — dual-agent handoff system
ResolutionFlow uses two coding agents: **Claude Code** (primary) and **OpenAI Codex** (resume when Claude hits session or weekly limits). This directory holds the shared state that lets either agent start a session with full context.
## Files
| File | Holds | Written when | Read when |
|---|---|---|---|
| [PROJECT_CONTEXT.md](PROJECT_CONTEXT.md) | Stable repo truth: stack, structure, SaaS shape, ConnectWise, coding standards, frontend patterns, critical lessons | Only when the repo's shape changes | Every session start |
| [CURRENT_TASK.md](CURRENT_TASK.md) | The single active task: goal, DoD, assumptions, out-of-scope | On task start; status updates during work | Every session start |
| [HANDOFF.md](HANDOFF.md) | Exact resume point: branch, where you left off, next steps, blockers | On session end / context-window limit | Every session start (most important) |
| [TODO.md](TODO.md) | Backlog of work NOT currently active | When deferring or queueing work | Only when `CURRENT_TASK.md` is `complete` |
| [DECISIONS.md](DECISIONS.md) | Append-only architectural decision log | When an architectural choice is made | Skim top entries each session |
| [SESSION_LOG.md](SESSION_LOG.md) | Append-only chronological history | On session end | Only when broader context is needed |
Agent-specific tooling lives at the repo root:
- [../CLAUDE.md](../CLAUDE.md) — Claude Code's tooling (GitNexus, gstack slash commands, Claude trailer)
- [../AGENTS.md](../AGENTS.md) — OpenAI Codex's tooling (grep/rg fallbacks, Codex trailer)
Both root files contain an **identical shared-protocol block**. If you edit one, edit the other.
## The handoff ritual
At session end (limit hit, task complete, or user stop): update `HANDOFF.md` to reflect the new resume point, update `CURRENT_TASK.md` status if it changed, append to `DECISIONS.md` if you made an architectural call, append a session entry to `SESSION_LOG.md`, and WIP-commit any dirty working tree with `wip(handoff): <one-line>` unless told otherwise. Don't push.
## How to invoke a resume
Tell the agent:
> Read CLAUDE.md (or AGENTS.md) and follow its instructions.
The agent will read its root file, which directs it to `.ai/PROJECT_CONTEXT.md`, `.ai/CURRENT_TASK.md`, and `.ai/HANDOFF.md` before doing anything else.
## Recovery
The previous monolithic CLAUDE.md is recoverable via:
```bash
git show pre-ai-handoff:CLAUDE.md
```
(Tag `pre-ai-handoff` on commit `e110fed` — the snapshot taken before this migration.)

View File

@@ -1,23 +0,0 @@
# SESSION_LOG.md
> Append-only chronological record. Newest entries at the top. Skim when broader context is needed.
> Entry format:
>
> ```
> ## YYYY-MM-DD HH:MM <timezone> — <agent> — <one-line summary>
> - What was accomplished
> - What was left for next session
> - Files touched
> ```
---
## 2026-04-24 — Claude Code — Migrate to dual-agent handoff system
- Split CLAUDE.md into `.ai/PROJECT_CONTEXT.md` + shared-protocol root files (`CLAUDE.md`, `AGENTS.md`).
- Seeded `CURRENT_TASK.md`, `HANDOFF.md`, `TODO.md`, `DECISIONS.md`, `SESSION_LOG.md`, `README.md`.
- Deleted legacy `SESSION-HANDOFF.md` (superseded).
- Left for next session: first real feature task should replace the seed `CURRENT_TASK.md` and update `HANDOFF.md` with real resume state.
- Files touched: `.ai/*.md` (created), `CLAUDE.md` (rewritten), `AGENTS.md` (created), `SESSION-HANDOFF.md` (deleted).
- Follow-up (same day): Codex review pass flagged stale SaaS-role claim and incomplete file-listings carried over from the pre-migration CLAUDE.md. Verified against `backend/app/core/permissions.py`, `frontend/src/hooks/usePermissions.ts`, `backend/app/api/deps.py`, `backend/app/api/router.py`, and `backend/app/services/psa/`. Corrected PROJECT_CONTEXT.md role hierarchy (`super_admin > owner > engineer > viewer`, not `team_admin`), added `require_account_owner` / `require_team_admin` to deps list, replaced stale endpoint comment with a summary pointing at `api/router.py`, added `exceptions.py` + `ticket_context.py` to the PSA file list. Also replaced seed-example content in `CURRENT_TASK.md` and `TODO.md` with clearer empty-state sentinels.
- Branch cleanup (same day): committed pending test-isolation work as `b14a16a chore(tests): gate RLS tests behind RUN_RLS_TESTS flag`, new Phase 9 review doc as `b3506b5 docs(pilot): phase 9 review issues`, and `.remember/` gitignore entry as `b3be1e0 chore: ignore .remember/ skill runtime state`. Deleted `docs/landing-handoff/` (prepared for external design work, not meant to live in the repo). Working tree clean; 3 cleanup commits unpushed.

View File

@@ -1,12 +0,0 @@
# TODO.md
> Backlog of work NOT currently active. Read only when `CURRENT_TASK.md` status is `complete`.
> Format: `- [ ] short description — optional link to issue/PR`
## Up next
- [ ] No queued backlog yet.
## Backlog
- [ ] No queued backlog yet.

View File

@@ -1,20 +0,0 @@
#!/bin/bash
# Block skill usage when gstack is not installed globally.
if [ ! -d "$HOME/.claude/skills/gstack/bin" ]; then
cat >&2 <<'MSG'
BLOCKED: gstack is not installed globally.
gstack is required for AI-assisted work in this repo.
Install it:
git clone --depth 1 https://github.com/garrytan/gstack.git ~/.claude/skills/gstack
cd ~/.claude/skills/gstack && ./setup --team
Then restart your AI coding tool.
MSG
echo '{"permissionDecision":"deny","message":"gstack is required but not installed. See stderr for install instructions."}'
exit 0
fi
echo '{}'

View File

@@ -1,15 +0,0 @@
{
"hooks": {
"PreToolUse": [
{
"matcher": "Skill",
"hooks": [
{
"type": "command",
"command": "\"$CLAUDE_PROJECT_DIR/.claude/hooks/check-gstack.sh\""
}
]
}
]
}
}

View File

@@ -1,154 +0,0 @@
name: CI
on:
push:
branches: [main]
pull_request:
branches: [main]
jobs:
backend:
runs-on: ubuntu-latest
services:
postgres:
image: pgvector/pgvector:pg16
env:
POSTGRES_USER: postgres
POSTGRES_PASSWORD: postgres
POSTGRES_DB: resolutionflow_test
ports:
- 5432:5432
options: >-
--health-cmd pg_isready
--health-interval 10s
--health-timeout 5s
--health-retries 5
env:
DATABASE_URL: postgresql+asyncpg://postgres:postgres@postgres:5432/resolutionflow_test
DATABASE_URL_SYNC: postgresql://postgres:postgres@postgres:5432/resolutionflow_test
SECRET_KEY: ci-test-secret-key-not-for-production
DEBUG: "true"
APP_NAME: ResolutionFlow
TEST_DB_NAME: resolutionflow_test
DB_APP_ROLE_PASSWORD: app_secret_ci
steps:
- uses: actions/checkout@v4
- name: Install dependencies
run: pip install --break-system-packages -r backend/requirements.txt -r backend/requirements-dev.txt
- name: Run Alembic migrations
run: cd backend && alembic upgrade head
- name: Check tenant filter enforcement
run: cd backend && python scripts/check_tenant_filters.py
- name: Run tests with coverage
run: cd backend && python -m pytest --override-ini="addopts=" --cov=app --cov-report=term-missing --cov-report=json:coverage.json --cov-fail-under=50
- name: Display coverage summary
if: always()
run: |
cd backend
python -c "
import json
with open('coverage.json') as f:
data = json.load(f)
total = data['totals']['percent_covered_display']
print(f'Total coverage: {total}%')
print()
print('Module coverage:')
for fname, fdata in sorted(data['files'].items()):
pct = fdata['summary']['percent_covered_display']
if float(pct) < 80:
print(f' WARNING {fname}: {pct}%')
else:
print(f' OK {fname}: {pct}%')
"
frontend:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Install dependencies
run: cd frontend && npm ci
- name: Lint
run: cd frontend && npm run lint
- name: Test with coverage
run: cd frontend && npm run test:coverage
- name: Build
run: cd frontend && NODE_OPTIONS="--max-old-space-size=4096" npm run build
- name: Upload build artifact
uses: actions/upload-artifact@v4
with:
name: frontend-dist
path: frontend/dist
retention-days: 1
e2e:
needs: [frontend]
runs-on: ubuntu-latest
services:
postgres:
image: pgvector/pgvector:pg16
env:
POSTGRES_USER: postgres
POSTGRES_PASSWORD: postgres
POSTGRES_DB: resolutionflow_test
ports:
- 5432:5432
options: >-
--health-cmd pg_isready
--health-interval 10s
--health-timeout 5s
--health-retries 5
env:
PLAYWRIGHT_DATABASE_URL: postgresql+asyncpg://postgres:postgres@postgres:5432/resolutionflow_test
PLAYWRIGHT_DATABASE_URL_SYNC: postgresql://postgres:postgres@postgres:5432/resolutionflow_test
PLAYWRIGHT_API_ORIGIN: http://127.0.0.1:8000
PLAYWRIGHT_BASE_URL: http://127.0.0.1:4173
PLAYWRIGHT_SECRET_KEY: ci-playwright-secret-key
PLAYWRIGHT_TEST_EMAIL: teamadmin@resolutionflow.example.com
PLAYWRIGHT_TEST_PASSWORD: TestPass123!
steps:
- uses: actions/checkout@v4
- name: Install backend dependencies
run: pip install --break-system-packages -r backend/requirements.txt -r backend/requirements-dev.txt
- name: Install frontend dependencies
run: cd frontend && npm ci
- name: Download frontend build
uses: actions/download-artifact@v4
with:
name: frontend-dist
path: frontend/dist
- name: Install Playwright browser
run: cd frontend && npx playwright install --with-deps chromium
- name: Run Playwright smoke tests
run: cd frontend && npm run test:e2e
- name: Upload Playwright report
if: always()
uses: actions/upload-artifact@v4
with:
name: playwright-report
path: |
frontend/playwright-report
frontend/test-results
if-no-files-found: ignore

View File

@@ -1,19 +0,0 @@
name: Mirror to GitHub
on:
push:
branches:
- '**'
jobs:
mirror:
runs-on: ubuntu-latest
steps:
- name: Push to GitHub
run: |
cd /tmp
git clone --mirror https://gitea.resolutionflow.com/chihlasm/resolutionflow.git repo
cd repo
git remote add github https://x-access-token:${{ secrets.GH_MIRROR_TOKEN }}@github.com/${{ secrets.GH_MIRROR_REPO }}
git push github --all --force
git push github --tags --force

View File

@@ -1,43 +0,0 @@
name: Runner Probe
on:
workflow_dispatch:
jobs:
probe:
runs-on: ubuntu-latest
steps:
- name: Runner labels and OS
run: |
echo "=== OS ==="
uname -a
cat /etc/os-release 2>/dev/null || true
- name: Python versions
run: |
echo "=== Python ==="
which python3 && python3 --version || echo "python3 not found"
which python && python --version || echo "python not found"
ls /usr/bin/python* 2>/dev/null || true
- name: Node versions
run: |
echo "=== Node ==="
which node && node --version || echo "node not found"
which npm && npm --version || echo "npm not found"
ls /usr/bin/node* 2>/dev/null || true
ls ~/.nvm/versions/node/ 2>/dev/null || echo "no nvm versions"
- name: Docker
run: |
echo "=== Docker ==="
which docker && docker --version || echo "docker not found"
docker info 2>/dev/null | grep -E "Server Version|Operating System" || true
- name: User and home
run: |
echo "=== User ==="
whoami
echo "HOME=$HOME"
echo "PATH=$PATH"

9
.gitignore vendored
View File

@@ -207,11 +207,7 @@ marimo/_lsp/
__marimo__/
# Claude Code (local config, agents, settings)
.claude/*
!.claude/settings.json
!.claude/hooks/
.claude/hooks/*
!.claude/hooks/check-gstack.sh
.claude/
.agents/
# Database dumps
@@ -242,6 +238,3 @@ package-lock.json
# graphify knowledge graph outputs
graphify-out/
.graphify_python
# remember skill runtime state (hook logs, PIDs)
.remember/

View File

@@ -1,61 +0,0 @@
# AGENTS.md — ResolutionFlow
You are OpenAI Codex, the resume agent for ResolutionFlow. Claude Code is the primary coding agent; you step in when Claude hits session or weekly limits.
The first thing to do every session: read [`.ai/PROJECT_CONTEXT.md`](.ai/PROJECT_CONTEXT.md), [`.ai/CURRENT_TASK.md`](.ai/CURRENT_TASK.md), and [`.ai/HANDOFF.md`](.ai/HANDOFF.md). The ritual is spelled out below.
> The protocol section below is byte-identical to the shared block in CLAUDE.md. If you edit one, edit the other.
## Shared protocol
### Startup ritual (every session)
1. Read `.ai/PROJECT_CONTEXT.md` — architectural truth for this repo.
2. Read `.ai/CURRENT_TASK.md` — what we're actively working on.
3. Read `.ai/HANDOFF.md` — exact resume point.
4. Skim `.ai/DECISIONS.md` for recent entries relevant to the current task.
5. Run `git log --oneline -15` and `git status`.
6. Before taking action, state back in two sentences: the current goal and your proposed next action.
### Handoff ritual (session end — limit hit, task complete, or user stop)
1. Update `.ai/HANDOFF.md` to reflect new state. Keep it under ~2K tokens.
2. If `CURRENT_TASK.md` status changed, update it.
3. If you made an architectural decision, append to `.ai/DECISIONS.md`.
4. Append a session entry to `.ai/SESSION_LOG.md`.
5. If working tree is dirty, commit WIP with `wip(handoff): <one-line summary>`. Do not push unless explicitly asked.
### Writing rules for .ai/ files
- Use model-neutral voice in `HANDOFF.md`, `SESSION_LOG.md`, `DECISIONS.md` ("previous session did X", NOT "Claude did X" or "Codex did X"). Exception: `SESSION_LOG.md` entries include an `<agent>` field in the header.
- Do not duplicate content between files. `CURRENT_TASK.md` holds the goal, `HANDOFF.md` holds the resume point, `TODO.md` holds the backlog. If unsure where something goes, check `.ai/README.md`.
- Don't invent facts about the repo. If you're uncertain, write `TODO: confirm` and flag it.
### Project principle
Prefer correct architecture over minimal diff. Flag "simpler approach" tradeoffs for review before taking them.
## Codex-specific notes
### Tooling you do NOT have
- **No GitNexus tools.** Use `grep -r`, `rg`, `git grep`, or `find` for code search. For blast-radius reasoning, grep call sites manually and read the files.
- **No gstack slash commands** (`/review`, `/ship`, `/qa`, `/browse`, `/investigate`, `/design-review`, `/plan-*`). Run the equivalent work directly: `pytest` for tests, `npm run build` for frontend validation, manual PR description for review flow.
- **No `/codex` second-opinion command.** You are Codex.
### Git trailer
Every commit: `Co-Authored-By: Codex <noreply@openai.com>`
### Model selection
Handled on OpenAI's side. Do not attempt to set Anthropic model aliases for your own runtime. (The repo's application code still uses Anthropic aliases like `claude-sonnet-4-6` via `settings.get_model_for_action()` — that's runtime config for the product, not your agent.)
### Reviewing Claude's work
When you resume from a Claude session, assume some decisions may have been informed by GitNexus queries or gstack commands whose output isn't in the handoff. If a decision looks unverified from the `.ai/` files alone, either:
- re-verify with `grep`/`rg`/file reads, or
- flag it in `HANDOFF.md` under "Open questions" so Michael or Claude can confirm on the next handoff.
Do not assume tooling output that isn't written down.

View File

@@ -2,30 +2,6 @@
All notable changes to ResolutionFlow are documented here.
## [0.1.0.0] - 2026-04-16
### Added
- **PSA Ticket Management** — dedicated `/tickets` page with URL-param filter state (board, status, priority, company, assignment, closed), paginated ticket list, and slide-in detail panel
- **TicketDetailPanel** — full ticket view with notes feed, configurations, related tickets, and resource manager; optimistic status updates via dropdown
- **NewTicketModal** — two-tab ticket creation: "Quick Create (AI)" parses natural language into a pre-filled form via Claude, "Full Form" for manual entry; validates required fields before submitting to CW
- **AiTicketParseForm** — natural language → structured ticket data using Claude; resolves board and assignee automatically, flags fields needing manual selection
- **TicketResourceManager** — add/remove CW members as ticket resources with member search autocomplete
- **Spin-off ticket creation from ResolutionAssist** — AI can detect when a new ticket should be created mid-session and surface the NewTicketModal pre-filled with session context
- **TicketQueue improvements** — dashboard widget now detects member mapping, caps at 5 items, shows "View All" link to `/tickets`
- **Board statuses endpoint** — `GET /integrations/boards/{board_id}/statuses` for direct status lookup without a ticket context
- **Paginated ticket search** — `search_tickets` returns `{items, total, page, page_size}`; parallel CW count fetch for accurate totals
- **Ticket service layer** — `ticket_service.py` wraps all PSA mutations (create, update status, list/add/remove resources)
- **Priority lookup endpoint** — `GET /integrations/tickets/priorities` for form dropdowns
- **PSA error surfacing** — `/tickets` page shows inline error banner with specific guidance when CW returns a permissions error (replaces silent empty state)
### Fixed
- CW query injection: sanitize search `query` string to strip single quotes before interpolation into CW conditions
- `company_id` filter now correctly applied to CW ticket search conditions (was silently ignored)
- `linkedTicket` fetch in ResolutionAssist guarded with `currentChatRef` to prevent race condition on session switch
- Members endpoint auth gate no longer rejects engineers without a PSA mapping
- Board fallback: ticket list derives available boards from ticket data when the boards API returns empty (permissions)
- Assignment search and "Load More" removed from resource manager in favor of direct member list
## [Unreleased]
### Added
@@ -35,7 +11,6 @@ All notable changes to ResolutionFlow are documented here.
- **Tenant Isolation Phase 0** — multi-tenant data isolation (#132) with app-layer filtering helpers (`tenant_filter()`, `get_tenant_context`), cross-tenant access audit (analytics, categories, AI sessions, trees), UUID endpoint isolation with 404 responses for unauthorized access, ownership checks on all sensitive operations, and CI grep gate for missing tenant filters
- **Tenant Isolation Phase 2** — PostgreSQL Row Level Security (RLS) on 11 session-related tables (ai_sessions, session_steps, session_tags, etc.), account_id NOT NULL enforcement on all write paths, Alembic migrations with dual-env support (Railway native vars + explicit DATABASE_URL_SYNC), RLS test coverage with cross-account isolation verification, migration CI/CD integration
- **Tenant Isolation Phase 3** — RLS on audit_logs and tree_shares tables, cross-tenant session access for public shares (via get_admin_db), complete account_id propagation across PSA integration write paths, final RLS policy enforcement
- **Tenant Isolation Phase 4** (#136) — RLS enforcement on all 31 remaining tables (users, trees, teams, integrations, scripts, categories, templates, surveys, etc.), BYPASSRLS session pattern for auth deps and background jobs, admin session factory for startup routines (service accounts, seed data), global table exclusions (platform_steps, template_trees, script_categories, accounts), RLS tests with complete cross-tenant isolation verification, proper tree_shares ownership checks using tree owner's account_id
- **Script Library default view** — "All Scripts" tab now displays all accessible scripts (team + library)
- **Session documentation overhaul** — reformatted PSA resolution/escalation notes with cleaner headers, inline engineer responses, decimal hour display (0.25 hrs), follow-up recommendations, and improved "What We Know" section from evidence items
- **Client communication improvements** — new `request_info` audience type for client-facing information requests, improved status update and email draft prompts with per-context guidance
@@ -58,7 +33,6 @@ All notable changes to ResolutionFlow are documented here.
- **Category tree counts** — cross-tenant row count leakage via tree_count field in GET `/categories/{id}`. Now scoped to requesting account.
- **PSA retry ownership check** — retry-psa-push had no ownership validation (CRITICAL). Now validates user ownership before allowing retry.
- **Task Lane save operation** — invalid task_lane_item UUIDs returned 403 revealing existence. Now returns 404 and uses query-level filtering.
- **Phase 4 RLS enforcement** — fixed auth deps, user-mutation endpoints, background jobs, and lifespan routines to use BYPASSRLS sessions for reading/writing tenant-isolated tables; fixed seed scripts to use ADMIN_DATABASE_URL; bootstrap service account now initializes correctly with proper BYPASSRLS context
- Dark text rendering on blue accent step-number badges across all flow types
- Script Library tab ownership filter now preserved across category and search changes
- Race conditions in script builder session creation and slug generation

650
CLAUDE.md
View File

@@ -1,74 +1,628 @@
# CLAUDE.md ResolutionFlow
# CLAUDE.md - Patherly / ResolutionFlow Project Context
You are Claude Code, the primary coding agent for ResolutionFlow. OpenAI Codex is the resume agent when you hit session or weekly limits.
> **Last Updated:** April 6, 2026
The first thing to do every session: read [`.ai/PROJECT_CONTEXT.md`](.ai/PROJECT_CONTEXT.md), [`.ai/CURRENT_TASK.md`](.ai/CURRENT_TASK.md), and [`.ai/HANDOFF.md`](.ai/HANDOFF.md). The ritual is spelled out below.
---
> The protocol section below is byte-identical to the shared block in AGENTS.md. If you edit one, edit the other.
## Project Overview
## Shared protocol
**Patherly** (user-facing brand: **ResolutionFlow**) is a **SaaS product for MSP professionals**. It provides troubleshooting decision trees that guide engineers through proven troubleshooting paths, capture decisions and notes, and generate professional ticket documentation.
### Startup ritual (every session)
**Target Market:** MSP companies — IT service providers managing infrastructure and support for multiple clients.
1. Read `.ai/PROJECT_CONTEXT.md` — architectural truth for this repo.
2. Read `.ai/CURRENT_TASK.md` — what we're actively working on.
3. Read `.ai/HANDOFF.md` — exact resume point.
4. Skim `.ai/DECISIONS.md` for recent entries relevant to the current task.
5. Run `git log --oneline -15` and `git status`.
6. Before taking action, state back in two sentences: the current goal and your proposed next action.
**SaaS Context:** Multi-tenant design — teams represent MSP companies, trees shared within teams, tiered access (super_admin, team_admin, engineer, viewer).
### Handoff ritual (session end — limit hit, task complete, or user stop)
### Branding
1. Update `.ai/HANDOFF.md` to reflect new state. Keep it under ~2K tokens.
2. If `CURRENT_TASK.md` status changed, update it.
3. If you made an architectural decision, append to `.ai/DECISIONS.md`.
4. Append a session entry to `.ai/SESSION_LOG.md`.
5. If working tree is dirty, commit WIP with `wip(handoff): <one-line summary>`. Do not push unless explicitly asked.
| Context | Name Used |
|---------|-----------|
| Repository / directory / database | `patherly` (internal name) |
| Docker containers | `resolutionflow_postgres`, `resolutionflow_frontend`, `resolutionflow_backend` |
| Backend, frontend UI, production URLs | **ResolutionFlow** |
### Writing rules for .ai/ files
- **Design system:** [DESIGN-SYSTEM.md](DESIGN-SYSTEM.md) — THE source of truth for all design decisions
- **Design aesthetic:** Flat, high-contrast dark theme (Sentry/PostHog-inspired). No glass morphism, no gradients on surfaces, no ambient effects. Light mode planned.
- **Accent color:** Electric blue (#60a5fa dark / #2563eb light). Used sparingly — ≤5% of the UI. Warning is amber (#fbbf24), info is cyan (#67e8f9).
- **Fonts:** IBM Plex Sans (`font-sans`, body), Bricolage Grotesque (`font-heading`, headings), JetBrains Mono (`font-mono`, code) — loaded via Google Fonts
- **Logo:** 30px gradient square (ember orange) + "ResolutionFlow" in Bricolage Grotesque 700
- **Layout:** Icon rail sidebar (72px default) with hover flyout panels. Pinnable to full 260px sidebar. See [DESIGN-SYSTEM.md](DESIGN-SYSTEM.md)
- **Brand assets:** `brand-assets/` (source SVGs), `frontend/src/assets/brand/` (app assets), `frontend/public/icons/` (favicon)
- **Terminology:** User-facing label is "Flows" (not "Trees"). Procedural flows are called "Projects" in the UI. Step Library is called "Solutions Library" in the UI. Maintenance flows are hidden from UI for pilot (backend still supports them). `tree_type` column values unchanged in DB.
- **Reference mockups:** `docs/mockups/` (HTML files, open in browser)
- Use model-neutral voice in `HANDOFF.md`, `SESSION_LOG.md`, `DECISIONS.md` ("previous session did X", NOT "Claude did X" or "Codex did X"). Exception: `SESSION_LOG.md` entries include an `<agent>` field in the header.
- Do not duplicate content between files. `CURRENT_TASK.md` holds the goal, `HANDOFF.md` holds the resume point, `TODO.md` holds the backlog. If unsure where something goes, check `.ai/README.md`.
- Don't invent facts about the repo. If you're uncertain, write `TODO: confirm` and flag it.
**Component styling:** See Design System section below and [DESIGN-SYSTEM.md](DESIGN-SYSTEM.md). All colors via CSS variables. Use "Flows" not "Trees" in user-facing text; use "Projects" not "Procedures" for procedural flows.
### Project principle
## Implementation Principles
Prefer correct architecture over minimal diff. Flag "simpler approach" tradeoffs for review before taking them.
- Prefer correct architecture over minimal diff
- If two approaches exist, implement the one that scales, not the one that's faster to write
- Flag any "simpler approach" tradeoffs for product owner review before proceeding
## Claude-specific tooling
---
### GitNexus code intelligence
## Current State
Indexed as `resolutionflow`. Earns its cost on cross-cutting work only.
- **Phase:** Go-to-Market Validation (Pre-PMF)
- **Backend:** Complete (55+ API endpoints, 100+ integration tests)
- **Frontend:** Core features complete, Tree Editor functional
- **Database:** PostgreSQL with Docker, 101 migrations
- **Detailed status:** [CURRENT-STATE.md](CURRENT-STATE.md)
| Tool | When |
|---|---|
| `gitnexus_query({query})` | Find code by concept when you don't know where to look |
| `gitnexus_context({name})` | Callers/callees of a symbol before touching it |
| `gitnexus_impact({target, direction})` | Blast radius before editing shared symbols |
| `gitnexus_rename({symbol_name, new_name, dry_run: true})` | Safe multi-file rename |
### What's In Progress
**Use for:** core shared symbols (`flowpilot_engine`, `unified_chat_service`, auth middleware, `get_db`, shared hooks), cross-file renames, unfamiliar bug traces, refactor safety. **Skip for:** new endpoints, isolated fixes, changes you can read in one file.
- GTM validation: Shadow & Ship — founder dogfooding for 2 weeks, then 5 colleague pilot
- Solutions Library spec written (`docs/plans/2026-03-23-solutions-library-design.md`), implementation post-pilot
- Remaining open issues: #66 Templates + Import/Export, #60 Recurring Issue Detection, #58 Step Feedback Flag
Re-indexes automatically on commit (PostToolUse hook). Manual refresh if stale: `npx gitnexus analyze`.
---
### gstack skills
## Tech Stack
Always use `/browse` for web, never `mcp__claude-in-chrome__*`.
### Backend
Available commands:
- **Framework:** Python FastAPI
- **Database:** PostgreSQL 16 (async via SQLAlchemy 2.0 + asyncpg)
- **Migrations:** Alembic
- **Auth:** JWT (python-jose) + bcrypt, refresh token rotation (JTI-based)
- **Validation:** Pydantic v2
- **Scheduling:** APScheduler 3.x (async, in-process with FastAPI lifespan) + croniter + pytz
- **Planning & review:** `/autoplan`, `/plan-eng-review`, `/plan-design-review`, `/plan-ceo-review`, `/plan-devex-review`, `/devex-review`, `/review`, `/cso`, `/office-hours`
- **Design:** `/design-consultation`, `/design-shotgun`, `/design-html`, `/design-review`
- **Browser & QA:** `/browse`, `/connect-chrome`, `/qa`, `/qa-only`, `/setup-browser-cookies`
- **Ship & deploy:** `/ship`, `/land-and-deploy`, `/canary`, `/benchmark`, `/setup-deploy`, `/document-release`
- **Debug & investigate:** `/investigate`, `/careful`, `/freeze`, `/guard`, `/unfreeze`
- **Other:** `/codex` (OpenAI second opinion), `/setup-gbrain`, `/retro`, `/learn`, `/gstack-upgrade`
### Frontend
### Git trailer
- **Framework:** React 19 + Vite + TypeScript
- **Styling:** Tailwind CSS v4 (`@tailwindcss/vite` plugin, CSS-only config in `index.css`) — flat dark theme with ember orange accent (see [DESIGN-SYSTEM.md](DESIGN-SYSTEM.md))
- **State:** Zustand (with immer + zundo for undo/redo)
- **Routing:** React Router v7
- **API Client:** Axios with token refresh interceptor
- **Icons:** Lucide React
Every commit: `Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>`
---
### Model aliases
## Key Project Structure
Always use alias form (`claude-sonnet-4-6`, `claude-opus-4-6`, etc.) via `settings.get_model_for_action()`. Never hardcode a dated model ID.
```
patherly/
├── backend/
│ ├── app/
│ │ ├── main.py # FastAPI entry point
│ │ ├── api/endpoints/ # Route handlers (auth, trees, sessions, admin, steps, survey, copilot, assistant_chat, integrations)
│ │ │ ├── flow_proposals.py # Knowledge Flywheel review queue CRUD
│ │ │ └── flowpilot_analytics.py # FlowPilot dashboard metrics
│ │ ├── api/deps.py # Auth dependencies (includes require_team_admin)
│ │ ├── api/router.py # Route registration
│ │ ├── core/ # config, database, permissions, security, audit, rate_limit
│ │ ├── models/ # SQLAlchemy models (includes FlowProposal)
│ │ ├── schemas/ # Pydantic schemas
│ │ ├── services/psa/ # PSA provider abstraction (base, connectwise/, autotask/, halopsa/, cache, encryption, registry, types)
│ │ ├── services/knowledge_flywheel.py # AI session analysis → flow proposals
│ │ ├── services/knowledge_flywheel_scheduler.py # APScheduler job for batch analysis
│ │ └── services/knowledge_gap_service.py # Weak options & escalation signal detection
│ ├── alembic/ # Database migrations (001-070 sequential, then hash IDs)
│ ├── scripts/ # seed_data.py, seed_trees.py
│ └── tests/ # pytest integration tests
├── frontend/
│ ├── src/
│ │ ├── api/ # Axios client + endpoint modules
│ │ ├── components/ # common, layout, dashboard, tree-editor, session, procedural, procedural-editor, library, step-library, ui, flowpilot
│ │ ├── hooks/ # usePermissions, useSessionTimer, useKeyboardShortcuts
│ │ ├── pages/ # All page components
│ │ ├── store/ # Zustand stores (auth, treeEditor, proceduralEditor, userPreferences, scriptGeneratorStore)
│ │ └── types/ # TypeScript interfaces
│ └── (Tailwind v4: CSS-only config in src/index.css)
├── docs/plans/archive/ # Archived design/impl docs (pre-March 2026)
├── CLAUDE.md # This file
├── CURRENT-STATE.md # Detailed feature status
├── LESSONS-LEARNED.md # (Deprecated — consolidated into CLAUDE.md)
└── docs/plans/ # Design docs & implementation plans
```
---
## Environment Variables
### Backend (`backend/.env`)
```bash
APP_NAME=ResolutionFlow
DEBUG=true
DATABASE_URL=postgresql+asyncpg://postgres:postgres@localhost:5432/patherly
DATABASE_URL_SYNC=postgresql://postgres:postgres@localhost:5432/patherly
SECRET_KEY=<openssl rand -hex 32>
ACCESS_TOKEN_EXPIRE_MINUTES=5
REFRESH_TOKEN_EXPIRE_DAYS=7
REQUIRE_INVITE_CODE=true
```
### Frontend (`frontend/.env.local` - optional)
```bash
VITE_API_URL=http://localhost:8000
```
---
## ConnectWise PSA Integration
ResolutionFlow integrates with ConnectWise PSA (formerly Manage) as the primary PSA integration. All ConnectWise API reference materials live in `docs/connectwise/`.
### Best Practices Documentation
Official ConnectWise developer guides live in `docs/connectwise/best-practices/`. Read these BEFORE implementing any CW API integration code:
- `PSA-API-Requests.md` — HTTP methods, response codes, condition query syntax, PATCH format, URL encoding, partial responses, custom fields. READ FIRST.
- `PSA-Callbacks.md` — Callback type/level matrix, retry behavior, URL parameter gotcha, HMAC signature verification.
- `PSA-Pagination.md` — Navigable vs Forward-Only pagination, Link headers, while-loop pattern.
- `PSA-Service-Tickets.md` — Ticket field philosophy, recommended field mappings.
- `PSA-Versioning.md` — Pin API version via Accept header. Use `application/vnd.connectwise.com+json; version=2025.16`.
- `PSA-Cloud-URL-Formatting.md` — Dynamic base URL construction via `/login/companyinfo/{companyId}`.
- `Bundled-Requests.md` — Batch multiple API calls into one request via `/system/bundles`.
- `PSA-Markdown.md` — Ticket notes support markdown. Format session documentation output accordingly.
- `PSA-Company-Synchronization.md` — Filter companies by Status/Type for mapping UI.
- `PSA-Data-Protection.md` — Security role model, request minimal permissions (MY not ALL).
### Reference Files (read in this order)
1. `docs/connectwise/CONNECTWISE-API-REFERENCE.md` — Read FIRST. Quick reference covering auth patterns, tiered endpoint map, key field mappings, and integration architecture flows.
2. `docs/connectwise/connectwise-psa-resolutionflow-reference.json` — Extracted OpenAPI 3.0.1 spec (v2025.16) with only the 670 endpoints and 342 schemas relevant to ResolutionFlow. Use for exact field types, request/response shapes, and parameter details.
3. `docs/connectwise/connectwise-psa-openapi-full.json` — Complete ConnectWise PSA OpenAPI spec (1838 endpoints, 842 schemas). Only consult if you need an endpoint outside the extracted subset.
### Integration Architecture
- **Session → Ticket Notes:** Post auto-generated session documentation to ConnectWise tickets as internal analysis notes via `POST /service/tickets/{id}/notes`
- **Ticket Context → Session Runner:** Pull ticket details, company info, and attached configurations to give FlowPilot AI real-world context
- **Callbacks:** Register webhooks via `/system/callbacks` for real-time ticket event notifications to suggest relevant Flows
### Key Implementation Rules
- Auth: API Key auth (Base64 of `companyId+publicKey:privateKey`) + `clientId` header on every request
- `clientId` is server-side config (`CW_CLIENT_ID` in `config.py`) — identifies the ResolutionFlow app, NOT per-tenant. Per-connection credentials: `company_id`, `public_key`, `private_key`, `server_url`
- All PSA integration code in `services/psa/` — provider pattern with `PSAProvider` abstract base class, `ConnectWiseProvider` implementation, `PsaProviderRegistry` for multi-PSA dispatch
- PSA endpoints in `api/endpoints/integrations.py` — connection CRUD, ticket ops, member mapping
- Credentials encrypted at rest via `services/psa/encryption.py` (Fernet)
- Each MSP tenant provides their own CW credentials — ResolutionFlow stores these per-team, never per-user
- Design for the Autotask integration following the same service layer pattern (future PSA)
- In-memory TTL cache in `services/psa/cache.py` for board/status/priority lookups
- Respect CW API: paginate with max 1000 per page, handle retries gracefully
---
## Development Commands
```powershell
# Start PostgreSQL (run from VPS SSH — docker not available inside code-server, see Lesson 103)
docker start resolutionflow_postgres
# Backend (from backend/)
source venv/bin/activate # Linux/Mac
# .\venv\Scripts\Activate # Windows
uvicorn app.main:app --reload
# Frontend (from frontend/)
npm run dev
# Run tests (from backend/)
pytest --override-ini="addopts="
# First time only: create test database
docker exec -it resolutionflow_postgres psql -U postgres -c "CREATE DATABASE resolutionflow_test;"
# Frontend build (IMPORTANT: stricter than tsc --noEmit — always use as final check)
cd frontend && npm run build
# Database migrations
cd backend && alembic upgrade head
alembic revision --autogenerate -m "Description"
# Sequential 3-digit IDs (001070) were used historically. New migrations use Alembic's default hex hash IDs.
# Do NOT pass --rev-id — let Alembic generate the hash automatically.
# Access PostgreSQL (run from VPS SSH — docker not available inside code-server, see Lesson 103)
docker exec -it resolutionflow_postgres psql -U postgres -d resolutionflow
# Seed data
cd backend && pip install httpx && python -m scripts.seed_trees
# CI/CD debugging
gh run list --limit 5 # Recent CI runs
gh run view <id> --log-failed # Failed job logs
gh run view <id> --json jobs --jq '.jobs[] | {name: .name, conclusion: .conclusion}'
# NEVER use `gh run watch` — it holds context open and burns tokens while waiting
```
### URLs
- Frontend: <http://localhost:5173>
- Backend API: <http://localhost:8000>
- API Docs: <http://localhost:8000/api/docs>
### Test Users (seeded via `scripts/seed_test_users.py`)
- All share password: `TestPass123!`
- `admin@resolutionflow.example.com` (super_admin), `teamadmin@resolutionflow.example.com` (team_admin), `engineer@resolutionflow.example.com` (engineer), `pro@resolutionflow.example.com` (solo pro)
---
## Critical Lessons Learned
> Lessons 1-40 archived to `docs/LESSONS-ARCHIVE.md` — fixes are baked into the codebase. Consult if you hit a regression.
### Active Lessons (41+)
**41. Assistant chat uses local React state, not Zustand:** `AssistantChatPage.tsx` uses `useState` for `chats`, `messages`, `input`, `loading`. No store.
**42. Public pages use raw `fetch()`, not `apiClient`:** Survey, shared sessions, and no-auth pages use `fetch()` with full URL. `apiClient` requires auth tokens.
**43. Adding new email types:** Add static async method to `EmailService` in `core/email.py`. Fire-and-forget from endpoints (log errors, don't fail).
**44. AI Chat Builder is flow-type-aware:** `ai_chat_service.py` dispatches by `flow_type`. Troubleshooting: `[TREE_UPDATE]` markers. Procedural: `[STEPS_UPDATE]` markers. Both support `[METADATA]`.
**45. Intake form field schema:** Uses `variable_name` and `field_type` (NOT `name` and `type`).
**46. `CreateFlowDropdown` uses `AIPromptDialog`:** Opens prompt modal, starts AI session, generates flow, navigates to editor with `{ state: { aiPanelOpen: true, sessionId } }`.
**47. Editor-Embedded Flow Assist:** `EditorAIPanel` (320px side panel) + `useEditorAI` hook. Ghost nodes use `_suggestion: true` flag. Actions route to model tiers via `settings.get_model_for_action()`. Delta responses use `[DELTA]...[/DELTA]` markers.
**48. Tree orphan validation uses dynamic root ID:** Orphan check compares against `state.treeStructure?.id` (NOT hardcoded `'root'`).
**49. Full-stack features — verify both ends:** Check the full data flow: schema → endpoint → API client → hook → store → UI.
**50. Anthropic SDK retry:** Set `max_retries=1` to fail fast. Default `max_retries=2` can take 3× timeout.
**51. AI model tier routing:** Use `settings.get_model_for_action(action_type)`. Model IDs: use alias form (`claude-sonnet-4-6`).
**52. Mobile scroll-to-top:** Use `ref.current.scrollIntoView()`, not `window.scrollTo()`. Trigger via `useEffect`.
**53. Flex height chain:** Every ancestor must be a flex container for `flex-1` to work. Missing `flex` class collapses React Flow to 0 height.
**54. React Flow CSS in Tailwind v4:** Import in `index.css`, not component JS. Override dark theme using `--xy-*` CSS custom properties.
**55. App shell height chain:** Every wrapper between `.main-content` and canvas needs `flex` + `flex-1` + `min-h-0` or `h-full`.
**56. Railway backend service name is `patherly`:** Production DB name is `railway`. Public Postgres proxy: `interchange.proxy.rlwy.net:45797`.
**57. Node field priority:** `title``question``description``content``label`. See `copilot_service.py`.
**58. `scriptGeneratorStore.generate()` optional param:** Always wrap: `onClick={() => generate()}`, never `onClick={generate}`.
**59. ConnectWise `clientId` is server-side config:** Set in `config.py` as `CW_CLIENT_ID`. Per-connection: `company_id`, `public_key`, `private_key`, `server_url`.
**60. Dockerfile build args for Vite env vars:** Any new `VITE_*` or `VITE_PUBLIC_*` env var must be added as `ARG` + `ENV` in `frontend/Dockerfile` for Railway deploys. Railway env vars are runtime-only unless explicitly passed through as Docker build args. Without this, `import.meta.env.VITE_*` resolves to `undefined` in production builds.
**61. Procedural sessions auto-start on page load:** `ProceduralNavigationPage` calls `startSession()` immediately in `loadTree()` — there is no intake form screen or "Start" button. Variables are filled inline during execution. Troubleshooting flows DO have a start screen with ticket/client fields. Don't write tests or UI that assume a Start button on procedural flows.
**62. Playwright strict mode — scope selectors to avoid ambiguity:** Step titles appear in both the sidebar checklist and main content heading. Use `getByRole('heading', { name })` for the main content, or scope with `page.locator('.animate-scale-in')` for command palette items. `getByText()` frequently matches multiple elements due to the sidebar + main content layout.
**63. Node 20 required for frontend builds:** Vite 7+ requires Node 20.19+. The system Node may be v18; use nvm: `export NVM_DIR="$HOME/.nvm" && source "$NVM_DIR/nvm.sh" && nvm use 20`. For direct binary access without nvm sourcing: `PATH="$HOME/.nvm/versions/node/v20.19.0/bin:$PATH"`.
**64. PostHog product analytics:** Initialized via `PostHogProvider` in `main.tsx` with explicit `posthog.init()` + `client` prop pattern. Event helpers in `lib/analytics.ts` — use `analytics.eventName(props)` to track. `identifyUser()` called in `authStore.fetchUser()`, `resetAnalytics()` on logout. Env vars: `VITE_PUBLIC_POSTHOG_KEY`, `VITE_PUBLIC_POSTHOG_HOST`. Autocapture enabled.
**65. Local Docker Compose uses `resolutionflow` database on port 5433:** Container name is `resolutionflow_postgres`, database is `resolutionflow` (not `patherly`), port mapped to `5433` (not `5432`). The `POSTGRES_PORT` env var controls this. Playwright config defaults must match: `postgresql+asyncpg://postgres:postgres@127.0.0.1:5433/resolutionflow`.
**66. Dev environment runs on Hostinger VPS (46.202.92.250), not localhost:** Code-server runs in Docker on a VPS (previously devserver01/192.168.0.9). Frontend/backend are accessed via `46.202.92.250`, not `localhost`. CORS must include the VPS IP in `CORS_ORIGINS` and `FRONTEND_URL`. Frontend `.env` must set `VITE_API_URL` to the VPS backend URL. See [DEV-ENV.md](DEV-ENV.md) for full setup, Docker config, networking, and known issues.
**67. Tree editor route is `/trees/new`:** NOT `/editor/new`. Check `router.tsx` line 156 for the canonical path. Use `getTreeEditorPath()` from `@/lib/routing` when navigating programmatically.
**68. APScheduler jobs need `max_instances=1`:** Without it, overlapping scheduler runs can process the same records twice (TOCTOU race). Always set `max_instances=1` on interval jobs in `main.py`.
**69. PostgreSQL `func.sum(case(...))` returns `Decimal` via asyncpg:** Cast to `int()` before storing in Pydantic `dict[str, Any]` fields, or JSON serialization may produce unexpected types.
**70. Toast library uses `toast.warning()` not `toast.warn()`:** Import from `@/lib/toast`. Methods: `success`, `error`, `warning`, `info`. See `frontend/src/lib/toast.ts`.
**71. Enhancement/branch_addition proposals cannot be directly approved:** Backend returns 400 — they require `modified_flow_data` via "Edit & Publish" flow. Only `new_flow` proposals support direct approve.
**72. `ai_sessions.status` column is `VARCHAR(30)`:** Must fit `requesting_escalation` (23 chars). If adding new status values, verify length. Migration `f0aad74ea51b` widened from 20→30.
**73. `get_db` rolls back on exception:** The dependency does `await session.rollback()` on error to prevent `InFailedSQLTransaction` cascade. Never remove this — without it, one failed request poisons subsequent requests on the same connection.
**74. FlowPilot action bar height chain:** The action bar (Resolve/Escalate/Pause) requires every ancestor from `app-shell` grid down to have proper flex constraints. Key fix: `ViewTransitionOutlet` wrapper needs `flex flex-col`. If action bar disappears, check height chain with DevTools `getBoundingClientRect()` walk.
**75. Dashboard prefill auto-submits:** `StartSessionInput` navigates to `/pilot` or `/assistant` with `{ state: { prefill } }`. `FlowPilotSessionPage` auto-submits via `useEffect` + `prefillHandledRef` guard — no double-enter. `AssistantChatPage` does the same pattern.
**76. Active session navigation guard:** `FlowPilotSessionPage` uses `useBlocker` (same as `TreeEditorPage`) to intercept navigation during active sessions. "Pause & Leave" auto-pauses before proceeding.
**77. Prefer manual Alembic migrations for targeted changes:** `alembic revision --autogenerate` picks up drift from all tables. For single-column fixes, use `alembic revision -m "desc"` and write `op.alter_column()` manually.
**78. Landing page subtitle is "AI-Powered Troubleshooting for MSPs":** Not "Decision Tree Platform". This tagline appears on login, register, and the HTML `<title>`. The old "Decision Tree Platform" was internal jargon misaligned with user-facing branding.
**79. Custom modals must be mobile-responsive:** Use `items-end sm:items-center` (bottom-sheet on mobile, centered on desktop) and `max-w-full sm:max-w-lg` (full-width on mobile). The shared `Modal.tsx` does this correctly — custom modal implementations must follow the same pattern. See `PrepareSessionModal.tsx` for the fix pattern.
**80. TopBar search collapses to icon on mobile:** Full search bar (`hidden sm:block`) shows on desktop; magnifying glass icon button (`sm:hidden`) shows on mobile (<640px). Both open the same CommandPalette. Don't add `w-full` search bar without the mobile icon fallback.
**81. Never use `transition: all` in landing.css:** Specify exact properties: `transition: background 0.3s, border-color 0.3s, box-shadow 0.3s, transform 0.3s, opacity 0.3s`. `transition: all` animates layout properties and causes jank.
**82. `bun` requires PATH setup on devserver01:** `export BUN_INSTALL="$HOME/.bun" && export PATH="$BUN_INSTALL/bin:$PATH"`. The gstack browse binary and Playwright need this. Chromium system deps: `libatk1.0-0 libatk-bridge2.0-0 libcups2 libxkbcommon0 libatspi2.0-0 libxcomposite1 libxdamage1 libxfixes3 libxrandr2 libgbm1 libasound2`.
**83. ~~FlowPilot ActionBar fixed bottom~~ (Superseded by Lesson 93):** Actions moved to the page header. `FlowPilotActionBar` component exists but is no longer used in the main session flow. The only fixed-bottom element is the message input.
**84. AI session `abandoned` status is fully wired:** `POST /ai-sessions/{id}/abandon` sets status to `abandoned` with optional `reason` param. Frontend: `aiSessionsApi.abandonSession()`, `useFlowPilotSession().abandonSession()`, "Close" button in `FlowPilotActionBar`. Redirects to `/sessions` after closing.
**85. Date range filter end dates must use end-of-day:** `toDate.toISOString()` sends midnight (start of day), excluding items created later that day. Always set `toDate.setHours(23, 59, 59, 999)` before sending. For string-based date inputs (AI sessions), append `T23:59:59.999Z`. See `SessionHistoryPage.tsx`.
**86. Script Builder system:** AI-powered script generation at `/script-builder`. Chat-style interface generates PowerShell/Bash/Python scripts from natural language. Backend: `ScriptBuilderSession` model, `script_builder_service.py`, endpoints at `/scripts/builder/`. Frontend: `ScriptBuilderPage`, `ScriptCodeBlock`, `ScriptPreviewModal`, `SaveToLibraryDialog`. FlowPilot can hand off to Script Builder via `action_type: "open_script_builder"` with `sessionStorage` context passing.
**87. FlowPilot must ask GUI vs script preference:** When a task can be done via GUI or script (e.g., creating AD users), FlowPilot must ask the engineer which approach they prefer BEFORE suggesting either. Never assume the user wants a script. See `FLOWPILOT_SYSTEM_PROMPT` rules in `flowpilot_engine.py`.
**88. Charcoal palette — sidebar-darkest approach:** Sidebar `#0e1016`, page `#16181f`, cards `#1e2028`, borders `#2a2e3a`. This gives more contrast range than true-dark. All colors via CSS variables in `index.css` `@theme` block. Accent is electric blue (#60a5fa), not orange or cyan.
*(Lessons 8991 were retracted.)*
**92. `tsc -b` in Dockerfile is stricter than `npx tsc --noEmit`:** The production build (`tsc -b && vite build`) enforces `noUnusedLocals` and `noUnusedParameters` as hard errors. After any refactor that moves logic between components or removes features, trace every import and destructured prop to remove orphans. IDE warnings (yellow squiggles) flag these — check them before pushing.
**93. FlowPilot actions live in the page header, not a bottom bar:** `FlowPilotSessionPage` renders Resolve/Escalate/Share Update in the header bar. Desktop: inline buttons + `⋯` overflow (Pause/Close). Mobile: single `⋯` menu. The bottom only has the message input. `FlowPilotActionBar` component still exists but is no longer used in the main session flow.
**94. Frontend chat uses unified_chat_service, not assistant_chat_service:** `AssistantChatPage` calls `/ai-sessions/{id}/chat``unified_chat_service.py`. The old `assistant_chat_service` endpoints were removed (only retention settings remain at `/assistant/retention`). When tracing chat features, start from `aiSessionsApi.sendChatMessage``ai_sessions.py``unified_chat_service.py`. Never wire chat features into `assistant_chat.py`.
**95. Image upload → AI vision pipeline:** Paste/attach images → upload to Railway S3 bucket via `uploadsApi.upload()` → send `upload_ids` with chat message → backend fetches from S3 via `storage_service.download_file()` → resized via `storage_service.resize_image_for_vision()` (Pillow, 1568px max, PNG→JPEG) → base64-encoded → sent as Claude multimodal content blocks. Max 3 images/message. Images are NOT stored in conversation history (text-only). Vision helpers live in `storage_service.py`.
**96. `bg-accent` is electric blue — never use for code/kbd elements:** In Tailwind v4, `bg-accent` maps to `--color-accent: #60a5fa` (dark) / `#2563eb` (light). Use `bg-code` for code blocks, `bg-white/[0.12] border border-white/[0.06]` for inline code/badges, `bg-white/[0.08]` for kbd shortcuts. Blue accent is reserved for interactive elements only (buttons, active nav, links). Ember orange (#f97316) is deprecated — do not use.
**97. Railway Object Storage (S3 bucket) is provisioned:** Bucket `resolutionflow-uploads` on Railway canvas. Variables: `STORAGE_ENDPOINT`, `STORAGE_ACCESS_KEY`, `STORAGE_SECRET_KEY`, `STORAGE_BUCKET_NAME`, `STORAGE_REGION` — mapped via variable references on the `patherly` backend service. Accessed via boto3 in `storage_service.py`. Pillow (`Pillow>=10.0.0`) + `libjpeg-dev`/`zlib1g-dev` in Dockerfile for image resize.
**98. `lazyWithRetry` for stale chunk errors:** All lazy-loaded routes use `lazyWithRetry` from `@/lib/lazyWithRetry.ts` instead of `React.lazy`. Auto-reloads the page on chunk load failures (stale deploys). Uses sessionStorage debounce (10s) to prevent loops. When adding new lazy routes, use `lazyWithRetry`, not `lazy`.
**99. Tailwind v4 `text-secondary` renders invisible on dark backgrounds:** `text-secondary` maps to `--color-secondary: #2e3140` (a dark surface color), NOT `--color-text-secondary`. For readable secondary text, use `text-muted-foreground` (`#848b9b`). Also avoid `text-muted` (`#4f5666`) for body text — it's for labels only. This applies to ALL new components.
**100. Hover pop-out card pattern:** For cards that expand on hover "in front of everything": use `pointer-events-none` on the scrim (`fixed inset-0 z-40 bg-black/30`), absolute-position the expanded card at `z-50` with its own `onClick` handler, and dismiss via `onMouseLeave` on the wrapper div. Never put interactive event handlers on the scrim — it blocks clicks on sibling elements.
**101. AI marker format compliance:** The AI assistant uses `[QUESTIONS]`, `[ACTIONS]`, and `[FORK]` markers in responses. Parsed by `unified_chat_service.py` (`_parse_*_marker` functions), returned as structured data in the API response. System prompt in `assistant_chat_service.py` has a final reminder section, and each user message gets an invisible `[SYSTEM: ...]` reminder appended in `_call_anthropic_cached()`. If markers stop appearing: check conversation history stores `display_content` (stripped), verify system prompt final reminder exists, check user message reminder injection is active.
**102. TaskLane activation must happen in ALL chat response paths:** `AssistantChatPage.tsx` has three code paths calling `sendChatMessage`: `handleSend` (regular messages), `sendPrefill` (dashboard handoff), `handleResumeNew` (resume from concluded session). ALL three must check `response.actions`/`response.questions` and call `setShowTaskLane(true)`. Missing this in any path causes TaskLane to not appear on first message.
**103. Docker not available in code-server container:** The dev environment runs code-server inside Docker on the VPS. The `docker` CLI is not available inside the code-server container. To query the database, use the VPS SSH session: `docker exec resolutionflow_postgres psql -U postgres -d resolutionflow -t -c "SQL"`. Python is also not available in the container.
**104. `landing.css` uses self-contained `--lp-*` color variables:** The landing page defines its own color palette at the top of `landing.css` (`--lp-bg`, `--lp-accent`, `--lp-text-*`, etc.). Never use `var(--color-*)` theme tokens in `landing.css` — they may resolve incorrectly outside the app shell context. Extend the `--lp-*` palette for any new landing page colors.
**105. `npm run build` fails with `EACCES: permission denied` on `dist/` in code-server:** This is a filesystem permission issue in the Docker environment, not a TypeScript error — the TS compilation completes successfully. Use `npx tsc -b` to verify TypeScript cleanly without needing to write to `dist/`.
**106. Guard async "select item → load data → apply state" flows with a ref:** When a component lets the user switch between items (chat sessions, flows, scripts) and loads data asynchronously on each switch, the load for item A can complete *after* the user has already switched to item B — overwriting B's state with A's stale data. Fix pattern: keep a `currentSelectionRef = useRef(initialId)` and update it synchronously whenever the selection changes (in every creation/switch path). After every `await`, bail out if `currentSelectionRef.current !== thisItemId`. See `AssistantChatPage.tsx` `selectChat` for the reference implementation (`currentChatRef`).
**107. Startup routines must use `_admin_session_factory()` after Phase 4 RLS:** Any code that runs at startup (lifespan, `ensure_service_account`, seed scripts) and touches tenant-isolated tables (`users`, etc.) must use `_admin_session_factory()` — not `get_db()`. Phase 4 enabled RLS on `users`; a tenant-scoped session has no `app.current_account_id` set at startup, so all queries return 0 rows or fail. `get_service_account_id` in `deps.py` is safe — it reads from `app.state` cached at startup, never hits the DB per-request.
**108. Tables with no `account_id` column (never add to RLS migrations):** `script_categories`, `platform_steps`, `template_trees`, `plan_feature_defaults`, `accounts` — global/platform tables documented with "No account_id. No RLS." in their model files. When writing RLS migrations, scan at the class level (check for `account_id: Mapped` within the class block), not the file level — multiple classes in one `.py` file can have different columns (e.g. `ScriptCategory` vs `ScriptTemplate` in `script_template.py`).
**109. `tree_shares.account_id` must equal `tree.account_id`, not the actor's account:** When creating a `TreeShare`, always use `account_id=tree.account_id` (tree owner's tenant). A super admin in tenant A sharing tenant B's tree must produce a share row in tenant B's RLS context — using `current_user.account_id` instead makes the share invisible to the tree owner after RLS is enforced.
## RBAC & Permissions
- **Role hierarchy:** super_admin > team_admin > engineer > viewer
- **Team Admin:** `role='engineer'` + `is_team_admin=True` + valid `team_id`
- **Backend deps:** `get_current_active_user(user, db)` (any active + auto-downgrades expired trials), `require_engineer_or_admin` (blocks viewers), `require_admin` (super admin only)
- **Never use** `role == "admin"` — use `is_super_admin` instead
- **Frontend:** `usePermissions()` hook for all permission checks
- **Centralized:** `backend/app/core/permissions.py`, `frontend/src/hooks/usePermissions.ts`
---
## Design System
**Source of truth:** [DESIGN-SYSTEM.md](DESIGN-SYSTEM.md) — always read this before making visual or UI decisions.
- **Theme:** Flat, high-contrast dark theme (Sentry/PostHog-inspired). No glass morphism, no backdrop blur, no ambient orbs, no gradient backgrounds on surfaces. Light mode fully specified (v6).
- **Backgrounds:** `bg-page` (`#16181f`), `bg-sidebar` (`#0e1016`), `bg-card` (`#1e2028`), `bg-elevated` (`#2a2d38`)
- **Cards:** `bg-card` with 1px `border-default` (`#2a2e3a`), 8px radius. No shadows, no blur, no gradients. Hover: `border-hover` (`#3d4252`)
- **Buttons:** Primary: solid `accent` (#60a5fa dark / #2563eb light), white text, 5px radius. Ghost: transparent + 1px border, hover `bg-elevated`
- **Inputs:** `bg-input` (`#252830`) with 1px `border-default`, 5px radius. Focus: `border-color: accent` + `box-shadow: 0 0 0 2px accent-dim`
- **Text:** `text-heading` (`#f0f2f5`) → `text-primary` (`#e2e5eb`) → `text-muted-foreground` (`#848b9b`) → `text-muted` (`#4f5666`). NEVER use `text-secondary` — in Tailwind v4 it maps to a surface color, not a text color.
- **Borders:** `border-default` (`#2a2e3a`), `border-hover` (`#3d4252`)
- **Functional colors:** `#34d399` (success), `#fbbf24` (warning/amber), `#f87171` (danger), `#67e8f9` (info/cyan) — each with `-dim` variant at 10% opacity
- **Accent:** Electric blue `#60a5fa` (dark) / `#2563eb` (light) — used sparingly (≤5% of UI). `accent-dim` = `rgba(96,165,250,0.10)`, `accent-text` = `#93c5fd`
- **Deprecated:** Do NOT use `glass-card`, `glass-stat`, `bg-gradient-brand`, `text-gradient-brand`, `backdrop-filter: blur()`, ambient orbs, purple gradients, ember orange (`#f97316`), or cyan (`#22d3ee`) as accent — cyan is now the info color only
---
## Frontend Patterns
- **Component guidelines:** Use `cn()` from `@/lib/utils`, Lucide icons (wrap in `<span>` for title), modals with fixed header/footer
- **Type organization:** Create in `types/`, export from `types/index.ts`, import with `import type { T } from '@/types'`
- **Scratchpad overlay:** `position: fixed`, `onOpenChange` callback for parent padding adjustment, `right-2` positioning
- **Custom step flow:** `CustomStepModal``PostStepActionModal``ContinuationModal` → custom step view. Key state: `pendingStep`, `pendingContinuationNodeId`, `customBranchMode`, `branchOriginNodeId`. Use `findCustomStep()` not `findNode()` for custom step UUIDs.
- **Session sharing:** `ShareSessionModal` manages share links, `SharedSessionPage` renders public/account views. Helper utils in `lib/sessionShare.ts`. Share URLs use `/shared/sessions/:token`.
- **Procedural navigation:** `ProceduralNavigationPage` handles intake forms, step-by-step execution, and resume via `location.state.sessionId`. Uses `StepChecklist`, `StepDetail`, `ProgressBar`, `CompletionSummary` components.
- **Routing helper:** Use `getTreeNavigatePath()` and `getTreeEditorPath()` from `@/lib/routing` for all tree/session navigation.
- **Account section layout:** `AccountLayout` has NO sidebar nav. Account sub-pages (categories, target-lists) are reached via link cards on `AccountSettingsPage.tsx`. New account pages: add route in `router.tsx` under `account` children + add a link card in `AccountSettingsPage`.
- **Dashboard cockpit:** `QuickStartPage` is the copilot-first launchpad. Greeting + "What are you troubleshooting?" + ChatGPT-style `StartSessionInput` (auto-growing textarea, paste images, drag-drop files, attach button, paste logs, suggestion chips). Below: `PendingEscalations`, `ActiveFlowPilotSessions`, `RecentFlowPilotSessions`. Collapsible "Dashboard" section for `PerformanceCards`, `KnowledgeBaseCards`, `TeamSummary`.
- **Sidebar sections:** Amber "New Session" button → Home → RESOLVE (History) → KNOWLEDGE (Flows with Solutions Library sub-item, Scripts) → INSIGHTS (Data). Footer: Account, Pin/Unpin. No help/guides/feedback in sidebar — accessible via TopBar.
---
## Common Tasks
- **New endpoint:** Create in `endpoints/` → add to `router.py` → schema in `schemas/` → tests → frontend API client
- **New page:** Create in `pages/` → add route in `router.tsx` → nav link in `AppLayout.tsx`
- **New public route (no auth):** Add at top level in `router.tsx` alongside `/login`, `/register` — NOT inside the `ProtectedRoute`/`AppLayout` children.
- **Schema change:** Update model → `alembic revision --autogenerate -m "desc" --rev-id=NNN` (NNN = next sequential number, e.g., 068 → 069) → review → `alembic upgrade head`
- **New frontend API module:** Types in `types/` → export from `types/index.ts` → client in `api/` → export from `api/index.ts`
---
## Coding Standards
### Python
- Type hints everywhere, async/await for DB, Pydantic for validation, `DateTime(timezone=True)` always
### TypeScript
- Interfaces for all data, `const` over `let`, functional components + hooks, reusable logic in custom hooks
### Git
- Format: `type: description` (feat, fix, refactor, docs, test, chore)
- Always include `Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>`
- Always create feature branch BEFORE committing: `git checkout -b feat/feature-name`
- Large features: commit per phase with `npm run build` validation
### After Completing Work
When a feature, fix, or significant piece of work is finished and merged/committed:
1. **Update `CURRENT-STATE.md`** — move completed items, update "In Progress" and "What's Next" sections
2. **Update `03-DEVELOPMENT-ROADMAP.md`** — check off completed work, update phase status
3. **Close related GitHub Issues** — use `gh issue close #N` for any issues resolved by the work
4. **Update `CLAUDE.md`** if the work introduced new patterns, lessons learned, or changed project structure
---
## gstack (Browser & Workflow Skills)
**Web browsing:** Always use the `/browse` skill from gstack for all web browsing needs. Never use `mcp__claude-in-chrome__*` tools.
**Available skills:**
| Skill | Purpose |
|-------|---------|
| `/office-hours` | Brainstorm new ideas (YC-style office hours) |
| `/plan-ceo-review` | CEO/founder-mode plan review (scope, ambition) |
| `/plan-eng-review` | Engineering plan review (architecture, edge cases) |
| `/plan-design-review` | Design plan review (UI/UX critique) |
| `/design-consultation` | Create a design system / DESIGN.md |
| `/review` | Pre-landing PR code review |
| `/ship` | Ship workflow (tests, review, PR creation) |
| `/browse` | Headless browser for QA testing and site dogfooding |
| `/qa` | Systematic QA testing + auto-fix bugs found |
| `/qa-only` | QA report only (no fixes) |
| `/design-review` | Visual QA — find and fix design inconsistencies |
| `/setup-browser-cookies` | Import cookies from real browser for authenticated testing |
| `/retro` | Weekly engineering retrospective |
| `/investigate` | Systematic debugging with root cause analysis |
| `/document-release` | Post-ship documentation updates |
| `/codex` | Second opinion via OpenAI Codex CLI |
| `/careful` | Safety guardrails for destructive commands |
| `/freeze` | Restrict edits to a specific directory |
| `/guard` | Full safety mode (careful + freeze) |
| `/unfreeze` | Remove edit restrictions |
| `/gstack-upgrade` | Upgrade gstack to latest version |
---
## Deployment (Railway)
- **Production:** `resolutionflow.com` (frontend), `api.resolutionflow.com` (backend)
- Auto-deploys on push to `main`
- PR environments auto-created (need manual domain generation in Railway dashboard)
- PR envs need `VITE_API_URL` set with `https://` prefix on frontend service
- `ALLOW_RAILWAY_ORIGINS=true` enables CORS for `*.up.railway.app`
- Shared Variables (project-level in Railway dashboard) auto-propagate to all environments including PR envs — use for secrets like `ANTHROPIC_API_KEY`
- Super admin utility: `backend/make_superadmin_simple.py list|<email>`
---
## Future Roadmap
- **Phase 3:** PSA integrations (ConnectWise in progress), file attachments, client context, analytics
- **Phase 4:** Additional PSA integrations (Autotask/Kaseya), PowerShell automation, enterprise SSO
---
## Quick Reference
| What | Where |
|------|-------|
| API Docs | <http://localhost:8000/api/docs> |
| Detailed Status | [CURRENT-STATE.md](CURRENT-STATE.md) |
| Development Roadmap | [03-DEVELOPMENT-ROADMAP.md](03-DEVELOPMENT-ROADMAP.md) |
| GitHub Issues | `gh issue list --state open` |
| Bugs & Fixes | CLAUDE.md → Critical Lessons Learned section |
| Design System | [DESIGN-SYSTEM.md](DESIGN-SYSTEM.md) |
| Dev Environment | [DEV-ENV.md](DEV-ENV.md) — 46.202.92.250 setup, Docker, CORS, networking |
<!-- gitnexus:start -->
# GitNexus — Code Intelligence
This project is indexed by GitNexus as **resolutionflow** (16703 symbols, 35922 relationships, 300 execution flows). Use the GitNexus MCP tools to understand code, assess impact, and navigate safely.
> If any GitNexus tool warns the index is stale, run `npx gitnexus analyze` in terminal first.
## Always Do
- **MUST run impact analysis before editing any symbol.** Before modifying a function, class, or method, run `gitnexus_impact({target: "symbolName", direction: "upstream"})` and report the blast radius (direct callers, affected processes, risk level) to the user.
- **MUST run `gitnexus_detect_changes()` before committing** to verify your changes only affect expected symbols and execution flows.
- **MUST warn the user** if impact analysis returns HIGH or CRITICAL risk before proceeding with edits.
- When exploring unfamiliar code, use `gitnexus_query({query: "concept"})` to find execution flows instead of grepping. It returns process-grouped results ranked by relevance.
- When you need full context on a specific symbol — callers, callees, which execution flows it participates in — use `gitnexus_context({name: "symbolName"})`.
## When Debugging
1. `gitnexus_query({query: "<error or symptom>"})` — find execution flows related to the issue
2. `gitnexus_context({name: "<suspect function>"})` — see all callers, callees, and process participation
3. `READ gitnexus://repo/resolutionflow/process/{processName}` — trace the full execution flow step by step
4. For regressions: `gitnexus_detect_changes({scope: "compare", base_ref: "main"})` — see what your branch changed
## When Refactoring
- **Renaming**: MUST use `gitnexus_rename({symbol_name: "old", new_name: "new", dry_run: true})` first. Review the preview — graph edits are safe, text_search edits need manual review. Then run with `dry_run: false`.
- **Extracting/Splitting**: MUST run `gitnexus_context({name: "target"})` to see all incoming/outgoing refs, then `gitnexus_impact({target: "target", direction: "upstream"})` to find all external callers before moving code.
- After any refactor: run `gitnexus_detect_changes({scope: "all"})` to verify only expected files changed.
## Never Do
- NEVER edit a function, class, or method without first running `gitnexus_impact` on it.
- NEVER ignore HIGH or CRITICAL risk warnings from impact analysis.
- NEVER rename symbols with find-and-replace — use `gitnexus_rename` which understands the call graph.
- NEVER commit changes without running `gitnexus_detect_changes()` to check affected scope.
## Tools Quick Reference
| Tool | When to use | Command |
|------|-------------|---------|
| `query` | Find code by concept | `gitnexus_query({query: "auth validation"})` |
| `context` | 360-degree view of one symbol | `gitnexus_context({name: "validateUser"})` |
| `impact` | Blast radius before editing | `gitnexus_impact({target: "X", direction: "upstream"})` |
| `detect_changes` | Pre-commit scope check | `gitnexus_detect_changes({scope: "staged"})` |
| `rename` | Safe multi-file rename | `gitnexus_rename({symbol_name: "old", new_name: "new", dry_run: true})` |
| `cypher` | Custom graph queries | `gitnexus_cypher({query: "MATCH ..."})` |
## Impact Risk Levels
| Depth | Meaning | Action |
|-------|---------|--------|
| d=1 | WILL BREAK — direct callers/importers | MUST update these |
| d=2 | LIKELY AFFECTED — indirect deps | Should test |
| d=3 | MAY NEED TESTING — transitive | Test if critical path |
## Resources
| Resource | Use for |
|----------|---------|
| `gitnexus://repo/resolutionflow/context` | Codebase overview, check index freshness |
| `gitnexus://repo/resolutionflow/clusters` | All functional areas |
| `gitnexus://repo/resolutionflow/processes` | All execution flows |
| `gitnexus://repo/resolutionflow/process/{name}` | Step-by-step execution trace |
## Self-Check Before Finishing
Before completing any code modification task, verify:
1. `gitnexus_impact` was run for all modified symbols
2. No HIGH/CRITICAL risk warnings were ignored
3. `gitnexus_detect_changes()` confirms changes match expected scope
4. All d=1 (WILL BREAK) dependents were updated
## Keeping the Index Fresh
After committing code changes, the GitNexus index becomes stale. Re-run analyze to update it:
```bash
npx gitnexus analyze
```
If the index previously included embeddings, preserve them by adding `--embeddings`:
```bash
npx gitnexus analyze --embeddings
```
To check whether embeddings exist, inspect `.gitnexus/meta.json` — the `stats.embeddings` field shows the count (0 means no embeddings). **Running analyze without `--embeddings` will delete any previously generated embeddings.**
> Claude Code users: A PostToolUse hook handles this automatically after `git commit` and `git merge`.
## CLI
| Task | Read this skill file |
|------|---------------------|
| Understand architecture / "How does X work?" | `.claude/skills/gitnexus/gitnexus-exploring/SKILL.md` |
| Blast radius / "What breaks if I change X?" | `.claude/skills/gitnexus/gitnexus-impact-analysis/SKILL.md` |
| Trace bugs / "Why is X failing?" | `.claude/skills/gitnexus/gitnexus-debugging/SKILL.md` |
| Rename / extract / split / refactor | `.claude/skills/gitnexus/gitnexus-refactoring/SKILL.md` |
| Tools, resources, schema reference | `.claude/skills/gitnexus/gitnexus-guide/SKILL.md` |
| Index, status, clean, wiki CLI commands | `.claude/skills/gitnexus/gitnexus-cli/SKILL.md` |
<!-- gitnexus:end -->

View File

@@ -1,671 +1,262 @@
# ResolutionFlow Dev Environment Setup & Operations Guide
# ResolutionFlow Dev Environment Setup & Operations Guide
> **Scope:** Stand up a working ResolutionFlow dev environment from scratch on any Linux host (VPS, on-prem Proxmox LXC/VM, bare metal). Self-contained — do not read another doc to get the dev stack running.
> **Last rewritten:** April 2026, post-Hostinger-VPS deprecation, ahead of Proxmox migration.
> **Audience:** You (returning to the project), a teammate, or a fresh Claude Code session.
## Server Overview
If you're picking up mid-migration and need to know what code state is on the current branch, read `docs/FlowAssist_Migration/MIGRATION-HANDOFF.md` first.
- **Provider:** Hostinger KVM VPS (srv1522117)
- **IP Address:** 46.202.92.250
- **OS:** Ubuntu 24.04 LTS
- **CPU:** 2 vCPU cores
- **RAM:** 8GB
- **Disk:** 100GB NVMe SSD
- **Swap:** 4GB (`/swapfile`, swappiness=10)
---
## Architecture
## 1. What this project needs, regardless of host
All services run as Docker containers on the host, managed via SSH or from the VS Code Server integrated terminal.
These are non-negotiable. If your host can't provide them, fix that before anything else.
```
Host (root@srv1522117)
├── Traefik → reverse proxy + auto SSL (Let's Encrypt)
├── VS Code Server → browser IDE at https://code.resolutionflow.com
└── ResolutionFlow Stack
├── resolutionflow_frontend → Vite/React on port 5173
├── resolutionflow_backend → FastAPI/Uvicorn on port 8000
└── resolutionflow_postgres → PostgreSQL 16 + pgvector on port 5432
```
| Component | Required version | Notes |
|---|---|---|
| **Linux** | any mainstream distro | Ubuntu 22.04+ / Debian 12+ tested; Alpine fine for containers |
| **Python** | 3.11+ | Backend and migrations |
| **Node.js** | 20.19+ | Vite 7 fails on older versions — CLAUDE.md Lesson 63 |
| **PostgreSQL** | 16 | `gen_random_uuid()` + `jsonb` + RLS are all leaned on |
| **Docker + Docker Compose** | recent | Only if you are running Postgres and/or backend as containers |
| **Git** | recent | |
## Access URLs
Optional but recommended:
| Tool | Why |
| Service | URL |
|---|---|
| **code-server** | Browser-based VS Code; how this project has historically been edited |
| **`gh` CLI** | Mirror repo is on GitHub via Gitea; `gh` reads issues and PRs |
| **bun** | Required for the gstack `/browse` + `/qa` skills (CLAUDE.md Lesson 82) |
| **`npx gitnexus analyze`** | Code-graph for Phase 2+ work that touches `unified_chat_service` |
| **Claude Code CLI** | If you want to run Claude Code locally on the host |
| VS Code Server | https://code.resolutionflow.com |
| Frontend (dev) | http://46.202.92.250:5173 |
| Backend API | http://46.202.92.250:8000 |
| API Docs | http://46.202.92.250:8000/docs |
---
## 2. Architectural shape
The project is three services plus your editor. Keep these facts in mind regardless of topology:
## Docker Layout
```
Your browser
├─► code-server (editor, optional — usually port 8080 or behind TLS)
├─► frontend (Vite) (dev server, port 5173)
└─► backend (FastAPI) (dev server, port 8000)
└─► PostgreSQL (port 5432)
/docker/
├── traefik/
├── docker-compose.yml → Traefik reverse proxy
└── .env → ACME_EMAIL for Let's Encrypt
└── vscode/
├── docker-compose.yml → VS Code Server
└── .env → CODE_PASSWORD
```
**The frontend calls the backend by URL at runtime.** The frontend does not proxy through the backend. Whatever URL your browser uses to reach the backend is what `VITE_API_URL` must be set to, **baked in at build time**. Changing `VITE_API_URL` requires rebuilding the frontend.
**The backend calls the database by URL at runtime.** The URL depends on where Postgres is relative to the backend — Docker service name if both are in the same compose network, `localhost` if Postgres is native on the same host, or a DNS name if they're in separate containers/VMs.
**CORS is configured explicitly.** The backend's `CORS_ORIGINS` list must include every origin your browser will use to reach the frontend. A missing origin shows up as failed preflight requests.
---
## 3. Topology choices — pick one before you start
The project is agnostic to topology, but each shape has different setup steps.
### Option A — all-in-one LXC/VM/host (simplest)
Postgres, backend, and frontend all run on one Linux host. code-server runs on the same host or a sibling. No Docker required. Best for a single-developer Proxmox LXC.
### Option B — Docker Compose on one host
Postgres, backend, and frontend run as Docker containers on one host. code-server runs outside the compose network (on the host or in another container). This is how the old Hostinger VPS was configured. Best if you want reproducible container images.
### Option C — split services across containers/VMs
Postgres in one container/VM, backend and frontend in another, code-server in a third. Most complex; requires explicit networking between them. Use only if you have a specific reason.
**Pick one and stick with it for the entire setup.** Mixing Options A and B halfway through is where setup runs off the rails.
---
## 4. Per-host configuration
These values are specific to your host. Fill them in once and reference them by name throughout the rest of the doc.
Project lives inside the VS Code Server Docker volume:
```
DEV_HOST = <hostname or IP your browser uses, e.g. dev.internal, 10.0.0.42>
DEV_HOST_SCHEME = <http or https; http is fine for internal dev, https if behind a TLS proxy>
FRONTEND_PORT = 5173
BACKEND_PORT = 8000
POSTGRES_PORT = 5433 # host-side port. 5433 is the recommended default on any shared host to avoid collision with a host-level Postgres. The container's internal port stays 5432.
POSTGRES_DB_NAME = resolutionflow
POSTGRES_USER = postgres
POSTGRES_PASSWORD = <local-dev-password; anything, this is not prod>
SECRET_KEY = <openssl rand -hex 32 — generate fresh per host, do not reuse>
ANTHROPIC_API_KEY = <from https://console.anthropic.com>
GOOGLE_AI_API_KEY = <optional, only if using Gemini as a fallback>
/var/lib/docker/volumes/vscode_vscode-data/_data/resolutionflow/
```
Store these somewhere you can copy from during setup. Do not commit them.
## VS Code Server
> **Naming note:** the canonical database name is `resolutionflow`. If you see `patherly` in a config file, that's drift from an earlier rename and is being swept in a separate commit — use `resolutionflow`. CLAUDE.md tracks the live-code files that still reference `patherly`.
- **Container user:** `coder` (UID 1000)
- **Home directory:** `/home/coder`
- **Project location:** `/home/coder/resolutionflow`
- **Host volume path:** `/var/lib/docker/volumes/vscode_vscode-data/_data`
- **Access URL:** `https://code.resolutionflow.com`
- **HTTPS:** Auto-provisioned via Traefik + Let's Encrypt
---
### Compose File Location
`/docker/vscode/docker-compose.yml`
## 5. Setup procedure
## Traefik
Run these in order. Stop at the first failure and investigate.
Handles reverse proxying and automatic SSL for all services. HTTP automatically redirects to HTTPS.
### 5.1 Install system dependencies
### Adding A New Service Behind Traefik
Add these labels to any new Docker service:
```yaml
labels:
- "traefik.enable=true"
- "traefik.http.routers.<n>.rule=Host(`subdomain.resolutionflow.com`)"
- "traefik.http.routers.<n>.entrypoints=websecure"
- "traefik.http.routers.<n>.tls.certresolver=letsencrypt"
- "traefik.http.services.<n>.loadbalancer.server.port=<port>"
```
Also create an A record in DNS pointing the subdomain to `46.202.92.250`.
## ResolutionFlow Dev Stack
### Important: No Docker Inside VS Code Container
The VS Code Server container does NOT have Docker. All `docker compose` commands must be run via SSH as root on the host.
### Environment Files
| File | Purpose |
|---|---|
| `.env` | Root — Docker Compose interpolation (`SECRET_KEY`, `ANTHROPIC_API_KEY`, `GOOGLE_AI_API_KEY`, `POSTGRES_PORT`) |
| `backend/.env` | Backend source of truth — all FastAPI settings, API keys, DB URLs, CORS |
| `frontend/.env` | Frontend — `VITE_API_URL` pointing to backend |
### Critical Remote Access Config
**`frontend/.env`:**
```
VITE_API_URL=http://46.202.92.250:8000
```
**`backend/.env`:**
```
CORS_ORIGINS=["http://localhost:3000","http://localhost:5173","http://127.0.0.1:3000","http://127.0.0.1:5173","http://46.202.92.250:5173","http://46.202.92.250:3000","https://resolutionflow.com","https://www.resolutionflow.com"]
FRONTEND_URL=http://46.202.92.250:5173
DATABASE_URL=postgresql+asyncpg://postgres:postgres@db:5432/resolutionflow
DATABASE_URL_SYNC=postgresql://postgres:postgres@db:5432/resolutionflow
```
Note: `DATABASE_URL` uses `@db:5432` (Docker service name), not `@localhost`.
**`docker-compose.dev.yml`:**
```yaml
- VITE_API_URL=http://46.202.92.250:8000
```
### Starting the Dev Environment
SSH into host as root:
```bash
# Ubuntu / Debian
sudo apt update && sudo apt install -y \
git curl build-essential \
python3.11 python3.11-venv python3-pip \
postgresql-client # not the server — only if running Postgres natively
# Node 20 via nvm (survives container rebuilds if stored in a volume)
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash
export NVM_DIR="$HOME/.nvm" && source "$NVM_DIR/nvm.sh"
nvm install 20
nvm alias default 20
cd /var/lib/docker/volumes/vscode_vscode-data/_data/resolutionflow
docker compose -f docker-compose.dev.yml up -d
```
For Option B (Docker Compose), also:
### Running Migrations (Fresh Database)
```bash
curl -fsSL https://get.docker.com | sh
sudo usermod -aG docker $USER # log out and back in for this to take effect
```
### 5.2 Clone the repo
```bash
git clone https://gitea.resolutionflow.com/chihlasm/resolutionflow.git
# or the GitHub mirror:
# git clone https://github.com/chihlasm/resolutionflow.git
cd resolutionflow
# Check out the working branch if you're continuing mid-migration.
git fetch origin
git checkout feat/flowpilot-migration
```
### 5.3 Start PostgreSQL
**Option A (native Postgres on the host):**
```bash
sudo apt install -y postgresql-16
sudo -u postgres psql -c "CREATE DATABASE resolutionflow;"
sudo -u postgres psql -c "ALTER USER postgres PASSWORD 'postgres';"
# Adjust pg_hba.conf if you need non-local connections.
```
**Option B (Postgres via Docker Compose):** The repo has a `docker-compose.dev.yml` at the root. Check its Postgres service for the container name, port mapping, and volume. The local compose defaults use container name `resolutionflow_postgres`, database `resolutionflow`, and host-side port `5433` (mapped to the container's internal `5432`) — see CLAUDE.md Lesson 65. The host-side `5433` is the recommended default on any shared host: it keeps the port free for a host-level Postgres if you ever need one. The compose file also defines explicit `command:` directives on both `backend` and `frontend` to force `--host 0.0.0.0`, and expects the caller to pass `REPO_ROOT` (see 5.4) for bind-mount resolution. Confirm what the compose file actually says on your branch before trusting these values.
```bash
docker compose -f docker-compose.dev.yml up -d db
docker compose -f docker-compose.dev.yml logs db # wait for "ready to accept connections"
```
**Verify:**
```bash
# From the host (Option A) or the backend container/LXC (Option B):
psql -h <db-host> -p <POSTGRES_PORT> -U postgres -d resolutionflow -c "SELECT now();"
```
### 5.4 Write the `.env` files
The repo expects three env files. Create each one:
**`backend/.env`** — backend source of truth:
```bash
APP_NAME=ResolutionFlow
DEBUG=true
# DB URLs — `<db-host>` is `localhost` for Option A, the Docker service name
# (e.g. `db`) for Option B, or the DB container/VM hostname for Option C.
DATABASE_URL=postgresql+asyncpg://postgres:postgres@<db-host>:<POSTGRES_PORT>/resolutionflow
DATABASE_URL_SYNC=postgresql://postgres:postgres@<db-host>:<POSTGRES_PORT>/resolutionflow
# Auth
SECRET_KEY=<SECRET_KEY>
ACCESS_TOKEN_EXPIRE_MINUTES=5
REFRESH_TOKEN_EXPIRE_DAYS=7
REQUIRE_INVITE_CODE=true
# AI providers
AI_PROVIDER=anthropic
ANTHROPIC_API_KEY=<ANTHROPIC_API_KEY>
GOOGLE_AI_API_KEY=<GOOGLE_AI_API_KEY or leave unset>
# FlowPilot MCP telemetry — leave on so the Phase 0.5 baseline data keeps accruing
ENABLE_MCP_MICROSOFT_LEARN=true
# CORS + frontend URL
FRONTEND_URL=<DEV_HOST_SCHEME>://<DEV_HOST>:<FRONTEND_PORT>
CORS_ORIGINS=["http://localhost:5173","http://127.0.0.1:5173","<DEV_HOST_SCHEME>://<DEV_HOST>:<FRONTEND_PORT>"]
```
**`frontend/.env.local`** — frontend build-time config:
```bash
VITE_API_URL=<DEV_HOST_SCHEME>://<DEV_HOST>:<BACKEND_PORT>
```
Optional PostHog (CLAUDE.md Lesson 64 — enables product analytics locally):
```bash
VITE_PUBLIC_POSTHOG_KEY=<from PostHog project settings>
VITE_PUBLIC_POSTHOG_HOST=https://us.i.posthog.com
```
**Repo root `.env`** — only needed for Option B (Docker Compose interpolation):
```bash
SECRET_KEY=<SECRET_KEY>
ANTHROPIC_API_KEY=<ANTHROPIC_API_KEY>
GOOGLE_AI_API_KEY=<GOOGLE_AI_API_KEY or leave unset>
POSTGRES_PORT=<POSTGRES_PORT>
# Absolute host-side path to the repo root. REQUIRED whenever docker-compose is
# invoked from inside a container (e.g. a code-server container with the host
# Docker socket mounted in). Without it, the bind mounts in
# docker-compose.dev.yml (`${REPO_ROOT}/backend:/app`, `${REPO_ROOT}/frontend:/app`)
# resolve against the CLI's CWD — a path the host daemon cannot see — and
# Docker silently creates empty directories there instead of mounting the code.
# If you run docker compose directly on the host shell, you can set this to `.`
# or the absolute path of the repo; being explicit is safer either way.
REPO_ROOT=/absolute/path/to/resolutionflow
```
> **Never commit any `.env` file.** The `.gitignore` already covers this.
### 5.5 Run the backend setup
**Option A (native):**
```bash
cd backend
python3.11 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
# Migrate the DB to head.
alembic upgrade head
```
**Option B (Docker):**
```bash
docker compose -f docker-compose.dev.yml up -d backend
cd /var/lib/docker/volumes/vscode_vscode-data/_data/resolutionflow
docker compose -f docker-compose.dev.yml run --rm backend alembic upgrade head
```
**Expected alembic head** (as of `feat/flowpilot-migration`): `f07010f17b01`. If `alembic current` shows anything else after `upgrade head`, something has gone wrong — stop and investigate.
### 5.6 Seed test users
### Seeding Test Users
```bash
# Option A
cd backend && source venv/bin/activate
python -m scripts.seed_test_users
# Option B
docker exec resolutionflow_backend python -m scripts.seed_test_users
```
Test users (all share password `TestPass123!`):
Test accounts (password: `TestPass123!`):
| Email | Role |
|---|---|
| `admin@resolutionflow.example.com` | super admin |
| `teamadmin@resolutionflow.example.com` | team admin |
| `engineer@resolutionflow.example.com` | engineer |
| `pro@resolutionflow.example.com` | solo pro |
| Email | Role | Plan |
|---|---|---|
| admin@resolutionflow.example.com | Owner | Team |
| pro@resolutionflow.example.com | Owner | Pro |
| teamadmin@resolutionflow.example.com | Owner | Team |
| engineer@resolutionflow.example.com | Engineer | Shared |
### 5.7 Run the backend
**Option A:**
```bash
cd backend && source venv/bin/activate
uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
```
**Option B:** Already running from `docker compose up -d backend`. Tail logs:
```bash
docker compose -f docker-compose.dev.yml logs -f backend
```
**Verify:** `curl <DEV_HOST_SCHEME>://<DEV_HOST>:<BACKEND_PORT>/api/docs` — OpenAPI docs page loads.
### 5.8 Run the frontend
**Option A:**
```bash
cd frontend
npm install
npm run dev -- --host 0.0.0.0 --port 5173
```
**Option B:**
### Rebuilding After Config Changes
**Frontend** (Vite bakes env vars at build time — requires rebuild):
```bash
cd /var/lib/docker/volumes/vscode_vscode-data/_data/resolutionflow
docker compose -f docker-compose.dev.yml up -d --build frontend
```
**Verify:** Open `<DEV_HOST_SCHEME>://<DEV_HOST>:<FRONTEND_PORT>` in your browser. Log in with one of the test users. Navigate to `/pilot` — the FlowPilot session page should render.
---
## 6. Verification — proof the env actually works
Run these after setup. Every item has a concrete expected outcome.
### 6.1 Database schema is at the right version
**Backend** (restart only):
```bash
# Option A
cd backend && source venv/bin/activate && alembic current
# Option B
docker compose -f docker-compose.dev.yml run --rm backend alembic current
```
Expected: `f07010f17b01 (head)` on the `feat/flowpilot-migration` branch. On `main`, expected: `074 (head)`.
### 6.2 Alembic reversibility
```bash
alembic downgrade -1 # should complete cleanly
alembic upgrade head # should return to f07010f17b01
```
If either step fails, the migration has a bug and Phase 2 cannot start.
### 6.3 Prompt-cache hit verification (the deferred Phase 0 TODO)
`backend/app/core/ai_provider.py` module docstring has a `TODO(phase0-verify)` note describing this. Procedure:
1. Confirm `AI_PROVIDER=anthropic` and `ANTHROPIC_API_KEY` is set in `backend/.env`.
2. Start the backend with log level INFO or lower.
3. In the UI, open `/pilot` and send a chat message. Wait a few seconds for the response.
4. Send a second chat message in the same session, within 5 minutes of the first.
5. In backend logs, grep for lines containing `anthropic.cache`:
```bash
# Option A
grep 'anthropic.cache' <log-path>
# Option B
docker compose -f docker-compose.dev.yml logs backend | grep 'anthropic.cache'
```
6. Expected: two `anthropic.cache` log events. First has `cache_creation_input_tokens > 0`. Second has `cache_read_input_tokens > 0`.
7. If the second shows zero reads, inspect the prompt prefix for silent invalidators (timestamps, unsorted JSON keys, varying tool list ordering). Fix before proceeding with any Phase 2 work.
### 6.4 Frontend build is TypeScript-clean
```bash
cd frontend
npx tsc -b # no errors
npm run build # no errors
```
CLAUDE.md Lesson 105 notes that `npm run build` may fail with an `EACCES` on `dist/` inside code-server — that is a Docker filesystem permission issue, not a real build error. Use `npx tsc -b` to verify TypeScript cleanliness in that case.
### 6.5 `/assistant` → `/pilot` redirect
Open `<DEV_HOST_SCHEME>://<DEV_HOST>:<FRONTEND_PORT>/assistant/<some-real-session-id>` in the browser. Expected: URL changes to `/pilot/<that-id>`; the FlowPilot session page renders. Bare `/assistant` redirects to bare `/pilot`.
### 6.6 Dispatcher de-branching
Navigate to the dashboard. Click a session in `ActiveFlowPilotSessions` or `RecentFlowPilotSessions`. Expected: routes to `/pilot/:id` regardless of the session's `session_type` value. (Check the browser URL bar.)
### 6.7 CORS
Open the browser DevTools Network tab, navigate to any backend-hitting page. Expected: no CORS errors. If you see "blocked by CORS policy," the missing origin needs adding to `backend/.env`'s `CORS_ORIGINS`.
---
## 7. Runbook
Day-to-day commands after setup is complete.
### Restart services
```bash
# Option A
# backend — Ctrl-C and re-run uvicorn
# frontend — Ctrl-C and re-run npm run dev
# Option B
docker compose -f docker-compose.dev.yml restart backend
docker compose -f docker-compose.dev.yml up -d --build frontend # rebuild required if VITE_* changed
docker compose -f docker-compose.dev.yml down && docker compose -f docker-compose.dev.yml up -d # full restart
```
### Apply a new migration
**Full restart:**
```bash
docker compose -f docker-compose.dev.yml down
docker compose -f docker-compose.dev.yml up -d
```
## Installed Tools (Inside VS Code Server Container)
Installed in `/home/coder` — persists via Docker volume:
- **nvm** — Node version manager
- **Node.js 20.x** — via nvm, default alias set
- **npm** — latest
- **GitHub CLI (gh)** — authenticated via personal access token
- **Claude Code CLI** — `@anthropic-ai/claude-code` (global npm)
### Permanent Tool Installs
Tools installed via `apt` inside the container do NOT survive container rebuilds. To add permanently, modify the VS Code Server Docker image and rebuild.
Temporary (session only):
```bash
sudo apt update && sudo apt install -y <tool>
```
## SSH Access
```bash
# Option A
cd backend && source venv/bin/activate && alembic upgrade head
# Option B
docker compose -f docker-compose.dev.yml run --rm backend alembic upgrade head
ssh root@46.202.92.250
```
### Create a new migration
Key auth configured via `~/.ssh/authorized_keys` on host.
## Useful Commands
### Check all running containers
```bash
# Option A
cd backend && source venv/bin/activate
alembic revision -m "short description" # manual, preferred per CLAUDE.md Lesson 77
# OR
alembic revision --autogenerate -m "description" # pulls in drift; review carefully
docker ps --format "table {{.Names}}\t{{.Status}}\t{{.Ports}}"
```
Never pass `--rev-id` — let Alembic generate the hex hash.
### Inspect the database
### View container logs
```bash
# Option A (native Postgres)
psql -h localhost -p 5432 -U postgres -d resolutionflow
# Option B (Docker)
docker exec -it resolutionflow_postgres psql -U postgres -d resolutionflow
docker logs <container_name> --tail 30 -f
```
### Run tests
### Restart VS Code Server
```bash
# Option A
cd backend && source venv/bin/activate
pytest --override-ini="addopts="
# Option B
docker compose -f docker-compose.dev.yml run --rm backend pytest --override-ini="addopts="
cd /docker/vscode && docker compose restart
```
First time only, create the test database:
### Restart Traefik
```bash
# Option A
sudo -u postgres psql -c "CREATE DATABASE resolutionflow_test;"
# Option B
docker exec -it resolutionflow_postgres psql -U postgres -c "CREATE DATABASE resolutionflow_test;"
cd /docker/traefik && docker compose restart
```
### View backend logs
### Restart dev stack
```bash
# Option A: wherever you ran uvicorn
# Option B
docker compose -f docker-compose.dev.yml logs -f --tail=100 backend
cd /var/lib/docker/volumes/vscode_vscode-data/_data/resolutionflow
docker compose -f docker-compose.dev.yml down
docker compose -f docker-compose.dev.yml up -d
```
Structured events to grep for:
- `anthropic.cache` — prompt-cache hit/creation telemetry (Phase 0.1)
- `mcp.turn` — per-turn MCP availability/invocation (Phase 0.5)
- `mcp.fallback` — MCP silent-retry fallback fired (Phase 0.5)
---
## 8. Troubleshooting
### CORS errors in the browser
The backend did not accept the origin your browser used. Check `backend/.env`'s `CORS_ORIGINS` — it must include the exact scheme + host + port the browser sent. Restart the backend after editing.
### `VITE_API_URL` points at the wrong place
The frontend was built with a stale value. Rebuild the frontend. Option B: `docker compose up -d --build frontend`. Option A: restart `npm run dev`.
### `alembic upgrade head` fails with "target database is not up to date"
Your DB migration chain is out of sync with the code. On a dev box, the safe recovery is to drop the DB and re-migrate from scratch:
### Check swap
```bash
# Option A
sudo -u postgres psql -c "DROP DATABASE resolutionflow;" -c "CREATE DATABASE resolutionflow;"
cd backend && source venv/bin/activate && alembic upgrade head
# Option B
docker exec resolutionflow_postgres psql -U postgres -c "DROP DATABASE resolutionflow;" -c "CREATE DATABASE resolutionflow;"
docker compose -f docker-compose.dev.yml run --rm backend alembic upgrade head
free -h && swapon --show
```
Only do this on a dev box — it destroys all local data.
### `alembic heads` shows more than one head
Only on a local branch that has diverged from `origin/main`. Production `main` has a single head. If this happens on a fresh clone, one of your local migration files has the wrong `down_revision`. Inspect each file's `down_revision` and reconnect the chain.
### Frontend build fails with "EACCES: permission denied" on `dist/`
Filesystem permission issue inside the code-server container (CLAUDE.md Lesson 105). TypeScript compilation itself completes — use `npx tsc -b` to verify cleanliness without needing to write to `dist/`.
### Backend/frontend containers start but `/app` is empty (no code mounted)
Almost always a `REPO_ROOT` problem. `docker-compose.dev.yml` uses `${REPO_ROOT}/backend:/app` and `${REPO_ROOT}/frontend:/app` bind mounts. If `REPO_ROOT` is unset, or set to a path that doesn't exist *on the Docker host* (not inside the code-server container), Docker silently creates an empty directory at that path and mounts it — the containers come up but have no source code. Symptom: backend returns import errors, or frontend serves a default Vite page. Fix: set `REPO_ROOT` in the repo-root `.env` to the absolute host-side path to the repo, then `docker compose down && docker compose up -d`. See 5.4 for the full note. This matters specifically when `docker compose` is invoked from inside a container (e.g. code-server with the host Docker socket mounted) — the CLI's CWD is container-local but the daemon resolves paths against the host filesystem.
### Frontend shows "Blocked request. This host is not allowed" in the browser
Vite 5+ ships DNS-rebinding protection that rejects any `Host:` header not in `server.allowedHosts`. The browser's hostname must be in that list. Edit `frontend/vite.config.ts` — the `server.allowedHosts` array should include every hostname you reach the dev server from (e.g. `'docker-01'`, `'localhost'`, `.ts.net` as a wildcard for Tailscale MagicDNS). Restart the Vite dev server (for Option B: `docker compose restart frontend`). This is unrelated to CORS — Vite blocks the request before any app code runs.
### `docker` command not found inside code-server
If your code-server is itself inside a container, Docker is probably not exposed to it. CLAUDE.md Lesson 103 was written for this case on the old VPS. On Proxmox, the fix depends on topology — either SSH to the host to run Docker commands, or mount the host's Docker socket into the code-server container.
### Backend returns 500 with `InsufficientPrivilegeError: new row violates row-level security policy`
RLS is enabled on a table your code wrote to without the right `account_id`. CLAUDE.md Lessons 107, 108, 110 cover this family of bugs. The fix is always at the service layer: make sure every model creation passes `account_id=` explicitly, and that startup routines that touch tenant-isolated tables use `_admin_session_factory()` rather than `get_db()`.
### Anthropic cache reads are zero on the second turn
Something in the cached prefix is changing between turns. Inspect the system-block list and the first N history messages for timestamps, `datetime.now()`, unsorted dict keys in JSON prompts, or varying tool-list order. The `anthropic.cache` telemetry shows exactly how many tokens were read vs created — use it to narrow down the invalidator.
---
## 9. Security posture for dev environments
This doc is about dev, not production. But:
- Never commit `.env` files. The `.gitignore` covers this.
- `SECRET_KEY` should be generated per-host, not reused across environments.
- `ANTHROPIC_API_KEY` is billable — rotate if leaked into logs or chat.
- Postgres on a dev host should not be exposed to the internet. Bind it to `127.0.0.1` or to a private network interface only.
- If you expose the frontend or backend publicly (for teammates to test against), put it behind TLS with a real certificate. Do not let dev credentials travel over plain HTTP on the public internet.
---
## 10. What's not in this doc
- **Production deployment.** This is a dev-env doc. Production lives on Railway — see `CLAUDE.md`'s Deployment section.
- **How to set up Traefik or any particular reverse proxy.** Whichever proxy you use is your choice; the dev stack just needs something that routes `<host>:5173` and `<host>:8000` to the right services. **Direct port exposure over a private network** (Tailscale, WireGuard, a VPN, or a LAN behind a firewall) is a fully supported option for dev and is what the homelab reference topology in Section 11 uses — no reverse proxy, no TLS, just `http://<host>:5173` and `http://<host>:8000` reachable only from the private network. That's a perfectly reasonable choice; it's just not the only one.
- **How to configure code-server itself.** Install it however you prefer (native, Docker, LXC); point it at the repo, and the rest of this doc applies.
- **Where to host the Proxmox instance.** Up to you.
If something in this doc turns out to be wrong on your host, fix the doc. This is a living document — the whole point of rewriting it from the Hostinger-specific version was to make it survive host changes.
---
## 11. Reference topology: homelab Proxmox + code-server (Option B)
This section documents the first concrete host instantiation since the April 2026 host-agnostic rewrite. It's a worked example, not the canonical topology — Section 3's Option A/B/C framing still stands. If your setup looks different, follow Sections 110 and ignore this appendix.
### 11.1 Host
- **Hypervisor:** Proxmox (homelab).
- **VM:** `docker-01`, Debian 13, running Docker Engine + Docker Compose natively.
- **Tailscale IP:** `100.64.78.44`. MagicDNS hostname: `docker-01` (and the full `.ts.net` FQDN).
- **code-server:** runs on the same VM in its own container, with the host's Docker socket mounted in so it can drive `docker compose`. Its workspace bind-mounts the repo at `/opt/docker/code-server/workspace/resolutionflow`.
This is a concrete instance of Option B from Section 3: Postgres, backend, and frontend all run as containers from `docker-compose.dev.yml`; the editor lives outside that compose network.
### 11.2 Access pattern — direct port over Tailscale, no reverse proxy
The browser reaches the dev stack directly:
- Frontend: `http://docker-01:5173`
- Backend: `http://docker-01:8000`
- Backend API docs: `http://docker-01:8000/api/docs`
There is **no Caddy, no Traefik, no nginx, no TLS, no basic auth** in front of either service. The tailnet provides the wire encryption and access control — only devices on the tailnet can resolve `docker-01` or reach `100.64.78.44`, and Tailscale ACLs decide which of those devices are allowed to connect.
Why this choice:
- **Zero routing config to maintain.** There is no proxy rulebook to keep in sync with new services. Add a container, expose a port, you're done.
- **Backend-to-backend services stay private.** Redis, Celery workers, the planned ConnectWise proxy, the MCP server — none of them need to be reachable from the browser, so none of them need proxy rules. They stay inside the `resolutionflow` Docker network and talk by service name. The proxy would only ever have carried frontend and backend traffic, so the proxy's value was small relative to its maintenance cost.
- **Debuggability.** `curl http://docker-01:8000/api/docs` from any tailnet device works without auth headers, TLS handshakes, or DNS shenanigans.
Tradeoff: **this only works because every client device is on the tailnet.** If someone needed to test from a non-tailnet device, they'd either join the tailnet or we'd need to front the stack with a proxy. For the current single-developer setup, the tailnet-only assumption holds.
### 11.3 Per-host config values (as actually configured on `docker-01`)
Plugging these into Section 4's template:
```
DEV_HOST = docker-01
DEV_HOST_SCHEME = http
FRONTEND_PORT = 5173
BACKEND_PORT = 8000
POSTGRES_PORT = 5433 # host-side; container-internal stays 5432
POSTGRES_DB_NAME = resolutionflow
POSTGRES_USER = postgres
POSTGRES_PASSWORD = postgres # local-dev only
SECRET_KEY = <generated per host; do not reuse>
ANTHROPIC_API_KEY = <from console.anthropic.com>
GOOGLE_AI_API_KEY = <unset; Anthropic is sole provider in dev>
```
And the repo-root `.env` that `docker-compose.dev.yml` interpolates from:
### Check disk
```bash
SECRET_KEY=<redacted>
ANTHROPIC_API_KEY=<redacted>
POSTGRES_PORT=5433
REPO_ROOT=/opt/docker/code-server/workspace/resolutionflow
df -h
```
### 11.4 Why `REPO_ROOT` is non-optional on this host
code-server runs inside a container. When you open a terminal in code-server and run `docker compose -f docker-compose.dev.yml up -d`, the Docker CLI talks to the *host* daemon via the mounted socket — but the CWD it reports (`/config/workspace/resolutionflow`) is a path that only exists inside the code-server container. The host daemon has never heard of it.
Relative bind mounts like `./backend:/app` therefore resolve against a path the host can't see, and Docker silently creates empty directories there rather than erroring out. The containers come up, but `/app` is empty.
`docker-compose.dev.yml` sidesteps this by using `${REPO_ROOT}/backend:/app` and `${REPO_ROOT}/frontend:/app`. `REPO_ROOT` must be set to the absolute path **on the host** (`/opt/docker/code-server/workspace/resolutionflow`), not the path inside the code-server container. Same contents, different mount point, different name.
If you ever run `docker compose` directly from a host shell (SSH'd into `docker-01`), set `REPO_ROOT` to `.` or the absolute host path. Being explicit is always safe; leaving it unset is the failure mode.
### 11.5 Vite `server.allowedHosts` — required for `docker-01` to resolve
Vite 5+ rejects any `Host:` header not in `server.allowedHosts` (DNS-rebinding protection). `frontend/vite.config.ts` has:
```ts
server: {
host: '0.0.0.0',
allowedHosts: ['docker-01', '.ts.net', 'localhost'],
...
}
```
- `docker-01` — the MagicDNS short name the browser uses day-to-day.
- `.ts.net` — wildcard for the full Tailscale MagicDNS FQDN, in case anyone uses it.
- `localhost` — for the "am I serving anything at all" smoke-test from inside the container.
If you move this setup to a different host, add that host's hostname to `allowedHosts` or the browser will see "Blocked request. This host is not allowed." See Section 8's troubleshooting entry for the full symptom/fix.
### 11.6 CORS origins on this host
The `backend` service's `CORS_ORIGINS` environment variable is pinned in the compose file to:
```
["http://localhost:5173","http://127.0.0.1:5173","http://docker-01:5173","http://100.64.78.44:5173"]
```
The last two are what make browser calls from tailnet clients work — they cover both MagicDNS (`docker-01`) and the raw Tailscale IP. If you add a new hostname to reach the frontend from, also add the matching origin here and restart the backend.
### 11.7 Compose file shape (as of this writing)
`docker-compose.dev.yml` has been through a round of cleanup for this topology. Specifics worth knowing if you're comparing against older revisions of the file:
- **No Traefik labels.** They were removed — nothing in this topology uses Traefik.
- **No Hostinger-VPS-era origins** in `CORS_ORIGINS`.
- `Dockerfile.dev` for both `backend` and `frontend` is still the build source — this didn't change.
- Explicit `command:` directives on both `backend` (`uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload`) and `frontend` (`npm run dev -- --host 0.0.0.0 --port 5173`) — this guarantees `--host 0.0.0.0` regardless of what's baked into the image, so the services listen on all interfaces and are reachable from outside the container.
- `REPO_ROOT` is interpolated into both service volume mounts (see 11.4).
If you're adapting the file for a different host, the things most likely to need editing are `REPO_ROOT` (see 11.4), `CORS_ORIGINS` (see 11.6), `FRONTEND_URL`, `VITE_API_URL`, and `POSTGRES_PORT` if you want something other than `5433`.
### 11.8 End-to-end sanity check for this topology
From any device on the tailnet:
### Check memory + container usage
```bash
# Backend reachable
curl -sSf http://docker-01:8000/api/docs >/dev/null && echo OK
# Frontend reachable
curl -sSf http://docker-01:5173 >/dev/null && echo OK
# Alembic head matches the branch expectation
docker exec resolutionflow_backend alembic current
# expect f07010f17b01 on feat/flowpilot-migration, 074 on main
# Postgres is alive inside the compose network
docker exec resolutionflow_postgres psql -U postgres -d resolutionflow -c "SELECT now();"
free -h && docker stats --no-stream
```
All four passing = the dev environment is live end-to-end.
## DNS Records (resolutionflow.com)
| Type | Name | Value | Purpose |
|---|---|---|---|
| A | code | 46.202.92.250 | VS Code Server |
## Security Notes
- UFW is inactive — Traefik and Docker manage port exposure
- All public-facing services run through Traefik with valid HTTPS certs
- PostgreSQL port 5432 is exposed on all interfaces — restrict if needed in production
- Rotate API keys (Anthropic, Voyage) if ever exposed in logs or chat
- Never commit `.env` files to Git
## VS Code Server Browser Tips
- **Command Palette:** `F1`
- **Terminal:** Ctrl+`
- **Rename file:** `F2`
- **Go to definition:** `F12`
- **Find references:** `Shift+F12`
- **Context Menu:** `Alt + Right Click`

70
SESSION-HANDOFF.md Normal file
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# Session Handoff — Design System v4 Migration
> **For the next Claude session:** Read this file completely, internalize the context, then delete it (`rm SESSION-HANDOFF.md`). This is a one-time context transfer.
---
## What Was Done This Session
### 1. FlowPilot Message Bar + AI Script Builder (MERGED to main)
- PR #118 merged. Always-visible message bar in FlowPilot sessions, AI Script Builder at `/script-builder`, library reorg (My/Team Scripts tabs), FlowPilot-to-Script-Builder handoff, session abandon/close, unified session history.
- Eng review completed: normalized `script_builder_messages` table, typed content helpers, 6 edge case tests.
### 2. Design System v4 Migration (PR #119, open, branch: `refactor/design-system-v4`)
- Complete frontend redesign from glassmorphism to flat dark theme (Sentry/PostHog-inspired)
- **CSS Foundation:** New color tokens in `index.css`, all via CSS custom properties. Light mode ready (just needs `.light` class values).
- **Icon Rail Sidebar:** 72px rail with 5 grouped icons (Home, Work, Knowledge, Insights, Help). Full-height resizable drawer on hover. Pin-to-expand to 260px. Mobile hamburger overlay.
- **Component Sweep:** ~200 files migrated. All hardcoded hex replaced with semantic Tailwind tokens (bg-card, text-foreground, border-border, etc.).
- **Landing Page:** Flat surfaces, no glow, solid buttons.
- **Interactive Shadows:** Dark-mode-aware — elevated surfaces + faint cyan accent glow (black shadows invisible on dark bg).
- **Stat Cards:** 3px colored left borders.
- **Tab Toggles:** Active state uses `tab-active-shadow` (elevated bg + faint glow).
### 3. GTM Strategy (from /office-hours)
- Shadow & Ship approach: Michael uses ResolutionFlow on real tickets for 2 weeks, then hands logins to 5 MSP colleagues. Key metric: unprompted return.
- Design doc at `~/.gstack/projects/patherly-patherly/`
---
## What Needs To Be Done Next
### Immediate (Design System v4 polish)
1. **Home icon color fix:** The Home icon in the sidebar shouldn't have a cyan background when not active. Instead, the Home icon itself should always be cyan (brand accent), and only show the `bg-accent-dim` background when the route is actually `/`. Michael specifically requested this.
2. **Visual QA pass:** Michael hasn't done a full page-by-page walkthrough yet. Expect feedback on individual pages once he does.
3. **`font-label` cleanup:** ~10 files still reference `font-label` (deprecated alias for `font-mono`). Each needs inspection — some should be `font-mono`, others `font-sans text-xs`.
4. **Inline `style` attributes:** ~29 instances still use hardcoded hex in inline styles (sidebar, drawer, badges). Should be converted to CSS variable references or Tailwind classes where possible.
### Before Merging PR #119
- Run migrations: `docker exec resolutionflow_backend alembic upgrade head` (new tables from the Script Builder PR are on main now)
- Full visual QA with backend running
- Test mobile responsive (hamburger menu)
- Test FlowPilot session with new message bar + action bar positioning
### Future
- **Light mode toggle:** CSS variables are ready. Need to add `.light` class values in `index.css` + toggle in user settings/account page.
- **Script Builder testing:** The AI Script Builder hasn't been tested end-to-end with the backend running yet.
---
## Key Files to Know
| File | What it does |
|------|-------------|
| `DESIGN-SYSTEM.md` | Single source of truth for all design decisions |
| `frontend/src/index.css` | CSS tokens, component utilities, shadow patterns |
| `frontend/src/components/layout/Sidebar.tsx` | Icon rail + drawer + pinned sidebar |
| `frontend/src/components/layout/AppLayout.tsx` | CSS Grid shell |
| `frontend/src/components/dashboard/StartSessionInput.tsx` | The Guided/Chat toggle |
| `frontend/src/components/dashboard/PerformanceCards.tsx` | Stat cards with colored borders |
## Key Lessons From This Session
- The component sweep agents missed `editor-ai/`, `guides/`, `maintenance/`, `scripts/`, `settings/` directories and `text-brand-dark` references. Always do a final grep audit after sweeps.
- `bg-[#hex]` hardcoding defeats the purpose of CSS variables. We had to do a second pass to replace 3,200+ hardcoded values with semantic tokens.
- Black shadows (`rgba(0,0,0,...)`) are invisible on dark backgrounds. Use elevated surfaces + faint accent glow instead.
- The sidebar flyout needed `position: fixed` to escape the CSS Grid cell clipping — `absolute` positioning was hidden behind the main content area.
- Flyout hover timing: individual item `onMouseLeave` was killing the flyout before the mouse reached the drawer. Only the outer wrapper should handle `onMouseLeave`.
---
> **After reading this file:** Save relevant context to your session memory, then run `rm SESSION-HANDOFF.md` and `git add -A && git commit -m "chore: remove session handoff file"`.

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0.1.0.0

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"""Add account-scoped device_types table with platform seed data.
Revision ID: 073
Revises: b3c7e9f2a1d8
Create Date: 2026-04-12
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects.postgresql import UUID
import uuid
revision = "073"
down_revision = "b3c7e9f2a1d8"
branch_labels = None
depends_on = None
_PLATFORM_UUID = "00000000-0000-0000-0000-000000000001"
_CURRENT_ACCOUNT = (
"COALESCE("
"NULLIF(current_setting('app.current_account_id', TRUE), ''), "
"'00000000-0000-0000-0000-000000000000'"
")::uuid"
)
SYSTEM_DEVICE_TYPES = [
("router", "Router", "network", 0),
("switch", "Switch", "network", 1),
("firewall", "Firewall", "network", 2),
("access-point", "Access Point", "network", 3),
("load-balancer", "Load Balancer", "network", 4),
("server", "Server", "compute", 0),
("workstation", "Workstation", "compute", 1),
("vm", "Virtual Machine", "compute", 2),
("container", "Container", "compute", 3),
("nas", "NAS", "storage", 0),
("san", "SAN", "storage", 1),
("cloud-storage", "Cloud Storage", "storage", 2),
("cloud", "Cloud", "cloud", 0),
("aws", "AWS", "cloud", 1),
("azure", "Azure", "cloud", 2),
("gcp", "Google Cloud", "cloud", 3),
("printer", "Printer", "endpoint", 0),
("phone", "Phone", "endpoint", 1),
("iot", "IoT Device", "endpoint", 2),
("camera", "Camera", "endpoint", 3),
("tablet", "Tablet", "endpoint", 4),
("laptop", "Laptop", "endpoint", 5),
("ups", "UPS", "infrastructure", 0),
("pdu", "PDU", "infrastructure", 1),
("rack", "Rack", "infrastructure", 2),
("patch-panel", "Patch Panel", "infrastructure", 3),
("nvr", "NVR", "security", 0),
("badge-reader", "Badge Reader", "security", 1),
]
def upgrade() -> None:
op.create_table(
"device_types",
sa.Column("id", UUID(as_uuid=True), primary_key=True, server_default=sa.text("gen_random_uuid()")),
sa.Column("slug", sa.String(50), nullable=False),
sa.Column("label", sa.String(100), nullable=False),
sa.Column("category", sa.String(50), nullable=False),
sa.Column("is_system", sa.Boolean(), nullable=False, server_default=sa.text("false")),
sa.Column("account_id", UUID(as_uuid=True), sa.ForeignKey("accounts.id", ondelete="CASCADE"), nullable=False),
sa.Column("sort_order", sa.Integer(), nullable=False, server_default=sa.text("0")),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("now()")),
)
op.create_unique_constraint("uq_device_types_slug_account", "device_types", ["slug", "account_id"])
op.create_index("ix_device_types_account_id", "device_types", ["account_id"])
device_types_table = sa.table(
"device_types",
sa.column("id", UUID(as_uuid=True)),
sa.column("slug", sa.String),
sa.column("label", sa.String),
sa.column("category", sa.String),
sa.column("is_system", sa.Boolean),
sa.column("account_id", UUID(as_uuid=True)),
sa.column("sort_order", sa.Integer),
)
op.bulk_insert(device_types_table, [
{
"id": uuid.uuid4(),
"slug": slug,
"label": label,
"category": category,
"is_system": True,
"account_id": uuid.UUID(_PLATFORM_UUID),
"sort_order": sort_order,
}
for slug, label, category, sort_order in SYSTEM_DEVICE_TYPES
])
op.execute("ALTER TABLE device_types ENABLE ROW LEVEL SECURITY")
op.execute("ALTER TABLE device_types FORCE ROW LEVEL SECURITY")
op.execute(f"""
CREATE POLICY device_types_select ON device_types
FOR SELECT
USING (
account_id = {_CURRENT_ACCOUNT}
OR account_id = '{_PLATFORM_UUID}'::uuid
)
""")
op.execute(f"""
CREATE POLICY device_types_insert ON device_types
FOR INSERT
WITH CHECK (account_id = {_CURRENT_ACCOUNT})
""")
op.execute(f"""
CREATE POLICY device_types_update ON device_types
FOR UPDATE
USING (account_id = {_CURRENT_ACCOUNT})
WITH CHECK (account_id = {_CURRENT_ACCOUNT})
""")
op.execute(f"""
CREATE POLICY device_types_delete ON device_types
FOR DELETE
USING (account_id = {_CURRENT_ACCOUNT})
""")
def downgrade() -> None:
op.execute("DROP POLICY IF EXISTS device_types_delete ON device_types")
op.execute("DROP POLICY IF EXISTS device_types_update ON device_types")
op.execute("DROP POLICY IF EXISTS device_types_insert ON device_types")
op.execute("DROP POLICY IF EXISTS device_types_select ON device_types")
op.execute("ALTER TABLE device_types DISABLE ROW LEVEL SECURITY")
op.drop_table("device_types")

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@@ -1,57 +0,0 @@
"""Add network_diagrams table.
Revision ID: 074
Revises: 073
Create Date: 2026-04-12
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects.postgresql import UUID, JSONB
revision = "074"
down_revision = "073"
branch_labels = None
depends_on = None
_CURRENT_ACCOUNT = (
"COALESCE("
"NULLIF(current_setting('app.current_account_id', TRUE), ''), "
"'00000000-0000-0000-0000-000000000000'"
")::uuid"
)
def upgrade() -> None:
op.create_table(
"network_diagrams",
sa.Column("id", UUID(as_uuid=True), primary_key=True, server_default=sa.text("gen_random_uuid()")),
sa.Column("account_id", UUID(as_uuid=True), sa.ForeignKey("accounts.id", ondelete="CASCADE"), nullable=False),
sa.Column("name", sa.String(255), nullable=False),
sa.Column("client_name", sa.String(255), nullable=True),
sa.Column("asset_name", sa.String(255), nullable=True),
sa.Column("description", sa.Text(), nullable=True),
sa.Column("nodes", JSONB(), nullable=False, server_default=sa.text("'[]'::jsonb")),
sa.Column("edges", JSONB(), nullable=False, server_default=sa.text("'[]'::jsonb")),
sa.Column("thumbnail_url", sa.Text(), nullable=True),
sa.Column("is_archived", sa.Boolean(), nullable=False, server_default=sa.text("false")),
sa.Column("created_by", UUID(as_uuid=True), sa.ForeignKey("users.id"), nullable=True),
sa.Column("created_at", sa.DateTime(timezone=True), server_default=sa.text("now()")),
sa.Column("updated_at", sa.DateTime(timezone=True), server_default=sa.text("now()")),
)
op.create_index("ix_network_diagrams_account_id", "network_diagrams", ["account_id"])
op.create_index("idx_network_diagrams_account_client", "network_diagrams", ["account_id", "client_name"])
op.execute("ALTER TABLE network_diagrams ENABLE ROW LEVEL SECURITY")
op.execute("ALTER TABLE network_diagrams FORCE ROW LEVEL SECURITY")
op.execute(f"""
CREATE POLICY tenant_isolation ON network_diagrams
USING (account_id = {_CURRENT_ACCOUNT})
WITH CHECK (account_id = {_CURRENT_ACCOUNT})
""")
def downgrade() -> None:
op.execute("DROP POLICY IF EXISTS tenant_isolation ON network_diagrams")
op.execute("ALTER TABLE network_diagrams DISABLE ROW LEVEL SECURITY")
op.drop_table("network_diagrams")

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"""add fix outcome tracking columns to session_suggested_fixes
Adds: status, applied_at, verified_at, partial_notes, failure_reason,
ai_outcome_proposal.
status is the outcome dimension (did the fix work?), orthogonal to the
existing user_decision column (which script-path the engineer took).
Revision ID: 6492ec8d2d5b
Revises: f07010f17b01
Create Date: 2026-04-23 18:32:38.609719
"""
from typing import Sequence, Union
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects import postgresql
# revision identifiers, used by Alembic.
revision: str = '6492ec8d2d5b'
down_revision: Union[str, None] = 'f07010f17b01'
branch_labels: Union[str, Sequence[str], None] = None
depends_on: Union[str, Sequence[str], None] = None
def upgrade() -> None:
op.add_column(
"session_suggested_fixes",
sa.Column("status", sa.String(length=20), nullable=False, server_default=sa.text("'proposed'")),
)
op.add_column(
"session_suggested_fixes",
sa.Column("applied_at", sa.DateTime(timezone=True), nullable=True),
)
op.add_column(
"session_suggested_fixes",
sa.Column("verified_at", sa.DateTime(timezone=True), nullable=True),
)
op.add_column(
"session_suggested_fixes",
sa.Column("partial_notes", sa.Text(), nullable=True),
)
op.add_column(
"session_suggested_fixes",
sa.Column("failure_reason", sa.Text(), nullable=True),
)
op.add_column(
"session_suggested_fixes",
sa.Column("ai_outcome_proposal", postgresql.JSONB(), nullable=True),
)
# Backfill before constraint creation so dismissed rows satisfy the new CHECK.
op.execute(
"UPDATE session_suggested_fixes "
"SET status = 'dismissed' "
"WHERE user_decision = 'dismissed'"
)
op.create_check_constraint(
"ck_session_suggested_fixes_status",
"session_suggested_fixes",
"status IN ('proposed', 'applied_success', 'applied_failed', 'applied_partial', 'dismissed')",
)
op.alter_column("session_suggested_fixes", "status", server_default=None)
def downgrade() -> None:
op.drop_constraint("ck_session_suggested_fixes_status", "session_suggested_fixes", type_="check")
op.drop_column("session_suggested_fixes", "ai_outcome_proposal")
op.drop_column("session_suggested_fixes", "failure_reason")
op.drop_column("session_suggested_fixes", "partial_notes")
op.drop_column("session_suggested_fixes", "verified_at")
op.drop_column("session_suggested_fixes", "applied_at")
op.drop_column("session_suggested_fixes", "status")

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"""add origin discriminator + inline idempotency to script_builder_sessions
Adds:
- origin VARCHAR(20) NOT NULL DEFAULT 'standalone' with CHECK enum
- invariant: pilot_inline rows must have ai_session_id
- partial unique index: one pilot_inline session per (user, pilot session)
Revision ID: 71efd2102f49
Revises: 6492ec8d2d5b
Create Date: 2026-04-24 04:22:10.819809
"""
from alembic import op
import sqlalchemy as sa
# revision identifiers, used by Alembic.
revision: str = '71efd2102f49'
down_revision = '6492ec8d2d5b'
branch_labels = None
depends_on = None
def upgrade() -> None:
op.add_column(
"script_builder_sessions",
sa.Column(
"origin",
sa.String(length=20),
nullable=False,
server_default=sa.text("'standalone'"),
),
)
op.create_check_constraint(
"ck_script_builder_sessions_origin",
"script_builder_sessions",
"origin IN ('standalone', 'pilot_inline')",
)
op.create_check_constraint(
"ck_script_builder_sessions_origin_ai_session",
"script_builder_sessions",
"origin <> 'pilot_inline' OR ai_session_id IS NOT NULL",
)
op.create_index(
"ux_script_builder_sessions_pilot_inline",
"script_builder_sessions",
["user_id", "ai_session_id"],
unique=True,
postgresql_where=sa.text("origin = 'pilot_inline'"),
)
# Drop the server_default — app code owns the default via model default.
op.alter_column("script_builder_sessions", "origin", server_default=None)
def downgrade() -> None:
op.drop_index(
"ux_script_builder_sessions_pilot_inline",
table_name="script_builder_sessions",
)
op.drop_constraint(
"ck_script_builder_sessions_origin_ai_session",
"script_builder_sessions",
type_="check",
)
op.drop_constraint(
"ck_script_builder_sessions_origin",
"script_builder_sessions",
type_="check",
)
op.drop_column("script_builder_sessions", "origin")

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"""FlowPilot migration Phase 1 — schema for the unified session surface.
Revision ID: f07010f17b01
Revises: 074
Create Date: 2026-04-17
Creates the backing store for the FlowPilot unified session surface:
- `session_facts` — "What we know" facts, keyed to a session, with a polymorphic
`source_ref` pointing at a task-lane item inside `ai_sessions.pending_task_lane`
(no DB-level FK; integrity enforced at the service layer per the design doc).
- `session_suggested_fixes` — AI-proposed resolution paths. Only one active
(`superseded_at IS NULL`) per session at a time.
- `draft_templates` — scripts pending post-resolve templatization
(Option 2 in the three-option dialog).
- `account_settings` — new per-account key/value settings table with a JSONB
`preferences` grab-bag. Rows are created lazily on first write.
- Column additions to `ai_sessions` — resolution/escalation markdown + external IDs,
plus `state_version` (incremented by any write that invalidates the resolution
note preview cache).
- Column additions to `script_templates` — provenance fields for templates
promoted from draft_templates.
All four new tenant-scoped tables have RLS enabled + forced with a
`tenant_isolation` policy matching the repo pattern (USING + WITH CHECK on
`account_id = app.current_account_id`). Downgrade is reversible: drops in the
inverse order of creation.
Chained from `074` (add_network_diagrams_table) per the single-head state of
production; the other local heads on feat/flowpilot-migration are branch
artifacts not present in production.
"""
from alembic import op
import sqlalchemy as sa
from sqlalchemy.dialects.postgresql import UUID, JSONB
revision = "f07010f17b01"
down_revision = "074"
branch_labels = None
depends_on = None
_CURRENT_ACCOUNT = (
"COALESCE("
"NULLIF(current_setting('app.current_account_id', TRUE), ''), "
"'00000000-0000-0000-0000-000000000000'"
")::uuid"
)
def upgrade() -> None:
# ── ai_sessions: resolution / escalation columns + state_version ───────
op.add_column(
"ai_sessions",
sa.Column("resolution_note_markdown", sa.Text(), nullable=True),
)
op.add_column(
"ai_sessions",
sa.Column("resolution_note_posted_at", sa.DateTime(timezone=True), nullable=True),
)
op.add_column(
"ai_sessions",
sa.Column("resolution_note_external_id", sa.String(128), nullable=True),
)
op.add_column(
"ai_sessions",
sa.Column("escalation_package_markdown", sa.Text(), nullable=True),
)
op.add_column(
"ai_sessions",
sa.Column("escalation_package_posted_at", sa.DateTime(timezone=True), nullable=True),
)
op.add_column(
"ai_sessions",
sa.Column("escalation_package_external_id", sa.String(128), nullable=True),
)
op.add_column(
"ai_sessions",
sa.Column(
"state_version",
sa.Integer(),
nullable=False,
server_default=sa.text("0"),
),
)
# ── script_templates: provenance for post-resolve promotion ────────────
op.add_column(
"script_templates",
sa.Column(
"source_session_id",
UUID(as_uuid=True),
sa.ForeignKey("ai_sessions.id"),
nullable=True,
),
)
op.add_column(
"script_templates",
sa.Column(
"source_user_id",
UUID(as_uuid=True),
sa.ForeignKey("users.id"),
nullable=True,
),
)
op.add_column(
"script_templates",
sa.Column("source_ticket_ref", sa.String(64), nullable=True),
)
# ── session_facts ──────────────────────────────────────────────────────
op.create_table(
"session_facts",
sa.Column(
"id",
UUID(as_uuid=True),
primary_key=True,
server_default=sa.text("gen_random_uuid()"),
),
sa.Column(
"session_id",
UUID(as_uuid=True),
sa.ForeignKey("ai_sessions.id", ondelete="CASCADE"),
nullable=False,
),
sa.Column(
"account_id",
UUID(as_uuid=True),
sa.ForeignKey("accounts.id"),
nullable=False,
),
sa.Column("text", sa.Text(), nullable=False),
sa.Column("source_type", sa.String(32), nullable=False),
# `source_ref` is a polymorphic pointer to a task-lane item inside
# ai_sessions.pending_task_lane JSON, NOT a FK to any table.
# Integrity enforced at the service layer per Section 4.2 of the
# migration design doc.
sa.Column("source_ref", UUID(as_uuid=True), nullable=True),
sa.Column("source_summary", sa.Text(), nullable=True),
sa.Column(
"created_by",
UUID(as_uuid=True),
sa.ForeignKey("users.id"),
nullable=False,
),
sa.Column(
"created_at",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.text("now()"),
),
sa.Column(
"updated_at",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.text("now()"),
),
sa.Column("deleted_at", sa.DateTime(timezone=True), nullable=True),
sa.CheckConstraint(
"source_type IN ('question', 'diagnostic_check', 'user_note', 'ai_synthesis')",
name="ck_session_facts_source_type",
),
)
# Active-facts-per-session; partial index excludes soft-deleted rows.
op.create_index(
"idx_session_facts_session",
"session_facts",
["session_id"],
postgresql_where=sa.text("deleted_at IS NULL"),
)
op.create_index(
"idx_session_facts_account",
"session_facts",
["account_id"],
)
op.execute("ALTER TABLE session_facts ENABLE ROW LEVEL SECURITY")
op.execute("ALTER TABLE session_facts FORCE ROW LEVEL SECURITY")
op.execute(f"""
CREATE POLICY tenant_isolation ON session_facts
USING (account_id = {_CURRENT_ACCOUNT})
WITH CHECK (account_id = {_CURRENT_ACCOUNT})
""")
# ── session_suggested_fixes ────────────────────────────────────────────
op.create_table(
"session_suggested_fixes",
sa.Column(
"id",
UUID(as_uuid=True),
primary_key=True,
server_default=sa.text("gen_random_uuid()"),
),
sa.Column(
"session_id",
UUID(as_uuid=True),
sa.ForeignKey("ai_sessions.id", ondelete="CASCADE"),
nullable=False,
),
sa.Column(
"account_id",
UUID(as_uuid=True),
sa.ForeignKey("accounts.id"),
nullable=False,
),
sa.Column("title", sa.String(200), nullable=False),
sa.Column("description", sa.Text(), nullable=False),
sa.Column("confidence_pct", sa.Integer(), nullable=False),
sa.Column(
"script_template_id",
UUID(as_uuid=True),
sa.ForeignKey("script_templates.id"),
nullable=True,
),
sa.Column("ai_drafted_script", sa.Text(), nullable=True),
sa.Column("ai_drafted_parameters", JSONB(), nullable=True),
sa.Column("user_decision", sa.String(32), nullable=True),
sa.Column("superseded_at", sa.DateTime(timezone=True), nullable=True),
sa.Column(
"created_at",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.text("now()"),
),
sa.CheckConstraint(
"confidence_pct BETWEEN 0 AND 100",
name="ck_session_suggested_fixes_confidence_pct",
),
sa.CheckConstraint(
"user_decision IS NULL OR user_decision IN ("
"'one_off', 'draft_template', 'build_template', 'dismissed')",
name="ck_session_suggested_fixes_user_decision",
),
)
# Only-one-active-per-session is enforced by service-layer supersession;
# this partial index serves the "find active fix" query.
op.create_index(
"idx_session_suggested_fixes_session_active",
"session_suggested_fixes",
["session_id"],
postgresql_where=sa.text("superseded_at IS NULL"),
)
op.execute("ALTER TABLE session_suggested_fixes ENABLE ROW LEVEL SECURITY")
op.execute("ALTER TABLE session_suggested_fixes FORCE ROW LEVEL SECURITY")
op.execute(f"""
CREATE POLICY tenant_isolation ON session_suggested_fixes
USING (account_id = {_CURRENT_ACCOUNT})
WITH CHECK (account_id = {_CURRENT_ACCOUNT})
""")
# ── draft_templates ────────────────────────────────────────────────────
op.create_table(
"draft_templates",
sa.Column(
"id",
UUID(as_uuid=True),
primary_key=True,
server_default=sa.text("gen_random_uuid()"),
),
sa.Column(
"account_id",
UUID(as_uuid=True),
sa.ForeignKey("accounts.id"),
nullable=False,
),
sa.Column(
"source_session_id",
UUID(as_uuid=True),
sa.ForeignKey("ai_sessions.id"),
nullable=False,
),
sa.Column(
"source_user_id",
UUID(as_uuid=True),
sa.ForeignKey("users.id"),
nullable=False,
),
sa.Column("script_body", sa.Text(), nullable=False),
sa.Column("proposed_parameters", JSONB(), nullable=False),
sa.Column("proposed_name", sa.String(200), nullable=True),
sa.Column(
"proposed_category_id",
UUID(as_uuid=True),
sa.ForeignKey("script_categories.id"),
nullable=True,
),
sa.Column(
"status",
sa.String(32),
nullable=False,
server_default=sa.text("'pending'"),
),
sa.Column("resolved_at", sa.DateTime(timezone=True), nullable=True),
sa.Column(
"promoted_template_id",
UUID(as_uuid=True),
sa.ForeignKey("script_templates.id"),
nullable=True,
),
sa.Column(
"created_at",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.text("now()"),
),
sa.CheckConstraint(
"status IN ('pending', 'accepted', 'rejected')",
name="ck_draft_templates_status",
),
)
# Supports the Script Library "N scripts ready to review" badge.
op.create_index(
"idx_draft_templates_account_pending",
"draft_templates",
["account_id"],
postgresql_where=sa.text("status = 'pending'"),
)
op.execute("ALTER TABLE draft_templates ENABLE ROW LEVEL SECURITY")
op.execute("ALTER TABLE draft_templates FORCE ROW LEVEL SECURITY")
op.execute(f"""
CREATE POLICY tenant_isolation ON draft_templates
USING (account_id = {_CURRENT_ACCOUNT})
WITH CHECK (account_id = {_CURRENT_ACCOUNT})
""")
# ── account_settings ───────────────────────────────────────────────────
# One row per account, created lazily on first write. The `preferences`
# JSONB is a grab-bag for simple settings (e.g. templatize_prompt_enabled).
# Settings graduate to typed columns via future migrations when they meet
# the promotion criteria in Section 4.6 of the design doc (hot path /
# validation / joins).
op.create_table(
"account_settings",
sa.Column(
"account_id",
UUID(as_uuid=True),
sa.ForeignKey("accounts.id", ondelete="CASCADE"),
primary_key=True,
),
sa.Column(
"preferences",
JSONB(),
nullable=False,
server_default=sa.text("'{}'::jsonb"),
),
sa.Column(
"created_at",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.text("now()"),
),
sa.Column(
"updated_at",
sa.DateTime(timezone=True),
nullable=False,
server_default=sa.text("now()"),
),
)
op.execute("ALTER TABLE account_settings ENABLE ROW LEVEL SECURITY")
op.execute("ALTER TABLE account_settings FORCE ROW LEVEL SECURITY")
op.execute(f"""
CREATE POLICY tenant_isolation ON account_settings
USING (account_id = {_CURRENT_ACCOUNT})
WITH CHECK (account_id = {_CURRENT_ACCOUNT})
""")
def downgrade() -> None:
# Drop in reverse order so FK dependencies unwind cleanly.
op.execute("DROP POLICY IF EXISTS tenant_isolation ON account_settings")
op.execute("ALTER TABLE account_settings DISABLE ROW LEVEL SECURITY")
op.drop_table("account_settings")
op.execute("DROP POLICY IF EXISTS tenant_isolation ON draft_templates")
op.execute("ALTER TABLE draft_templates DISABLE ROW LEVEL SECURITY")
op.drop_index("idx_draft_templates_account_pending", table_name="draft_templates")
op.drop_table("draft_templates")
op.execute("DROP POLICY IF EXISTS tenant_isolation ON session_suggested_fixes")
op.execute("ALTER TABLE session_suggested_fixes DISABLE ROW LEVEL SECURITY")
op.drop_index(
"idx_session_suggested_fixes_session_active",
table_name="session_suggested_fixes",
)
op.drop_table("session_suggested_fixes")
op.execute("DROP POLICY IF EXISTS tenant_isolation ON session_facts")
op.execute("ALTER TABLE session_facts DISABLE ROW LEVEL SECURITY")
op.drop_index("idx_session_facts_account", table_name="session_facts")
op.drop_index("idx_session_facts_session", table_name="session_facts")
op.drop_table("session_facts")
op.drop_column("script_templates", "source_ticket_ref")
op.drop_column("script_templates", "source_user_id")
op.drop_column("script_templates", "source_session_id")
op.drop_column("ai_sessions", "state_version")
op.drop_column("ai_sessions", "escalation_package_external_id")
op.drop_column("ai_sessions", "escalation_package_posted_at")
op.drop_column("ai_sessions", "escalation_package_markdown")
op.drop_column("ai_sessions", "resolution_note_external_id")
op.drop_column("ai_sessions", "resolution_note_posted_at")
op.drop_column("ai_sessions", "resolution_note_markdown")

View File

@@ -16,7 +16,6 @@ from app.models.refresh_token import RefreshToken
from app.core.email import EmailService
from app.models.account import Account
from app.models.account_invite import AccountInvite
from app.models.account_settings import AccountSettings
from app.models.subscription import Subscription
from app.models.user import User
from app.schemas.account import AccountResponse, AccountUpdate, AccountInviteCreate, AccountInviteResponse, TransferOwnershipRequest
@@ -560,65 +559,3 @@ async def get_sso_status(
sso_enabled=account.sso_enabled,
sso_provider=account.sso_provider,
)
# ─── Account Preferences (FlowPilot Phase 6) ──────────────────────────────────
#
# Preferences live in `account_settings.preferences` as a JSONB grab-bag
# (per FLOWPILOT-MIGRATION.md Section 4.6). Rows are lazily created on first
# write. Any engineer-role user can read + update preferences because the
# keys stored here (templatize_prompt_enabled, cw_resolved_status_id, etc.)
# are team-level toggles rather than account-owner-gated admin settings.
class AccountPreferencesResponse(BaseModel):
preferences: dict
class AccountPreferencesUpdate(BaseModel):
"""Merge-style update — each key in `preferences` overwrites that key in
the stored JSONB, other keys are preserved. Omit the body entirely to
no-op.
"""
preferences: dict
@router.get("/me/preferences", response_model=AccountPreferencesResponse)
async def get_my_preferences(
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
):
"""Return the current account's preferences JSONB (empty dict if no row)."""
result = await db.execute(
select(AccountSettings.preferences).where(
AccountSettings.account_id == current_user.account_id
)
)
prefs = result.scalar_one_or_none() or {}
return AccountPreferencesResponse(preferences=prefs)
@router.patch("/me/preferences", response_model=AccountPreferencesResponse)
async def update_my_preferences(
data: AccountPreferencesUpdate,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
):
"""Upsert preference keys. Existing keys not present in the payload are kept.
Example: posting `{"preferences": {"templatize_prompt_enabled": false}}`
from the post-resolve "Don't ask me again for this team" checkbox sets
just that key without clobbering any other preferences.
"""
for key, value in data.preferences.items():
await AccountSettings.set_setting(db, current_user.account_id, key, value)
await db.commit()
# Return the merged state so the client doesn't need a second GET.
result = await db.execute(
select(AccountSettings.preferences).where(
AccountSettings.account_id == current_user.account_id
)
)
prefs = result.scalar_one_or_none() or {}
return AccountPreferencesResponse(preferences=prefs)

View File

@@ -431,19 +431,10 @@ async def create_account(
current_user: Annotated[User, Depends(require_admin)],
):
"""Create a new account without requiring an initial user."""
owner_id = None
if data.owner_email:
result = await db.execute(select(User).where(User.email == data.owner_email.strip()))
owner = result.scalar_one_or_none()
if not owner:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"No user found with email '{data.owner_email}'")
owner_id = owner.id
display_code = await _generate_unique_display_code(db)
new_account = Account(
name=data.name.strip(),
display_code=display_code,
owner_id=owner_id,
)
db.add(new_account)
await db.flush()
@@ -457,7 +448,7 @@ async def create_account(
await log_audit(
db, current_user.id, "account.create_admin", "account", new_account.id,
{"name": new_account.name, "plan": data.plan, "owner_email": data.owner_email},
{"name": new_account.name, "plan": data.plan},
)
await db.commit()
return await _get_account_detail_payload(new_account.id, db)

View File

@@ -1,120 +0,0 @@
"""Device types API endpoints."""
from typing import Annotated
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException
from sqlalchemy import select, or_
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.database import get_db
from app.api.deps import get_current_active_user
from app.models.user import User
from app.models.device_type import DeviceType
from app.schemas.device_type import (
DeviceTypeCreate,
DeviceTypeUpdate,
DeviceTypeResponse,
)
from app.core.service_account import PLATFORM_ACCOUNT_ID
router = APIRouter(prefix="/device-types", tags=["device-types"])
@router.get("/", response_model=list[DeviceTypeResponse])
async def list_device_types(
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> list[DeviceTypeResponse]:
stmt = (
select(DeviceType)
.where(
or_(
DeviceType.account_id == PLATFORM_ACCOUNT_ID,
DeviceType.account_id == current_user.account_id,
)
)
.order_by(DeviceType.category, DeviceType.sort_order, DeviceType.label)
)
result = await db.execute(stmt)
rows = result.scalars().all()
return [DeviceTypeResponse.model_validate(r) for r in rows]
@router.post("/", response_model=DeviceTypeResponse, status_code=201)
async def create_device_type(
data: DeviceTypeCreate,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> DeviceTypeResponse:
existing = await db.execute(
select(DeviceType).where(
DeviceType.slug == data.slug,
DeviceType.account_id == current_user.account_id,
)
)
if existing.scalar_one_or_none():
raise HTTPException(status_code=409, detail=f"Device type '{data.slug}' already exists for your account")
system_existing = await db.execute(
select(DeviceType).where(
DeviceType.slug == data.slug,
DeviceType.account_id == PLATFORM_ACCOUNT_ID,
)
)
if system_existing.scalar_one_or_none():
raise HTTPException(status_code=409, detail=f"Device type '{data.slug}' conflicts with a system type")
device_type = DeviceType(
slug=data.slug,
label=data.label,
category=data.category,
is_system=False,
account_id=current_user.account_id,
sort_order=data.sort_order,
)
db.add(device_type)
await db.commit()
await db.refresh(device_type)
return DeviceTypeResponse.model_validate(device_type)
@router.put("/{device_type_id}", response_model=DeviceTypeResponse)
async def update_device_type(
device_type_id: UUID,
data: DeviceTypeUpdate,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> DeviceTypeResponse:
device_type = await db.get(DeviceType, device_type_id)
if not device_type:
raise HTTPException(status_code=404, detail="Device type not found")
if device_type.is_system:
raise HTTPException(status_code=403, detail="Cannot modify system device types")
if device_type.account_id != current_user.account_id:
raise HTTPException(status_code=404, detail="Device type not found")
update_data = data.model_dump(exclude_unset=True)
for field, value in update_data.items():
setattr(device_type, field, value)
await db.commit()
await db.refresh(device_type)
return DeviceTypeResponse.model_validate(device_type)
@router.delete("/{device_type_id}", status_code=204)
async def delete_device_type(
device_type_id: UUID,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> None:
device_type = await db.get(DeviceType, device_type_id)
if not device_type:
raise HTTPException(status_code=404, detail="Device type not found")
if device_type.is_system:
raise HTTPException(status_code=403, detail="Cannot delete system device types")
if device_type.account_id != current_user.account_id:
raise HTTPException(status_code=404, detail="Device type not found")
await db.delete(device_type)
await db.commit()

View File

@@ -1,221 +0,0 @@
"""Draft template endpoints — Phase 6 post-resolve templatization flow.
Engineers who picked "Run now, templatize after resolve" on the three-option
dialog (Phase 5) generate a `draft_templates` row at decision time. After
the session resolves, the TemplatizePrompt component lets them either:
- Accept → promotes the draft to a real `script_templates` row
- Reject → marks the draft rejected, no library entry created
The Script Library sidebar uses the list endpoint to surface a
"X drafts ready to review" badge for the account.
See FLOWPILOT-MIGRATION.md Section 5.3.
"""
import logging
import re
from datetime import datetime, timezone
from typing import Annotated
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.api.deps import get_current_active_user, get_db, require_engineer_or_admin
from app.models.ai_session import AISession
from app.models.draft_template import DraftTemplate
from app.models.script_template import ScriptCategory, ScriptTemplate
from app.models.user import User
from app.schemas.draft_template import (
DraftTemplateAcceptRequest,
DraftTemplateAcceptResponse,
DraftTemplateListResponse,
DraftTemplateRejectResponse,
DraftTemplateResponse,
)
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/draft-templates", tags=["draft-templates"])
def _slugify(name: str) -> str:
"""Same slug rule as scripts.create_template — lowercase, kebab-case, ASCII."""
return re.sub(r"[^a-z0-9]+", "-", name.lower()).strip("-")
# ── List ─────────────────────────────────────────────────────────────────
@router.get("", response_model=DraftTemplateListResponse)
async def list_drafts(
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
pending_only: bool = True,
) -> DraftTemplateListResponse:
"""List drafts for the current user's account.
Defaults to pending-only — that's what the Script Library badge counts
and what the post-resolve TemplatizePrompt iterates over. Pass
`pending_only=false` to include accepted/rejected for an audit view.
"""
stmt = select(DraftTemplate).order_by(DraftTemplate.created_at.desc())
if pending_only:
stmt = stmt.where(DraftTemplate.status == "pending")
result = await db.execute(stmt)
drafts = list(result.scalars().all())
return DraftTemplateListResponse(
drafts=[DraftTemplateResponse.model_validate(d) for d in drafts]
)
# ── Get one ──────────────────────────────────────────────────────────────
@router.get("/{draft_id}", response_model=DraftTemplateResponse)
async def get_draft(
draft_id: UUID,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> DraftTemplateResponse:
draft = await _load_draft_or_404(db, draft_id)
return DraftTemplateResponse.model_validate(draft)
# ── Accept ───────────────────────────────────────────────────────────────
@router.post(
"/{draft_id}/accept",
response_model=DraftTemplateAcceptResponse,
status_code=201,
)
async def accept_draft(
draft_id: UUID,
body: DraftTemplateAcceptRequest,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> DraftTemplateAcceptResponse:
"""Promote a draft to a real `script_templates` row.
Provenance fields (`source_session_id`, `source_user_id`,
`source_ticket_ref`) are copied so the Script Library can render the
"generated from CW #X · resolved by Y · used N times" chip.
On success: draft.status='accepted', draft.promoted_template_id set,
draft.resolved_at set. The new template is owned by the engineer's team
(matches scripts.create_template's behavior).
Returns 409 if the draft is already accepted/rejected.
"""
draft = await _load_draft_or_404(db, draft_id)
if draft.status != "pending":
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=f"Draft is already {draft.status}",
)
# Validate the category exists and belongs to (or is global for) this account.
cat_result = await db.execute(
select(ScriptCategory).where(
ScriptCategory.id == body.category_id,
ScriptCategory.is_active == True, # noqa: E712
)
)
if cat_result.scalar_one_or_none() is None:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="category_id does not reference an active script category",
)
# Look up source-session ticket ref for the provenance chip. RLS makes
# cross-account ai_session lookup impossible — the draft must belong to
# the same account as the requesting user.
source_session = (
await db.execute(
select(AISession).where(AISession.id == draft.source_session_id)
)
).scalar_one_or_none()
source_ticket_ref = (
f"CW #{source_session.psa_ticket_id}"
if source_session and source_session.psa_ticket_id
else None
)
slug = _slugify(body.name)
template = ScriptTemplate(
category_id=body.category_id,
team_id=current_user.team_id,
account_id=current_user.account_id,
created_by=current_user.id,
name=body.name,
slug=slug,
description=body.description,
script_body=body.edited_body or draft.script_body,
parameters_schema=body.parameters_schema,
# FlowPilot provenance — drives the Script Library chip.
source_session_id=draft.source_session_id,
source_user_id=draft.source_user_id,
source_ticket_ref=source_ticket_ref,
)
db.add(template)
await db.flush() # populate template.id
draft.status = "accepted"
draft.promoted_template_id = template.id
draft.resolved_at = datetime.now(timezone.utc)
await db.commit()
await db.refresh(template)
return DraftTemplateAcceptResponse(
draft_id=draft.id,
promoted_template_id=template.id,
template_slug=template.slug,
)
# ── Reject ───────────────────────────────────────────────────────────────
@router.post("/{draft_id}/reject", response_model=DraftTemplateRejectResponse)
async def reject_draft(
draft_id: UUID,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> DraftTemplateRejectResponse:
"""Mark a draft rejected.
No template is created. The row stays for audit (so a team admin can see
the engineer reviewed and explicitly declined). Returns 409 on a draft
that's already accepted/rejected.
"""
draft = await _load_draft_or_404(db, draft_id)
if draft.status != "pending":
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=f"Draft is already {draft.status}",
)
draft.status = "rejected"
draft.resolved_at = datetime.now(timezone.utc)
await db.commit()
return DraftTemplateRejectResponse(draft_id=draft.id, status="rejected")
# ── Helpers ─────────────────────────────────────────────────────────────
async def _load_draft_or_404(
db: AsyncSession, draft_id: UUID
) -> DraftTemplate:
"""RLS-scoped draft load. 404 covers missing + cross-tenant."""
result = await db.execute(
select(DraftTemplate).where(DraftTemplate.id == draft_id)
)
draft = result.scalar_one_or_none()
if draft is None:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="Draft template not found",
)
return draft

View File

@@ -1,7 +1,6 @@
"""PSA integration endpoints — connection CRUD and test."""
from __future__ import annotations
import logging
from datetime import datetime, timezone
from typing import Annotated
from uuid import UUID
@@ -12,8 +11,6 @@ from sqlalchemy.ext.asyncio import AsyncSession
from sqlalchemy import delete
logger = logging.getLogger(__name__)
from app.api.deps import get_current_active_user, require_account_owner, require_engineer_or_admin
from app.core.database import get_db
from app.models.psa_connection import PsaConnection
@@ -30,20 +27,8 @@ from app.schemas.psa_connection import (
PsaMemberMappingSaveRequest,
PsaMemberResponse,
AutoMatchResult,
PSABoardResponse,
)
from app.core.config import settings
from app.schemas.psa_tickets import (
PSAResourceSchema,
PSATicketCreatedSchema,
PSATicketStatusUpdateSchema,
TicketCreatePayloadSchema,
PSAPrioritySchema,
TicketListResponseSchema,
AiParseRequestSchema,
AiParseResponseSchema,
)
import app.services.ticket_service as ticket_svc
from app.services.psa.encryption import (
decrypt_credentials,
encrypt_credentials,
@@ -360,335 +345,43 @@ async def update_flowpilot_settings(
# ── ticket / status / company endpoints ──────────────────────────
@router.get("/boards", response_model=list[PSABoardResponse])
async def list_boards(
current_user: Annotated[User, Depends(require_engineer_or_admin)],
db: Annotated[AsyncSession, Depends(get_db)],
):
"""List PSA service boards."""
if not current_user.account_id:
raise HTTPException(status_code=400, detail="User has no account")
from app.services.psa.registry import get_provider_for_account
from app.services.psa.exceptions import PSAError
try:
provider = await get_provider_for_account(current_user.account_id, db)
boards = await provider.list_boards()
return [PSABoardResponse(id=b.id, name=b.name) for b in boards]
except PSAError as e:
# Boards are optional UI chrome — degrade gracefully rather than surfacing a toast
logger.warning("list_boards failed: %s", e)
return []
@router.get("/tickets/search", response_model=TicketListResponseSchema)
@router.get("/tickets/search", response_model=list[PSATicketSearchResult])
async def search_tickets(
current_user: Annotated[User, Depends(require_engineer_or_admin)],
db: Annotated[AsyncSession, Depends(get_db)],
query: str = "",
board_id: int | None = None,
status_id: int | None = None,
status_name: str | None = None,
include_closed: bool = False,
assigned_to_me: bool = False,
unassigned: bool = False,
board_ids: str = "",
priority: str | None = None,
company_id: int | None = None,
page: int = 1,
page_size: int = 25,
):
"""Search ConnectWise tickets — returns paginated TicketListResponse."""
"""Search ConnectWise tickets."""
if not current_user.account_id:
raise HTTPException(status_code=400, detail="User has no account")
from app.services.psa.registry import get_provider_for_account
from app.services.psa.exceptions import PSAError
member_identifier: str | None = None
if assigned_to_me:
conn_result = await db.execute(
select(PsaConnection).where(
PsaConnection.account_id == current_user.account_id,
PsaConnection.is_active.is_(True),
)
)
conn = conn_result.scalar_one_or_none()
if conn:
mapping_result = await db.execute(
select(PsaMemberMapping).where(
PsaMemberMapping.psa_connection_id == conn.id,
PsaMemberMapping.user_id == current_user.id,
)
)
mapping = mapping_result.scalar_one_or_none()
if not mapping:
return {"items": [], "total": 0, "page": page, "page_size": page_size}
try:
_provider = await get_provider_for_account(current_user.account_id, db)
cw_members = await _provider.list_members()
matched = next((m for m in cw_members if m.id == mapping.external_member_id), None)
if matched:
member_identifier = matched.identifier
else:
return {"items": [], "total": 0, "page": page, "page_size": page_size}
except PSAError:
return {"items": [], "total": 0, "page": page, "page_size": page_size}
parsed_board_ids: list[int] = []
if board_ids:
try:
parsed_board_ids = [int(bid.strip()) for bid in board_ids.split(",") if bid.strip()]
except ValueError:
raise HTTPException(status_code=400, detail="board_ids must be comma-separated integers")
try:
provider = await get_provider_for_account(current_user.account_id, db)
result = await provider.search_tickets(
query,
board_id=board_id,
status_id=status_id,
status_name=status_name,
include_closed=include_closed,
member_identifier=member_identifier,
unassigned=unassigned,
board_ids=parsed_board_ids,
company_id=company_id,
page=page,
page_size=page_size,
tickets = await provider.search_tickets(
query, board_id=board_id, status_id=status_id, include_closed=include_closed
)
items = [
return [
PSATicketSearchResult(
id=t.id,
summary=t.summary,
company_name=t.company_name,
company_id=t.company_id,
board_name=t.board_name,
board_id=t.board_id,
status_name=t.status_name,
status_id=t.status_id,
priority_name=t.priority_name,
priority_id=t.priority_id,
closed=t.closed,
)
for t in result.items
for t in tickets
]
return {"items": items, "total": result.total, "page": result.page, "page_size": result.page_size}
except PSAError as e:
raise HTTPException(status_code=502, detail=str(e))
@router.post("/tickets", response_model=PSATicketCreatedSchema, status_code=201)
async def create_ticket(
data: TicketCreatePayloadSchema,
current_user: Annotated[User, Depends(require_engineer_or_admin)],
db: Annotated[AsyncSession, Depends(get_db)],
):
"""Create a new PSA ticket."""
if not current_user.account_id:
raise HTTPException(status_code=400, detail="User has no account")
from app.services.psa.exceptions import PSAError
from app.services.psa.types import TicketCreatePayload
try:
return await ticket_svc.create_ticket(
current_user.account_id,
TicketCreatePayload(**data.model_dump()),
db,
)
except PSAError as e:
raise HTTPException(status_code=502, detail=str(e))
@router.post("/tickets/ai-parse", response_model=AiParseResponseSchema)
async def ai_parse_ticket(
data: AiParseRequestSchema,
current_user: Annotated[User, Depends(require_engineer_or_admin)],
db: Annotated[AsyncSession, Depends(get_db)],
):
"""Parse natural language into a ticket pre-fill payload using Claude."""
if not current_user.account_id:
raise HTTPException(status_code=400, detail="User has no account")
from app.services.psa.registry import get_provider_for_account
from app.services.psa.exceptions import PSAError
import anthropic
import json
# Fetch boards + members for context (both cached)
boards = []
members = []
try:
provider = await get_provider_for_account(current_user.account_id, db)
boards = await provider.list_boards()
members = await provider.list_members()
except PSAError:
pass
boards_list = [{"id": b.id, "name": b.name} for b in boards]
members_list = [{"id": m.id, "name": m.name, "identifier": m.identifier} for m in members]
system_prompt = """You are a ticket triage assistant for an MSP help desk.
Extract structured ticket information from the engineer's natural language description.
Return ONLY valid JSON matching this exact schema — no other text:
{
"summary": "short one-line ticket title or null",
"board_id": "integer matching one of the provided boards or null",
"priority_name": "one of: Critical, High, Medium, Low, or null",
"description": "expanded description or null",
"assignee_identifier": "member identifier string from the provided members list or null",
"warnings": ["list of strings explaining what could not be resolved"]
}"""
user_msg = f"""Available boards: {json.dumps(boards_list)}
Available members: {json.dumps(members_list[:50])}
Engineer's description: {data.prompt}"""
missing_fields: list[str] = []
warnings: list[str] = []
response_data = AiParseResponseSchema()
try:
client = anthropic.AsyncAnthropic(
api_key=settings.ANTHROPIC_API_KEY,
max_retries=1,
)
msg = await client.messages.create(
model=settings.get_model_for_action("default"),
max_tokens=512,
system=system_prompt,
messages=[{"role": "user", "content": user_msg}],
)
raw = msg.content[0].text.strip()
# Strip markdown fences if present
if raw.startswith("```"):
import re
raw = re.sub(r'^```(?:json)?\s*', '', raw)
raw = re.sub(r'\s*```$', '', raw.strip())
parsed = json.loads(raw)
response_data.summary = parsed.get("summary")
response_data.description = parsed.get("description")
warnings = parsed.get("warnings", [])
# Resolve board_id
if parsed.get("board_id"):
board_match = next((b for b in boards if b.id == int(parsed["board_id"])), None)
if board_match:
response_data.board_id = board_match.id
else:
missing_fields.append("board_id")
warnings.append(f"Board ID {parsed['board_id']} not found")
else:
missing_fields.append("board_id")
# Resolve assignee
if parsed.get("assignee_identifier"):
member = next((m for m in members if m.identifier == parsed["assignee_identifier"]), None)
if member:
response_data.assigned_member_id = int(member.id)
else:
warnings.append(f"Member '{parsed['assignee_identifier']}' not found")
# Priority/status/company always need manual selection
missing_fields.extend(["status_id", "priority_id", "company_id"])
except Exception as e:
logger.warning("AI parse failed: %s", e)
missing_fields = ["summary", "board_id", "status_id", "priority_id", "company_id"]
warnings = ["AI parsing failed — please fill in manually"]
response_data.missing_fields = missing_fields
response_data.warnings = warnings
return response_data
@router.patch("/tickets/{ticket_id}/status", response_model=PSATicketStatusUpdateSchema)
async def update_ticket_status_endpoint(
ticket_id: int,
status_id: int,
current_user: Annotated[User, Depends(require_engineer_or_admin)],
db: Annotated[AsyncSession, Depends(get_db)],
):
"""Update a ticket's status."""
if not current_user.account_id:
raise HTTPException(status_code=400, detail="User has no account")
from app.services.psa.exceptions import PSAError
try:
return await ticket_svc.update_status(current_user.account_id, ticket_id, status_id, db)
except PSAError as e:
raise HTTPException(status_code=502, detail=str(e))
@router.get("/tickets/{ticket_id}/resources", response_model=list[PSAResourceSchema])
async def list_ticket_resources(
ticket_id: int,
current_user: Annotated[User, Depends(require_engineer_or_admin)],
db: Annotated[AsyncSession, Depends(get_db)],
):
if not current_user.account_id:
raise HTTPException(status_code=400, detail="User has no account")
from app.services.psa.exceptions import PSAError
try:
return await ticket_svc.list_resources(current_user.account_id, ticket_id, db)
except PSAError as e:
# Resources are optional display data — degrade gracefully rather than surfacing a toast
logger.warning("list_resources(%s) failed: %s", ticket_id, e)
return []
@router.post("/tickets/{ticket_id}/resources", response_model=PSAResourceSchema, status_code=201)
async def add_ticket_resource(
ticket_id: int,
member_id: int,
current_user: Annotated[User, Depends(require_engineer_or_admin)],
db: Annotated[AsyncSession, Depends(get_db)],
):
if not current_user.account_id:
raise HTTPException(status_code=400, detail="User has no account")
from app.services.psa.exceptions import PSAError
try:
return await ticket_svc.add_resource(current_user.account_id, ticket_id, member_id, db)
except PSAError as e:
raise HTTPException(status_code=502, detail=str(e))
@router.delete("/tickets/{ticket_id}/resources/{member_id}", status_code=204)
async def remove_ticket_resource(
ticket_id: int,
member_id: int,
current_user: Annotated[User, Depends(require_engineer_or_admin)],
db: Annotated[AsyncSession, Depends(get_db)],
):
if not current_user.account_id:
raise HTTPException(status_code=400, detail="User has no account")
from app.services.psa.exceptions import PSAError
try:
await ticket_svc.remove_resource(current_user.account_id, ticket_id, member_id, db)
except PSAError as e:
raise HTTPException(status_code=502, detail=str(e))
@router.get("/priorities", response_model=list[PSAPrioritySchema])
async def list_priorities(
current_user: Annotated[User, Depends(require_engineer_or_admin)],
db: Annotated[AsyncSession, Depends(get_db)],
):
"""List PSA priority levels for ticket creation form."""
if not current_user.account_id:
raise HTTPException(status_code=400, detail="User has no account")
from app.services.psa.registry import get_provider_for_account
from app.services.psa.exceptions import PSAError
try:
provider = await get_provider_for_account(current_user.account_id, db)
raw = await provider.list_priorities()
return [PSAPrioritySchema(id=p["id"], name=p["name"]) for p in raw if p.get("id")]
except PSAError as e:
logger.warning("list_priorities failed: %s", e)
return []
@router.get("/tickets/{ticket_id}/context")
async def get_ticket_context(
ticket_id: int,
@@ -790,30 +483,7 @@ async def get_ticket_statuses(
except PSANotFoundError:
raise HTTPException(status_code=404, detail="Ticket not found")
except PSAError as e:
logger.warning("get_ticket_statuses(%s) failed: %s", ticket_id, e)
return []
@router.get("/boards/{board_id}/statuses", response_model=list[PSATicketStatusItem])
async def get_board_statuses(
board_id: int,
current_user: Annotated[User, Depends(require_engineer_or_admin)],
db: Annotated[AsyncSession, Depends(get_db)],
):
"""Get available statuses for a service board directly (no ticket lookup required)."""
if not current_user.account_id:
raise HTTPException(status_code=400, detail="User has no account")
from app.services.psa.registry import get_provider_for_account
from app.services.psa.exceptions import PSAError
try:
provider = await get_provider_for_account(current_user.account_id, db)
statuses = await provider.get_ticket_statuses(board_id)
return [PSATicketStatusItem(id=s.id, name=s.name, is_closed=s.is_closed) for s in statuses]
except PSAError as e:
logger.warning("get_board_statuses(%s) failed: %s", board_id, e)
return []
raise HTTPException(status_code=502, detail=str(e))
# ── member mapping endpoints ─────────────────────────────────────────
@@ -821,7 +491,7 @@ async def get_board_statuses(
@router.get("/members", response_model=list[PsaMemberResponse])
async def list_members(
current_user: Annotated[User, Depends(require_engineer_or_admin)],
current_user: Annotated[User, Depends(require_account_owner)],
db: Annotated[AsyncSession, Depends(get_db)],
):
"""List CW members (from CW API)."""
@@ -839,9 +509,7 @@ async def list_members(
for m in members
]
except PSAError as e:
# Members are optional display data — degrade gracefully
logger.warning("list_members failed: %s", e)
return []
raise HTTPException(status_code=502, detail=str(e))
@router.get("/member-mappings", response_model=list[PsaMemberMappingResponse])
@@ -849,37 +517,31 @@ async def get_member_mappings(
current_user: Annotated[User, Depends(require_account_owner)],
db: Annotated[AsyncSession, Depends(get_db)],
):
"""Get all account users with their PSA member mappings (unmapped users included)."""
"""Get all member mappings for the account."""
conn = await _get_account_connection(current_user.account_id, db)
if not conn:
return []
# Fetch all active account users
users_result = await db.execute(
select(User).where(User.account_id == current_user.account_id, User.is_active.is_(True))
)
users = users_result.scalars().all()
# Fetch all existing mappings keyed by user_id for O(1) lookup
mappings_result = await db.execute(
result = await db.execute(
select(PsaMemberMapping).where(PsaMemberMapping.psa_connection_id == conn.id)
)
mapping_by_user: dict[str, PsaMemberMapping] = {
str(m.user_id): m for m in mappings_result.scalars().all()
}
mappings = result.scalars().all()
return [
PsaMemberMappingResponse(
id=str(m.id) if (m := mapping_by_user.get(str(user.id))) else None,
user_id=str(user.id),
user_email=user.email,
user_name=user.name,
external_member_id=m.external_member_id if m else None,
external_member_name=m.external_member_name if m else None,
matched_by=m.matched_by if m else None,
)
for user in users
]
response = []
for m in mappings:
user_result = await db.execute(select(User).where(User.id == m.user_id))
user = user_result.scalar_one_or_none()
if user:
response.append(PsaMemberMappingResponse(
id=str(m.id),
user_id=str(m.user_id),
user_email=user.email,
user_name=user.name,
external_member_id=m.external_member_id,
external_member_name=m.external_member_name,
matched_by=m.matched_by,
))
return response
@router.post("/member-mappings", response_model=list[PsaMemberMappingResponse])
@@ -902,7 +564,6 @@ async def save_member_mappings(
for m in mappings:
mapping = PsaMemberMapping(
psa_connection_id=conn.id,
account_id=current_user.account_id,
user_id=UUID(m.user_id),
external_member_id=m.external_member_id,
external_member_name=m.external_member_name,
@@ -963,7 +624,6 @@ async def auto_match_members(
if not existing.scalar_one_or_none():
mapping = PsaMemberMapping(
psa_connection_id=conn.id,
account_id=current_user.account_id,
user_id=user.id,
external_member_id=cw_member.id,
external_member_name=cw_member.name,

View File

@@ -1,362 +0,0 @@
"""Network diagrams API endpoints."""
import base64
import logging
from datetime import datetime, timezone
from typing import Annotated
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException, Query
from pydantic import BaseModel
from sqlalchemy import select, or_
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.database import get_db
from app.api.deps import get_current_active_user
from app.models.user import User
from app.models.device_type import DeviceType
from app.models.network_diagram import NetworkDiagram
from app.core.service_account import PLATFORM_ACCOUNT_ID
from app.schemas.network_diagram import (
NetworkDiagramCreate,
NetworkDiagramUpdate,
NetworkDiagramResponse,
NetworkDiagramListItem,
AIGenerateRequest,
AIGenerateResponse,
DiagramImportRequest,
DiagramImportResponse,
DiagramExportResponse,
DiagramNode,
DiagramEdge,
)
from app.services import network_diagram_ai_service, storage_service
# Maps system device-type slugs to their category — mirrors frontend deviceRegistry.ts
_SLUG_CATEGORY: dict[str, str] = {
"router": "network", "switch": "network", "access-point": "network", "load-balancer": "network",
"firewall": "security", "badge-reader": "security",
"server": "compute", "vm": "compute", "container": "compute",
"nas": "storage", "san": "storage", "cloud-storage": "storage",
"cloud": "cloud", "aws": "cloud", "azure": "cloud", "gcp": "cloud", "isp": "cloud",
"workstation": "endpoint", "laptop": "endpoint", "tablet": "endpoint",
"phone": "endpoint", "printer": "endpoint",
"ups": "infrastructure", "pdu": "infrastructure", "rack": "infrastructure",
"patch-panel": "infrastructure", "camera": "infrastructure",
"nvr": "infrastructure", "iot": "infrastructure",
}
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/network-diagrams", tags=["network-diagrams"])
async def _get_diagram_or_404(
diagram_id: UUID,
account_id: UUID,
db: AsyncSession,
) -> NetworkDiagram:
diagram = await db.get(NetworkDiagram, diagram_id)
if not diagram or diagram.account_id != account_id or diagram.is_archived:
raise HTTPException(status_code=404, detail="Diagram not found")
return diagram
def _diagram_to_response(diagram: NetworkDiagram) -> NetworkDiagramResponse:
return NetworkDiagramResponse.model_validate(diagram)
def _diagram_to_list_item(
diagram: NetworkDiagram,
custom_slug_category: dict[str, str] | None = None,
) -> NetworkDiagramListItem:
nodes = diagram.nodes if isinstance(diagram.nodes, list) else []
slug_to_cat = {**_SLUG_CATEGORY, **(custom_slug_category or {})}
category_counts: dict[str, int] = {}
for node in nodes:
slug = node.get("type", "") if isinstance(node, dict) else ""
cat = slug_to_cat.get(slug, "other")
category_counts[cat] = category_counts.get(cat, 0) + 1
return NetworkDiagramListItem(
id=diagram.id,
name=diagram.name,
client_name=diagram.client_name,
description=diagram.description,
node_count=len(nodes),
category_counts=category_counts,
thumbnail_url=diagram.thumbnail_url,
created_by=diagram.created_by,
created_at=diagram.created_at,
updated_at=diagram.updated_at,
)
async def _get_available_slugs(account_id: UUID, db: AsyncSession) -> set[str]:
stmt = select(DeviceType.slug).where(
or_(
DeviceType.account_id == PLATFORM_ACCOUNT_ID,
DeviceType.account_id == account_id,
)
)
result = await db.execute(stmt)
return {row[0] for row in result.all()}
@router.get("/clients", response_model=list[str])
async def list_client_names(
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> list[str]:
stmt = (
select(NetworkDiagram.client_name)
.where(
NetworkDiagram.account_id == current_user.account_id,
NetworkDiagram.is_archived.is_(False),
NetworkDiagram.client_name.isnot(None),
NetworkDiagram.client_name != "",
)
.distinct()
.order_by(NetworkDiagram.client_name)
)
result = await db.execute(stmt)
return [row[0] for row in result.all()]
@router.get("/", response_model=list[NetworkDiagramListItem])
async def list_diagrams(
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
client_name: str | None = Query(default=None),
search: str | None = Query(default=None),
) -> list[NetworkDiagramListItem]:
stmt = (
select(NetworkDiagram)
.where(
NetworkDiagram.account_id == current_user.account_id,
NetworkDiagram.is_archived.is_(False),
)
.order_by(NetworkDiagram.updated_at.desc())
)
if client_name:
stmt = stmt.where(NetworkDiagram.client_name == client_name)
if search:
escaped = search.replace("\\", "\\\\").replace("%", "\\%").replace("_", "\\_")
search_filter = f"%{escaped}%"
stmt = stmt.where(
or_(
NetworkDiagram.name.ilike(search_filter),
NetworkDiagram.client_name.ilike(search_filter),
)
)
# Single query for custom device types so category_counts is accurate
dt_stmt = select(DeviceType.slug, DeviceType.category).where(
DeviceType.is_system.is_(False),
DeviceType.account_id == current_user.account_id,
)
dt_result = await db.execute(dt_stmt)
custom_slug_category = {row[0]: row[1] for row in dt_result.all()}
result = await db.execute(stmt)
rows = result.scalars().all()
return [_diagram_to_list_item(r, custom_slug_category) for r in rows]
@router.post("/", response_model=NetworkDiagramResponse, status_code=201)
async def create_diagram(
data: NetworkDiagramCreate,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> NetworkDiagramResponse:
diagram = NetworkDiagram(
account_id=current_user.account_id,
name=data.name,
client_name=data.client_name,
asset_name=data.asset_name,
description=data.description,
nodes=[n.model_dump() for n in data.nodes],
edges=[e.model_dump() for e in data.edges],
created_by=current_user.id,
)
db.add(diagram)
await db.commit()
await db.refresh(diagram)
return _diagram_to_response(diagram)
@router.get("/{diagram_id}", response_model=NetworkDiagramResponse)
async def get_diagram(
diagram_id: UUID,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> NetworkDiagramResponse:
diagram = await _get_diagram_or_404(diagram_id, current_user.account_id, db)
return _diagram_to_response(diagram)
@router.put("/{diagram_id}", response_model=NetworkDiagramResponse)
async def update_diagram(
diagram_id: UUID,
data: NetworkDiagramUpdate,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> NetworkDiagramResponse:
diagram = await _get_diagram_or_404(diagram_id, current_user.account_id, db)
update_data = data.model_dump(exclude_unset=True)
if "nodes" in update_data and update_data["nodes"] is not None:
update_data["nodes"] = [n.model_dump() if hasattr(n, "model_dump") else n for n in update_data["nodes"]]
if "edges" in update_data and update_data["edges"] is not None:
update_data["edges"] = [e.model_dump() if hasattr(e, "model_dump") else e for e in update_data["edges"]]
for field, value in update_data.items():
setattr(diagram, field, value)
diagram.updated_at = datetime.now(timezone.utc)
await db.commit()
await db.refresh(diagram)
return _diagram_to_response(diagram)
@router.delete("/{diagram_id}", status_code=204)
async def archive_diagram(
diagram_id: UUID,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> None:
diagram = await _get_diagram_or_404(diagram_id, current_user.account_id, db)
diagram.is_archived = True
diagram.updated_at = datetime.now(timezone.utc)
await db.commit()
@router.post("/{diagram_id}/duplicate", response_model=NetworkDiagramResponse, status_code=201)
async def duplicate_diagram(
diagram_id: UUID,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> NetworkDiagramResponse:
source = await _get_diagram_or_404(diagram_id, current_user.account_id, db)
copy = NetworkDiagram(
account_id=current_user.account_id,
name=f"Copy of {source.name}",
client_name=source.client_name,
asset_name=source.asset_name,
description=source.description,
nodes=source.nodes,
edges=source.edges,
created_by=current_user.id,
)
db.add(copy)
await db.commit()
await db.refresh(copy)
return _diagram_to_response(copy)
@router.get("/{diagram_id}/export", response_model=DiagramExportResponse)
async def export_diagram(
diagram_id: UUID,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> DiagramExportResponse:
diagram = await _get_diagram_or_404(diagram_id, current_user.account_id, db)
nodes = [DiagramNode(**n) for n in (diagram.nodes or [])]
edges = [DiagramEdge(**e) for e in (diagram.edges or [])]
return DiagramExportResponse(
schemaVersion=1,
name=diagram.name,
client_name=diagram.client_name,
description=diagram.description,
nodes=nodes,
edges=edges,
exportedAt=datetime.now(timezone.utc).isoformat(),
)
@router.post("/import", response_model=DiagramImportResponse, status_code=201)
async def import_diagram(
data: DiagramImportRequest,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> DiagramImportResponse:
available_slugs = await _get_available_slugs(current_user.account_id, db)
warnings: list[str] = []
for node in data.nodes:
if node.type not in available_slugs:
warnings.append(f"Unknown device type '{node.type}' — will render with default icon")
diagram = NetworkDiagram(
account_id=current_user.account_id,
name=data.name,
client_name=data.client_name,
description=data.description,
nodes=[n.model_dump() for n in data.nodes],
edges=[e.model_dump() for e in data.edges],
created_by=current_user.id,
)
db.add(diagram)
await db.commit()
await db.refresh(diagram)
return DiagramImportResponse(
diagram=_diagram_to_response(diagram),
warnings=warnings,
)
class ThumbnailUploadRequest(BaseModel):
data_url: str # base64 PNG data URL: "data:image/png;base64,..."
@router.post("/{diagram_id}/thumbnail", status_code=204)
async def upload_thumbnail(
diagram_id: UUID,
body: ThumbnailUploadRequest,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> None:
diagram = await _get_diagram_or_404(diagram_id, current_user.account_id, db)
try:
header, encoded = body.data_url.split(",", 1)
except ValueError:
raise HTTPException(status_code=422, detail="Invalid data URL format")
image_bytes = base64.b64decode(encoded)
storage_key = await storage_service.upload_file(
file_data=image_bytes,
filename=f"thumbnail-{diagram_id}.png",
content_type="image/png",
account_id=str(current_user.account_id),
)
presigned_url = storage_service.get_presigned_url(storage_key)
diagram.thumbnail_url = presigned_url
await db.commit()
@router.post("/ai-generate", response_model=AIGenerateResponse)
async def ai_generate_diagram(
data: AIGenerateRequest,
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> AIGenerateResponse:
available_slugs_set = await _get_available_slugs(current_user.account_id, db)
available_slugs = list(available_slugs_set)
existing_node_ids: list[str] | None = None
if data.mode == "merge" and data.existingBounds:
existing_node_ids = []
try:
return await network_diagram_ai_service.generate_diagram(
request=data,
available_slugs=available_slugs,
existing_node_ids=existing_node_ids,
)
except ValueError as e:
raise HTTPException(status_code=422, detail=str(e))
except Exception:
logger.exception("AI diagram generation failed")
raise HTTPException(status_code=500, detail="Diagram generation failed")

View File

@@ -3,14 +3,12 @@ from typing import Annotated
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException, Request
from sqlalchemy import select, text
from sqlalchemy.exc import IntegrityError
from sqlalchemy import text
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.database import get_db
from app.core.rate_limit import limiter
from app.api.deps import get_current_active_user
from app.models.ai_session import AISession
from app.models.user import User
from app.models.script_builder_session import ScriptBuilderSession
from app.schemas.script_builder import (
@@ -69,85 +67,15 @@ async def create_session(
db: Annotated[AsyncSession, Depends(get_db)],
current_user: Annotated[User, Depends(get_current_active_user)],
) -> ScriptBuilderSessionDetail:
"""Start a new Script Builder session.
When origin='pilot_inline', behaves as get-or-create: the same row is
returned on repeated calls with the same (user, ai_session_id) pair.
Inline sessions are excluded from the session cap and the list endpoint.
"""
# Phase 9: inline origin validation + authorization
if data.origin == "pilot_inline":
if data.ai_session_id is None:
raise HTTPException(
status_code=400,
detail="ai_session_id is required when origin='pilot_inline'",
)
# Ownership check: the pilot session must belong to the current user.
ai_session = await db.scalar(
select(AISession).where(
AISession.id == data.ai_session_id,
AISession.user_id == current_user.id,
)
)
if ai_session is None:
raise HTTPException(
status_code=404,
detail="Session not found",
)
# Idempotent get-or-create: if a pilot_inline row already exists for
# this (user, ai_session_id) pair, return it without creating a duplicate.
existing = await db.scalar(
select(ScriptBuilderSession).where(
ScriptBuilderSession.user_id == current_user.id,
ScriptBuilderSession.ai_session_id == data.ai_session_id,
ScriptBuilderSession.origin == "pilot_inline",
)
)
if existing is not None:
# Re-fetch with message_records loaded
session = await script_builder_service.get_session(db, existing.id, current_user.id)
return _session_to_detail(session)
# Create the inline session — wrap in IntegrityError catch for races.
try:
session = await script_builder_service.create_session(
db=db,
user_id=current_user.id,
account_id=current_user.account_id,
team_id=current_user.team_id,
language=data.language,
origin=data.origin,
ai_session_id=data.ai_session_id,
)
await db.commit()
except IntegrityError:
await db.rollback()
# Race: another request won the unique index — re-read the winner row.
existing = await db.scalar(
select(ScriptBuilderSession).where(
ScriptBuilderSession.user_id == current_user.id,
ScriptBuilderSession.ai_session_id == data.ai_session_id,
ScriptBuilderSession.origin == "pilot_inline",
)
)
if existing is None:
raise
session = existing
# Re-fetch with message_records loaded
session = await script_builder_service.get_session(db, session.id, current_user.id)
return _session_to_detail(session)
# ── Standalone session ──────────────────────────────────────────────────
"""Start a new Script Builder session."""
# Acquire per-user advisory lock so concurrent create requests are serialized.
# Without this, two simultaneous requests both read count < limit and both
# insert, exceeding MAX_SESSIONS_PER_USER.
user_lock_key = hash(str(current_user.id)) % (2**62)
await db.execute(text("SELECT pg_advisory_xact_lock(:key)"), {"key": user_lock_key})
# Enforce max concurrent sessions (inline sessions excluded from cap)
count = await script_builder_service.count_user_sessions(db, current_user.id, include_inline=False)
# Enforce max concurrent sessions
count = await script_builder_service.count_user_sessions(db, current_user.id)
if count >= MAX_SESSIONS_PER_USER:
raise HTTPException(
status_code=400,
@@ -160,8 +88,6 @@ async def create_session(
account_id=current_user.account_id,
team_id=current_user.team_id,
language=data.language,
origin=data.origin,
ai_session_id=data.ai_session_id,
)
await db.commit()
# Re-fetch with message_records loaded

View File

@@ -5,7 +5,7 @@ import re
from fastapi import APIRouter, Depends, HTTPException, Query, status
from sqlalchemy.ext.asyncio import AsyncSession
from sqlalchemy import select, func, or_, literal, update as sa_update
from sqlalchemy import select, func, or_, literal
from app.core.database import get_db
from app.api.deps import get_current_active_user
@@ -374,20 +374,6 @@ async def generate_script(
)
db.add(generation)
template.usage_count += 1
# FlowPilot Phase 3: bump the linked AI session's state_version so the
# resolution-note preview cache invalidates. One-off scripts run outside
# any FlowPilot session — in that case the UPDATE matches zero rows.
if data.ai_session_id is not None:
# Local import: scripts endpoint stays independent of AI-session
# imports for non-AI generation paths.
from app.models.ai_session import AISession
await db.execute(
sa_update(AISession)
.where(AISession.id == data.ai_session_id)
.values(state_version=AISession.state_version + 1)
)
await db.commit()
await db.refresh(generation)

View File

@@ -1,315 +0,0 @@
"""Session fact endpoints — the "What we know" CRUD surface for a FlowPilot session.
All routes are sub-resources of `/ai-sessions/{session_id}`. Tenant isolation is
enforced by RLS on `session_facts.account_id`; a user from another account
literally cannot see or write facts for this session.
Editability rule (per FLOWPILOT-MIGRATION.md Section 7.3):
- `user_note` and `ai_synthesis` facts are editable at the card level.
- `question` and `diagnostic_check` facts are read-only at the card level —
edit the source question/check instead. PATCH returns 403 for those.
Fact promotion writes always bump `ai_sessions.state_version` so the
resolution-note preview cache invalidates (Section 5.5).
"""
import logging
from datetime import datetime, timezone
from typing import Annotated
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.api.deps import get_current_active_user, get_db, require_engineer_or_admin
from app.models.ai_session import AISession
from app.models.session_fact import SessionFact
from app.models.user import User
from app.schemas.session_fact import (
SessionFactCreateRequest,
SessionFactListResponse,
SessionFactPromoteRequest,
SessionFactResponse,
SessionFactUpdateRequest,
)
from app.services.fact_synthesis_service import (
FactSynthesisService,
list_facts_for_session,
)
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/ai-sessions/{session_id}", tags=["session-facts"])
# Source types whose facts can be edited at the card level (Section 7.3).
_EDITABLE_SOURCE_TYPES = frozenset({"user_note", "ai_synthesis"})
def _to_response(fact: SessionFact) -> SessionFactResponse:
"""Wrap an ORM SessionFact in the response model with the editable flag."""
return SessionFactResponse(
id=fact.id,
session_id=fact.session_id,
text=fact.text,
source_type=fact.source_type, # type: ignore[arg-type]
source_ref=fact.source_ref,
source_summary=fact.source_summary,
created_by=fact.created_by,
created_at=fact.created_at,
updated_at=fact.updated_at,
editable=fact.source_type in _EDITABLE_SOURCE_TYPES,
)
async def _load_session_or_404(db: AsyncSession, session_id: UUID) -> AISession:
"""Load the session via RLS-scoped SELECT. Returns 404 if missing/cross-tenant.
Tenant isolation: RLS on `ai_sessions` filters by current account, so a
cross-tenant access returns no rows and we 404 (rather than 403, which
would leak the row's existence).
"""
result = await db.execute(select(AISession).where(AISession.id == session_id))
session = result.scalar_one_or_none()
if session is None:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Session not found")
return session
async def _load_fact_or_404(
db: AsyncSession, session_id: UUID, fact_id: UUID
) -> SessionFact:
"""Load a non-deleted fact for the session. 404 if missing or already deleted."""
result = await db.execute(
select(SessionFact).where(
SessionFact.id == fact_id,
SessionFact.session_id == session_id,
SessionFact.deleted_at.is_(None),
)
)
fact = result.scalar_one_or_none()
if fact is None:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Fact not found")
return fact
# ── List ──
@router.get("/facts", response_model=SessionFactListResponse)
async def list_facts(
session_id: UUID,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> SessionFactListResponse:
"""List facts for a session, oldest first."""
await _load_session_or_404(db, session_id)
facts = await list_facts_for_session(db, session_id)
return SessionFactListResponse(facts=[_to_response(f) for f in facts])
# ── Create (manual user note) ──
@router.post("/facts", response_model=SessionFactResponse, status_code=201)
async def create_fact(
session_id: UUID,
body: SessionFactCreateRequest,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> SessionFactResponse:
"""Create a manual fact (the "+ Add a note" UI affordance).
Always recorded as `source_type=user_note`. Source-typed creation goes
through `/facts/promote` so the originating item ID is captured.
"""
session = await _load_session_or_404(db, session_id)
service = FactSynthesisService(db)
try:
fact = await service.create_fact(
session_id=session.id,
account_id=session.account_id,
user_id=current_user.id,
source_type="user_note",
text=body.text,
summary=body.summary,
source_ref=None,
)
except ValueError as e:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(e))
await db.commit()
await db.refresh(fact)
return _to_response(fact)
# ── Update ──
@router.patch("/facts/{fact_id}", response_model=SessionFactResponse)
async def update_fact(
session_id: UUID,
fact_id: UUID,
body: SessionFactUpdateRequest,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> SessionFactResponse:
"""Edit fact text or summary.
Returns 403 for `question` and `diagnostic_check`-sourced facts: the
source item is the canonical input, so editing the fact card would
desync the two. Engineers edit the source instead.
"""
fact = await _load_fact_or_404(db, session_id, fact_id)
if fact.source_type not in _EDITABLE_SOURCE_TYPES:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=(
f"Facts sourced from {fact.source_type!r} are read-only at the "
"card level. Edit the originating question or diagnostic check instead."
),
)
if body.text is None and body.summary is None:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="At least one of `text` or `summary` must be provided",
)
service = FactSynthesisService(db)
try:
fact = await service.update_fact(fact, text=body.text, summary=body.summary)
except ValueError as e:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(e))
await db.commit()
await db.refresh(fact)
return _to_response(fact)
# ── Soft delete ──
@router.delete("/facts/{fact_id}", status_code=204)
async def delete_fact(
session_id: UUID,
fact_id: UUID,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> None:
"""Soft-delete a fact. All source types are deletable.
Soft delete (rather than hard) preserves provenance for audit and lets
accidental deletes be recovered if needed. The `editable` flag does NOT
control deletion — even read-only facts can be removed when the
underlying question/check turned out to be wrong.
"""
fact = await _load_fact_or_404(db, session_id, fact_id)
service = FactSynthesisService(db)
await service.soft_delete_fact(fact)
await db.commit()
# ── Promote (AI marker + engineer-driven) ──
@router.post("/facts/promote", response_model=SessionFactResponse, status_code=201)
async def promote_fact(
session_id: UUID,
body: SessionFactPromoteRequest,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> SessionFactResponse:
"""Convert a question answer / check result into a fact.
Two modes:
- `proposed_text` provided → persisted as-is.
- `raw_input` provided → server drafts text/summary via FactSynthesisService.
Exactly one of the two must be set. The engineer-facing UI typically uses
`proposed_text` after letting the engineer review/edit a draft.
"""
if (body.proposed_text is None) == (body.raw_input is None):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Exactly one of `proposed_text` or `raw_input` must be provided",
)
if body.source_type == "ai_synthesis" and body.source_ref is not None:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="`source_ref` must be null for source_type=ai_synthesis",
)
session = await _load_session_or_404(db, session_id)
service = FactSynthesisService(db)
text = body.proposed_text
summary = body.proposed_summary
if text is None:
# Synthesize via LLM. Caller must hint which task-lane item the input
# came from so we can shape the prompt appropriately.
raw = body.raw_input or ""
if body.source_type == "question":
draft = await service.synthesize_from_question(
question_text=_lookup_task_lane_text(session, body.source_ref, "questions"),
raw_answer=raw,
)
elif body.source_type == "diagnostic_check":
draft = await service.synthesize_from_check(
check_label=_lookup_task_lane_text(session, body.source_ref, "actions"),
check_output=raw,
)
else:
# ai_synthesis with raw_input: the raw input IS the synthesis.
# Re-run through the question synthesizer with an empty question
# so the conservative prompt still applies.
draft = await service.synthesize_from_question(
question_text="(none — synthesizing from engineer summary)",
raw_answer=raw,
)
text = draft["text"]
summary = summary or draft["summary"]
if not text:
raise HTTPException(
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
detail=(
"Synthesizer found no substantive fact in the input. "
"Edit the input or supply `proposed_text` directly."
),
)
try:
fact = await service.create_fact(
session_id=session.id,
account_id=session.account_id,
user_id=current_user.id,
source_type=body.source_type,
text=text,
summary=summary,
source_ref=body.source_ref,
)
except ValueError as e:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=str(e))
await db.commit()
await db.refresh(fact)
return _to_response(fact)
def _lookup_task_lane_text(
session: AISession, source_ref: UUID | None, list_key: str
) -> str:
"""Find the originating question text / action label from pending_task_lane.
Falls back to a generic placeholder if the source item is no longer in
the lane (e.g., the AI dropped it from a later turn). The synthesizer is
forgiving — an empty/generic question still produces a useful fact when
the engineer's answer is substantive on its own.
"""
if source_ref is None:
return ""
lane = session.pending_task_lane or {}
items = lane.get(list_key) or []
sref = str(source_ref)
for item in items:
if isinstance(item, dict) and str(item.get("id")) == sref:
return str(item.get("text") or item.get("label") or "")
return ""

View File

@@ -1,759 +0,0 @@
"""Suggested-fix + resolution-note / escalation-package preview-and-post endpoints.
Phase 3: active suggested fix lookup + decision recording, resolution-note
preview with state_version cache.
Phase 4: resolution-note POST (writeback to PSA + mark resolved), escalation
package preview + POST (writeback + mark escalated). Local-only path when
the session has no linked PSA ticket: markdown is stored on the session and
the status flipped, no external call.
Per FLOWPILOT-MIGRATION.md Sections 5.2 + 5.4.
"""
import logging
from datetime import datetime, timezone
from typing import Annotated
from uuid import UUID
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy import select, update
from sqlalchemy.ext.asyncio import AsyncSession
from app.api.deps import get_current_active_user, get_db, require_engineer_or_admin
from app.models.ai_session import AISession
from app.models.session_suggested_fix import SessionSuggestedFix
from app.models.user import User
from app.schemas.session_suggested_fix import (
EscalationPackagePostRequest,
ResolutionNotePostRequest,
ResolutionNotePreviewResponse,
ResolutionPostResponse,
SessionSuggestedFixDecisionRequest,
SessionSuggestedFixDecisionResponse,
SessionSuggestedFixOutcomeRequest,
SessionSuggestedFixResponse,
SessionSuggestedFixScriptRequest,
)
from app.models.draft_template import DraftTemplate
from app.models.session_fact import SessionFact
from app.services.escalation_package_generator import EscalationPackageGeneratorService
from app.services.preview_cache import preview_cache
from app.services.psa_writeback_service import (
PSAStatusVerificationError,
PSAWritebackService,
)
from app.services.resolution_note_generator import ResolutionNoteGeneratorService
from app.services.template_extraction_service import extract_parameters as _extract_template_parameters
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/ai-sessions/{session_id}", tags=["session-suggested-fixes"])
async def _load_session_or_404(db: AsyncSession, session_id: UUID) -> AISession:
"""RLS-scoped session load. 404 covers both missing and cross-tenant."""
result = await db.execute(select(AISession).where(AISession.id == session_id))
session = result.scalar_one_or_none()
if session is None:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Session not found")
return session
# ── Suggested fix: active ──────────────────────────────────────────────────
@router.get(
"/suggested-fixes/active",
response_model=SessionSuggestedFixResponse,
)
async def get_active_suggested_fix(
session_id: UUID,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> SessionSuggestedFixResponse:
"""Return the current active suggested fix (`superseded_at IS NULL`) or 404.
A session has at most one active fix. Multiple historical rows persist
for audit, but only the most-recent un-superseded one is returned here.
"""
await _load_session_or_404(db, session_id)
result = await db.execute(
select(SessionSuggestedFix)
.where(
SessionSuggestedFix.session_id == session_id,
SessionSuggestedFix.superseded_at.is_(None),
)
.order_by(SessionSuggestedFix.created_at.desc())
)
fix = result.scalars().first()
if fix is None:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail="No active suggested fix for this session",
)
return SessionSuggestedFixResponse.model_validate(fix)
# ── Suggested fix: decision ────────────────────────────────────────────────
@router.post(
"/suggested-fixes/{fix_id}/decision",
response_model=SessionSuggestedFixDecisionResponse,
)
async def record_decision(
session_id: UUID,
fix_id: UUID,
body: SessionSuggestedFixDecisionRequest,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> SessionSuggestedFixDecisionResponse:
"""Record the engineer's path choice on a suggested fix.
Phase 3 recorded the choice and (for `dismissed`) superseded the fix.
Phase 5 adds side effects: one_off / draft_template return the rendered
script; draft_template also creates a `draft_templates` row via the
TemplateExtractionService; build_template returns a redirect to the
Script Builder.
"""
session_obj = await _load_session_or_404(db, session_id)
result = await db.execute(
select(SessionSuggestedFix).where(
SessionSuggestedFix.id == fix_id,
SessionSuggestedFix.session_id == session_id,
)
)
fix = result.scalar_one_or_none()
if fix is None:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Suggested fix not found"
)
# Once a fix has been superseded we still record the engineer's
# decision (it's a historical signal — "engineer dismissed the
# interim hypothesis"), but `dismissed` on a superseded row would
# be redundant noise.
if fix.superseded_at is not None and body.decision == "dismissed":
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail="This fix is already superseded by a newer suggestion",
)
fix.user_decision = body.decision
if body.decision == "dismissed" and fix.superseded_at is None:
fix.superseded_at = datetime.now(timezone.utc)
# Engineer's choice changes the bundle the resolution-note preview sees,
# so bump state_version too.
await db.execute(
update(AISession)
.where(AISession.id == session_id)
.values(state_version=AISession.state_version + 1)
)
rendered_script: str | None = None
draft_template_id: UUID | None = None
redirect_path: str | None = None
# Phase 5 side effects. All three non-dismiss paths assume the fix has
# either a script_template_id (template match — use the dedicated
# /scripts/generate endpoint from the frontend, not this one) or an
# ai_drafted_script (custom script — this is the entry point).
if body.decision in ("one_off", "draft_template", "build_template"):
drafted = body.edited_script or fix.ai_drafted_script
if not drafted:
# Template-matched fixes take the regular /scripts/generate path.
# If a fix somehow reaches here without a drafted script AND
# without a template, that's a client-side wiring bug.
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=(
"Suggested fix has no ai_drafted_script — use "
"/api/v1/scripts/generate for template-matched fixes."
),
)
rendered_script = drafted.strip()
if body.decision == "draft_template":
# TemplateExtractionService proposes the parameterization. Runs
# under the same transaction so a failure rolls back the decision.
session_ctx = await _summarize_session_for_extraction(db, session_id)
extraction = await _extract_template_parameters(
script_body=rendered_script or "",
session_context=session_ctx,
ticket_context=None, # ticket context wiring lands in Phase 5 polish
)
draft = DraftTemplate(
account_id=session_obj.account_id,
source_session_id=session_obj.id,
source_user_id=current_user.id,
script_body=extraction["templated_body"] or (rendered_script or ""),
proposed_parameters={"parameters": extraction["parameters"]},
proposed_name=fix.title[:200] if fix.title else None,
status="pending",
)
db.add(draft)
await db.flush()
draft_template_id = draft.id
if body.decision == "build_template":
# Frontend navigates to the Script Builder preloaded with the
# drafted body. The builder wires the full parameterization flow;
# we hand it a scratch-pad query string, not persistent state.
redirect_path = (
f"/scripts/builder?from_session={session_obj.id}&fix={fix.id}"
)
await db.commit()
await db.refresh(fix)
return SessionSuggestedFixDecisionResponse(
id=fix.id,
user_decision=fix.user_decision, # type: ignore[arg-type]
rendered_script=rendered_script,
draft_template_id=draft_template_id,
redirect_path=redirect_path,
)
# ── Suggested fix: apply (stamp applied_at) ──────────────────────────────
@router.post(
"/suggested-fixes/{fix_id}/apply",
response_model=SessionSuggestedFixResponse,
)
async def apply_suggested_fix(
session_id: UUID,
fix_id: UUID,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> SessionSuggestedFixResponse:
"""Stamp applied_at when the engineer clicks Apply in the ProposalBanner.
This does NOT change status (fix remains 'proposed'). Status only flips
when the engineer records an outcome via PATCH /outcome.
Rules:
- Fix must be in 'proposed' status; any other status → 409.
- Idempotent: if applied_at is already set, returns 200 with the unchanged row.
- Bumps ai_sessions.state_version so resolve/escalate preview generators
know the fix has entered the verifying phase.
"""
await _load_session_or_404(db, session_id)
result = await db.execute(
select(SessionSuggestedFix).where(
SessionSuggestedFix.id == fix_id,
SessionSuggestedFix.session_id == session_id,
)
)
fix = result.scalar_one_or_none()
if fix is None:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Suggested fix not found"
)
if fix.status != "proposed":
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=f"Apply is only valid from 'proposed'; fix is already '{fix.status}'",
)
# Idempotent: already stamped → return as-is without bumping state_version again.
if fix.applied_at is not None:
return SessionSuggestedFixResponse.model_validate(fix)
fix.applied_at = datetime.now(timezone.utc)
# Bump state_version so preview generators see the verifying-phase signal.
await db.execute(
update(AISession)
.where(AISession.id == session_id)
.values(state_version=AISession.state_version + 1)
)
await db.commit()
await db.refresh(fix)
return SessionSuggestedFixResponse.model_validate(fix)
# ── Suggested fix: outcome ────────────────────────────────────────────────
@router.patch(
"/suggested-fixes/{fix_id}/outcome",
response_model=SessionSuggestedFixResponse,
)
async def patch_suggested_fix_outcome(
session_id: UUID,
fix_id: UUID,
body: SessionSuggestedFixOutcomeRequest,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> SessionSuggestedFixResponse:
"""Record the engineer's outcome for an applied fix.
See `SessionSuggestedFixOutcomeRequest` for transition rules.
"""
await _load_session_or_404(db, session_id)
now = datetime.now(timezone.utc)
result = await db.execute(
select(SessionSuggestedFix).where(
SessionSuggestedFix.id == fix_id,
SessionSuggestedFix.session_id == session_id,
)
)
fix = result.scalar_one_or_none()
if fix is None:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Suggested fix not found"
)
if body.outcome == "applied_partial" and not (body.notes and body.notes.strip()):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="notes are required when outcome is applied_partial",
)
TERMINAL = {"applied_success", "applied_failed", "dismissed"}
if fix.status in TERMINAL:
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=f"Fix is already in terminal status {fix.status!r}",
)
fix.status = body.outcome
if body.outcome == "applied_partial":
fix.partial_notes = (body.notes or "").strip() or None
elif body.outcome == "applied_failed":
fix.failure_reason = (body.notes or "").strip() or None
fix.verified_at = now
elif body.outcome == "applied_success":
fix.verified_at = now
# dismissed: no timestamp/notes stamping
if fix.applied_at is None and body.outcome != "dismissed":
fix.applied_at = now
# Clear any pending AI outcome proposal — engineer has taken a terminal action.
fix.ai_outcome_proposal = None
# Outcome changes the bundle that resolution-note/escalation-package
# previews see, so bump state_version inside the same transaction —
# mirrors the pattern in record_decision above.
await db.execute(
update(AISession)
.where(AISession.id == session_id)
.values(state_version=AISession.state_version + 1)
)
await db.commit()
await db.refresh(fix)
return SessionSuggestedFixResponse.model_validate(fix)
# ── Suggested fix: attach drafted script ─────────────────────────────────────
@router.patch(
"/suggested-fixes/{fix_id}/script",
response_model=SessionSuggestedFixResponse,
)
async def patch_suggested_fix_script(
session_id: UUID,
fix_id: UUID,
body: SessionSuggestedFixScriptRequest,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> SessionSuggestedFixResponse:
"""Attach an engineer-drafted script to a suggested fix.
Called by the inline Script Builder tab on Submit. Does NOT stamp
applied_at — a draft is not an application. Bumps state_version so
the Resolve/Escalate preview bundles regenerate.
"""
await _load_session_or_404(db, session_id)
fix = await db.scalar(
select(SessionSuggestedFix).where(
SessionSuggestedFix.id == fix_id,
SessionSuggestedFix.session_id == session_id,
)
)
if fix is None:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Suggested fix not found")
TERMINAL = {"applied_success", "applied_failed", "dismissed"}
if fix.status in TERMINAL:
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=f"Fix is already in terminal status {fix.status!r}",
)
fix.ai_drafted_script = body.ai_drafted_script
fix.ai_drafted_parameters = body.ai_drafted_parameters
# Bump state_version on the parent session — previews cached by
# (session_id, state_version) must regenerate to reflect the new draft.
await db.execute(
update(AISession)
.where(AISession.id == session_id)
.values(state_version=AISession.state_version + 1)
)
await db.commit()
await db.refresh(fix)
return SessionSuggestedFixResponse.model_validate(fix)
# ── Suggested fix: clear AI outcome proposal ("Not yet") ─────────────────────
@router.delete(
"/suggested-fixes/{fix_id}/ai-outcome-proposal",
response_model=SessionSuggestedFixResponse,
)
async def clear_ai_outcome_proposal(
session_id: UUID,
fix_id: UUID,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> SessionSuggestedFixResponse:
"""Explicitly dismiss the AI-proposed outcome banner ("Not yet").
Clears `ai_outcome_proposal` without touching status or state_version
(this is pure UI state, not outcome data). Idempotent: returns 200 even
when the field is already null. After this call the banner will not
re-surface on the next refreshSessionDerived unless the AI emits a new
proposal.
"""
await _load_session_or_404(db, session_id)
result = await db.execute(
select(SessionSuggestedFix).where(
SessionSuggestedFix.id == fix_id,
SessionSuggestedFix.session_id == session_id,
)
)
fix = result.scalar_one_or_none()
if fix is None:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND, detail="Suggested fix not found"
)
fix.ai_outcome_proposal = None
await db.commit()
await db.refresh(fix)
return SessionSuggestedFixResponse.model_validate(fix)
async def _summarize_session_for_extraction(
db: AsyncSession, session_id: UUID,
) -> str:
"""Compact fact list for TemplateExtractionService context.
We don't send the full chat transcript — the extractor only needs enough
signal to decide which values in the script are session-specific (and
therefore worth parameterizing).
"""
result = await db.execute(
select(SessionFact)
.where(
SessionFact.session_id == session_id,
SessionFact.deleted_at.is_(None),
)
.order_by(SessionFact.created_at.asc())
)
facts = list(result.scalars().all())
if not facts:
return ""
lines = [f"- {f.text}" for f in facts]
return "\n".join(lines)
# ── Resolution note preview ────────────────────────────────────────────────
@router.post(
"/resolution-note/preview",
response_model=ResolutionNotePreviewResponse,
)
async def resolution_note_preview(
session_id: UUID,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> ResolutionNotePreviewResponse:
"""Generate (or return cached) draft markdown for the Resolve note.
Cache key: `(resolution_note, session_id, state_version)`. State_version is
bumped by every fact / suggested-fix / script-generation write, so two
consecutive calls with no intervening writes return the same cached
payload (and won't pay for a Sonnet call).
Posted to PSA in Phase 4. Until then, this endpoint is read-only.
"""
await _load_session_or_404(db, session_id)
gen = ResolutionNoteGeneratorService(db)
try:
payload = await gen.generate_or_get_cached(session_id)
except ValueError as e:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(e))
except Exception as e:
logger.exception("Resolution note preview failed for session %s", session_id)
raise HTTPException(
status_code=status.HTTP_502_BAD_GATEWAY,
detail=f"Resolution-note generator error ({type(e).__name__})",
)
return ResolutionNotePreviewResponse(**payload)
# ── Phase 4: escalation-package preview ────────────────────────────────────
@router.post(
"/escalation-package/preview",
response_model=ResolutionNotePreviewResponse,
)
async def escalation_package_preview(
session_id: UUID,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> ResolutionNotePreviewResponse:
"""Generate (or return cached) draft markdown for the Escalate handoff package.
Same caching story as the resolution-note preview: keyed on
`(session_id, state_version)`. Separate cache kind so a Resolve preview
and an Escalate preview for the same state can coexist.
"""
await _load_session_or_404(db, session_id)
gen = EscalationPackageGeneratorService(db)
try:
payload = await gen.generate_or_get_cached(session_id)
except ValueError as e:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=str(e))
except Exception as e:
logger.exception("Escalation package preview failed for session %s", session_id)
raise HTTPException(
status_code=status.HTTP_502_BAD_GATEWAY,
detail=f"Escalation-package generator error ({type(e).__name__})",
)
return ResolutionNotePreviewResponse(**payload)
# ── Phase 4: Resolve & post ────────────────────────────────────────────────
@router.post(
"/resolution-note/post",
response_model=ResolutionPostResponse,
)
async def post_resolution_note(
session_id: UUID,
body: ResolutionNotePostRequest,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> ResolutionPostResponse:
"""Commit the engineer-edited resolution note and close the session.
Three outcomes:
- **External post + status verified** — session.status='resolved',
markdown + external_id + posted_at persisted, CW status flipped to
the configured Resolved status ID and re-fetch-verified.
- **External post only** — markdown posted, but no cw_resolved_status_id
configured → session.status='resolved', `status_transition_skipped_reason`
explains the skip. Not an error — posting the note is meaningful.
- **Local-only** — session has no linked PSA ticket → markdown stored on
`resolution_note_markdown`, session.status='resolved', outcome =
'resolved_local'. No external call.
Status verification failure raises 502: the engineer intended to close
the ticket but we cannot confirm it actually closed. Surfacing silent
success would be a footgun.
"""
session_obj = await _load_session_or_404(db, session_id)
if session_obj.status not in ("active", "paused", "requesting_escalation", "escalated"):
# Already-resolved sessions shouldn't be re-posted; caller should
# query first. escalated→resolved is allowed (engineer revised course).
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=f"Session is already {session_obj.status}",
)
service = PSAWritebackService(db)
summary = (body.resolution_summary or body.markdown.strip().splitlines()[0])[:500]
# Local-only path — no PSA ticket linked, nothing to post.
if not session_obj.psa_ticket_id or not session_obj.psa_connection_id:
session_obj.resolution_note_markdown = body.markdown.strip()
session_obj.status = "resolved"
session_obj.resolved_at = datetime.now(timezone.utc)
session_obj.resolution_summary = summary
await db.commit()
return ResolutionPostResponse(
outcome="resolved_local",
session_status=session_obj.status,
)
try:
posted = await service.post_resolution_note(session_obj, body.markdown)
except Exception as e:
logger.exception("post_resolution_note failed for session %s", session_id)
await db.rollback()
raise HTTPException(
status_code=status.HTTP_502_BAD_GATEWAY,
detail=f"PSA post failed ({type(e).__name__})",
)
# Attempt the status transition if configured; failed verification is
# surfaced loudly (status_code 502) per the ConnectWise anti-silent-
# success principle. Not configured → skip with a reason, not an error.
target_status_id = await service.resolved_status_id_for_account(session_obj.account_id)
verified_status_id: int | None = None
verified_status_name: str | None = None
skipped_reason: str | None = None
if target_status_id is None:
skipped_reason = (
"No cw_resolved_status_id configured in account_settings.preferences — "
"note posted, status unchanged."
)
else:
try:
result = await service.transition_ticket_status(session_obj, target_status_id)
verified_status_id = result["verified_status_id"]
verified_status_name = result["verified_status_name"]
except PSAStatusVerificationError as e:
logger.error("Status verification failed for session %s: %s", session_id, e)
# Note was already posted — roll that partial side effect back in
# the session record (the CW note itself can't be un-posted).
await db.rollback()
raise HTTPException(
status_code=status.HTTP_502_BAD_GATEWAY,
detail=str(e),
)
except Exception as e:
logger.exception("Status transition failed for session %s", session_id)
await db.rollback()
raise HTTPException(
status_code=status.HTTP_502_BAD_GATEWAY,
detail=f"PSA status transition error ({type(e).__name__})",
)
session_obj.status = "resolved"
session_obj.resolved_at = datetime.now(timezone.utc)
session_obj.resolution_summary = summary
await db.commit()
return ResolutionPostResponse(
outcome="resolved",
session_status=session_obj.status,
external_id=posted["external_id"],
posted_at=posted["posted_at"],
verified_status_id=verified_status_id,
verified_status_name=verified_status_name,
status_transition_skipped_reason=skipped_reason,
)
# ── Phase 4: Escalate & post ──────────────────────────────────────────────
@router.post(
"/escalation-package/post",
response_model=ResolutionPostResponse,
)
async def post_escalation_package(
session_id: UUID,
body: EscalationPackagePostRequest,
current_user: Annotated[User, Depends(get_current_active_user)],
db: Annotated[AsyncSession, Depends(get_db)],
_: None = Depends(require_engineer_or_admin),
) -> ResolutionPostResponse:
"""Commit the engineer-edited escalation package and mark the session escalated.
Structure mirrors post_resolution_note:
- Local-only when no PSA ticket: markdown stored, session.status='escalated'.
- PSA post: internal-analysis note (handoff is for the next engineer,
not the customer), optional status transition via cw_escalated_status_id,
re-fetch verified.
"""
session_obj = await _load_session_or_404(db, session_id)
if session_obj.status not in ("active", "paused", "resolved"):
# resolved→escalated is allowed (engineer realized they need help
# after closing); escalated→escalated would be a no-op, block it.
raise HTTPException(
status_code=status.HTTP_409_CONFLICT,
detail=f"Session is already {session_obj.status}",
)
service = PSAWritebackService(db)
reason = body.escalation_reason or body.markdown.strip().splitlines()[0][:500]
if not session_obj.psa_ticket_id or not session_obj.psa_connection_id:
session_obj.escalation_package_markdown = body.markdown.strip()
session_obj.status = "escalated"
session_obj.escalation_reason = reason
await db.commit()
return ResolutionPostResponse(
outcome="escalated_local",
session_status=session_obj.status,
)
try:
posted = await service.post_escalation_package(session_obj, body.markdown)
except Exception as e:
logger.exception("post_escalation_package failed for session %s", session_id)
await db.rollback()
raise HTTPException(
status_code=status.HTTP_502_BAD_GATEWAY,
detail=f"PSA post failed ({type(e).__name__})",
)
target_status_id = await service.escalated_status_id_for_account(session_obj.account_id)
verified_status_id: int | None = None
verified_status_name: str | None = None
skipped_reason: str | None = None
if target_status_id is None:
skipped_reason = (
"No cw_escalated_status_id configured — package posted, status unchanged."
)
else:
try:
result = await service.transition_ticket_status(session_obj, target_status_id)
verified_status_id = result["verified_status_id"]
verified_status_name = result["verified_status_name"]
except PSAStatusVerificationError as e:
logger.error("Status verification failed for session %s: %s", session_id, e)
await db.rollback()
raise HTTPException(status_code=status.HTTP_502_BAD_GATEWAY, detail=str(e))
except Exception as e:
logger.exception("Status transition failed for session %s", session_id)
await db.rollback()
raise HTTPException(
status_code=status.HTTP_502_BAD_GATEWAY,
detail=f"PSA status transition error ({type(e).__name__})",
)
session_obj.status = "escalated"
session_obj.escalation_reason = reason
await db.commit()
return ResolutionPostResponse(
outcome="escalated",
session_status=session_obj.status,
external_id=posted["external_id"],
posted_at=posted["posted_at"],
verified_status_id=verified_status_id,
verified_status_name=verified_status_name,
status_transition_skipped_reason=skipped_reason,
)
# ── Helper used by tests ───────────────────────────────────────────────────
def _clear_preview_cache_for_tests() -> None:
"""Reset the singleton cache between tests."""
preview_cache._store.clear() # noqa: SLF001 — test-only access

View File

@@ -24,8 +24,6 @@ from app.api.endpoints import (
branding,
categories,
copilot,
device_types,
draft_templates,
feedback,
flow_proposals,
flowpilot_analytics,
@@ -34,7 +32,6 @@ from app.api.endpoints import (
invite,
kb_accelerator,
maintenance_schedules,
network_diagrams,
notifications,
onboarding,
public_templates,
@@ -42,10 +39,8 @@ from app.api.endpoints import (
scripts,
script_builder,
session_branches,
session_facts,
session_handoffs,
session_resolutions,
session_suggested_fixes,
sessions,
shared,
shares,
@@ -98,6 +93,7 @@ api_router.include_router(admin_settings.router)
api_router.include_router(admin_categories.router)
api_router.include_router(admin_survey.router)
api_router.include_router(admin_gallery.router)
# ---------------------------------------------------------------------------
# User-facing endpoints — tenant context required
# ---------------------------------------------------------------------------
@@ -134,15 +130,9 @@ api_router.include_router(integrations.router, dependencies=_tenant_deps)
api_router.include_router(onboarding.router, dependencies=_tenant_deps)
api_router.include_router(branding.router, dependencies=_tenant_deps)
api_router.include_router(supporting_data.router, dependencies=_tenant_deps)
api_router.include_router(network_diagrams.router, dependencies=_tenant_deps)
# session_handoffs queue router must come before ai_sessions to avoid conflict
api_router.include_router(session_handoffs.queue_router, dependencies=_tenant_deps)
api_router.include_router(session_resolutions.router, dependencies=_tenant_deps)
# session_facts mounts under /ai-sessions/{id}/facts — register before ai_sessions
# so the {session_id}/facts subpaths take precedence over any future generic catchalls.
api_router.include_router(session_facts.router, dependencies=_tenant_deps)
api_router.include_router(session_suggested_fixes.router, dependencies=_tenant_deps)
api_router.include_router(draft_templates.router, dependencies=_tenant_deps)
api_router.include_router(ai_sessions.router, dependencies=_tenant_deps)
api_router.include_router(flow_proposals.router, dependencies=_tenant_deps)
api_router.include_router(flowpilot_analytics.router, dependencies=_tenant_deps)
@@ -152,4 +142,3 @@ api_router.include_router(script_builder.router, dependencies=_tenant_deps)
api_router.include_router(beta_feedback.router, dependencies=_tenant_deps)
api_router.include_router(session_branches.router, dependencies=_tenant_deps)
api_router.include_router(session_handoffs.router, dependencies=_tenant_deps)
api_router.include_router(device_types.router, dependencies=_tenant_deps)

View File

@@ -40,7 +40,7 @@ CRITICAL BEHAVIORS:
- Act as a senior engineer, not a chatbot. Use your domain knowledge to SUGGEST diagnostic steps, not just record what the user says.
- When the user describes a problem area, demonstrate understanding by naming specific sub-categories, common causes, and relevant tools.
- Challenge assumptions constructively: "Before we go down that path, have you considered checking X first? In my experience, that resolves 60% of these cases."
- Capture SPECIFIC commands with exact syntax (PowerShell/CLI invocations the engineer would actually paste into a shell), not vague directives like "check the service".
- Capture SPECIFIC commands with exact syntax. Not "check the service" but "Get-Service ADSync | Select-Object Status, StartType".
- Include expected outcomes for every action: what does success look like?
- Surface edge cases proactively: "What about multi-forest environments?" or "Does this change if they have conditional access policies?"
- Explain WHY the diagnostic order matters: "We check connectivity before auth because a network issue masquerades as an auth failure."
@@ -74,7 +74,7 @@ STRUCTURAL RULES:
- All IDs must be unique strings (use descriptive slugs like "check-service-status")
CROSS-REFERENCE / LOOP-BACK PATTERN:
When a troubleshooting path needs to loop back (e.g., after remediation, re-verify from an earlier checkpoint), set next_node_id to the target node's ID — including ancestor decision nodes for re-verification loops. The target ID must already exist somewhere in the tree.
When a troubleshooting path needs to loop back (e.g., after remediation, re-verify from an earlier checkpoint), set next_node_id to the target node's ID. Example: an action node "restart-ssh-service" can set next_node_id to "verify-ssh-connection" (an ancestor decision node) to create a re-verification loop.
"""
INTERVIEW_PROTOCOL = """
@@ -85,7 +85,7 @@ Ask broad questions to understand the problem domain and scope:
- What type of issue is this flow for?
- Who is the target audience? (Tier 1 help desk, Tier 2, Tier 3?)
- What environment assumptions? (On-prem, hybrid, specific vendors?)
Demonstrate domain expertise immediately. When the user names a technology, ask a follow-up that proves you know its common failure modes — a sub-categorization question that only someone fluent in that area would think to ask. Use vocabulary native to whatever the user actually mentioned, not stock examples from past conversations.
Demonstrate domain expertise immediately. If the user says "Azure AD Sync failures," show understanding: "Are you primarily seeing password hash sync issues, object attribute sync failures, or full directory sync errors?"
DO NOT emit [TREE_UPDATE] during scoping. You are still understanding the problem.
PHASE 2 - DISCOVERY (current_phase: discovery):
@@ -130,7 +130,7 @@ Your response is natural conversational text. When the tree structure changes, i
3. Metadata capture (when you learn the flow's name, description, or tags):
[METADATA]
{"name": "<flow name>", "description": "<one-sentence summary>", "tags": ["<tag1>", "<tag2>"]}
{"name": "...", "description": "...", "tags": ["..."]}
[/METADATA]
IMPORTANT:
@@ -172,8 +172,8 @@ STRUCTURAL RULES:
- All IDs must be unique descriptive slugs (e.g., "check-dns-resolution", not UUIDs)
- The last step MUST be type "procedure_end"
- Use section_headers to organize steps into logical phases
- Commands are arrays of objects: [{"code": "<exact command>", "label": "<short label>", "language": "powershell|bash|cmd"}]
- Descriptions support [VAR:variable_name] interpolation for intake form variables. Pick variable names that fit the procedure being built — do not reuse names from prior conversations.
- Commands are arrays of objects: [{"code": "Get-Service ADSync", "label": "Check sync service", "language": "powershell"}]
- Descriptions support [VAR:variable_name] interpolation for intake form variables (e.g., "Connect to [VAR:server_name] via RDP")
VARIABLE INTERPOLATION:
When the procedure needs per-execution input (server name, IP address, client name, etc.), use [VAR:variable_name] syntax in descriptions and commands. These map to intake form fields that the engineer fills in before starting.
@@ -188,7 +188,7 @@ Understand the process being documented:
- Who will execute it? (Tier 1 help desk, Tier 2, senior engineers?)
- What environment context? (Specific vendor, on-prem vs cloud, tools available?)
- Will this need per-execution input? (server name, client info, IP addresses → intake form fields)
Demonstrate domain expertise: when the user names a process, ask a sub-categorization question that distinguishes which variant of that process they mean (the variants will differ by technology — use vocabulary specific to whatever the user mentioned, not examples from prior chats).
Demonstrate domain expertise: if the user says "Exchange Online mailbox migration," show understanding: "Are we covering full tenant-to-tenant migration, on-prem to Exchange Online cutover, or individual mailbox moves with hybrid?"
DO NOT emit [STEPS_UPDATE] during scoping. You are still understanding the process.
PHASE 2 - DISCOVERY (current_phase: discovery):
@@ -238,12 +238,12 @@ Your response is natural conversational text. When the step structure changes, i
3. Metadata capture (when you learn the flow's name, description, or tags):
[METADATA]
{"name": "<flow name>", "description": "<one-sentence summary>", "tags": ["<tag1>", "<tag2>"]}
{"name": "...", "description": "...", "tags": ["..."]}
[/METADATA]
4. Intake form suggestion (when intake form fields are identified):
[INTAKE_FORM]
[{"variable_name": "<snake_case_name>", "label": "<Human Label>", "field_type": "text|password|select|textarea|number|boolean", "required": true|false, "placeholder": "<short hint, optional>", "group_name": "<section heading, optional>", "display_order": <integer>}]
[{"variable_name": "server_name", "label": "Server Name", "field_type": "text", "required": true, "placeholder": "e.g., DC01", "group_name": "Server Details", "display_order": 1}]
[/INTAKE_FORM]
IMPORTANT:
@@ -659,12 +659,12 @@ Requirements:
Also provide metadata as a separate JSON object after the steps:
[METADATA]
{"name": "<flow name>", "description": "<one-sentence summary>", "tags": ["<tag1>", "<tag2>"]}
{"name": "...", "description": "...", "tags": ["..."]}
[/METADATA]
If we discussed intake form fields, also include:
[INTAKE_FORM]
[{"variable_name": "<snake_case_name>", "label": "<Human Label>", "field_type": "text|password|select|textarea|number|boolean", "required": true|false, "placeholder": "<short hint, optional>", "group_name": "<section heading, optional>", "display_order": <integer>}]
[{"variable_name": "server_name", "label": "Server Name", "field_type": "text", "required": true, "placeholder": "e.g., DC01", "group_name": "Server Details", "display_order": 1}]
[/INTAKE_FORM]"""
else:
generation_instruction = """Based on our entire conversation, generate the COMPLETE and FINAL TreeStructure JSON for this flow.
@@ -681,7 +681,7 @@ Requirements:
Also provide metadata as a separate JSON object after the tree:
[METADATA]
{"name": "<flow name>", "description": "<one-sentence summary>", "tags": ["<tag1>", "<tag2>"]}
{"name": "...", "description": "...", "tags": ["..."]}
[/METADATA]"""
provider_messages.append({"role": "user", "content": generation_instruction})

View File

@@ -199,10 +199,7 @@ async def generate_fixes(
try:
text, in_tok, out_tok = await provider.generate_json(
system_prompt=[
{"type": "text", "text": FIX_SYSTEM_PROMPT},
# cacheable: stable constant across all fix attempts
],
system_prompt=FIX_SYSTEM_PROMPT,
messages=messages,
max_tokens=2048,
)
@@ -235,11 +232,7 @@ async def generate_fixes(
try:
text2, in_tok2, out_tok2 = await provider.generate_json(
system_prompt=[
{"type": "text", "text": FIX_SYSTEM_PROMPT},
# cacheable: stable constant; retry reads the cached
# system block from the first attempt above
],
system_prompt=FIX_SYSTEM_PROMPT,
messages=messages,
max_tokens=2048,
)

View File

@@ -3,169 +3,16 @@ AI Provider abstraction layer.
Supports Gemini (google-genai) and Anthropic (anthropic) as interchangeable
backends for JSON generation used by the AI Flow Builder.
## Prompt caching (Anthropic only)
Callers may pass `system_prompt` as either:
- `str` — backward-compatible, uncached.
- `list[SystemBlock]` — Anthropic structured system blocks. Each block is a
dict of shape `{"type": "text", "text": str, "cache_control": {...}?}`.
Caching policy (policy α, per Phase 0.1 design):
- If any block in the list carries an explicit `cache_control` key, that
caller-authored configuration is honored verbatim.
- If no block carries `cache_control`, the provider applies
`cache_control: {"type": "ephemeral"}` to the first block only. First block
is the common "large static prefix" case (e.g. system prompt, reference data).
Gemini ignores cache_control and concatenates list blocks into one system
string — callers should not rely on Gemini for cache-hit behavior.
TODO(phase0-verify): When a dev environment is available, verify cache-hit
behavior by hitting any FlowPilot endpoint twice within the 5-minute
ephemeral TTL. First call should emit `anthropic.cache` with
`cache_creation_input_tokens > 0`; second call with `cache_read_input_tokens > 0`.
If the second call returns zero reads, inspect the prefix for silent
invalidators (timestamps, unsorted JSON keys, varying tool list ordering).
"""
import logging
from abc import ABC, abstractmethod
from collections.abc import AsyncIterator
from typing import Any
from app.core.config import settings
logger = logging.getLogger(__name__)
# Anthropic structured system block. See module docstring for caching policy.
SystemBlock = dict[str, Any]
def _normalize_system_for_anthropic(
system_prompt: str | list[SystemBlock],
) -> str | list[SystemBlock]:
"""Return the value to pass as the `system=` parameter to the Anthropic API.
- Plain strings pass through untouched (uncached path).
- Lists are returned as structured system blocks. If no block in the list
carries an explicit `cache_control`, `cache_control: {"type": "ephemeral"}`
is applied to the FIRST block only (policy α).
- Caller-authored `cache_control` is never overwritten.
"""
if isinstance(system_prompt, str):
return system_prompt
if not system_prompt:
# Empty list is not a meaningful system prompt — pass empty string so
# Anthropic treats this as "no system prompt" rather than erroring.
return ""
blocks = [dict(b) for b in system_prompt]
already_cached = any("cache_control" in b for b in blocks)
if not already_cached:
blocks[0]["cache_control"] = {"type": "ephemeral"}
return blocks
def _flatten_system_for_gemini(
system_prompt: str | list[SystemBlock],
) -> str:
"""Gemini has no structured system blocks; concatenate list entries."""
if isinstance(system_prompt, str):
return system_prompt
return "\n\n".join(b.get("text", "") for b in system_prompt)
def build_anthropic_chat_messages(
history: list[dict[str, Any]],
new_message: str,
images: list[dict[str, Any]] | None = None,
format_reminder: str | None = None,
) -> list[dict[str, Any]]:
"""Construct the Anthropic `messages` payload for a cached multi-turn chat.
Responsibilities:
- Copy the valid history messages in order.
- Apply `cache_control: ephemeral` to the LAST history message so the entire
conversation prefix is cached across turns. The new user message stays
uncached (it changes each turn).
- Append `format_reminder` to the new user message if provided. The reminder
is invisible to storage (caller's concern) but helps enforce structured
output compliance at generation time.
- If `images` are provided, render the new user message as a multimodal
content block list (images first, then text). Otherwise, render it as
a plain string.
This helper is Anthropic-specific: the cache-breakpoint pattern, ephemeral
cache_control, and multimodal block shape are all Anthropic conventions.
Do not call it from Gemini code paths.
"""
messages: list[dict[str, Any]] = []
for msg in history:
messages.append({"role": msg["role"], "content": msg["content"]})
# Cache breakpoint on the last existing history message so the entire
# conversation prefix is cached across turns. Safe only when there IS a
# history message; otherwise the new message is the only message.
if messages:
last = messages[-1]
messages[-1] = {
"role": last["role"],
"content": [
{
"type": "text",
"text": last["content"],
"cache_control": {"type": "ephemeral"},
}
],
}
effective_text = new_message + (format_reminder or "")
if images:
content_blocks: list[dict[str, Any]] = []
for img in images:
content_blocks.append(
{
"type": "image",
"source": {
"type": "base64",
"media_type": img["media_type"],
"data": img["data"],
},
}
)
content_blocks.append({"type": "text", "text": effective_text})
messages.append({"role": "user", "content": content_blocks})
else:
messages.append({"role": "user", "content": effective_text})
return messages
def _log_anthropic_cache_usage(usage: Any, model: str) -> None:
"""Emit a structured log line capturing cache_read / cache_creation tokens."""
cache_read = getattr(usage, "cache_read_input_tokens", 0) or 0
cache_creation = getattr(usage, "cache_creation_input_tokens", 0) or 0
input_tokens = getattr(usage, "input_tokens", 0) or 0
output_tokens = getattr(usage, "output_tokens", 0) or 0
if cache_read or cache_creation:
logger.info(
"anthropic.cache",
extra={
"event": "anthropic.cache",
"model": model,
"cache_read_input_tokens": cache_read,
"cache_creation_input_tokens": cache_creation,
"input_tokens": input_tokens,
"output_tokens": output_tokens,
},
)
class AIProvider(ABC):
"""Abstract base class for AI providers."""
@@ -173,16 +20,14 @@ class AIProvider(ABC):
@abstractmethod
async def generate_json(
self,
system_prompt: str | list[SystemBlock],
messages: list[dict[str, Any]],
system_prompt: str,
messages: list[dict[str, str]],
max_tokens: int = 4096,
) -> tuple[str, int, int]:
"""Generate a JSON response from the AI model.
Args:
system_prompt: System-level instruction. Plain `str` is uncached
(Anthropic) or used as-is (Gemini). `list[SystemBlock]` enables
Anthropic prompt caching per module-docstring policy.
system_prompt: System-level instruction for the model.
messages: List of message dicts with "role" and "content" keys.
max_tokens: Maximum output tokens.
@@ -194,25 +39,37 @@ class AIProvider(ABC):
@abstractmethod
async def generate_text(
self,
system_prompt: str | list[SystemBlock],
messages: list[dict[str, Any]],
system_prompt: str,
messages: list[dict[str, str]],
max_tokens: int = 4096,
) -> tuple[str, int, int]:
"""Generate a text response from the AI model (no JSON constraint).
See `generate_json` for argument semantics.
Args:
system_prompt: System-level instruction for the model.
messages: List of message dicts with "role" and "content" keys.
max_tokens: Maximum output tokens.
Returns:
Tuple of (response_text, input_tokens, output_tokens).
"""
...
async def generate_text_stream(
self,
system_prompt: str | list[SystemBlock],
messages: list[dict[str, Any]],
system_prompt: str,
messages: list[dict[str, str]],
max_tokens: int = 4096,
) -> "AsyncIterator[str]":
"""Stream a text response token by token.
See `generate_json` for argument semantics.
Args:
system_prompt: System-level instruction for the model.
messages: List of message dicts with "role" and "content" keys.
max_tokens: Maximum output tokens.
Yields:
Text chunks as they are generated.
"""
raise NotImplementedError("Streaming not supported for this provider")
# Make this an async generator to satisfy type checker
@@ -228,15 +85,14 @@ class GeminiProvider(AIProvider):
async def generate_json(
self,
system_prompt: str | list[SystemBlock],
messages: list[dict[str, Any]],
system_prompt: str,
messages: list[dict[str, str]],
max_tokens: int = 4096,
) -> tuple[str, int, int]:
from google import genai
from google.genai import types as genai_types
client = genai.Client(api_key=self._api_key)
system_text = _flatten_system_for_gemini(system_prompt)
# Convert messages to Gemini Content format
contents: list[genai_types.Content] = []
@@ -250,7 +106,7 @@ class GeminiProvider(AIProvider):
)
config = genai_types.GenerateContentConfig(
system_instruction=system_text,
system_instruction=system_prompt,
max_output_tokens=max_tokens,
response_mime_type="application/json",
)
@@ -281,15 +137,14 @@ class GeminiProvider(AIProvider):
async def generate_text(
self,
system_prompt: str | list[SystemBlock],
messages: list[dict[str, Any]],
system_prompt: str,
messages: list[dict[str, str]],
max_tokens: int = 4096,
) -> tuple[str, int, int]:
from google import genai
from google.genai import types as genai_types
client = genai.Client(api_key=self._api_key)
system_text = _flatten_system_for_gemini(system_prompt)
contents: list[genai_types.Content] = []
for msg in messages:
@@ -302,7 +157,7 @@ class GeminiProvider(AIProvider):
)
config = genai_types.GenerateContentConfig(
system_instruction=system_text,
system_instruction=system_prompt,
max_output_tokens=max_tokens,
# No response_mime_type — allow free-form text
)
@@ -359,17 +214,16 @@ class AnthropicProvider(AIProvider):
async def generate_json(
self,
system_prompt: str | list[SystemBlock],
messages: list[dict[str, Any]],
system_prompt: str,
messages: list[dict[str, str]],
max_tokens: int = 4096,
) -> tuple[str, int, int]:
client = _get_anthropic_client(self._api_key, self._timeout)
normalized_system = _normalize_system_for_anthropic(system_prompt)
response = await client.messages.create(
model=self._model,
max_tokens=max_tokens,
system=normalized_system,
system=system_prompt,
messages=messages,
)
@@ -377,14 +231,12 @@ class AnthropicProvider(AIProvider):
input_tokens = response.usage.input_tokens
output_tokens = response.usage.output_tokens
_log_anthropic_cache_usage(response.usage, self._model)
return text, input_tokens, output_tokens
async def generate_text(
self,
system_prompt: str | list[SystemBlock],
messages: list[dict[str, Any]],
system_prompt: str,
messages: list[dict[str, str]],
max_tokens: int = 4096,
) -> tuple[str, int, int]:
# Anthropic doesn't differentiate between JSON and text mode
@@ -392,28 +244,20 @@ class AnthropicProvider(AIProvider):
async def generate_text_stream(
self,
system_prompt: str | list[SystemBlock],
messages: list[dict[str, Any]],
system_prompt: str,
messages: list[dict[str, str]],
max_tokens: int = 4096,
) -> AsyncIterator[str]:
client = _get_anthropic_client(self._api_key, self._timeout)
normalized_system = _normalize_system_for_anthropic(system_prompt)
async with client.messages.stream(
model=self._model,
max_tokens=max_tokens,
system=normalized_system,
system=system_prompt,
messages=messages,
) as stream:
async for text in stream.text_stream:
yield text
# Per Anthropic SDK, get_final_message() resolves the stream's
# final usage object (including cache_read/cache_creation tokens).
try:
final = await stream.get_final_message()
_log_anthropic_cache_usage(final.usage, self._model)
except Exception as exc: # best-effort telemetry, never fail the stream
logger.debug("anthropic.cache streaming usage unavailable: %s", exc)
def get_ai_provider(model: str | None = None) -> AIProvider:

View File

@@ -89,10 +89,8 @@ Additional rules:
5. Use unique node IDs prefixed with the branch context (e.g., "gpo-check-link")
6. Build the tree bottom-up in your head: create solution/leaf nodes first, then build parent nodes referencing their IDs
SHAPE-ONLY schema example (do not copy this content verbatim — it shows
how IDs link, NOT what to ask or run; your real tree must reflect the
branch the user described):
{"id": "<root-slug>", "type": "decision", "question": "<diagnostic question for THIS branch>", "help_text": "<optional hint>", "options": [{"id": "<opt-1>", "label": "<observable answer 1>", "next_node_id": "<child-1>"}, {"id": "<opt-2>", "label": "<observable answer 2>", "next_node_id": "<child-2>"}], "children": [{"id": "<child-1>", "type": "action", "title": "<what to do>", "description": "<details>", "commands": ["<exact command for THIS branch>"], "expected_outcome": "<what success looks like>", "next_node_id": "<sibling-id>"}, {"id": "<sibling-id>", "type": "solution", "title": "<resolution title>", "description": "<resolution description>", "resolution_steps": ["<step 1>", "<step 2>"]}, {"id": "<child-2>", "type": "solution", "title": "<other resolution>", "description": "<...>", "resolution_steps": ["<step 1>"]}]}"""
Few-shot example showing correct action node next_node_id usage:
{"id": "dns-root", "type": "decision", "question": "Can the client resolve any DNS names?", "help_text": "Run: nslookup google.com", "options": [{"id": "dns-opt-none", "label": "No — nslookup times out or returns 'server failed'", "next_node_id": "dns-check-service"}, {"id": "dns-opt-partial", "label": "Some names resolve but others fail", "next_node_id": "dns-check-specific"}], "children": [{"id": "dns-check-service", "type": "action", "title": "Check DNS Client Service", "description": "Verify the DNS Client service is running on the affected machine", "commands": ["Get-Service -Name Dnscache | Select-Object Status,StartType"], "expected_outcome": "Status should be Running", "next_node_id": "dns-service-solution"}, {"id": "dns-service-solution", "type": "solution", "title": "DNS Service Was Stopped", "description": "The DNS Client service was stopped, preventing all name resolution", "resolution_steps": ["Run: Start-Service Dnscache", "Set startup type: Set-Service Dnscache -StartupType Automatic", "Flush cache: ipconfig /flushdns", "Test: nslookup google.com"]}, {"id": "dns-check-specific", "type": "solution", "title": "Selective DNS Failure — Stale or Missing Records", "description": "Some records resolve correctly, indicating DNS is functional but specific records are stale or missing", "resolution_steps": ["Check DNS server for missing A/CNAME records", "Clear DNS cache on the DNS server: Clear-DnsServerCache", "Flush client cache: ipconfig /flushdns", "Verify with: nslookup <failing-hostname>"]}]}"""
CORRECTIVE_PROMPT_TEMPLATE = """Your previous JSON was invalid for ResolutionFlow's tree schema.
@@ -148,10 +146,7 @@ async def scaffold_branches(
user_message += f"Environment: {', '.join(tags)}\n"
raw_text, input_tokens, output_tokens = await provider.generate_json(
system_prompt=[
{"type": "text", "text": SCAFFOLD_SYSTEM_PROMPT},
# cacheable: stable constant across all scaffold calls
],
system_prompt=SCAFFOLD_SYSTEM_PROMPT,
messages=[{"role": "user", "content": user_message}],
max_tokens=2048,
)
@@ -212,13 +207,7 @@ async def generate_branch_detail(
for attempt in range(3):
raw_text, input_tokens, output_tokens = await provider.generate_json(
system_prompt=[
{"type": "text", "text": BRANCH_DETAIL_SYSTEM_PROMPT},
# cacheable: stable constant. Retries in this loop re-read the
# cached system block rather than paying full input cost each
# attempt — the ~2.5k-token prompt with few-shot example is
# the dominant cost here.
],
system_prompt=BRANCH_DETAIL_SYSTEM_PROMPT,
messages=messages,
max_tokens=8192,
)

View File

@@ -128,24 +128,6 @@ class Settings(BaseSettings):
"variable_inference": "fast",
"kb_convert": "standard",
"script_build": "standard",
"network_diagram_generate": "standard",
# FlowPilot migration Phase 2 — short, latency-sensitive transformation
# of an engineer's answer/check output into a candidate fact.
# Doc Section 6.6 sets Haiku as the default; instrumentation tracks
# disputed_fact_rate so we can escalate to Sonnet if quality drops.
"fact_synthesis": "fast",
# FlowPilot migration Phase 3 — resolution-note preview that ships to
# the customer ticket. Sonnet because customer-facing artifact quality
# matters more than latency; the in-process state_version cache keeps
# cost manageable.
"resolution_note": "standard",
# FlowPilot migration Phase 4 — escalation handoff package. Parallel
# to resolution_note: Sonnet, same cache story, no MCP.
"escalation_package": "standard",
# FlowPilot migration Phase 5 — extract a parameter schema from a
# concrete rendered script so a draft_template can be proposed.
# Creates a persistent library artifact on accept, so Sonnet.
"template_extraction": "standard",
}
def get_model_for_action(self, action_type: str) -> str:

View File

@@ -153,29 +153,48 @@ Identify values that would change between executions (server names, IPs, usernam
## Output Format
Return a JSON object with this SHAPE (DO NOT copy the placeholders below
verbatim — fill each field with content derived from the actual KB article
the engineer attached, NOT from this schema):
Return a JSON object:
```json
{
"title": "<procedure title derived from the article>",
"description": "<brief description of what this procedure accomplishes>",
"title": "Procedure title derived from the article",
"description": "Brief description of what this procedure accomplishes",
"steps": [
{
"id": "<unique-kebab-case-id>",
"type": "step|warning|section_header",
"content": "<step body — may include [VAR:<your_variable>] interpolation>",
"confidence": <float 0.0-1.0>,
"source_excerpt": "<the verbatim sentence/phrase from the article that this step came from>"
"id": "unique-step-id",
"type": "step",
"content": "Open Server Manager and navigate to Add Roles on [VAR:server_name]",
"confidence": 0.95,
"source_excerpt": "Step 1: Open Server Manager on DC01..."
},
{
"id": "warning-dns",
"type": "warning",
"content": "WARNING: This will restart DNS and cause brief connectivity loss",
"confidence": 0.90,
"source_excerpt": "Note: Restarting DNS will cause a brief outage"
},
{
"id": "section-verification",
"type": "section_header",
"content": "Verification Steps",
"confidence": 1.0,
"source_excerpt": "Verification"
}
],
"intake_form": [
{
"variable_name": "<snake_case_name fitting THIS procedure>",
"label": "<Human Label>",
"field_type": "text|password|select|textarea|number|boolean",
"required": true|false,
"display_order": <integer>
"variable_name": "server_name",
"label": "Server Name",
"field_type": "text",
"required": true,
"display_order": 1
},
{
"variable_name": "ip_address",
"label": "IP Address",
"field_type": "text",
"required": true,
"display_order": 2
}
]
}
@@ -406,12 +425,7 @@ async def convert_document(
try:
raw_text, input_tokens, output_tokens = await provider.generate_json(
system_prompt=[
{"type": "text", "text": system_prompt},
# cacheable: one of two stable constants (TROUBLESHOOTING_SYSTEM_PROMPT
# or PROCEDURAL_SYSTEM_PROMPT) selected by target_type. Each
# variant caches independently by text content.
],
system_prompt=system_prompt,
messages=[{"role": "user", "content": user_message}],
max_tokens=16384,
)

View File

@@ -56,12 +56,6 @@ from .session_handoff import SessionHandoff
from .session_resolution_output import SessionResolutionOutput
from .template_tree import TemplateTree
from .platform_step import PlatformStep
from .device_type import DeviceType
from .network_diagram import NetworkDiagram
from .session_fact import SessionFact
from .session_suggested_fix import SessionSuggestedFix
from .draft_template import DraftTemplate
from .account_settings import AccountSettings
__all__ = [
"User",
@@ -132,10 +126,4 @@ __all__ = [
"SessionResolutionOutput",
"TemplateTree",
"PlatformStep",
"DeviceType",
"NetworkDiagram",
"SessionFact",
"SessionSuggestedFix",
"DraftTemplate",
"AccountSettings",
]

View File

@@ -1,99 +0,0 @@
"""Per-account settings with a JSONB preferences grab-bag.
Rows are created lazily on first write. Reads of a missing row return the
caller-supplied default — no upfront row creation per account.
Settings live in `preferences` until they meet the promotion criteria in
Section 4.6 of FLOWPILOT-MIGRATION.md (hot path / validation / joins), at
which point a future migration adds a typed column and the helpers prefer it.
"""
from __future__ import annotations
import uuid
from datetime import datetime, timezone
from typing import Any, TYPE_CHECKING
from sqlalchemy import DateTime, ForeignKey, text
from sqlalchemy.orm import Mapped, mapped_column, relationship
from sqlalchemy.dialects.postgresql import UUID, JSONB, insert as pg_insert
from sqlalchemy.ext.asyncio import AsyncSession
from sqlalchemy.sql import select
from app.core.database import Base
if TYPE_CHECKING:
from app.models.account import Account
class AccountSettings(Base):
"""One row per account. Created lazily on first `set_setting` call."""
__tablename__ = "account_settings"
account_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("accounts.id", ondelete="CASCADE"),
primary_key=True,
)
preferences: Mapped[dict[str, Any]] = mapped_column(
JSONB, nullable=False, default=dict, server_default=text("'{}'::jsonb")
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True),
default=lambda: datetime.now(timezone.utc),
onupdate=lambda: datetime.now(timezone.utc),
)
account: Mapped["Account"] = relationship("Account", foreign_keys=[account_id])
@classmethod
async def get_setting(
cls,
db: AsyncSession,
account_id: uuid.UUID,
key: str,
default: Any = None,
) -> Any:
"""Return preferences[key] for the account, or `default` if no row/no key.
Never creates a row — this is the pure-read path.
"""
result = await db.execute(
select(cls.preferences).where(cls.account_id == account_id)
)
prefs = result.scalar_one_or_none()
if prefs is None:
return default
return prefs.get(key, default)
@classmethod
async def set_setting(
cls,
db: AsyncSession,
account_id: uuid.UUID,
key: str,
value: Any,
) -> None:
"""Upsert preferences[key] = value for the account.
Creates the row on first write; on subsequent writes, merges the key
into the existing preferences JSON without clobbering other keys.
Uses PostgreSQL's `||` jsonb merge operator via ON CONFLICT DO UPDATE.
"""
stmt = pg_insert(cls).values(
account_id=account_id,
preferences={key: value},
)
stmt = stmt.on_conflict_do_update(
index_elements=[cls.account_id],
set_={
# Merge the new {key: value} into the existing preferences.
# The `||` operator on jsonb overwrites matching keys and keeps
# all other keys intact.
"preferences": cls.preferences.op("||")(stmt.excluded.preferences),
"updated_at": text("now()"),
},
)
await db.execute(stmt)

View File

@@ -214,38 +214,6 @@ class AISession(Base):
comment="Current task lane state: {questions: [...], actions: [...]}",
)
# ── Resolution / Escalation artifacts (Phase 1 — FlowPilot migration) ──
# Markdown of the posted note + PSA external ID for round-trip traceability.
resolution_note_markdown: Mapped[Optional[str]] = mapped_column(
Text, nullable=True,
comment="Final Resolve note markdown, as posted to the PSA",
)
resolution_note_posted_at: Mapped[Optional[datetime]] = mapped_column(
DateTime(timezone=True), nullable=True,
)
resolution_note_external_id: Mapped[Optional[str]] = mapped_column(
String(128), nullable=True,
comment="PSA (e.g. CW) ticket-note ID returned at post time",
)
escalation_package_markdown: Mapped[Optional[str]] = mapped_column(
Text, nullable=True,
comment="Final Escalate handoff package markdown, as posted to the PSA",
)
escalation_package_posted_at: Mapped[Optional[datetime]] = mapped_column(
DateTime(timezone=True), nullable=True,
)
escalation_package_external_id: Mapped[Optional[str]] = mapped_column(
String(128), nullable=True,
comment="PSA ticket-note ID for the escalation package",
)
# Incremented atomically by any write that invalidates the resolution
# note preview cache (facts, suggested fixes, script generations).
# See FLOWPILOT-MIGRATION.md Section 5.5.
state_version: Mapped[int] = mapped_column(
Integer, nullable=False, default=0, server_default=sa.text("0"),
comment="Monotonic preview-cache version; bumped on state-changing writes",
)
# ── Branching ──
is_branching: Mapped[bool] = mapped_column(
default=False,

View File

@@ -1,47 +0,0 @@
"""Device type model for network diagrams."""
import uuid
from datetime import datetime, timezone
from sqlalchemy import String, Boolean, Integer, DateTime, ForeignKey
from sqlalchemy.orm import Mapped, mapped_column
from sqlalchemy.dialects.postgresql import UUID
from app.core.database import Base
class DeviceType(Base):
"""A device type for network diagram nodes (platform or account-custom)."""
__tablename__ = "device_types"
id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid.uuid4
)
slug: Mapped[str] = mapped_column(
String(50), nullable=False,
comment="Unique identifier used in diagram node data",
)
label: Mapped[str] = mapped_column(
String(100), nullable=False,
comment="Display name",
)
category: Mapped[str] = mapped_column(
String(50), nullable=False,
comment="network, compute, storage, cloud, endpoint, infrastructure, security",
)
is_system: Mapped[bool] = mapped_column(
Boolean, nullable=False, default=False,
comment="True for built-in types that cannot be deleted",
)
account_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("accounts.id", ondelete="CASCADE"),
nullable=False,
comment="Platform account for system types, tenant account for custom types",
)
sort_order: Mapped[int] = mapped_column(
Integer, nullable=False, default=0,
comment="Display order within category",
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
)

View File

@@ -1,91 +0,0 @@
"""Draft template model — scripts generated during a session, pending templatization.
Created when an engineer picks "Run now, templatize after resolve" in the
three-option dialog. Post-resolve, the TemplatizePrompt component reads pending
drafts and lets the engineer accept (promotes to `script_templates`) or reject.
"""
import uuid
from datetime import datetime, timezone
from typing import Any, TYPE_CHECKING
from sqlalchemy import (
Text, DateTime, ForeignKey, String, CheckConstraint,
)
from sqlalchemy.orm import Mapped, mapped_column, relationship
from sqlalchemy.dialects.postgresql import UUID, JSONB
from app.core.database import Base
if TYPE_CHECKING:
from app.models.account import Account
from app.models.ai_session import AISession
from app.models.user import User
from app.models.script_template import ScriptCategory, ScriptTemplate
class DraftTemplate(Base):
"""A session-generated script pending conversion to a reusable template."""
__tablename__ = "draft_templates"
__table_args__ = (
CheckConstraint(
"status IN ('pending', 'accepted', 'rejected')",
name="ck_draft_templates_status",
),
)
id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid.uuid4
)
account_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("accounts.id"),
nullable=False,
)
source_session_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("ai_sessions.id"),
nullable=False,
)
source_user_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("users.id"),
nullable=False,
)
script_body: Mapped[str] = mapped_column(Text, nullable=False)
proposed_parameters: Mapped[dict[str, Any]] = mapped_column(
JSONB, nullable=False
)
proposed_name: Mapped[str | None] = mapped_column(String(200), nullable=True)
proposed_category_id: Mapped[uuid.UUID | None] = mapped_column(
UUID(as_uuid=True),
ForeignKey("script_categories.id"),
nullable=True,
)
status: Mapped[str] = mapped_column(
String(32), nullable=False, default="pending"
)
resolved_at: Mapped[datetime | None] = mapped_column(
DateTime(timezone=True), nullable=True
)
# Set when status transitions to 'accepted' and the draft is promoted
# to a real script_templates row.
promoted_template_id: Mapped[uuid.UUID | None] = mapped_column(
UUID(as_uuid=True),
ForeignKey("script_templates.id"),
nullable=True,
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
)
account: Mapped["Account"] = relationship("Account", foreign_keys=[account_id])
source_session: Mapped["AISession"] = relationship(
"AISession", foreign_keys=[source_session_id]
)
source_user: Mapped["User"] = relationship("User", foreign_keys=[source_user_id])
proposed_category: Mapped["ScriptCategory | None"] = relationship(
"ScriptCategory", foreign_keys=[proposed_category_id]
)
promoted_template: Mapped["ScriptTemplate | None"] = relationship(
"ScriptTemplate", foreign_keys=[promoted_template_id]
)

View File

@@ -1,53 +0,0 @@
"""Network diagram model."""
import uuid
from datetime import datetime, timezone
from typing import Any, TYPE_CHECKING
from sqlalchemy import String, Text, Boolean, DateTime, ForeignKey, text
from sqlalchemy.orm import Mapped, mapped_column, relationship
from sqlalchemy.dialects.postgresql import UUID, JSONB
from app.core.database import Base
if TYPE_CHECKING:
from app.models.user import User
class NetworkDiagram(Base):
"""A network topology diagram scoped to one account."""
__tablename__ = "network_diagrams"
id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid.uuid4
)
account_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("accounts.id", ondelete="CASCADE"),
nullable=False,
index=True,
)
name: Mapped[str] = mapped_column(String(255), nullable=False)
client_name: Mapped[str | None] = mapped_column(String(255), nullable=True)
asset_name: Mapped[str | None] = mapped_column(String(255), nullable=True)
description: Mapped[str | None] = mapped_column(Text, nullable=True)
nodes: Mapped[list[dict[str, Any]]] = mapped_column(JSONB, nullable=False, server_default=text("'[]'::jsonb"))
edges: Mapped[list[dict[str, Any]]] = mapped_column(JSONB, nullable=False, server_default=text("'[]'::jsonb"))
thumbnail_url: Mapped[str | None] = mapped_column(Text, nullable=True)
is_archived: Mapped[bool] = mapped_column(
Boolean, nullable=False, default=False,
)
created_by: Mapped[uuid.UUID | None] = mapped_column(
UUID(as_uuid=True),
ForeignKey("users.id"),
nullable=True,
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True),
default=lambda: datetime.now(timezone.utc),
onupdate=lambda: datetime.now(timezone.utc),
)
creator: Mapped["User | None"] = relationship("User", foreign_keys=[created_by])

View File

@@ -62,16 +62,6 @@ class ScriptBuilderSession(Base):
nullable=True,
comment="Link to FlowPilot session if launched from there",
)
origin: Mapped[str] = mapped_column(
String(20),
nullable=False,
default="standalone",
comment=(
"Session origin — 'standalone' (from /script-builder) or "
"'pilot_inline' (from FlowPilot Script Builder tab). "
"Invariant: pilot_inline rows must have ai_session_id set."
),
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
)

View File

@@ -78,20 +78,6 @@ class ScriptTemplate(Base):
is_gallery_featured: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False, server_default=text("false"), index=True)
gallery_sort_order: Mapped[int] = mapped_column(Integer, nullable=False, default=0, server_default=text("0"))
usage_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0, server_default=text("0"))
# ── Provenance (Phase 1 — FlowPilot migration) ──
# Populated when a template is promoted from a post-resolve draft_templates row.
# Powers the Script Library provenance chip:
# "generated from CW #X · resolved by Y · used N times"
source_session_id: Mapped[Optional[uuid.UUID]] = mapped_column(
UUID(as_uuid=True), ForeignKey("ai_sessions.id"), nullable=True,
)
source_user_id: Mapped[Optional[uuid.UUID]] = mapped_column(
UUID(as_uuid=True), ForeignKey("users.id"), nullable=True,
)
source_ticket_ref: Mapped[Optional[str]] = mapped_column(
String(64), nullable=True,
comment="Human-readable PSA ticket ref for display, e.g. 'CW #48307'",
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
)

View File

@@ -1,79 +0,0 @@
"""Session fact model — the "What we know" backing store for a FlowPilot session.
A fact is an atomic, engineer-readable statement of what has been confirmed
during troubleshooting. Facts accumulate across the session and drive the
resolution note preview.
`source_ref` is a polymorphic pointer to a task-lane item inside
`ai_sessions.pending_task_lane` JSON — it is NOT a FK. Integrity is enforced
at the service layer per the FLOWPILOT-MIGRATION design doc Section 4.2.
Phase 2 assigns stable UUIDs to those task-lane items so `source_ref` has
something reliable to point to.
"""
import uuid
from datetime import datetime, timezone
from typing import TYPE_CHECKING
from sqlalchemy import Text, DateTime, ForeignKey, String, CheckConstraint
from sqlalchemy.orm import Mapped, mapped_column, relationship
from sqlalchemy.dialects.postgresql import UUID
from app.core.database import Base
if TYPE_CHECKING:
from app.models.ai_session import AISession
from app.models.account import Account
from app.models.user import User
class SessionFact(Base):
"""A single fact in the What-we-know section of a session's task lane."""
__tablename__ = "session_facts"
__table_args__ = (
CheckConstraint(
"source_type IN ('question', 'diagnostic_check', 'user_note', 'ai_synthesis')",
name="ck_session_facts_source_type",
),
)
id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid.uuid4
)
session_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("ai_sessions.id", ondelete="CASCADE"),
nullable=False,
)
account_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("accounts.id"),
nullable=False,
)
text: Mapped[str] = mapped_column(Text, nullable=False)
source_type: Mapped[str] = mapped_column(String(32), nullable=False)
# Pointer to a task-lane item UUID inside ai_sessions.pending_task_lane.
# NOT a FK. Null for `user_note` and `ai_synthesis` sources.
source_ref: Mapped[uuid.UUID | None] = mapped_column(
UUID(as_uuid=True), nullable=True
)
source_summary: Mapped[str | None] = mapped_column(Text, nullable=True)
created_by: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("users.id"),
nullable=False,
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True),
default=lambda: datetime.now(timezone.utc),
onupdate=lambda: datetime.now(timezone.utc),
)
deleted_at: Mapped[datetime | None] = mapped_column(
DateTime(timezone=True), nullable=True
)
session: Mapped["AISession"] = relationship("AISession", foreign_keys=[session_id])
account: Mapped["Account"] = relationship("Account", foreign_keys=[account_id])
creator: Mapped["User"] = relationship("User", foreign_keys=[created_by])

View File

@@ -1,100 +0,0 @@
"""Session suggested-fix model — AI-proposed resolution path for a session.
A session can have multiple suggested fixes over its lifetime as the AI's
understanding evolves. Only one is active at a time (superseded_at IS NULL);
emitting a new [SUGGEST_FIX] marker supersedes the prior active one.
"""
import uuid
from datetime import datetime, timezone
from typing import Any, TYPE_CHECKING
from sqlalchemy import (
Text, DateTime, ForeignKey, String, Integer, CheckConstraint,
)
from sqlalchemy.orm import Mapped, mapped_column, relationship
from sqlalchemy.dialects.postgresql import UUID, JSONB
from app.core.database import Base
if TYPE_CHECKING:
from app.models.ai_session import AISession
from app.models.account import Account
from app.models.script_template import ScriptTemplate
class SessionSuggestedFix(Base):
"""One AI-proposed fix for a FlowPilot session."""
__tablename__ = "session_suggested_fixes"
__table_args__ = (
CheckConstraint(
"confidence_pct BETWEEN 0 AND 100",
name="ck_session_suggested_fixes_confidence_pct",
),
CheckConstraint(
"user_decision IS NULL OR user_decision IN ("
"'one_off', 'draft_template', 'build_template', 'dismissed')",
name="ck_session_suggested_fixes_user_decision",
),
CheckConstraint(
"status IN ('proposed', 'applied_success', 'applied_failed', "
"'applied_partial', 'dismissed')",
name="ck_session_suggested_fixes_status",
),
)
id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid.uuid4
)
session_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("ai_sessions.id", ondelete="CASCADE"),
nullable=False,
)
account_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("accounts.id"),
nullable=False,
)
title: Mapped[str] = mapped_column(String(200), nullable=False)
description: Mapped[str] = mapped_column(Text, nullable=False)
confidence_pct: Mapped[int] = mapped_column(Integer, nullable=False)
script_template_id: Mapped[uuid.UUID | None] = mapped_column(
UUID(as_uuid=True),
ForeignKey("script_templates.id"),
nullable=True,
)
# Populated only when there's no matching template and the AI has
# drafted a session-specific script.
ai_drafted_script: Mapped[str | None] = mapped_column(Text, nullable=True)
ai_drafted_parameters: Mapped[dict[str, Any] | None] = mapped_column(
JSONB, nullable=True
)
user_decision: Mapped[str | None] = mapped_column(String(32), nullable=True)
# Outcome dimension — did the fix work? Orthogonal to user_decision.
status: Mapped[str] = mapped_column(
String(20), nullable=False, default="proposed"
)
applied_at: Mapped[datetime | None] = mapped_column(
DateTime(timezone=True), nullable=True
)
verified_at: Mapped[datetime | None] = mapped_column(
DateTime(timezone=True), nullable=True
)
partial_notes: Mapped[str | None] = mapped_column(Text, nullable=True)
failure_reason: Mapped[str | None] = mapped_column(Text, nullable=True)
ai_outcome_proposal: Mapped[dict[str, Any] | None] = mapped_column(
JSONB, nullable=True
)
# Set when a newer suggested fix supersedes this one.
superseded_at: Mapped[datetime | None] = mapped_column(
DateTime(timezone=True), nullable=True
)
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
)
session: Mapped["AISession"] = relationship("AISession", foreign_keys=[session_id])
account: Mapped["Account"] = relationship("Account", foreign_keys=[account_id])
script_template: Mapped["ScriptTemplate | None"] = relationship(
"ScriptTemplate", foreign_keys=[script_template_id]
)

View File

@@ -20,7 +20,6 @@ from .psa_connection import (
PSATicketSearchResult, PSATicketStatusItem,
PsaPostRequest, PsaPostResponse, PsaPreviewResponse, PsaPostLogResponse,
PsaMemberMappingResponse, PsaMemberMappingSaveRequest, PsaMemberResponse, AutoMatchResult,
PSABoardResponse,
)
__all__ = [
@@ -51,5 +50,4 @@ __all__ = [
"PSATicketSearchResult", "PSATicketStatusItem",
"PsaPostRequest", "PsaPostResponse", "PsaPreviewResponse", "PsaPostLogResponse",
"PsaMemberMappingResponse", "PsaMemberMappingSaveRequest", "PsaMemberResponse", "AutoMatchResult",
"PSABoardResponse",
]

View File

@@ -126,7 +126,6 @@ class AdminAccountDetailResponse(AdminAccountListItem):
class AdminAccountCreate(BaseModel):
name: str = Field(..., min_length=1, max_length=255)
plan: Literal["free", "pro", "team"] = "free"
owner_email: Optional[EmailStr] = Field(None, description="Email of an existing user to set as owner")
class AdminAccountUpdate(BaseModel):
@@ -320,7 +319,7 @@ class AdminUserCreate(BaseModel):
name: str = Field(..., min_length=1, max_length=255)
account_mode: Literal["existing", "personal"]
account_display_code: Optional[str] = Field(None, description="Required when account_mode='existing'")
account_role: Optional[Literal["owner", "admin", "engineer", "viewer"]] = Field(None, description="Required when account_mode='existing'")
account_role: Optional[Literal["engineer", "viewer"]] = Field(None, description="Required when account_mode='existing'")
send_email: bool = True

View File

@@ -1,37 +0,0 @@
"""Pydantic schemas for device types."""
from datetime import datetime
from uuid import UUID
from pydantic import BaseModel, Field
class DeviceTypeCreate(BaseModel):
slug: str = Field(min_length=1, max_length=50, pattern=r"^[a-z0-9\-]+$")
label: str = Field(min_length=1, max_length=100)
category: str = Field(
min_length=1, max_length=50,
pattern=r"^(network|compute|storage|cloud|endpoint|infrastructure|security)$",
)
sort_order: int = Field(default=0, ge=0)
class DeviceTypeUpdate(BaseModel):
label: str | None = Field(default=None, min_length=1, max_length=100)
category: str | None = Field(
default=None, min_length=1, max_length=50,
pattern=r"^(network|compute|storage|cloud|endpoint|infrastructure|security)$",
)
sort_order: int | None = Field(default=None, ge=0)
class DeviceTypeResponse(BaseModel):
id: UUID
slug: str
label: str
category: str
is_system: bool
account_id: UUID
sort_order: int
created_at: datetime
model_config = {"from_attributes": True}

View File

@@ -1,68 +0,0 @@
"""Pydantic schemas for FlowPilot Phase 6 draft templates.
A draft is the engineer's "Run now, templatize after resolve" path output:
the script ran for the ticket, and the AI proposed a parameterization.
Post-resolve, the engineer accepts (promotes to a real template) or rejects.
See FLOWPILOT-MIGRATION.md Section 5.3.
"""
from __future__ import annotations
from datetime import datetime
from typing import Any, Literal
from uuid import UUID
from pydantic import BaseModel, Field
DraftStatus = Literal["pending", "accepted", "rejected"]
class DraftTemplateResponse(BaseModel):
id: UUID
account_id: UUID
source_session_id: UUID
source_user_id: UUID
script_body: str
proposed_parameters: dict[str, Any]
proposed_name: str | None
proposed_category_id: UUID | None
status: DraftStatus
resolved_at: datetime | None
promoted_template_id: UUID | None
created_at: datetime
model_config = {"from_attributes": True}
class DraftTemplateListResponse(BaseModel):
drafts: list[DraftTemplateResponse]
class DraftTemplateAcceptRequest(BaseModel):
"""Engineer's confirmation that this draft should become a real template.
Engineer may override the AI's proposed name / category and edit the
parameter schema before promotion. Body and parameters_schema are
persisted to the new `script_templates` row.
"""
name: str = Field(..., min_length=1, max_length=200)
category_id: UUID
description: str | None = Field(None, max_length=2000)
# Final parameter schema in the Script Generator's standard shape.
# See ScriptTemplate.parameters_schema for the contract.
parameters_schema: dict[str, Any]
# Optional last-minute edits to the script body. Defaults to the draft's
# `script_body` (which TemplateExtractionService produced as the templated
# form with `{{ key }}` placeholders).
edited_body: str | None = Field(None, min_length=1, max_length=50_000)
class DraftTemplateAcceptResponse(BaseModel):
draft_id: UUID
promoted_template_id: UUID
template_slug: str
class DraftTemplateRejectResponse(BaseModel):
draft_id: UUID
status: Literal["rejected"]

View File

@@ -1,145 +0,0 @@
"""Pydantic schemas for network diagrams."""
from datetime import datetime
from uuid import UUID
from pydantic import BaseModel, Field
class Position(BaseModel):
x: float
y: float
class DeviceProperties(BaseModel):
hostname: str | None = None
ip: str | None = None
subnet: str | None = None
vendor: str | None = None
model: str | None = None
role: str | None = None
vlan: str | None = None
notes: str | None = None
status: str = Field(default="unknown", pattern=r"^(unknown|online|offline|degraded)$")
class NodeStyle(BaseModel):
width: float | None = None
height: float | None = None
class DiagramNode(BaseModel):
id: str
type: str
label: str
position: Position
properties: DeviceProperties = Field(default_factory=DeviceProperties)
nodeType: str | None = None
style: NodeStyle | None = None
parentId: str | None = None
class DiagramEdge(BaseModel):
id: str
source: str
target: str
label: str | None = None
connectionType: str = "ethernet"
speed: str | None = None
notes: str | None = None
routing: str | None = None
class NetworkDiagramCreate(BaseModel):
name: str = Field(min_length=1, max_length=255)
client_name: str | None = None
asset_name: str | None = None
description: str | None = None
nodes: list[DiagramNode] = Field(default_factory=list)
edges: list[DiagramEdge] = Field(default_factory=list)
class NetworkDiagramUpdate(BaseModel):
name: str | None = Field(default=None, min_length=1, max_length=255)
client_name: str | None = None
asset_name: str | None = None
description: str | None = None
nodes: list[DiagramNode] | None = None
edges: list[DiagramEdge] | None = None
class NetworkDiagramResponse(BaseModel):
id: UUID
account_id: UUID
name: str
client_name: str | None = None
asset_name: str | None = None
description: str | None = None
nodes: list[DiagramNode] = Field(default_factory=list)
edges: list[DiagramEdge] = Field(default_factory=list)
thumbnail_url: str | None = None
is_archived: bool = False
created_by: UUID | None = None
created_at: datetime
updated_at: datetime
model_config = {"from_attributes": True}
class NetworkDiagramListItem(BaseModel):
id: UUID
name: str
client_name: str | None = None
description: str | None = None
node_count: int = 0
category_counts: dict[str, int] = Field(default_factory=dict)
thumbnail_url: str | None = None
created_by: UUID | None = None
created_at: datetime
updated_at: datetime
model_config = {"from_attributes": True}
class ExistingBounds(BaseModel):
minX: float
maxX: float
minY: float
maxY: float
class AIGenerateRequest(BaseModel):
description: str = Field(min_length=1, max_length=5000)
client_name: str | None = None
mode: str = Field(default="replace", pattern=r"^(replace|merge)$")
existingBounds: ExistingBounds | None = None
class AIGenerateResponse(BaseModel):
nodes: list[DiagramNode]
edges: list[DiagramEdge]
suggestedName: str | None = None
notes: str | None = None
class DiagramImportRequest(BaseModel):
schemaVersion: int = Field(ge=1, le=1)
name: str = Field(min_length=1, max_length=255)
client_name: str | None = None
description: str | None = None
nodes: list[DiagramNode] = Field(default_factory=list)
edges: list[DiagramEdge] = Field(default_factory=list)
class DiagramImportResponse(BaseModel):
diagram: NetworkDiagramResponse
warnings: list[str] = Field(default_factory=list)
class DiagramExportResponse(BaseModel):
schemaVersion: int = 1
name: str
client_name: str | None = None
description: str | None = None
nodes: list[DiagramNode]
edges: list[DiagramEdge]
exportedAt: str

View File

@@ -53,13 +53,9 @@ class PSATicketSearchResult(BaseModel):
id: str
summary: str
company_name: str | None = None
company_id: str | None = None
board_name: str | None = None
board_id: int | None = None
status_name: str | None = None
status_id: int | None = None
priority_name: str | None = None
priority_id: int | None = None
closed: bool = False
@@ -115,13 +111,13 @@ class PsaPostLogResponse(BaseModel):
class PsaMemberMappingResponse(BaseModel):
id: str | None = None # None for users without a mapping
id: str
user_id: str
user_email: str
user_name: str
external_member_id: str | None = None
external_member_name: str | None = None
matched_by: str | None = None
external_member_id: str
external_member_name: str
matched_by: str
class PsaMemberMappingSaveRequest(BaseModel):
@@ -140,8 +136,3 @@ class PsaMemberResponse(BaseModel):
class AutoMatchResult(BaseModel):
matched: list[PsaMemberMappingResponse]
unmatched_users: int
class PSABoardResponse(BaseModel):
id: int
name: str

View File

@@ -1,65 +0,0 @@
"""Normalized DTOs for ticket management endpoints."""
from __future__ import annotations
from pydantic import BaseModel
class PSAResourceSchema(BaseModel):
member_id: int
member_name: str
member_identifier: str
is_rf_user: bool = False
class PSATicketCreatedSchema(BaseModel):
id: int
summary: str
board_name: str
status_name: str
priority_name: str
company_name: str
resources: list[PSAResourceSchema] = []
class PSATicketStatusUpdateSchema(BaseModel):
ticket_id: int
previous_status: str
new_status: str
new_status_id: int
class TicketCreatePayloadSchema(BaseModel):
summary: str
company_id: int
board_id: int
status_id: int
priority_id: int
description: str | None = None
assigned_member_id: int | None = None
class TicketListResponseSchema(BaseModel):
items: list = []
total: int = 0
page: int = 1
page_size: int = 25
class AiParseRequestSchema(BaseModel):
prompt: str
class AiParseResponseSchema(BaseModel):
summary: str | None = None
company_id: int | None = None
board_id: int | None = None
priority_id: int | None = None
status_id: int | None = None
assigned_member_id: int | None = None
description: str | None = None
missing_fields: list[str] = []
warnings: list[str] = []
class PSAPrioritySchema(BaseModel):
id: int
name: str

View File

@@ -1,27 +1,18 @@
"""Pydantic schemas for the AI Script Builder."""
from datetime import datetime
from typing import Literal, Optional
from typing import Optional
from uuid import UUID
from pydantic import BaseModel, Field
class ScriptBuilderCreateRequest(BaseModel):
"""Request to start (or get-or-create, for inline origin) a builder session.
When `origin='pilot_inline'`, `ai_session_id` is REQUIRED and must
reference a pilot session owned by the current user. The endpoint's
get-or-create semantics kick in: if a pilot_inline session already
exists for (user_id, ai_session_id), that row is returned instead of
creating a duplicate.
"""
"""Request to start a new builder session."""
language: str = Field(
default="powershell",
pattern=r"^(powershell|bash|python)$",
description="Script language",
)
origin: Literal["standalone", "pilot_inline"] = "standalone"
ai_session_id: UUID | None = None
class ScriptBuilderMessageRequest(BaseModel):

View File

@@ -1,81 +0,0 @@
"""Pydantic schemas for the FlowPilot "What we know" session facts.
See FLOWPILOT-MIGRATION.md Section 4.2 for the data model rationale.
"""
from __future__ import annotations
from datetime import datetime
from typing import Literal
from uuid import UUID
from pydantic import BaseModel, Field
# AI-emittable source types are a subset (`user_note` is engineer-only).
AIEmittableSourceType = Literal["question", "diagnostic_check", "ai_synthesis"]
SourceType = Literal["question", "diagnostic_check", "user_note", "ai_synthesis"]
class SessionFactResponse(BaseModel):
"""A single fact card in the What-we-know panel."""
id: UUID
session_id: UUID
text: str
source_type: SourceType
source_ref: UUID | None
source_summary: str | None
created_by: UUID
created_at: datetime
updated_at: datetime
# `editable` is computed server-side so the client doesn't have to
# re-encode the editability rule. It mirrors the PATCH endpoint's
# 403 policy: only user_note and ai_synthesis facts are editable.
editable: bool
model_config = {"from_attributes": False}
class SessionFactListResponse(BaseModel):
facts: list[SessionFactResponse]
class SessionFactCreateRequest(BaseModel):
"""Engineer-created manual fact (the "+ Add a note" affordance).
The endpoint hard-codes source_type="user_note" — manual creation cannot
spoof a question/check origin. Source-type-bound creation goes through
`/promote` instead.
"""
text: str = Field(..., min_length=1, max_length=2000)
summary: str | None = Field(None, max_length=200)
class SessionFactUpdateRequest(BaseModel):
"""Edit an existing fact's text or summary.
The endpoint returns 403 when the fact's source_type is `question` or
`diagnostic_check` — those facts must be edited at the source item.
"""
text: str | None = Field(None, min_length=1, max_length=2000)
summary: str | None = Field(None, max_length=200)
class SessionFactPromoteRequest(BaseModel):
"""Promote a question answer / check result into a fact.
Two modes:
- **Direct**: caller provides `proposed_text` (and optionally `proposed_summary`).
The fact is persisted as-is. Used by the AI [PROMOTE] marker path and by the
engineer's "edit then save" affordance.
- **Synthesize**: caller provides `raw_input` (the engineer's typed answer or
the check output) and the server drafts `text`/`summary` via the
FactSynthesisService. The draft is persisted immediately for now —
the supervisor-staging review is a future enhancement (out of scope per
Section 12).
Exactly one of `proposed_text` or `raw_input` must be set.
"""
source_type: AIEmittableSourceType
source_ref: UUID | None = None
proposed_text: str | None = Field(None, min_length=1, max_length=2000)
proposed_summary: str | None = Field(None, max_length=200)
raw_input: str | None = Field(None, min_length=1, max_length=10_000)

View File

@@ -1,166 +0,0 @@
"""Pydantic schemas for session suggested fixes (Phase 3).
See FLOWPILOT-MIGRATION.md Section 5.2.
"""
from __future__ import annotations
from datetime import datetime
from typing import Any, Literal
from uuid import UUID
from pydantic import BaseModel, Field
UserDecision = Literal["one_off", "draft_template", "build_template", "dismissed"]
# "dismissed" here is the outcome dimension — orthogonal to UserDecision's
# "dismissed" (script-path choice), though the migration backfill aligns
# them for pre-existing rows.
FixStatus = Literal[
"proposed",
"applied_success",
"applied_failed",
"applied_partial",
"dismissed",
]
class SessionSuggestedFixResponse(BaseModel):
id: UUID
session_id: UUID
title: str
description: str
confidence_pct: int
script_template_id: UUID | None
ai_drafted_script: str | None
ai_drafted_parameters: dict[str, Any] | None
user_decision: UserDecision | None
superseded_at: datetime | None
created_at: datetime
status: FixStatus
applied_at: datetime | None
verified_at: datetime | None
partial_notes: str | None
failure_reason: str | None
ai_outcome_proposal: dict[str, Any] | None
model_config = {"from_attributes": True}
class SessionSuggestedFixDecisionRequest(BaseModel):
"""Engineer's path choice on a suggested fix.
Server-side side effects per Section 5.2:
- one_off: record decision, return the rendered (AI-drafted or
engineer-edited) script. No persistent library artifact created.
- draft_template: same as one_off, plus TemplateExtractionService
proposes a parameterization and a draft_templates row is created.
- build_template: return a redirect payload pointing at the Script
Builder page, pre-loaded with the drafted script body.
- dismissed: mark the fix superseded.
For one_off / draft_template, the engineer may have edited the drafted
script or its parameters in the dialog. The final versions are sent
back here so we persist what will actually run.
"""
decision: UserDecision
# Present for one_off / draft_template — the engineer's final version of
# the drafted script after any inline edits. Omit to use the fix's
# `ai_drafted_script` verbatim.
edited_script: str | None = Field(None, min_length=1, max_length=50_000)
# Parameter values used when rendering (informational, stored on the
# draft_template row so a reviewer can see what the first run used).
parameters_used: dict[str, Any] | None = None
class SessionSuggestedFixDecisionResponse(BaseModel):
"""Returned after recording a decision."""
id: UUID
user_decision: UserDecision
# Populated for one_off / draft_template — the script to display/run.
rendered_script: str | None = None
# Populated for draft_template — the ID of the draft_templates row so
# the post-resolve TemplatizePrompt can fetch it in Phase 6.
draft_template_id: UUID | None = None
# Populated for build_template — where to send the engineer next.
redirect_path: str | None = Field(
None,
description="Where to send the engineer next (e.g. /scripts/builder?... for build_template)",
)
# Subset of FixStatus that the engineer can set via the outcome endpoint —
# `proposed` is excluded because you can't un-decide a fix back to "proposed".
FixOutcome = Literal[
"applied_success", "applied_failed", "applied_partial", "dismissed"
]
class SessionSuggestedFixOutcomeRequest(BaseModel):
"""Engineer-reported outcome of applying a suggested fix.
Writes to session_suggested_fixes.status and companion columns. This is
orthogonal to `user_decision` (which records which script-path the
engineer took); outcome captures whether the fix actually worked.
Allowed transitions:
- from `proposed` or `applied_partial`: any outcome is valid
(partial is parked, not terminal — the engineer may update notes,
abandon via dismiss, or advance to success/failed)
- from any terminal outcome (`applied_success`, `applied_failed`,
`dismissed`): server returns 409
"""
outcome: FixOutcome
# Required for applied_partial, optional for applied_failed, ignored otherwise.
notes: str | None = Field(None, max_length=500)
class SessionSuggestedFixScriptRequest(BaseModel):
"""Engineer-submitted drafted script for a suggested fix.
Called when the inline Script Builder tab's Submit action fires. The
fix must be non-terminal (still proposed/applied_partial). Setting
the script does NOT stamp applied_at — a draft is not an application.
"""
ai_drafted_script: str = Field(..., min_length=1, max_length=50_000)
ai_drafted_parameters: dict[str, Any] | None = None
# ── Resolution note preview ────────────────────────────────────────────────
class ResolutionNotePreviewResponse(BaseModel):
markdown: str
target_ticket_ref: str | None
state_version: int
from_cache: bool
# ── Phase 4: Resolve + Escalate post ───────────────────────────────────────
class ResolutionNotePostRequest(BaseModel):
"""Engineer-edited resolution markdown. Server posts to PSA + marks resolved."""
markdown: str = Field(..., min_length=1, max_length=20_000)
# Optional override for resolution summary shown on the session listing;
# defaults to the first line of the markdown if omitted.
resolution_summary: str | None = Field(None, max_length=500)
class EscalationPackagePostRequest(BaseModel):
markdown: str = Field(..., min_length=1, max_length=20_000)
# Free-text reason shown in session listings and escalation queue.
escalation_reason: str | None = Field(None, max_length=500)
class ResolutionPostResponse(BaseModel):
"""Response shape for both Resolve/Escalate POST endpoints."""
# "resolved" / "escalated" / "resolved_local" / "escalated_local"
# The _local variants indicate the session has no linked PSA ticket —
# markdown is stored, session state is updated, nothing was posted externally.
outcome: str
session_status: str
external_id: str | None = None
posted_at: datetime | None = None
# Populated when a status transition was attempted and verified. None
# when no target status is configured in account_settings.preferences.
verified_status_id: int | None = None
verified_status_name: str | None = None
status_transition_skipped_reason: str | None = None

View File

@@ -68,4 +68,4 @@ class RoleUpdate(BaseModel):
class AccountRoleUpdate(BaseModel):
account_role: str = Field(..., pattern="^(owner|admin|engineer|viewer)$")
account_role: str = Field(..., pattern="^(engineer|viewer)$")

View File

@@ -10,32 +10,10 @@ Uses Anthropic prompt caching to reduce cost on multi-turn conversations:
Optionally connects to Microsoft Learn via Anthropic's MCP connector
for real-time documentation lookups (controlled by ENABLE_MCP_MICROSOFT_LEARN).
## Architectural note — this module is the one MCP/beta chat caller
`chat_call_cached` below is the ONLY caller in the codebase that uses
Anthropic's `client.beta.messages.create` endpoint, MCP servers, multimodal
user messages, and the retry-without-MCP fallback. It is deliberately NOT
routed through `AnthropicProvider` — MCP/beta/images are features of exactly
one optional Anthropic beta endpoint and do not belong in a provider-agnostic
abstraction that also serves Gemini.
If a new caller needs the same (MCP, beta, images, history caching) bundle,
call `chat_call_cached` directly rather than pushing those concerns into
`AnthropicProvider`. Cached-system-block plumbing is shared with the provider
via `_normalize_system_for_anthropic` / `build_anthropic_chat_messages` /
`_log_anthropic_cache_usage` in `app.core.ai_provider` — cache primitives are
reusable, but the MCP/beta orchestration stays here.
"""
import logging
from typing import Any
from app.core.ai_provider import (
_get_anthropic_client,
_log_anthropic_cache_usage,
_normalize_system_for_anthropic,
build_anthropic_chat_messages,
)
from app.core.config import settings
logger = logging.getLogger(__name__)
@@ -62,31 +40,29 @@ Every response you write MUST follow this exact structure:
1. **1-3 sentences of analysis** (what the symptoms tell you)
2. **[QUESTIONS] marker** with 1-3 questions for the engineer (if you need info)
3. **[ACTIONS] marker** with 1-4 diagnostic commands to run (if applicable)
4. **[PROMOTE] marker(s)** when the engineer's most recent message confirmed a fact \
worth recording (optional; see "Promoting facts" below)
You MUST include at least one marker ([QUESTIONS] or [ACTIONS]) in every response. \
A response with only prose and no markers is INVALID and will break the UI. \
[PROMOTE] is optional and IN ADDITION to the required markers, never a replacement.
A response with only prose and no markers is INVALID and will break the UI.
### Format-only schema (DO NOT reuse the literal text below)
### Complete example of a correct first response:
The structure to follow is shown below using PLACEHOLDERS. The placeholders \
are not real questions or commands — they describe the SHAPE of valid output. \
Your real response must contain analysis and markers tailored to the actual \
ticket the engineer just sent. Reusing any placeholder text (or text from a \
prior unrelated example you've seen) verbatim is a bug.
User: "Outlook disconnects every 10-15 min, Teams drops too, only this one user, WiFi"
Analysis prose: 1-3 sentences specific to the engineer's symptoms.
Your response:
Both apps dropping on the same 10-15 min cycle on WiFi points to a network-layer \
timeout — likely DHCP lease renewal, AP roaming, or NIC power management. Single-user \
scope narrows it to this endpoint.
[QUESTIONS]
[{"text": "<one short, specific question about THIS ticket>", "context": "<one-sentence justification, optional>"},
{"text": "<another specific question>", "context": "<...>"}]
[{"text": "Is this user on a laptop or desktop?", "context": "Laptops have power management and docking transitions that cause WiFi drops"},
{"text": "Are they on corporate WiFi or working from home?", "context": "Corporate WiFi with multiple APs can cause roaming disconnects"}]
[/QUESTIONS]
[ACTIONS]
[{"label": "<short imperative label for THIS ticket>", "command": "<exact PowerShell or shell command, omit for GUI-only steps>", "description": "<one sentence explaining what the output reveals>"},
{"label": "<...>", "command": "<...>", "description": "<...>"}]
[{"label": "Check DHCP lease time", "command": "ipconfig /all | Select-String -Pattern 'DHCP|IPv4|Lease|Gateway'", "description": "Short lease times (under 1 hour) cause brief drops at renewal"},
{"label": "Check NIC power management", "command": "Get-NetAdapterPowerManagement | Select Name, AllowComputerToTurnOffDevice", "description": "If True, Windows is likely killing the adapter during idle periods"},
{"label": "Check WiFi signal and AP", "command": "netsh wlan show interfaces", "description": "Shows current BSSID, signal strength, and whether they are bouncing between APs"}]
[/ACTIONS]
### Rules
@@ -114,128 +90,6 @@ information is no longer needed to resolve the issue. Default to keeping them.
**Both markers are stripped from display** — the engineer sees them as interactive UI cards, \
not raw JSON. Put analysis BEFORE markers. Markers go at the END of your response.
## Promoting facts to "What we know"
The engineer has a "What we know" panel that holds confirmed facts about this \
session. Each confirmed fact stays visible to the engineer for the rest of the \
session and feeds the resolution note posted to the customer ticket. Surface \
facts there using a `[PROMOTE]` marker.
**When to emit [PROMOTE]:**
- The engineer just answered a [QUESTIONS] item with a substantive answer that \
rules something in or out
- The engineer just shared diagnostic-check output that confirmed a finding
- You synthesized a new conclusion from two or more prior facts
**When NOT to emit [PROMOTE]:**
- The engineer's answer was "unknown", "I don't know", or a clarifying question \
back to you
- The diagnostic output was empty, errored, or inconclusive
- You're re-stating something already in What we know
- The "fact" is your own hypothesis, not something the engineer confirmed
**[PROMOTE] marker format:**
Each fact is its own block. You may emit multiple blocks per response.
[PROMOTE]
{"source_type": "question", "source_ref": "<task_lane_item_id>", "text": "<one short past-tense sentence stating what is now confirmed FROM THIS TICKET>", "summary": "<3-7 word provenance label specific to what the fact rules in/out>"}
[/PROMOTE]
- `source_type` is one of: `"question"` (fact derived from a question's answer), \
`"diagnostic_check"` (fact derived from a check's output), or `"ai_synthesis"` \
(you combined prior facts).
- `source_ref` is the `id` field of the originating task-lane item — the \
[QUESTIONS] and [ACTIONS] payloads you receive in conversation context include \
an `id` for each item. Copy that UUID verbatim. For `ai_synthesis`, OMIT \
`source_ref` (or set it to null).
- `text` is a short past-tense sentence stating what's now confirmed. Use ONLY \
information present in the engineer's CURRENT message — never invent specifics, \
never reuse phrasing from past tickets or example payloads.
- `summary` names the diagnostic value (what the fact rules in or out), 3-7 \
words, no period.
**Strict rule:** [PROMOTE] is for confirmed facts only. If you're not certain \
the engineer's message confirms the fact, do not emit a [PROMOTE]. Hallucinated \
facts get posted to customer tickets and will erode trust in the system.
## Proposing a fix with [SUGGEST_FIX]
When you have a concrete proposed resolution path with reasonable confidence, \
emit a `[SUGGEST_FIX]` marker. This populates the "Suggested fix" card the \
engineer can act on (run a script, build a template, etc.). A new \
[SUGGEST_FIX] supersedes any prior suggested fix on the session — emit a fresh \
one whenever your top hypothesis changes meaningfully.
**When to emit [SUGGEST_FIX]:**
- You have a concrete resolution path (not just "investigate further")
- Confidence is at least ~50% — below that, keep diagnosing
- Either a known Script Library template applies, OR you can draft a script \
that resolves the issue end-to-end
**When NOT to emit [SUGGEST_FIX]:**
- You're still narrowing causes and the fix depends on the next answer
- The "fix" is just running another diagnostic — that goes in [ACTIONS]
- Two paths are equally likely — fork or ask first, suggest later
**[SUGGEST_FIX] marker format (one block per response, last one wins).**
Schema below — DO NOT copy these placeholders into your real response, fill \
each field with content specific to the actual ticket:
[SUGGEST_FIX]
{"title": "<short imperative summary of the fix, ≤200 chars>", "description": "<one short paragraph: root cause + how the fix resolves it>", "confidence": <integer 0-100>, "script_template_slug": "<slug-of-existing-template-or-omit>"}
[/SUGGEST_FIX]
- `title`: short imperative summary, ≤ 200 chars
- `description`: one short paragraph explaining the root cause and the fix
- `confidence`: integer 0-100 (what you'd bet this resolves the ticket)
- `script_template_slug`: slug of an existing Script Library template if one \
applies; OMIT or set null otherwise
- `ai_drafted_script`: full script body if no template matches (only when \
`script_template_slug` is null/omitted)
- `ai_drafted_parameters`: optional JSON object of suggested parameter values \
for the drafted script
The marker is stripped from display — the engineer sees the suggested fix as \
an interactive card with confidence badge, not raw JSON.
## Reporting fix outcome with [FIX_OUTCOME]
When the engineer clearly indicates in chat that a previously proposed fix
worked, didn't work, or was partially applied, emit a [FIX_OUTCOME] marker
on its own lines. This surfaces a "confirm outcome?" banner in the UI — it
does NOT mark the fix resolved on its own; the engineer confirms via the UI.
**When to emit [FIX_OUTCOME]:**
- The engineer states the user's problem is resolved after applying the fix
(affirmative resolution language → outcome="success")
- The engineer states the issue persists after applying the fix
(→ outcome="failure")
- The engineer describes applying only part of the fix
(→ outcome="partial")
**When NOT to emit [FIX_OUTCOME]:**
- The engineer is still verifying (user rebooting, testing, etc.)
- The outcome is ambiguous or inferred rather than stated
- No [SUGGEST_FIX] has been emitted this session
**[FIX_OUTCOME] marker format (one block per response, on its own lines).**
Schema below — DO NOT copy these placeholders into your real response, fill \
each field with content specific to the actual ticket:
[FIX_OUTCOME]
{"fix_id": "<uuid-of-the-active-suggested-fix>",
"outcome": "<success|failure|partial>",
"reason": "<one-line-quote-or-paraphrase-of-what-the-engineer-said>"}
[/FIX_OUTCOME]
- `fix_id`: the UUID of the active suggested fix (provided in session context)
- `outcome`: one of `"success"`, `"failure"`, or `"partial"`
- `reason`: one-line paraphrase of what the engineer said — derived from \
their CURRENT message, not invented
The marker is stripped from display — the engineer sees a "confirm outcome?" \
banner in the UI, not raw JSON.
## Using the Team's Flow Library
Your team has built troubleshooting flows in ResolutionFlow. When relevant flows \
appear in the context below, reference them by name so the engineer can launch them \
@@ -263,7 +117,7 @@ forking, branching, or paths to the engineer. You just continue the conversation
The fork marker is metadata that the system uses behind the scenes.
**You MUST fork when:**
- Symptoms affect multiple applications or layers simultaneously
- Symptoms affect multiple applications or layers (e.g., Outlook AND Teams dropping)
- The problem could be endpoint-side OR infrastructure-side
- Multiple well-known causes match the exact same symptom pattern
@@ -278,6 +132,11 @@ to those, not a replacement. Do NOT ask questions in prose — put them in [QUES
Structure: 1-3 sentences of analysis → [QUESTIONS] and/or [ACTIONS] → [FORK] at the very end.
Example flow:
- Engineer: "Outlook disconnects every 15 min, Teams drops too, only one user"
- You: "The 10-15 min pattern with both apps points to network layer."
- Then: [QUESTIONS] marker, then [ACTIONS] marker, then [FORK] marker last.
The fork marker is stripped from display — the engineer never sees it. \
The system creates branches silently. Based on the engineer's answer, you pick \
the most relevant branch to investigate first.
@@ -285,7 +144,7 @@ the most relevant branch to investigate first.
To create a fork, append this marker AFTER your [QUESTIONS]/[ACTIONS] markers:
[FORK]
{"fork_reason": "<one short sentence: why these branches need independent investigation>", "options": [{"label": "<short hypothesis name for branch 1>", "description": "<one sentence: what this branch will check>"}, {"label": "<branch 2 name>", "description": "<...>"}]}
{"fork_reason": "Brief reason", "options": [{"label": "Short name", "description": "One sentence"}, {"label": "Another", "description": "One sentence"}]}
[/FORK]
2-4 options. Never mention "fork", "branch", or "path" in your visible text.
@@ -295,48 +154,12 @@ To create a fork, append this marker AFTER your [QUESTIONS]/[ACTIONS] markers:
- If a question is clearly outside your domain, say so briefly and redirect.
- Never fabricate error codes, KB article numbers, or CLI flags. If unsure, say so.
## SPIN-OFF TICKET CREATION
When you identify a second distinct issue that is clearly separate from the primary topic \
of this session, suggest creating a spin-off ticket using the [ACTIONS] marker below. \
Use this sparingly — only when the issue is genuinely independent, not for every tangential mention.
Format:
[ACTIONS]
[
{
"label": "Create ticket: <brief issue title>",
"command": "create_spin_off_ticket",
"description": "<one sentence description of the separate issue>"
}
]
[/ACTIONS]
## FINAL REMINDER — THIS OVERRIDES EVERYTHING ABOVE
Every single response MUST contain [QUESTIONS] and/or [ACTIONS] markers with valid JSON. \
No exceptions. Not even when forking. A response without at least one of these markers \
will crash the UI. If you are unsure, include both. The markers are REQUIRED output, not optional.
If any tasks in the engineer's message are marked `_(not yet completed)_`, re-include them \
in your markers unless you are ≥75% confident that information is no longer relevant.
[PROMOTE] markers are OPTIONAL and IN ADDITION to the required ones — emit them only \
when the engineer's most recent message confirmed something worth recording, and copy \
the originating item's `id` into `source_ref` verbatim.
[SUGGEST_FIX] is OPTIONAL — emit one at most per response, only when you have a \
concrete proposed resolution at ~50%+ confidence. A new [SUGGEST_FIX] supersedes \
any prior suggested fix.
[FIX_OUTCOME] is OPTIONAL — emit one at most per response, only when the engineer \
has clearly stated the outcome in their current message.
ANTI-PARROT RULE: The schemas above use placeholders in `<angle brackets>` to show \
the SHAPE of valid output. Your real questions, actions, facts, and suggested fixes \
must be derived from the engineer's CURRENT message — never copy placeholder text, \
never reuse content from a prior unrelated session, never invent ticket-specific \
details (usernames, hostnames, IPs, error codes, application names, ticket numbers) \
that the engineer has not stated. The technology, vocabulary, and named entities in \
your output must match the technology, vocabulary, and named entities in the \
engineer's most recent message. If the engineer's ticket is about a different \
domain than the last ticket you saw, your output must reflect the new domain — \
do not let the previous ticket's specifics bleed into the new one.
"""
@@ -361,7 +184,7 @@ async def _call_ai(
to include alongside the new_message as vision content.
"""
if settings.AI_PROVIDER == "anthropic" and settings.ANTHROPIC_API_KEY:
return await chat_call_cached(
return await _call_anthropic_cached(
system_base, rag_context, history, new_message, max_tokens,
images=images,
)
@@ -379,18 +202,7 @@ async def _call_ai(
)
# Appended to every chat turn's user message immediately before generation.
# Invisible to storage (unified_chat_service strips markers before persisting),
# but critical for structured output compliance — the model emits invalid
# responses often enough without it that removing this reminder regresses UX.
_CHAT_FORMAT_REMINDER = (
"\n\n[SYSTEM: Remember — your response MUST end with [QUESTIONS] "
"and/or [ACTIONS] markers containing valid JSON arrays. "
"Responses without markers break the UI.]"
)
async def chat_call_cached(
async def _call_anthropic_cached(
system_base: str,
rag_context: str,
history: list[dict[str, Any]],
@@ -398,56 +210,79 @@ async def chat_call_cached(
max_tokens: int,
images: list[dict[str, Any]] | None = None,
) -> tuple[str, int, int]:
"""Call Anthropic's chat surface with caching, MCP, images, and retry-without-MCP.
"""Call Anthropic with prompt caching on system prompt and history.
This is the ONE MCP/beta/multimodal chat caller. It is deliberately NOT
routed through `AnthropicProvider`. See module docstring for rationale.
Responsibilities unique to this function (not in the provider):
- Anthropic beta endpoint (`client.beta.messages.create`)
- Microsoft Learn MCP connector wiring (optional via ENABLE_MCP_MICROSOFT_LEARN)
- Retry-without-MCP fallback when the MCP server misbehaves
- Multimodal image blocks in the user message
- Format-reminder append for structured-output compliance
- Telemetry (`mcp.turn`, `mcp.fallback`) for Phase 0.5 MCP usage signal
Cache plumbing is shared with the provider via helpers in `ai_provider`:
`_normalize_system_for_anthropic` (policy α — ephemeral on first block if
none specified), `build_anthropic_chat_messages` (history cache breakpoint +
multimodal user message + format reminder), `_log_anthropic_cache_usage`.
Uses structured system blocks so the static base prompt is cached
independently from the per-query RAG context. Optionally connects
to Microsoft Learn via MCP for real-time documentation lookups.
"""
import anthropic
client = _get_anthropic_client(
settings.ANTHROPIC_API_KEY,
client = anthropic.AsyncAnthropic(
api_key=settings.ANTHROPIC_API_KEY,
timeout=settings.AI_REQUEST_TIMEOUT_SECONDS,
)
# System prompt as structured blocks. The static base is cacheable; the
# RAG context changes per query and must NOT be cached — so we mark the
# base explicitly and leave the RAG block unmarked. `_normalize_system`
# honors caller-authored cache_control verbatim (policy α).
# System prompt as structured blocks:
# Block 1: static base prompt (cached)
# Block 2: RAG context (changes per query, not cached)
system_blocks: list[dict[str, Any]] = [
{
"type": "text",
"text": system_base,
"cache_control": {"type": "ephemeral"},
# cacheable: static system prompt, stable across all turns of all sessions
},
]
if rag_context:
system_blocks.append(
{"type": "text", "text": rag_context}
# uncached: RAG retrieval varies per query
)
normalized_system = _normalize_system_for_anthropic(system_blocks)
system_blocks.append({"type": "text", "text": rag_context})
messages = build_anthropic_chat_messages(
history=history,
new_message=new_message,
images=images,
format_reminder=_CHAT_FORMAT_REMINDER,
# Build messages with cache breakpoint on conversation history
messages: list[dict[str, Any]] = []
for msg in history:
messages.append({"role": msg["role"], "content": msg["content"]})
# Place cache breakpoint on the last history message so the entire
# conversation prefix is cached across turns
if messages:
last = messages[-1]
messages[-1] = {
"role": last["role"],
"content": [
{
"type": "text",
"text": last["content"],
"cache_control": {"type": "ephemeral"},
}
],
}
# Add the new user message (uncached — it's new each turn)
# Append a format reminder to the user message so the model sees it
# immediately before generating. This is invisible to the user (stripped
# before storage) but critical for structured output compliance.
format_reminder = (
"\n\n[SYSTEM: Remember — your response MUST end with [QUESTIONS] "
"and/or [ACTIONS] markers containing valid JSON arrays. "
"Responses without markers break the UI.]"
)
reminded_message = new_message + format_reminder
# If images are attached, build multimodal content blocks
if images:
content_blocks: list[dict[str, Any]] = []
for img in images:
content_blocks.append({
"type": "image",
"source": {
"type": "base64",
"media_type": img["media_type"],
"data": img["data"],
},
})
content_blocks.append({"type": "text", "text": reminded_message})
messages.append({"role": "user", "content": content_blocks})
else:
messages.append({"role": "user", "content": reminded_message})
# MCP server config (optional — controlled by settings)
mcp_servers = anthropic.NOT_GIVEN
@@ -469,13 +304,12 @@ async def chat_call_cached(
]
_mcp_active = mcp_servers is not anthropic.NOT_GIVEN
_mcp_fallback_triggered = False
try:
response = await client.beta.messages.create(
model=settings.AI_MODEL_ANTHROPIC,
max_tokens=max_tokens,
system=normalized_system,
system=system_blocks,
messages=messages,
mcp_servers=mcp_servers,
tools=tools,
@@ -492,24 +326,14 @@ async def chat_call_cached(
or isinstance(e, (anthropic.BadRequestError, anthropic.APIStatusError))
)
if _is_mcp_error:
_mcp_fallback_triggered = True
logger.warning(
"MCP server error (%s), retrying without MCP: %s",
type(e).__name__, e,
)
# Phase 0.5 telemetry: per-turn fallback event.
logger.info(
"mcp.fallback",
extra={
"event": "mcp.fallback",
"mcp_error_type": type(e).__name__,
"mcp_error_message": str(e)[:500],
},
)
response = await client.messages.create(
model=settings.AI_MODEL_ANTHROPIC,
max_tokens=max_tokens,
system=normalized_system,
system=system_blocks,
messages=messages,
)
else:
@@ -531,27 +355,18 @@ async def chat_call_cached(
input_tokens = usage.input_tokens
output_tokens = usage.output_tokens
# Phase 0.5 telemetry: per-turn MCP event. Emitted for every turn that
# reached this code path (i.e., AI_PROVIDER=anthropic chat). `mcp_available`
# reflects whether MCP was actually wired into the request (scope (ii) from
# the Phase 0.5 design — Anthropic code path AND flag on). `mcp_invoked`
# reflects whether the model chose to call an MCP tool on this turn.
logger.info(
"mcp.turn",
extra={
"event": "mcp.turn",
"mcp_available": _mcp_active,
"mcp_invoked": bool(mcp_tools_used),
"mcp_tools": mcp_tools_used,
"mcp_fallback_triggered": _mcp_fallback_triggered,
},
)
# Human-readable log retained for grep-based inspection.
# Log MCP tool usage
if mcp_tools_used:
logger.info("MCP tools used: %s", ", ".join(mcp_tools_used))
_log_anthropic_cache_usage(usage, settings.AI_MODEL_ANTHROPIC)
# Log cache performance
cache_read = getattr(usage, "cache_read_input_tokens", 0) or 0
cache_creation = getattr(usage, "cache_creation_input_tokens", 0) or 0
if cache_read or cache_creation:
logger.info(
"Anthropic cache: read=%d creation=%d input=%d output=%d",
cache_read, cache_creation, input_tokens, output_tokens,
)
return text, input_tokens, output_tokens

View File

@@ -1,309 +0,0 @@
"""EscalationPackageGeneratorService — drafts the handoff package for a session.
Parallel to ResolutionNoteGeneratorService but oriented around handoff to
another engineer instead of closing the ticket. The output markdown follows
FLOWPILOT-MIGRATION.md Section 6.3:
## Problem
## What we've confirmed
## What we've tried
## Current hypothesis
## Suggested next steps
Same caching story as resolution-note previews: keyed on
`(session_id, ai_sessions.state_version)` via `preview_cache`, invalidated by
any fact / suggested-fix / script-generation write.
Model: Sonnet (`escalation_package` action tier per Section 6.6). MCP off.
"""
from __future__ import annotations
import logging
from typing import Any
from uuid import UUID
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.ai_provider import get_ai_provider
from app.core.config import settings
from app.models.ai_session import AISession
from app.models.script_template import ScriptGeneration, ScriptTemplate
from app.models.session_fact import SessionFact
from app.models.session_suggested_fix import SessionSuggestedFix
from app.services.preview_cache import preview_cache
from app.services.script_template_engine import ScriptTemplateEngine
logger = logging.getLogger(__name__)
_ESCALATION_SYSTEM_PROMPT = """\
You produce structured escalation handoff packages for an MSP troubleshooting \
platform. The package is read by the next engineer picking up the ticket; it \
must give them a running start without making them re-read the chat transcript.
Output exactly this markdown structure, no preamble, no closing remarks, no \
extra headings:
## Problem
<one short paragraph stating the issue the first engineer was working on, \
past tense, no hedging. Derived from the session's intake/title and incident \
header.>
## What we've confirmed
<bulleted list of facts from the "What we know" section, each a short line. \
If there are no facts, write "Nothing confirmed yet." and continue.>
## What we've tried
<Bulleted list of diagnostic checks run and scripts generated during the \
session. The content of this section also depends on the outcome recorded for \
the active suggested fix, as given in the input bundle under "Outcome status":>
- applied_failed: List the fix as a tried path. Include the failure reason if \
provided. State that it did not resolve the issue.
- applied_partial: Include the fix as a partially tried path. Include partial \
notes if provided. Indicate it was not fully completed or not verified.
- applied_success: Note that the fix was applied and verified but escalation \
is still needed for another reason (unusual — reflect this accurately).
- dismissed: Do not mention the fix as a tried path; it was only considered.
- proposed (no outcome yet): Do not list it here; it goes in Current hypothesis.
If nothing has been tried at all (no checks, no scripts, no applied/partial \
fix), write "No diagnostic actions run yet." and continue.
## Current hypothesis
<The content depends on the outcome recorded for the active suggested fix:>
- proposed (no outcome yet): State the fix title and confidence. If confidence \
is below 60% or there is no active fix, say "No leading hypothesis yet — \
symptoms are still being narrowed."
- applied_failed or dismissed: Say the proposed fix did not hold or was set \
aside. State any remaining uncertainty.
- applied_partial: Note the partial application and what remains open.
- applied_success: Unusual in an escalate path — state the fix resolved the \
original symptom but a new or related issue requires escalation.
## Suggested next steps
<bulleted list of 2-4 concrete next actions the receiving engineer should \
take. Prefer specifics: commands to run, tickets to check, people to contact. \
Derive from the gap between confirmed facts and a complete resolution. \
If the active suggested fix failed (applied_failed), inform the next steps \
accordingly — e.g. suggest alternatives or deeper investigation paths, \
drawing on the failure reason if provided. \
If the fix is partially applied (applied_partial), the first step is typically \
to complete or verify it. \
If the fix is still proposed (no outcome), the first step is to try it if \
confidence is high (>80%).>
Strict rules:
- Use ONLY the input I provide. Never invent command names, KB articles, or \
configuration specifics that aren't in the input.
- Do not include placeholder text like "TBD" or empty bullets.
- Do not include the engineer's name, the AI's name, session IDs, or the \
chat transcript verbatim.
- Markdown headings exactly as shown (## level), no bolding.
- The tone is a peer handing off to a peer, not a status report.
"""
class EscalationPackageGeneratorService:
"""Generates and caches the five-section Escalate handoff markdown."""
KIND = "escalation_package"
def __init__(self, db: AsyncSession) -> None:
self.db = db
async def generate_or_get_cached(
self, session_id: UUID, *, force: bool = False,
) -> dict[str, Any]:
session = await self._load_session(session_id)
cached = preview_cache.get(self.KIND, session.id, session.state_version) if not force else None
if cached is not None:
return {**cached, "from_cache": True}
markdown = await self._render(session)
target = self._target_ticket_ref(session)
payload = {
"markdown": markdown,
"target_ticket_ref": target,
"state_version": session.state_version,
}
preview_cache.set(self.KIND, session.id, session.state_version, payload)
return {**payload, "from_cache": False}
# ── Internals (parallel to ResolutionNoteGenerator) ───────────────────
async def _load_session(self, session_id: UUID) -> AISession:
result = await self.db.execute(
select(AISession).where(AISession.id == session_id)
)
session = result.scalar_one_or_none()
if session is None:
raise ValueError(f"Session {session_id} not found")
return session
async def _render(self, session: AISession) -> str:
facts = await self._load_facts(session.id)
active_fix = await self._load_active_fix(session.id)
gens = await self._load_redacted_generations(session.id)
bundle = self._build_input_bundle(session, facts, active_fix, gens)
model = settings.get_model_for_action("escalation_package")
provider = get_ai_provider(model=model)
system_blocks: list[dict[str, Any]] = [
{
"type": "text",
"text": _ESCALATION_SYSTEM_PROMPT,
"cache_control": {"type": "ephemeral"},
# cacheable: identical across every escalation-package preview call
},
]
try:
text, _in, _out = await provider.generate_text(
system_prompt=system_blocks,
messages=[{"role": "user", "content": bundle}],
max_tokens=1400,
)
except Exception:
logger.exception("Escalation package generation failed for session %s", session.id)
raise
return text.strip()
async def _load_facts(self, session_id: UUID) -> list[SessionFact]:
result = await self.db.execute(
select(SessionFact)
.where(
SessionFact.session_id == session_id,
SessionFact.deleted_at.is_(None),
)
.order_by(SessionFact.created_at.asc())
)
return list(result.scalars().all())
async def _load_active_fix(self, session_id: UUID) -> SessionSuggestedFix | None:
result = await self.db.execute(
select(SessionSuggestedFix)
.where(
SessionSuggestedFix.session_id == session_id,
SessionSuggestedFix.superseded_at.is_(None),
)
.order_by(SessionSuggestedFix.created_at.desc())
)
return result.scalars().first()
async def _load_redacted_generations(
self, session_id: UUID
) -> list[dict[str, Any]]:
result = await self.db.execute(
select(ScriptGeneration)
.where(ScriptGeneration.ai_session_id == session_id)
.order_by(ScriptGeneration.created_at.asc())
)
gens = list(result.scalars().all())
if not gens:
return []
template_ids = {g.template_id for g in gens}
tpl_result = await self.db.execute(
select(ScriptTemplate).where(ScriptTemplate.id.in_(template_ids))
)
templates_by_id = {t.id: t for t in tpl_result.scalars().all()}
engine = ScriptTemplateEngine()
out: list[dict[str, Any]] = []
for g in gens:
tpl = templates_by_id.get(g.template_id)
sensitive_keys: set[str] = set()
schema = (tpl.parameters_schema if tpl else {}) or {}
params = schema.get("parameters") if isinstance(schema, dict) else None
if isinstance(params, list):
for p in params:
if isinstance(p, dict) and p.get("field_type") == "password":
k = p.get("key") or p.get("variable_name")
if isinstance(k, str):
sensitive_keys.add(k)
redacted_params = engine.redact_sensitive(g.parameters_used or {}, sensitive_keys)
out.append({
"template_name": tpl.name if tpl else "(unknown template)",
"template_slug": tpl.slug if tpl else None,
"parameters_used": redacted_params,
"created_at": g.created_at.isoformat(),
})
return out
@staticmethod
def _target_ticket_ref(session: AISession) -> str | None:
if not session.psa_ticket_id:
return None
return f"CW #{session.psa_ticket_id}"
@staticmethod
def _build_input_bundle(
session: AISession,
facts: list[SessionFact],
active_fix: SessionSuggestedFix | None,
generations: list[dict[str, Any]],
) -> str:
lines: list[str] = []
lines.append("# Session context")
lines.append(f"Title: {session.title or '(untitled)'}")
if session.problem_summary:
lines.append(f"Problem summary: {session.problem_summary}")
if session.problem_domain:
lines.append(f"Domain: {session.problem_domain}")
intake_text = (session.intake_content or {}).get("text") if isinstance(session.intake_content, dict) else None
if intake_text:
lines.append(f"Intake message: {intake_text}")
if session.psa_ticket_id:
lines.append(f"Linked PSA ticket: CW #{session.psa_ticket_id}")
lines.append("")
lines.append("# Confirmed facts (What we know)")
if not facts:
lines.append("(none)")
else:
for f in facts:
tag = f.source_type
summary = f"{f.source_summary}" if f.source_summary else ""
lines.append(f"- [{tag}] {f.text}{summary}")
lines.append("")
lines.append("# Diagnostic checks run during the session")
check_facts = [f for f in facts if f.source_type == "diagnostic_check"]
if not check_facts and not generations:
lines.append("(none)")
else:
for f in check_facts:
lines.append(f"- {f.text}")
for g in generations:
lines.append(f"- Ran script {g['template_name']} (slug={g['template_slug']})")
if g["parameters_used"]:
lines.append(f" parameters: {g['parameters_used']}")
lines.append("")
lines.append("# Active suggested fix (current hypothesis)")
if active_fix is None:
lines.append("(no active suggested fix)")
else:
lines.append(f"Title: {active_fix.title}")
lines.append(f"Confidence: {active_fix.confidence_pct}%")
lines.append(f"Description: {active_fix.description}")
lines.append(f"Outcome status: {active_fix.status}")
if active_fix.applied_at:
lines.append(f"Applied at: {active_fix.applied_at.isoformat()}")
if active_fix.verified_at:
lines.append(f"Verified at: {active_fix.verified_at.isoformat()}")
if active_fix.partial_notes:
lines.append(f"Partial notes: {active_fix.partial_notes}")
if active_fix.failure_reason:
lines.append(f"Failure reason: {active_fix.failure_reason}")
lines.append("")
lines.append(
"Produce the five-section escalation handoff now. Use only the input above."
)
return "\n".join(lines)

View File

@@ -1,285 +0,0 @@
"""FactSynthesisService — converts engineer answers and check output into facts.
Two paths feed this service:
1. **AI marker path (the common case).** When the model emits a `[PROMOTE]`
marker in the chat stream, `unified_chat_service` parses the marker (which
already contains the engineer-readable `text` and short provenance `summary`)
and calls `create_fact` directly. No LLM call is needed — the model already
wrote the fact.
2. **Engineer-driven synthesize path.** The "+ Promote to What we know" affordance
in the UI sends a raw answer or check output and asks the server to draft
`text` + `summary` for review. `synthesize_from_question` /
`synthesize_from_check` make a small Haiku call for that draft. The engineer
confirms (or edits) before persistence, so the LLM output is never
silently posted to a customer ticket.
Either way, persistence funnels through `create_fact`, which ALSO bumps
`ai_sessions.state_version` so the resolution-note preview cache invalidates
(see FLOWPILOT-MIGRATION.md Section 5.5).
Model tier is `fact_synthesis` in `settings.ACTION_MODEL_MAP` (Haiku per
Section 6.6). MCP is intentionally disabled for synthesis — these are
pure transformations of input, not research calls.
"""
from __future__ import annotations
import json
import logging
import re
from typing import Any
from uuid import UUID
from sqlalchemy import select, update
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.ai_provider import get_ai_provider
from app.core.config import settings
from app.models.ai_session import AISession
from app.models.session_fact import SessionFact
logger = logging.getLogger(__name__)
# Conservative synthesis prompt. Hallucinated specifics are a trust-killer
# because facts feed the resolution note posted to customer tickets — the
# prompt makes "no fact" an explicit, valid output.
_SYNTHESIS_SYSTEM_PROMPT = """\
You convert one engineer answer or one diagnostic-check output into a single \
candidate fact for a troubleshooting session's "What we know" log.
Return strict JSON with this shape:
{
"text": "<one short sentence stating what is now known, in past tense>",
"summary": "<3-7 word provenance label, e.g. 'rules out tenant/license'>"
}
If the answer/output does NOT contain a substantive fact (e.g. the engineer \
typed 'unknown', the command failed, the output is empty), return:
{
"text": null,
"summary": null
}
Strict rules:
- Use ONLY information present in the input. Never add details that were not stated.
- Do not speculate, infer causes, or extrapolate. State only what the input proves.
- The text is a fact a colleague could verify by looking at the original answer/output.
- The summary names the diagnostic value (what this fact rules in or out), not the topic.
- Output ONLY the JSON object, no prose, no markdown fences.
"""
class FactSynthesisService:
"""Persists session facts and (optionally) drafts them via an LLM call.
Methods that touch the database take an `AsyncSession` and assume the
caller commits. `create_fact` flushes so the returned row has a primary key.
"""
def __init__(self, db: AsyncSession) -> None:
self.db = db
# ── Persistence ────────────────────────────────────────────────────────
async def create_fact(
self,
*,
session_id: UUID,
account_id: UUID,
user_id: UUID,
source_type: str,
text: str,
summary: str | None = None,
source_ref: UUID | None = None,
) -> SessionFact:
"""Persist a fact and bump the session's preview-cache version.
`source_ref` MUST be None for `user_note` and `ai_synthesis` sources;
for `question` and `diagnostic_check` it should point at the stable
UUID of the originating task-lane item. The DB has no FK constraint
on `source_ref` (the target lives inside JSONB) — integrity is enforced
here.
"""
if source_type not in ("question", "diagnostic_check", "user_note", "ai_synthesis"):
raise ValueError(f"Invalid source_type: {source_type}")
if source_type in ("user_note", "ai_synthesis") and source_ref is not None:
# `source_ref` is a back-pointer to a question/check; user notes
# and AI-synthesized facts have no source item to point at.
raise ValueError(
f"source_ref must be None for source_type={source_type}"
)
text = (text or "").strip()
if not text:
raise ValueError("Fact text cannot be empty")
fact = SessionFact(
session_id=session_id,
account_id=account_id,
text=text,
source_type=source_type,
source_ref=source_ref,
source_summary=(summary or "").strip() or None,
created_by=user_id,
)
self.db.add(fact)
# Invalidate any preview cached against the prior state_version.
# Single UPDATE so the bump is atomic relative to the fact insert
# within this transaction; concurrent writers serialize on the row.
await self.db.execute(
update(AISession)
.where(AISession.id == session_id)
.values(state_version=AISession.state_version + 1)
)
await self.db.flush()
return fact
async def soft_delete_fact(self, fact: SessionFact) -> None:
"""Mark a fact deleted and bump state_version."""
from datetime import datetime, timezone
fact.deleted_at = datetime.now(timezone.utc)
await self.db.execute(
update(AISession)
.where(AISession.id == fact.session_id)
.values(state_version=AISession.state_version + 1)
)
await self.db.flush()
async def update_fact(
self,
fact: SessionFact,
*,
text: str | None = None,
summary: str | None = None,
) -> SessionFact:
"""Update an editable fact and bump state_version.
Caller is responsible for the editability check — only `user_note`
and `ai_synthesis` facts may be edited at the card level. The
endpoint enforces this and returns 403 for the read-only types.
"""
if text is not None:
stripped = text.strip()
if not stripped:
raise ValueError("Fact text cannot be empty")
fact.text = stripped
if summary is not None:
fact.source_summary = summary.strip() or None
await self.db.execute(
update(AISession)
.where(AISession.id == fact.session_id)
.values(state_version=AISession.state_version + 1)
)
await self.db.flush()
return fact
# ── LLM-backed drafting ────────────────────────────────────────────────
async def synthesize_from_question(
self, *, question_text: str, raw_answer: str
) -> dict[str, str | None]:
"""Draft `{text, summary}` from a question + engineer's free-text answer.
Returns `{"text": None, "summary": None}` when the answer doesn't
contain a substantive fact — caller should not persist in that case.
"""
return await self._synthesize(
user_input=(
f"Question asked: {question_text.strip()}\n"
f"Engineer's answer: {raw_answer.strip()}"
),
)
async def synthesize_from_check(
self, *, check_label: str, check_output: str
) -> dict[str, str | None]:
"""Draft `{text, summary}` from a diagnostic check label + its output."""
return await self._synthesize(
user_input=(
f"Diagnostic check: {check_label.strip()}\n"
f"Output:\n{check_output.strip()}"
),
)
async def _synthesize(self, *, user_input: str) -> dict[str, str | None]:
"""Single Haiku call with the conservative synthesis prompt."""
model = settings.get_model_for_action("fact_synthesis")
provider = get_ai_provider(model=model)
# Cache the system prompt — it's identical across every synthesis call.
system_blocks: list[dict[str, Any]] = [
{
"type": "text",
"text": _SYNTHESIS_SYSTEM_PROMPT,
"cache_control": {"type": "ephemeral"},
# cacheable: identical across all fact-synthesis calls
},
]
try:
text, _in, _out = await provider.generate_json(
system_prompt=system_blocks,
messages=[{"role": "user", "content": user_input}],
max_tokens=200,
)
except Exception:
logger.exception("Fact synthesis LLM call failed")
return {"text": None, "summary": None}
return self._parse_synthesis_response(text)
@staticmethod
def _parse_synthesis_response(raw: str) -> dict[str, str | None]:
"""Tolerant parse: strip fences, accept null fields, ignore extras."""
cleaned = raw.strip()
if cleaned.startswith("```"):
cleaned = re.sub(r"^```(?:json)?\s*", "", cleaned)
cleaned = re.sub(r"\s*```$", "", cleaned)
try:
data = json.loads(cleaned)
except (json.JSONDecodeError, ValueError):
logger.warning("Fact synthesis returned non-JSON: %r", raw[:200])
return {"text": None, "summary": None}
if not isinstance(data, dict):
return {"text": None, "summary": None}
text = data.get("text")
summary = data.get("summary")
if text is not None and not isinstance(text, str):
text = None
if summary is not None and not isinstance(summary, str):
summary = None
# Treat empty strings the same as null — "no substantive fact".
if isinstance(text, str) and not text.strip():
text = None
if isinstance(summary, str) and not summary.strip():
summary = None
return {"text": text, "summary": summary}
async def list_facts_for_session(
db: AsyncSession, session_id: UUID
) -> list[SessionFact]:
"""List non-deleted facts for a session, oldest first.
RLS filters by tenant; the explicit account_id check is unnecessary here.
"""
result = await db.execute(
select(SessionFact)
.where(
SessionFact.session_id == session_id,
SessionFact.deleted_at.is_(None),
)
.order_by(SessionFact.created_at.asc())
)
return list(result.scalars().all())

View File

@@ -330,7 +330,6 @@ async def start_session(
# 7. Create first step
step = _create_step_from_parsed(
session_id=session.id,
account_id=session.account_id,
step_order=0,
parsed=parsed,
input_tokens=input_tokens,
@@ -434,7 +433,6 @@ async def process_response(
# Create new step
step = _create_step_from_parsed(
session_id=session.id,
account_id=session.account_id,
step_order=session.step_count - 1,
parsed=parsed,
input_tokens=input_tokens,
@@ -696,7 +694,6 @@ async def pickup_session(
briefing_step = AISessionStep(
id=uuid.uuid4(),
session_id=session.id,
account_id=session.account_id,
branch_id=session.active_branch_id if session.is_branching else None,
step_order=session.step_count,
step_type="action",
@@ -768,7 +765,6 @@ async def pickup_session(
next_step = _create_step_from_parsed(
session_id=session.id,
account_id=session.account_id,
step_order=session.step_count - 1,
parsed=parsed,
input_tokens=input_tokens,
@@ -1001,7 +997,6 @@ async def generate_status_update(
step = AISessionStep(
id=uuid.uuid4(),
session_id=session.id,
account_id=session.account_id,
branch_id=session.active_branch_id if session.is_branching else None,
step_order=session.step_count,
step_type="status_update",
@@ -1445,7 +1440,6 @@ def _format_engineer_response(request: StepResponseRequest) -> str:
def _create_step_from_parsed(
session_id: UUID,
account_id: UUID,
step_order: int,
parsed: dict[str, Any],
input_tokens: int,
@@ -1493,7 +1487,6 @@ def _create_step_from_parsed(
return AISessionStep(
id=uuid.uuid4(),
session_id=session_id,
account_id=account_id,
branch_id=branch_id,
step_order=step_order,
step_type=step_type if parsed["type"] != "resolution_suggestion" else "action",

View File

@@ -1,151 +0,0 @@
"""AI service for generating network diagrams from natural language."""
import json
import logging
from app.core.ai_provider import get_ai_provider
from app.core.config import settings
from app.schemas.network_diagram import (
AIGenerateRequest,
AIGenerateResponse,
DiagramNode,
DiagramEdge,
DeviceProperties,
Position,
)
logger = logging.getLogger(__name__)
SYSTEM_PROMPT_TEMPLATE = """You are a network diagram generator for MSP engineers.
Given a plain English description of a network, you must return ONLY valid JSON with no markdown, no explanation, no preamble.
Return this exact structure:
{{
"nodes": [
{{
"id": "unique-string",
"type": "device-type-slug",
"label": "device label",
"position": {{ "x": number, "y": number }},
"properties": {{
"hostname": "string or null",
"ip": "string or null",
"subnet": "string or null",
"vendor": "string or null",
"model": "string or null",
"role": "string or null",
"vlan": "string or null",
"notes": "string or null",
"status": "unknown"
}}
}}
],
"edges": [
{{
"id": "unique-string",
"source": "node-id",
"target": "node-id",
"label": "connection label or null",
"connectionType": "ethernet|fiber|wifi|vpn|vlan|wan",
"speed": "string or null",
"notes": "string or null"
}}
],
"suggestedName": "short descriptive diagram name",
"notes": "any important assumptions or missing info, or null"
}}
Available device type slugs: {available_slugs}
Position nodes thoughtfully in a logical network topology layout.
Use x/y coordinates between 0 and 1200 for x, 0 and 800 for y.
Place WAN/internet at top, core network in middle, endpoints at bottom.
{merge_instructions}"""
MERGE_INSTRUCTIONS = """
IMPORTANT: You are ADDING devices to an existing diagram. Do NOT replace existing devices.
The existing diagram occupies this bounding box: minX={minX}, maxX={maxX}, minY={minY}, maxY={maxY}.
Place all new nodes OUTSIDE this bounding box — below (y > {maxY} + 100) or to the right (x > {maxX} + 100).
You may create edges that connect new nodes to existing nodes if the description implies a connection.
Use these existing node IDs for connections: {existing_node_ids}"""
async def generate_diagram(
request: AIGenerateRequest,
available_slugs: list[str],
existing_node_ids: list[str] | None = None,
) -> AIGenerateResponse:
merge_instructions = ""
if request.mode == "merge" and request.existingBounds:
b = request.existingBounds
merge_instructions = MERGE_INSTRUCTIONS.format(
minX=b.minX, maxX=b.maxX, minY=b.minY, maxY=b.maxY,
existing_node_ids=", ".join(existing_node_ids or []),
)
system_prompt = SYSTEM_PROMPT_TEMPLATE.format(
available_slugs=", ".join(available_slugs),
merge_instructions=merge_instructions,
)
model = settings.get_model_for_action("network_diagram_generate")
provider = get_ai_provider(model)
messages = [{"role": "user", "content": request.description}]
response_text, input_tokens, output_tokens = await provider.generate_json(
system_prompt=system_prompt,
messages=messages,
max_tokens=4096,
)
logger.info(
"Network diagram AI generation: input_tokens=%d, output_tokens=%d",
input_tokens, output_tokens,
)
try:
data = json.loads(response_text)
except json.JSONDecodeError as e:
logger.error("Failed to parse AI response as JSON: %s", e)
raise ValueError("AI generated an invalid response, please try again")
try:
nodes = []
for raw_node in data.get("nodes", []):
node_type = raw_node.get("type", "server")
if node_type not in available_slugs:
logger.warning("Unknown device type '%s', falling back to 'server'", node_type)
node_type = "server"
nodes.append(DiagramNode(
id=raw_node["id"],
type=node_type,
label=raw_node.get("label", node_type),
position=Position(**raw_node.get("position", {"x": 0, "y": 0})),
properties=DeviceProperties(**{
k: v for k, v in raw_node.get("properties", {}).items()
if k in DeviceProperties.model_fields
}),
))
edges = []
for raw_edge in data.get("edges", []):
edges.append(DiagramEdge(
id=raw_edge["id"],
source=raw_edge["source"],
target=raw_edge["target"],
label=raw_edge.get("label"),
connectionType=raw_edge.get("connectionType", "ethernet"),
speed=raw_edge.get("speed"),
notes=raw_edge.get("notes"),
))
except KeyError as e:
logger.warning("AI response missing required field: %s", e)
raise ValueError(f"AI generated incomplete data (missing {e}), please try again")
return AIGenerateResponse(
nodes=nodes,
edges=edges,
suggestedName=data.get("suggestedName"),
notes=data.get("notes"),
)

View File

@@ -1,52 +0,0 @@
"""In-process preview cache for FlowPilot resolution-note / escalation-package previews.
Phase 3 implementation per FLOWPILOT-MIGRATION.md Section 5.5:
- Cache key: `(kind, session_id, state_version)` — no TTL needed, state_version
is the source of truth.
- Invalidation: any write to session_facts, session_suggested_fixes, or
script_generations bumps `ai_sessions.state_version`. Old entries simply
stop being looked up and leak harmlessly until process restart.
- Storage: plain dict, single-process. When Session Sharing brings Redis,
swap the storage without changing the call sites.
Bound: best-effort soft cap of 5000 entries. When exceeded we drop the
oldest insertion. Not a TTL — at current scale, the cap is more about
resident-memory hygiene than correctness.
"""
from __future__ import annotations
from collections import OrderedDict
from typing import Any
from uuid import UUID
_MAX_ENTRIES = 5000
class _PreviewCache:
def __init__(self) -> None:
self._store: OrderedDict[tuple[str, UUID, int], Any] = OrderedDict()
def get(self, kind: str, session_id: UUID, state_version: int) -> Any | None:
key = (kind, session_id, state_version)
if key not in self._store:
return None
# Touch on access so LRU eviction is meaningful.
self._store.move_to_end(key)
return self._store[key]
def set(self, kind: str, session_id: UUID, state_version: int, value: Any) -> None:
key = (kind, session_id, state_version)
self._store[key] = value
self._store.move_to_end(key)
# Evict oldest if over cap. OrderedDict.popitem(last=False) is O(1).
while len(self._store) > _MAX_ENTRIES:
self._store.popitem(last=False)
def invalidate_session(self, session_id: UUID) -> None:
"""Drop all entries for a session — used when the session is deleted."""
keys = [k for k in self._store if k[1] == session_id]
for k in keys:
del self._store[k]
preview_cache = _PreviewCache()

View File

@@ -11,11 +11,6 @@ from app.services.psa.types import (
PSAMember,
PSAConfiguration,
PSATimeEntry,
PSABoard,
PaginatedTicketResult,
PSAResource,
PSACreatedTicket,
TicketCreatePayload,
)
@@ -32,7 +27,7 @@ class AutotaskProvider(PSAProvider):
async def get_ticket(self, ticket_id: str) -> PSATicket:
raise NotImplementedError("Autotask integration coming soon")
async def search_tickets(self, query: str, **filters) -> PaginatedTicketResult:
async def search_tickets(self, query: str, **filters) -> list[PSATicket]:
raise NotImplementedError("Autotask integration coming soon")
async def post_note(
@@ -63,9 +58,6 @@ class AutotaskProvider(PSAProvider):
async def list_members(self) -> list[PSAMember]:
raise NotImplementedError("Autotask integration coming soon")
async def list_boards(self) -> list[PSABoard]:
raise NotImplementedError("list_boards not implemented for this provider")
async def get_ticket_configurations(self, ticket_id: str) -> list[PSAConfiguration]:
raise NotImplementedError("Autotask integration coming soon")
@@ -78,18 +70,3 @@ class AutotaskProvider(PSAProvider):
work_type: str | None = None,
) -> PSATimeEntry:
raise NotImplementedError("Autotask integration coming soon")
async def list_resources(self, ticket_id: int) -> list[PSAResource]:
raise NotImplementedError("Autotask integration coming soon")
async def add_resource(self, ticket_id: int, member_id: int) -> PSAResource:
raise NotImplementedError("Autotask integration coming soon")
async def remove_resource(self, ticket_id: int, member_id: int) -> None:
raise NotImplementedError("Autotask integration coming soon")
async def create_ticket(self, payload: TicketCreatePayload) -> PSACreatedTicket:
raise NotImplementedError("Autotask integration coming soon")
async def list_priorities(self) -> list[dict]:
raise NotImplementedError("Autotask integration coming soon")

View File

@@ -12,11 +12,6 @@ from .types import (
PSAMember,
PSAConfiguration,
PSATimeEntry,
PSABoard,
PaginatedTicketResult,
PSAResource,
PSACreatedTicket,
TicketCreatePayload,
)
@@ -32,7 +27,7 @@ class PSAProvider(ABC):
...
@abstractmethod
async def search_tickets(self, query: str, **filters) -> PaginatedTicketResult:
async def search_tickets(self, query: str, **filters) -> list[PSATicket]:
...
@abstractmethod
@@ -69,10 +64,6 @@ class PSAProvider(ABC):
async def list_members(self) -> list[PSAMember]:
...
@abstractmethod
async def list_boards(self) -> list[PSABoard]:
...
@abstractmethod
async def get_ticket_configurations(self, ticket_id: str) -> list[PSAConfiguration]:
...
@@ -87,23 +78,3 @@ class PSAProvider(ABC):
work_type: str | None = None,
) -> PSATimeEntry:
...
@abstractmethod
async def list_resources(self, ticket_id: int) -> list[PSAResource]:
...
@abstractmethod
async def add_resource(self, ticket_id: int, member_id: int) -> PSAResource:
...
@abstractmethod
async def remove_resource(self, ticket_id: int, member_id: int) -> None:
...
@abstractmethod
async def create_ticket(self, payload: TicketCreatePayload) -> PSACreatedTicket:
...
@abstractmethod
async def list_priorities(self) -> list[dict]:
...

View File

@@ -7,7 +7,6 @@ from datetime import datetime, timezone
from app.services.psa.base import PSAProvider
from app.services.psa.cache import psa_cache
from app.services.psa.exceptions import PSAError
from app.services.psa.types import (
ConnectionTestResult,
PSATicket,
@@ -17,11 +16,6 @@ from app.services.psa.types import (
PSAMember,
PSAConfiguration,
PSATimeEntry,
PSABoard,
PaginatedTicketResult,
PSAResource,
PSACreatedTicket,
TicketCreatePayload,
)
from .client import ConnectWiseClient
@@ -60,62 +54,34 @@ class ConnectWiseProvider(PSAProvider):
)
return self._map_ticket(data)
async def search_tickets(self, query: str, **filters) -> PaginatedTicketResult:
"""Search CW tickets by summary. Supports board_id, status_id, member_identifier,
unassigned, board_ids, page, and page_size filters. Returns paginated result."""
page_size = filters.get("page_size", 10)
page = filters.get("page", 1)
async def search_tickets(self, query: str, **filters) -> list[PSATicket]:
"""Search CW tickets by summary. Supports board_id and status_id filters."""
params: dict = {
"fields": "id,summary,company,board,status,priority,closedFlag",
"orderBy": "priority/sort asc,dateEntered desc",
"pageSize": page_size,
"page": page,
"orderBy": "id desc",
"pageSize": 25,
}
# Build CW condition query
conditions: list[str] = []
if query:
# Sanitize: strip single quotes to prevent CW condition injection
safe_query = query.replace("'", "")
conditions.append(f"summary contains '{safe_query}'")
conditions.append(f"summary contains '{query}'")
if filters.get("board_id"):
conditions.append(f"board/id = {filters['board_id']}")
if filters.get("status_id"):
conditions.append(f"status/id = {filters['status_id']}")
elif filters.get("status_name"):
safe_status = str(filters["status_name"]).replace("'", "")
conditions.append(f"status/name = '{safe_status}'")
if not filters.get("include_closed", False):
conditions.append("closedFlag = false")
if filters.get("member_identifier") is not None:
conditions.append(f"resources contains '{filters['member_identifier']}'")
if filters.get("unassigned", False):
conditions.append("resources = null")
board_ids: list[int] = filters.get("board_ids") or []
if board_ids:
board_list = ", ".join(str(bid) for bid in board_ids)
conditions.append(f"board/id in ({board_list})")
if filters.get("company_id"):
conditions.append(f"company/id = {int(filters['company_id'])}")
condition_str = " and ".join(conditions) if conditions else ""
if condition_str:
params["conditions"] = condition_str
if conditions:
params["conditions"] = " and ".join(conditions)
count_params: dict = {}
if condition_str:
count_params["conditions"] = condition_str
data = await self.client.get("/service/tickets", params=params)
# Fire page fetch + count in parallel
data, count_data = await asyncio.gather(
self.client.get("/service/tickets", params=params),
self.client.get("/service/tickets/count", params=count_params),
)
items = [self._map_ticket(t) for t in (data if isinstance(data, list) else [])]
total = count_data.get("count", len(items)) if isinstance(count_data, dict) else len(items)
return PaginatedTicketResult(items=items, total=total, page=page, page_size=page_size)
return [
self._map_ticket(t)
for t in (data if isinstance(data, list) else [])
]
async def get_ticket_configurations(
self, ticket_id: str
@@ -266,30 +232,13 @@ class ConnectWiseProvider(PSAProvider):
async def update_ticket_status(
self, ticket_id: str, status_id: int
) -> PSATicket:
"""Update a CW ticket's status using JSON Patch format.
Verifies CW actually applied the change — CW silently returns 200 when
a status id is invalid for the ticket's board. We check the response
body's status.id matches what we sent, and raise PSAError if not.
"""
"""Update a CW ticket's status using JSON Patch format."""
patch_body = [
{"op": "replace", "path": "status", "value": {"id": status_id}}
]
data = await self.client.patch(
f"/service/tickets/{ticket_id}", json_body=patch_body
)
applied = (data.get("status") or {}) if isinstance(data, dict) else {}
applied_id = applied.get("id")
if applied_id != status_id:
logger.warning(
"CW status PATCH for ticket %s returned status id=%s instead of %s",
ticket_id, applied_id, status_id,
)
raise PSAError(
f"ConnectWise did not apply status {status_id} "
f"(still {applied.get('name') or applied_id}). "
"The status may not be valid for this ticket's board."
)
return self._map_ticket(data)
async def list_members(self) -> list[PSAMember]:
@@ -321,32 +270,6 @@ class ConnectWiseProvider(PSAProvider):
psa_cache.set(cache_key, result, ttl_seconds=900)
return result
async def list_boards(self) -> list[PSABoard]:
"""List active CW service boards (cached 1 hour)."""
cache_key = "boards"
cached = psa_cache.get(cache_key)
if cached is not None:
return cached
data = await self.client.get(
"/service/boards",
params={
"fields": "id,name,inactiveFlag",
"conditions": "inactiveFlag = false",
"pageSize": 100,
},
)
result = [
PSABoard(
id=b["id"],
name=b["name"],
inactive=b.get("inactiveFlag", False),
)
for b in (data if isinstance(data, list) else [])
]
psa_cache.set(cache_key, result, ttl_seconds=3600)
return result
# ── Ticket Context ────────────────────────────────────────────────
async def get_ticket_context(
@@ -613,7 +536,7 @@ class ConnectWiseProvider(PSAProvider):
if work_type:
payload["workType"] = {"name": work_type}
data = await self.client.post("/time/entries", payload)
data = await self._client.post("/time/entries", payload)
return PSATimeEntry(
id=str(data["id"]),
ticket_id=ticket_id,
@@ -628,247 +551,16 @@ class ConnectWiseProvider(PSAProvider):
@staticmethod
def _map_ticket(data: dict) -> PSATicket:
"""Map a CW ticket JSON dict to a PSATicket."""
company = data.get("company") or {}
board = data.get("board") or {}
status = data.get("status") or {}
priority = data.get("priority") or {}
return PSATicket(
id=str(data.get("id", "")),
id=str(data["id"]),
summary=data.get("summary", ""),
company_name=company.get("name"),
company_id=str(company.get("id")) if company.get("id") else None,
board_name=board.get("name"),
board_id=board.get("id"),
status_name=status.get("name"),
status_id=status.get("id"),
priority_name=priority.get("name"),
priority_id=priority.get("id"),
company_name=data.get("company", {}).get("name"),
company_id=str(data["company"]["id"]) if data.get("company") else None,
board_name=data.get("board", {}).get("name"),
board_id=data.get("board", {}).get("id"),
status_name=data.get("status", {}).get("name"),
status_id=data.get("status", {}).get("id"),
priority_name=data.get("priority", {}).get("name"),
priority_id=data.get("priority", {}).get("id"),
closed=data.get("closedFlag", False),
)
# ── Resource management ───────────────────────────────────────────
# Schedule type id for "Service Ticket" resources — CW's canonical type for ticket co-assignees
_SCHEDULE_TYPE_SERVICE_TICKET = 4
async def _get_ticket_owner(self, ticket_id: int) -> dict | None:
"""Fetch the ticket's current owner (MemberReference) or None if unassigned."""
data = await self.client.get(
f"/service/tickets/{ticket_id}",
params={"fields": "id,owner"},
)
if not isinstance(data, dict):
return None
owner_raw = data.get("owner")
return owner_raw if isinstance(owner_raw, dict) and owner_raw.get("id") else None
async def _list_ticket_schedule_entries(self, ticket_id: int) -> list[dict]:
"""List schedule entries for a ticket's co-assignees.
Returns raw CW schedule entry dicts with at least id and member info.
"""
data = await self.client.get(
"/schedule/entries",
params={
"conditions": (
f"type/id={self._SCHEDULE_TYPE_SERVICE_TICKET} AND objectId={ticket_id}"
),
"fields": "id,member,name",
"pageSize": 100,
},
)
return data if isinstance(data, list) else []
async def list_resources(self, ticket_id: int) -> list[PSAResource]:
"""List members assigned to a CW ticket.
Merges the `owner` MemberReference (primary assignee) with schedule entries
of type 4 (Service Ticket resources — co-assignees). Deduped by member id.
"""
owner = await self._get_ticket_owner(ticket_id)
entries = await self._list_ticket_schedule_entries(ticket_id)
members = await self.list_members()
by_id = {str(m.id): m for m in members}
seen_ids: set[str] = set()
results: list[PSAResource] = []
if owner is not None:
owner_id = str(owner.get("id"))
m = by_id.get(owner_id)
if m:
results.append(PSAResource(
member_id=int(m.id),
member_name=m.name,
member_identifier=m.identifier,
))
else:
results.append(PSAResource(
member_id=int(owner.get("id") or 0),
member_name=str(owner.get("name") or ""),
member_identifier=str(owner.get("identifier") or ""),
))
seen_ids.add(owner_id)
for entry in entries:
entry_member = entry.get("member") if isinstance(entry, dict) else None
if not isinstance(entry_member, dict):
continue
mid = str(entry_member.get("id") or "")
if not mid or mid in seen_ids:
continue
m = by_id.get(mid)
if m:
results.append(PSAResource(
member_id=int(m.id),
member_name=m.name,
member_identifier=m.identifier,
))
else:
results.append(PSAResource(
member_id=int(entry_member.get("id") or 0),
member_name=str(entry_member.get("name") or ""),
member_identifier=str(entry_member.get("identifier") or ""),
))
seen_ids.add(mid)
return results
async def add_resource(self, ticket_id: int, member_id: int) -> PSAResource:
"""Assign a member to a CW ticket.
- If the ticket has no owner, set the target as `owner` (CW's canonical
primary assignee field). CW typically mirrors this into the derived
`resources` string automatically.
- If the ticket is already owned by someone else, add the target as a
co-assignee via a schedule entry of type 4 (Service Ticket). The
existing owner is not changed.
- Idempotent when target is already owner or already has a schedule entry.
"""
members = await self.list_members()
target = next((m for m in members if str(m.id) == str(member_id)), None)
if target is None:
raise PSAError(f"Member {member_id} not found")
current_owner = await self._get_ticket_owner(ticket_id)
if current_owner is None:
# Primary assign — set owner
await self.client.patch(
f"/service/tickets/{ticket_id}",
json_body=[{"op": "replace", "path": "owner", "value": {"id": int(target.id)}}],
)
elif str(current_owner.get("id")) != str(target.id):
# Ticket owned by someone else — add as co-assignee via schedule entry.
# Idempotent: skip if a schedule entry already exists for this member.
existing = await self._list_ticket_schedule_entries(ticket_id)
already_assigned = any(
str((e.get("member") or {}).get("id") or "") == str(target.id)
for e in existing
)
if not already_assigned:
await self.client.post(
"/schedule/entries",
json_body={
"member": {"id": int(target.id)},
"objectId": int(ticket_id),
"type": {"id": self._SCHEDULE_TYPE_SERVICE_TICKET},
"name": target.name or target.identifier or f"Member {target.id}",
},
)
# else: already the owner — idempotent no-op
return PSAResource(
member_id=int(target.id),
member_name=target.name,
member_identifier=target.identifier,
)
async def remove_resource(self, ticket_id: int, member_id: int) -> None:
"""Remove a member from a CW ticket (idempotent).
- If the target is the current owner, clear the owner field.
- Otherwise, delete their schedule entry (Service Ticket type).
"""
members = await self.list_members()
target = next((m for m in members if str(m.id) == str(member_id)), None)
if target is None:
return
current_owner = await self._get_ticket_owner(ticket_id)
if current_owner is not None and str(current_owner.get("id")) == str(target.id):
# Unassign the owner. Try RFC 6902 "remove" first; fall back to
# "replace" with null if CW rejects it.
try:
await self.client.patch(
f"/service/tickets/{ticket_id}",
json_body=[{"op": "remove", "path": "owner"}],
)
except PSAError:
await self.client.patch(
f"/service/tickets/{ticket_id}",
json_body=[{"op": "replace", "path": "owner", "value": None}],
)
return
# Not the owner — find and delete the schedule entry for this member.
entries = await self._list_ticket_schedule_entries(ticket_id)
for entry in entries:
entry_member = entry.get("member") if isinstance(entry, dict) else None
if isinstance(entry_member, dict) and str(entry_member.get("id") or "") == str(target.id):
entry_id = entry.get("id")
if entry_id:
await self.client.delete(f"/schedule/entries/{entry_id}")
break
# ── Ticket creation ───────────────────────────────────────────────
async def create_ticket(self, payload: TicketCreatePayload) -> PSACreatedTicket:
"""Create a new CW service ticket."""
body: dict = {
"summary": payload.summary,
"board": {"id": payload.board_id},
"company": {"id": payload.company_id},
"status": {"id": payload.status_id},
"priority": {"id": payload.priority_id},
}
if payload.description:
body["initialDescription"] = payload.description
if payload.assigned_member_id:
body["owner"] = {"id": payload.assigned_member_id}
data = await self.client.post("/service/tickets", json_body=body)
ticket_id = data.get("id") if isinstance(data, dict) else None
resources: list[PSAResource] = []
if ticket_id and payload.assigned_member_id:
try:
resources = await self.list_resources(ticket_id)
except Exception:
pass
company = (data.get("company") or {}) if isinstance(data, dict) else {}
board = (data.get("board") or {}) if isinstance(data, dict) else {}
status = (data.get("status") or {}) if isinstance(data, dict) else {}
priority = (data.get("priority") or {}) if isinstance(data, dict) else {}
return PSACreatedTicket(
id=ticket_id or 0,
summary=data.get("summary", payload.summary) if isinstance(data, dict) else payload.summary,
board_name=board.get("name", ""),
status_name=status.get("name", ""),
priority_name=priority.get("name", ""),
company_name=company.get("name", ""),
resources=resources,
)
# ── Priorities ────────────────────────────────────────────────────
async def list_priorities(self) -> list[dict]:
"""List CW service priorities."""
data = await self.client.get("/service/priorities", params={"pageSize": 50})
return [
{"id": p.get("id"), "name": p.get("name")}
for p in (data if isinstance(data, list) else [])
]

View File

@@ -11,11 +11,6 @@ from app.services.psa.types import (
PSAMember,
PSAConfiguration,
PSATimeEntry,
PSABoard,
PaginatedTicketResult,
PSAResource,
PSACreatedTicket,
TicketCreatePayload,
)
@@ -32,7 +27,7 @@ class HaloPSAProvider(PSAProvider):
async def get_ticket(self, ticket_id: str) -> PSATicket:
raise NotImplementedError("Halo PSA integration coming soon")
async def search_tickets(self, query: str, **filters) -> PaginatedTicketResult:
async def search_tickets(self, query: str, **filters) -> list[PSATicket]:
raise NotImplementedError("Halo PSA integration coming soon")
async def post_note(
@@ -63,9 +58,6 @@ class HaloPSAProvider(PSAProvider):
async def list_members(self) -> list[PSAMember]:
raise NotImplementedError("Halo PSA integration coming soon")
async def list_boards(self) -> list[PSABoard]:
raise NotImplementedError("list_boards not implemented for this provider")
async def get_ticket_configurations(self, ticket_id: str) -> list[PSAConfiguration]:
raise NotImplementedError("Halo PSA integration coming soon")
@@ -78,18 +70,3 @@ class HaloPSAProvider(PSAProvider):
work_type: str | None = None,
) -> PSATimeEntry:
raise NotImplementedError("Halo PSA integration coming soon")
async def list_resources(self, ticket_id: int) -> list[PSAResource]:
raise NotImplementedError("Halo PSA integration coming soon")
async def add_resource(self, ticket_id: int, member_id: int) -> PSAResource:
raise NotImplementedError("Halo PSA integration coming soon")
async def remove_resource(self, ticket_id: int, member_id: int) -> None:
raise NotImplementedError("Halo PSA integration coming soon")
async def create_ticket(self, payload: TicketCreatePayload) -> PSACreatedTicket:
raise NotImplementedError("Halo PSA integration coming soon")
async def list_priorities(self) -> list[dict]:
raise NotImplementedError("Halo PSA integration coming soon")

View File

@@ -67,46 +67,6 @@ class PSATimeEntry(BaseModel):
created_at: str | None = None
class PSABoard(BaseModel):
id: int
name: str
inactive: bool = False
class PaginatedTicketResult(BaseModel):
items: list[PSATicket]
total: int
page: int
page_size: int
class PSAResource(BaseModel):
member_id: int
member_name: str
member_identifier: str
is_rf_user: bool = False
class PSACreatedTicket(BaseModel):
id: int
summary: str
board_name: str
status_name: str
priority_name: str
company_name: str
resources: list[PSAResource] = []
class TicketCreatePayload(BaseModel):
summary: str
company_id: int
board_id: int
status_id: int
priority_id: int
description: str | None = None
assigned_member_id: int | None = None
class NoteType:
INTERNAL_ANALYSIS = "internal_analysis"
RESOLUTION = "resolution"

View File

@@ -1,223 +0,0 @@
"""PSA writeback for FlowPilot Phase 4 — Resolve + Escalate round-trip.
Three primitives:
- `post_resolution_note` — post the engineer-edited resolution markdown to
the PSA ticket, store `{external_id, posted_at}` on the session.
- `post_escalation_package` — same pattern for the Escalate flow.
- `transition_ticket_status` — patch the ticket status, then re-fetch and
verify the change actually took. Failed verification raises loudly so the
UI never reports silent success (per the existing ConnectWise integration
principle called out in FLOWPILOT-MIGRATION.md Section 6.5 and CLAUDE.md).
The target status IDs live in `account_settings.preferences`
(`cw_resolved_status_id`, `cw_escalated_status_id`). When unset, the status
transition is a no-op and the endpoint response says so — we do not guess a
default because CW status IDs are board-specific.
Local-only path: callers handle sessions without `psa_ticket_id` before
calling this service. Nothing here tries to "post locally" — the service's
job ends at the PSA boundary.
"""
from __future__ import annotations
import logging
from datetime import datetime, timezone
from typing import Any
from uuid import UUID
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.models.account_settings import AccountSettings
from app.models.ai_session import AISession
from app.services.psa.exceptions import PSAConnectionError
from app.services.psa.registry import get_provider_for_connection
from app.services.psa.types import NoteType
logger = logging.getLogger(__name__)
class PSAStatusVerificationError(RuntimeError):
"""Raised when a ticket status transition didn't stick on re-fetch.
The `update_ticket_status` call returned OK but the subsequent
`get_ticket` still shows the prior status (or some unrelated one).
This is the exact failure mode CLAUDE.md flags as a ConnectWise
anti-pattern: reporting success when nothing changed.
"""
def __init__(self, ticket_id: str, expected_status_id: int, observed_status: Any) -> None:
super().__init__(
f"Ticket {ticket_id} status transition to {expected_status_id} "
f"did not verify — observed {observed_status!r} after re-fetch."
)
self.ticket_id = ticket_id
self.expected_status_id = expected_status_id
self.observed_status = observed_status
class PSAWritebackService:
"""Thin orchestration over the PSA provider for FlowPilot writebacks.
Instances are per-request — the AsyncSession is the one handling the
current HTTP call, and the provider is resolved lazily from the session's
`psa_connection_id`.
"""
def __init__(self, db: AsyncSession) -> None:
self.db = db
# ── Public API ────────────────────────────────────────────────────────
async def post_resolution_note(
self, session: AISession, markdown: str
) -> dict[str, Any]:
"""Post `markdown` as a resolution note on the linked CW ticket.
On success, persists `resolution_note_markdown`, `_posted_at`,
`_external_id` on the session and returns the same triple. Caller is
responsible for committing the transaction.
"""
return await self._post_note(
session=session,
markdown=markdown,
note_type=NoteType.RESOLUTION,
markdown_col="resolution_note_markdown",
posted_at_col="resolution_note_posted_at",
external_id_col="resolution_note_external_id",
kind="resolution",
)
async def post_escalation_package(
self, session: AISession, markdown: str
) -> dict[str, Any]:
"""Post `markdown` as an escalation handoff note on the CW ticket."""
return await self._post_note(
session=session,
markdown=markdown,
# Internal-analysis visibility: the handoff is for the next engineer,
# not the customer. CW fires no notifications, keeps the note internal.
note_type=NoteType.INTERNAL_ANALYSIS,
markdown_col="escalation_package_markdown",
posted_at_col="escalation_package_posted_at",
external_id_col="escalation_package_external_id",
kind="escalation",
)
async def transition_ticket_status(
self,
session: AISession,
target_status_id: int,
) -> dict[str, Any]:
"""PATCH ticket status, then re-fetch and verify.
Returns `{"success": True, "verified_status_id": <int>, "verified_status_name": <str>}`
when the observed status matches. Raises `PSAStatusVerificationError`
when the transition didn't take (most common real-world failure: CW
requires certain fields before allowing a status change to
Resolved — the PATCH returns 200 but the status silently stays put).
"""
if not session.psa_ticket_id or not session.psa_connection_id:
raise ValueError("Session has no linked PSA ticket for status transition")
provider = await get_provider_for_connection(session.psa_connection_id, self.db)
await provider.update_ticket_status(
ticket_id=session.psa_ticket_id, status_id=target_status_id,
)
# Verify by re-fetch — this is the load-bearing step.
verification = await provider.get_ticket(session.psa_ticket_id)
observed_id = getattr(verification, "status_id", None)
observed_name = getattr(verification, "status_name", None)
if observed_id != target_status_id:
raise PSAStatusVerificationError(
ticket_id=session.psa_ticket_id,
expected_status_id=target_status_id,
observed_status={"id": observed_id, "name": observed_name},
)
return {
"success": True,
"verified_status_id": observed_id,
"verified_status_name": observed_name,
}
async def resolved_status_id_for_account(
self, account_id: UUID
) -> int | None:
"""Return the configured CW "Resolved" status ID for the account.
None means "no transition configured" — callers should skip the
transition (posting the note is still meaningful). This lives in
account_settings.preferences per the Phase 1 JSONB grab-bag design.
"""
raw = await AccountSettings.get_setting(self.db, account_id, "cw_resolved_status_id", None)
return self._coerce_status_id(raw)
async def escalated_status_id_for_account(
self, account_id: UUID
) -> int | None:
raw = await AccountSettings.get_setting(self.db, account_id, "cw_escalated_status_id", None)
return self._coerce_status_id(raw)
# ── Internals ─────────────────────────────────────────────────────────
async def _post_note(
self,
*,
session: AISession,
markdown: str,
note_type: str,
markdown_col: str,
posted_at_col: str,
external_id_col: str,
kind: str,
) -> dict[str, Any]:
if not session.psa_ticket_id or not session.psa_connection_id:
raise ValueError(f"Session has no linked PSA ticket for {kind} post")
markdown = (markdown or "").strip()
if not markdown:
raise ValueError(f"{kind} markdown is empty")
try:
provider = await get_provider_for_connection(session.psa_connection_id, self.db)
except PSAConnectionError:
# Connection could have been deleted or deactivated since session
# creation — propagate as a clear error for the endpoint to surface.
logger.exception(
"PSA connection %s is no longer available for session %s",
session.psa_connection_id, session.id,
)
raise
posted = await provider.post_note(
ticket_id=session.psa_ticket_id,
text=markdown,
note_type=note_type,
)
posted_at = datetime.now(timezone.utc)
setattr(session, markdown_col, markdown)
setattr(session, posted_at_col, posted_at)
setattr(session, external_id_col, str(posted.id) if posted.id else None)
return {
"external_id": str(posted.id) if posted.id else None,
"posted_at": posted_at,
"kind": kind,
}
@staticmethod
def _coerce_status_id(raw: Any) -> int | None:
if raw is None:
return None
try:
return int(raw)
except (TypeError, ValueError):
logger.warning(
"Non-integer CW status ID in account_settings.preferences: %r",
raw,
)
return None

View File

@@ -1,342 +0,0 @@
"""ResolutionNoteGeneratorService — drafts the structured Resolve note for a session.
Produces the four-section markdown that ships to the customer ticket (per
FLOWPILOT-MIGRATION.md Section 6.2):
## Problem
## What we confirmed
## Root cause
## Resolution
The output is the *draft* — engineers review and edit in the preview popover
before clicking Confirm & post (Phase 4). Caching is keyed on
`(session_id, ai_sessions.state_version)` per Section 5.5; the cache lives in
`preview_cache` and invalidates automatically when any fact / suggested fix /
script generation bumps the session's state_version.
Model: Sonnet (`resolution_note` action tier — quality matters because the
output is customer-facing). MCP intentionally disabled — this is a summary
of existing state, not a research task.
Sensitive parameter values in script_generations are redacted using the
script template's `parameters_schema` (`field_type: "password"`). Existing
ScriptTemplateEngine.redact_sensitive handles the substitution.
"""
from __future__ import annotations
import logging
from typing import Any
from uuid import UUID
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.core.ai_provider import get_ai_provider
from app.core.config import settings
from app.models.ai_session import AISession
from app.models.script_template import ScriptGeneration, ScriptTemplate
from app.models.session_fact import SessionFact
from app.models.session_suggested_fix import SessionSuggestedFix
from app.services.preview_cache import preview_cache
from app.services.script_template_engine import ScriptTemplateEngine
logger = logging.getLogger(__name__)
_RESOLUTION_NOTE_SYSTEM_PROMPT = """\
You produce structured resolution notes for an MSP troubleshooting platform. \
The notes are posted as ticket notes in the customer's PSA, so they must read \
like a competent senior engineer summarized the work — not like an AI \
narration. Your output goes in front of paying customers.
Output exactly this markdown structure, no preamble, no closing remarks, no \
extra headings:
## Problem
<one short paragraph stating the issue the engineer worked on, derived from the \
session's intake/title and the incident header. Past tense. No "user reported" \
hedging — state the problem directly.>
## What we confirmed
<bulleted list of facts from the "What we know" section, each one a short line. \
Group similar facts together; do not invent connecting prose. If there are no \
facts, write "Nothing was confirmed." and skip to Root cause.>
## Root cause
<one short paragraph naming the root cause based on the active suggested fix \
and confirmed facts. If the suggested fix is low-confidence (<60%) or absent, \
say "Root cause not definitively isolated." and explain what is suspected based \
on facts.>
## Resolution
<The content of this section depends on the outcome recorded for the active \
suggested fix, as given in the input bundle under "fix.status":>
- applied_success: Write in past tense using closure language. State that the \
fix was applied and verified as working. If verified_at is provided, you may \
reference it as the time resolution was confirmed. Example phrasing: \
"Applied <fix title>; confirmed working."
- applied_failed: Acknowledge that the proposed fix did not resolve the issue \
and was discarded. If failure_reason is provided, include it. Then describe \
the actual resolution path taken (derived from facts and scripts run). This \
state means the engineer resolved the issue another way; the note should cover \
that actual resolution, not just the failed attempt.
- applied_partial: Note that the fix was partially applied. If partial_notes \
are provided, include them. Then describe the final resolution path taken.
- dismissed: Treat the fix as considered and set aside. Do not center the note \
on it. Describe the resolution based on what was actually confirmed and done.
- proposed (no outcome yet): Write "Resolution not yet applied — fix proposed: \
<fix title>." Pull verbatim script names and template references when available.
Strict rules:
- Use ONLY the facts and state I provide. Never invent specifics that are not \
in the input.
- Do not include placeholder text like "TBD", "TODO", or empty bullets.
- Do not include the engineer's name, the AI's name, internal session IDs, or \
the session's chat transcript.
- Markdown headings exactly as shown (## level), no bolding the headings.
- No trailing whitespace, no double-blank lines, no horizontal rules.
"""
class ResolutionNoteGeneratorService:
"""Generates and caches the four-section Resolve note markdown."""
KIND = "resolution_note"
def __init__(self, db: AsyncSession) -> None:
self.db = db
async def generate_or_get_cached(
self, session_id: UUID, *, force: bool = False,
) -> dict[str, Any]:
"""Return the preview for the session.
Reads `(KIND, session_id, state_version)` from the in-process cache;
on miss, generates fresh markdown and stores under the same key.
`force=True` bypasses the cache and refreshes the cached entry.
Returns `{"markdown": str, "target_ticket_ref": str | None,
"state_version": int, "from_cache": bool}`.
"""
session = await self._load_session(session_id)
cached = preview_cache.get(self.KIND, session.id, session.state_version) if not force else None
if cached is not None:
return {**cached, "from_cache": True}
markdown = await self._render(session)
target = self._target_ticket_ref(session)
payload = {
"markdown": markdown,
"target_ticket_ref": target,
"state_version": session.state_version,
}
preview_cache.set(self.KIND, session.id, session.state_version, payload)
return {**payload, "from_cache": False}
# ── Internals ─────────────────────────────────────────────────────────
async def _load_session(self, session_id: UUID) -> AISession:
result = await self.db.execute(
select(AISession).where(AISession.id == session_id)
)
session = result.scalar_one_or_none()
if session is None:
raise ValueError(f"Session {session_id} not found")
return session
async def _render(self, session: AISession) -> str:
"""Build the prompt input bundle, call the model, return markdown."""
facts = await self._load_facts(session.id)
active_fix = await self._load_active_fix(session.id)
gens = await self._load_redacted_generations(session.id)
bundle = self._build_input_bundle(session, facts, active_fix, gens)
model = settings.get_model_for_action("resolution_note")
provider = get_ai_provider(model=model)
# Cache the system prompt — identical across every preview call for
# every session. Per-session bundle is in the user message, uncached.
system_blocks: list[dict[str, Any]] = [
{
"type": "text",
"text": _RESOLUTION_NOTE_SYSTEM_PROMPT,
"cache_control": {"type": "ephemeral"},
# cacheable: identical across every resolution-note preview call
},
]
try:
text, _in, _out = await provider.generate_text(
system_prompt=system_blocks,
messages=[{"role": "user", "content": bundle}],
max_tokens=1200,
)
except Exception:
logger.exception("Resolution note generation failed for session %s", session.id)
raise
return text.strip()
async def _load_facts(self, session_id: UUID) -> list[SessionFact]:
result = await self.db.execute(
select(SessionFact)
.where(
SessionFact.session_id == session_id,
SessionFact.deleted_at.is_(None),
)
.order_by(SessionFact.created_at.asc())
)
return list(result.scalars().all())
async def _load_active_fix(self, session_id: UUID) -> SessionSuggestedFix | None:
result = await self.db.execute(
select(SessionSuggestedFix)
.where(
SessionSuggestedFix.session_id == session_id,
SessionSuggestedFix.superseded_at.is_(None),
)
.order_by(SessionSuggestedFix.created_at.desc())
)
return result.scalars().first()
async def _load_redacted_generations(
self, session_id: UUID
) -> list[dict[str, Any]]:
"""Pull script_generations for the session, redacting password params.
Password fields are inferred from the linked template's
`parameters_schema` (`field_type: "password"`). The existing
ScriptTemplateEngine.redact_sensitive handles the substitution.
"""
result = await self.db.execute(
select(ScriptGeneration)
.where(ScriptGeneration.ai_session_id == session_id)
.order_by(ScriptGeneration.created_at.asc())
)
gens = list(result.scalars().all())
if not gens:
return []
template_ids = {g.template_id for g in gens}
tpl_result = await self.db.execute(
select(ScriptTemplate).where(ScriptTemplate.id.in_(template_ids))
)
templates_by_id = {t.id: t for t in tpl_result.scalars().all()}
engine = ScriptTemplateEngine()
out: list[dict[str, Any]] = []
for g in gens:
tpl = templates_by_id.get(g.template_id)
sensitive_keys = self._sensitive_keys_from_schema(
(tpl.parameters_schema if tpl else {}) or {}
)
redacted_params = engine.redact_sensitive(g.parameters_used or {}, sensitive_keys)
out.append({
"template_name": tpl.name if tpl else "(unknown template)",
"template_slug": tpl.slug if tpl else None,
"parameters_used": redacted_params,
"created_at": g.created_at.isoformat(),
})
return out
@staticmethod
def _sensitive_keys_from_schema(schema: dict[str, Any]) -> set[str]:
"""Extract password-typed parameter keys from a template's schema.
The schema shape is `{"parameters": [{"key": "...", "field_type": "password", ...}]}`
per the existing Script Generator convention. Tolerate both that shape
and the simpler `{"key": {"field_type": "password"}}` form.
"""
keys: set[str] = set()
params = schema.get("parameters") if isinstance(schema, dict) else None
if isinstance(params, list):
for p in params:
if isinstance(p, dict) and p.get("field_type") == "password":
k = p.get("key") or p.get("variable_name")
if isinstance(k, str):
keys.add(k)
elif isinstance(schema, dict):
for k, v in schema.items():
if isinstance(v, dict) and v.get("field_type") == "password":
keys.add(k)
return keys
@staticmethod
def _target_ticket_ref(session: AISession) -> str | None:
"""Display ref for the linked PSA ticket, e.g. 'CW #48291'.
ConnectWise is the only PSA wired today (per the Phase 1 constraint),
so a CW prefix is reasonable. Other PSAs will need provider-aware
formatting in Phase 4.
"""
if not session.psa_ticket_id:
return None
return f"CW #{session.psa_ticket_id}"
@staticmethod
def _build_input_bundle(
session: AISession,
facts: list[SessionFact],
active_fix: SessionSuggestedFix | None,
generations: list[dict[str, Any]],
) -> str:
"""Compose the structured input the LLM sees for one preview call."""
lines: list[str] = []
lines.append("# Session context")
lines.append(f"Title: {session.title or '(untitled)'}")
if session.problem_summary:
lines.append(f"Problem summary: {session.problem_summary}")
if session.problem_domain:
lines.append(f"Domain: {session.problem_domain}")
intake_text = (session.intake_content or {}).get("text") if isinstance(session.intake_content, dict) else None
if intake_text:
lines.append(f"Intake message: {intake_text}")
if session.psa_ticket_id:
lines.append(f"Linked PSA ticket: CW #{session.psa_ticket_id}")
lines.append("")
lines.append("# Confirmed facts (What we know)")
if not facts:
lines.append("(none)")
else:
for f in facts:
tag = f.source_type
summary = f"{f.source_summary}" if f.source_summary else ""
lines.append(f"- [{tag}] {f.text}{summary}")
lines.append("")
lines.append("# Active suggested fix")
if active_fix is None:
lines.append("(no active suggested fix)")
else:
lines.append(f"Title: {active_fix.title}")
lines.append(f"Confidence: {active_fix.confidence_pct}%")
lines.append(f"Description: {active_fix.description}")
if active_fix.user_decision:
lines.append(f"Engineer decision: {active_fix.user_decision}")
lines.append(f"Outcome status: {active_fix.status}")
if active_fix.applied_at:
lines.append(f"Applied at: {active_fix.applied_at.isoformat()}")
if active_fix.verified_at:
lines.append(f"Verified at: {active_fix.verified_at.isoformat()}")
if active_fix.partial_notes:
lines.append(f"Partial notes: {active_fix.partial_notes}")
if active_fix.failure_reason:
lines.append(f"Failure reason: {active_fix.failure_reason}")
lines.append("")
lines.append("# Scripts run during the session (passwords redacted)")
if not generations:
lines.append("(none)")
else:
for g in generations:
lines.append(f"- {g['template_name']} (slug={g['template_slug']})")
if g["parameters_used"]:
lines.append(f" parameters: {g['parameters_used']}")
lines.append("")
lines.append(
"Produce the four-section resolution note now. Use only the input above."
)
return "\n".join(lines)

View File

@@ -148,8 +148,6 @@ async def create_session(
team_id: UUID | None,
language: str,
initial_prompt: str | None = None,
origin: str = "standalone",
ai_session_id: UUID | None = None,
) -> ScriptBuilderSession:
"""Create a new Script Builder session."""
session = ScriptBuilderSession(
@@ -157,8 +155,6 @@ async def create_session(
account_id=account_id,
team_id=team_id,
language=language,
origin=origin,
ai_session_id=ai_session_id,
)
db.add(session)
await db.flush()
@@ -224,15 +220,7 @@ async def send_message(
model = settings.get_model_for_action("script_build")
provider = get_ai_provider(model=model)
ai_text, input_tokens, output_tokens = await provider.generate_text(
system_prompt=[
{"type": "text", "text": system_prompt},
# cacheable: SYSTEM_PROMPT_TEMPLATE with a per-session language
# substitution. Two sessions on the same language share a cache
# entry; different languages cache independently. Conversation
# history (ai_messages) is NOT cached at this layer — if that
# becomes a cost driver, route script_builder through the chat
# wrapper (0.4) which handles history caching.
],
system_prompt=system_prompt,
messages=ai_messages,
max_tokens=8192,
)
@@ -299,22 +287,15 @@ async def list_sessions(
user_id: UUID,
limit: int = 20,
offset: int = 0,
*,
include_inline: bool = False,
) -> list[ScriptBuilderSession]:
"""List user's builder sessions ordered by updated_at desc.
By default (include_inline=False) excludes pilot_inline sessions so the
/script-builder dashboard only shows standalone sessions.
"""
stmt = (
"""List user's builder sessions ordered by updated_at desc."""
result = await db.execute(
select(ScriptBuilderSession)
.where(ScriptBuilderSession.user_id == user_id)
.order_by(ScriptBuilderSession.updated_at.desc())
.limit(limit)
.offset(offset)
)
if not include_inline:
stmt = stmt.where(ScriptBuilderSession.origin == "standalone")
stmt = stmt.order_by(ScriptBuilderSession.updated_at.desc()).limit(limit).offset(offset)
result = await db.execute(stmt)
return list(result.scalars().all())
@@ -332,23 +313,13 @@ async def delete_session(
return True
async def count_user_sessions(
db: AsyncSession,
user_id: UUID,
*,
include_inline: bool = False,
) -> int:
"""Count active builder sessions for a user.
By default (include_inline=False) excludes pilot_inline sessions so they
don't consume slots against the MAX_SESSIONS_PER_USER cap.
"""
stmt = select(func.count(ScriptBuilderSession.id)).where(
ScriptBuilderSession.user_id == user_id
async def count_user_sessions(db: AsyncSession, user_id: UUID) -> int:
"""Count active builder sessions for a user."""
result = await db.execute(
select(func.count(ScriptBuilderSession.id)).where(
ScriptBuilderSession.user_id == user_id
)
)
if not include_inline:
stmt = stmt.where(ScriptBuilderSession.origin == "standalone")
result = await db.execute(stmt)
return result.scalar_one()

View File

@@ -1,201 +0,0 @@
"""TemplateExtractionService — propose a parameter schema from a rendered script.
Phase 5 of the FlowPilot migration. Called when an engineer chooses
"Run now, templatize after resolve" on a suggested fix with no existing
library match. The service looks at the concrete script (with the values
the engineer is about to run with) and session/ticket context, then
proposes a parameterization that future engineers could use from the
Script Library.
Design choices (per FLOWPILOT-MIGRATION.md Section 6.4):
- **Conservative by default.** Prefer fewer parameters. Environment-agnostic
values (like a command name) should not be parameterized. The prompt calls
that out explicitly.
- **Round-trip check.** After the LLM proposes parameters, we validate that
the templated body renders back to the original script when given the
extracted parameter values. Failures log a warning and the caller falls
back to a single-parameter "raw script" proposal.
- **Model:** Sonnet (`template_extraction` tier). Creates a persistent
library artifact — quality matters more than latency.
Output shape mirrors the Script Generator's parameter schema:
{
"parameters": [
{"key": "<snake>", "label": "<human>", "type": "text|password|select|...",
"inferred_from": "<session fact / ticket field / ai guess>"}
],
"templated_body": "<script with {{ key }} placeholders>",
}
"""
from __future__ import annotations
import json
import logging
import re
from typing import Any
from app.core.ai_provider import get_ai_provider
from app.core.config import settings
logger = logging.getLogger(__name__)
_EXTRACTION_SYSTEM_PROMPT = """\
You are a senior MSP engineer drafting a reusable script template from a \
concrete script that resolved one ticket. Your job is to identify the values \
in the script that would change for a different invocation — those become \
parameters — and replace them with {{ snake_case }} placeholders.
Return strict JSON with this shape:
{
"parameters": [
{
"key": "<snake_case, ASCII>",
"label": "<Short human label, Title Case>",
"type": "text" | "password" | "select" | "boolean" | "number" | "textarea",
"inferred_from": "<short sentence naming the session fact or ticket \
field this value came from; or 'ai best-guess' when neither>"
}
],
"templated_body": "<the original script with each parameterized value \
replaced by {{ key }} matching the parameters above>"
}
Rules:
- Prefer FEWER parameters. If a value looks environment-agnostic — a cmdlet \
name, a standard path like C:\\Windows\\System32, a Microsoft-documented URL \
— keep it hardcoded.
- Secret-looking values (passwords, API keys, client secrets) MUST be \
parameterized with type=password.
- The templated_body MUST render back to the original script when the \
parameter values from the context are substituted in. Preserve all whitespace, \
comments, and casing.
- If the script has no meaningful parameters (e.g. it's a single read-only \
cmdlet like Get-Service), return parameters=[] and templated_body = original.
- No markdown fences, no prose, only the JSON object.
"""
async def extract_parameters(
*,
script_body: str,
session_context: str | None = None,
ticket_context: str | None = None,
) -> dict[str, Any]:
"""Return `{parameters, templated_body}` for the given rendered script.
On LLM failure or malformed output, returns a conservative fallback:
the original body with no parameters proposed. Callers can still create
a `draft_templates` row from this — the engineer reviews and refines
before accepting in the post-resolve prompt (Phase 6).
"""
model = settings.get_model_for_action("template_extraction")
provider = get_ai_provider(model=model)
input_lines = [
"# Script to templatize",
"```",
script_body.strip(),
"```",
]
if session_context:
input_lines.extend(["", "# Session context (facts, symptoms)", session_context.strip()])
if ticket_context:
input_lines.extend(["", "# Ticket context (company, user, priority)", ticket_context.strip()])
user_input = "\n".join(input_lines)
system_blocks: list[dict[str, Any]] = [
{
"type": "text",
"text": _EXTRACTION_SYSTEM_PROMPT,
"cache_control": {"type": "ephemeral"},
# cacheable: identical across every extraction call
},
]
try:
text, _in, _out = await provider.generate_json(
system_prompt=system_blocks,
messages=[{"role": "user", "content": user_input}],
max_tokens=3000,
)
except Exception:
logger.exception("TemplateExtractionService LLM call failed; returning fallback")
return _fallback(script_body)
parsed = _parse_response(text)
if parsed is None:
return _fallback(script_body)
# Round-trip validation: render parsed["templated_body"] with the
# `inferred_from` values and confirm it matches the original. We don't
# have the engineer's values yet here (those come at runtime), but we
# can at least check that every {{ key }} in templated_body maps to a
# declared parameter. A mismatch means the LLM referenced an undeclared
# placeholder — conservative fallback.
declared_keys = {p.get("key") for p in parsed["parameters"] if isinstance(p, dict)}
referenced_keys = set(re.findall(r"\{\{\s*(\w+)\s*\}\}", parsed["templated_body"]))
missing = referenced_keys - declared_keys
if missing:
logger.warning(
"TemplateExtractionService: templated_body references undeclared "
"keys %s; using fallback",
sorted(missing),
)
return _fallback(script_body)
return parsed
def _parse_response(raw: str) -> dict[str, Any] | None:
"""Tolerant parse. Returns None on any structural problem."""
cleaned = raw.strip()
if cleaned.startswith("```"):
cleaned = re.sub(r"^```(?:json)?\s*", "", cleaned)
cleaned = re.sub(r"\s*```$", "", cleaned)
try:
data = json.loads(cleaned)
except (json.JSONDecodeError, ValueError):
logger.warning("TemplateExtractionService returned non-JSON: %r", raw[:200])
return None
if not isinstance(data, dict):
return None
params = data.get("parameters")
body = data.get("templated_body")
if not isinstance(params, list) or not isinstance(body, str):
logger.warning("TemplateExtractionService missing parameters or templated_body")
return None
# Validate each parameter shape. Drop malformed entries rather than
# failing the whole response — the engineer will review before accept.
valid_params: list[dict[str, Any]] = []
allowed_types = {"text", "password", "select", "boolean", "number", "textarea", "multi_text"}
for p in params:
if not isinstance(p, dict):
continue
key = p.get("key")
if not isinstance(key, str) or not re.match(r"^[a-z_][a-z0-9_]*$", key):
continue
ptype = p.get("type", "text")
if ptype not in allowed_types:
ptype = "text"
valid_params.append({
"key": key,
"label": p.get("label") or key.replace("_", " ").title(),
"type": ptype,
"inferred_from": p.get("inferred_from") or "ai best-guess",
})
return {"parameters": valid_params, "templated_body": body}
def _fallback(script_body: str) -> dict[str, Any]:
"""Conservative no-op result: zero parameters, body unchanged.
Used when the LLM call fails or returns unusable output. The engineer
can still save this as a draft and refine in the post-resolve prompt —
it just won't propose a parameterization for them.
"""
return {"parameters": [], "templated_body": script_body}

View File

@@ -1,116 +0,0 @@
"""Ticket mutation service — wraps PSA provider, resolves is_rf_user flag."""
from __future__ import annotations
import logging
from uuid import UUID
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.models.psa_connection import PsaConnection
from app.models.psa_member_mapping import PsaMemberMapping
from app.schemas.psa_tickets import (
PSAResourceSchema,
PSATicketCreatedSchema,
PSATicketStatusUpdateSchema,
)
from app.services.psa.registry import get_provider_for_account
from app.services.psa.types import TicketCreatePayload
logger = logging.getLogger(__name__)
async def _get_mapped_member_ids(account_id: UUID, db: AsyncSession) -> set[int]:
"""Return set of external_member_id ints that are mapped to RF users."""
conn_result = await db.execute(
select(PsaConnection).where(PsaConnection.account_id == account_id)
)
conn = conn_result.scalar_one_or_none()
if not conn:
return set()
mappings = await db.execute(
select(PsaMemberMapping).where(PsaMemberMapping.psa_connection_id == conn.id)
)
return {int(m.external_member_id) for m in mappings.scalars().all() if m.external_member_id}
async def list_resources(
account_id: UUID, ticket_id: int, db: AsyncSession
) -> list[PSAResourceSchema]:
provider = await get_provider_for_account(account_id, db)
mapped_ids = await _get_mapped_member_ids(account_id, db)
resources = await provider.list_resources(ticket_id)
return [
PSAResourceSchema(
member_id=r.member_id,
member_name=r.member_name,
member_identifier=r.member_identifier,
is_rf_user=r.member_id in mapped_ids,
)
for r in resources
]
async def add_resource(
account_id: UUID, ticket_id: int, member_id: int, db: AsyncSession
) -> PSAResourceSchema:
provider = await get_provider_for_account(account_id, db)
mapped_ids = await _get_mapped_member_ids(account_id, db)
resource = await provider.add_resource(ticket_id, member_id)
return PSAResourceSchema(
member_id=resource.member_id,
member_name=resource.member_name,
member_identifier=resource.member_identifier,
is_rf_user=resource.member_id in mapped_ids,
)
async def remove_resource(
account_id: UUID, ticket_id: int, member_id: int, db: AsyncSession
) -> None:
provider = await get_provider_for_account(account_id, db)
await provider.remove_resource(ticket_id, member_id)
async def update_status(
account_id: UUID, ticket_id: int, status_id: int, db: AsyncSession
) -> PSATicketStatusUpdateSchema:
provider = await get_provider_for_account(account_id, db)
# get current status before updating
ticket = await provider.get_ticket(str(ticket_id))
previous_status = ticket.status_name or ""
await provider.update_ticket_status(str(ticket_id), status_id)
# get new status name from statuses list
statuses = await provider.get_ticket_statuses(ticket.board_id or 0)
new_status = next((s.name for s in statuses if s.id == status_id), str(status_id))
return PSATicketStatusUpdateSchema(
ticket_id=ticket_id,
previous_status=previous_status,
new_status=new_status,
new_status_id=status_id,
)
async def create_ticket(
account_id: UUID, payload: TicketCreatePayload, db: AsyncSession
) -> PSATicketCreatedSchema:
provider = await get_provider_for_account(account_id, db)
mapped_ids = await _get_mapped_member_ids(account_id, db)
result = await provider.create_ticket(payload)
return PSATicketCreatedSchema(
id=result.id,
summary=result.summary,
board_name=result.board_name,
status_name=result.status_name,
priority_name=result.priority_name,
company_name=result.company_name,
resources=[
PSAResourceSchema(
member_id=r.member_id,
member_name=r.member_name,
member_identifier=r.member_identifier,
is_rf_user=r.member_id in mapped_ids,
)
for r in result.resources
],
)

View File

@@ -3,41 +3,22 @@
Replaces assistant_chat_service for new chat sessions. Messages are stored
in ai_sessions.conversation_messages JSONB. Reuses the same AI calling
infrastructure and system prompt from assistant_chat_service.
## Markers parsed here
- `[QUESTIONS]` / `[ACTIONS]` — task-lane items shown to the engineer
- `[FORK]` — diagnostic forking, creates SessionBranch rows
- `[PROMOTE]` (Phase 2) — surfaces a fact to the What-we-know section.
Items in pending_task_lane carry stable UUIDs (assigned here) so PROMOTE
source_refs survive across turns even when the model re-emits the same
question/action.
- `[SUGGEST_FIX]` (Phase 3) — proposes a resolution path for the session.
Each new emission supersedes the previous active row (sets superseded_at)
so there's exactly one active fix at a time.
"""
import json
import logging
import re
import uuid as _uuid
from typing import Any
from uuid import UUID
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from datetime import datetime, timezone
from sqlalchemy import update
from app.models.ai_session import AISession
from app.models.script_template import ScriptTemplate
from app.models.session_suggested_fix import SessionSuggestedFix
from app.services.assistant_chat_service import (
ASSISTANT_SYSTEM_PROMPT,
_call_ai,
_auto_title,
)
from app.services.fact_synthesis_service import FactSynthesisService
from app.services.rag_service import search as rag_search, build_rag_context, extract_suggested_flows
logger = logging.getLogger(__name__)
@@ -166,378 +147,6 @@ def _parse_questions_marker(ai_content: str) -> tuple[str, list[dict[str, Any]]
return cleaned, valid_questions
def _parse_promote_marker(ai_content: str) -> tuple[str, list[dict[str, Any]] | None]:
"""Extract one or more [PROMOTE]...[/PROMOTE] JSON blocks from AI response.
Each block contains a JSON object describing a candidate fact:
{"source_type": "question"|"diagnostic_check"|"ai_synthesis",
"source_ref": "<task_lane_item_uuid>" | null,
"text": "<fact text>",
"summary": "<short provenance, optional>"}
Returns (cleaned_content, list_of_items_or_None). All matched blocks are
stripped from display text. Invalid items are dropped silently with a
warning — a malformed PROMOTE should never break the chat response.
Per FLOWPILOT-MIGRATION.md Section 8.1, the model emits text + summary
inline so no LLM round-trip is needed to persist the fact.
"""
blocks = list(re.finditer(r"\[PROMOTE\]\s*([\s\S]*?)\s*\[/PROMOTE\]", ai_content))
if not blocks:
return ai_content, None
items: list[dict[str, Any]] = []
for m in blocks:
raw = m.group(1).strip()
if raw.startswith("```"):
raw = re.sub(r"^```(?:json)?\s*", "", raw)
raw = re.sub(r"\s*```$", "", raw)
try:
data = json.loads(raw)
except (json.JSONDecodeError, ValueError) as e:
logger.warning("Failed to parse [PROMOTE] block: %s", e)
continue
if not isinstance(data, dict):
logger.warning("[PROMOTE] block must be a JSON object, got %s", type(data).__name__)
continue
source_type = data.get("source_type")
text = (data.get("text") or "").strip()
summary = (data.get("summary") or "").strip() or None
source_ref_raw = data.get("source_ref")
if source_type not in ("question", "diagnostic_check", "ai_synthesis"):
# `user_note` is engineer-only, not an AI-emittable type.
logger.warning("Invalid [PROMOTE] source_type=%r, skipping", source_type)
continue
if not text:
logger.warning("[PROMOTE] block missing text, skipping")
continue
source_ref: UUID | None = None
if source_ref_raw:
try:
source_ref = UUID(str(source_ref_raw))
except (ValueError, AttributeError):
logger.warning("[PROMOTE] source_ref %r is not a valid UUID, dropping ref", source_ref_raw)
source_ref = None
# `ai_synthesis` must NEVER carry a source_ref (no question/check item
# to point at) — surface mistakes from the model rather than tripping
# the FactSynthesisService validation later.
if source_type == "ai_synthesis":
source_ref = None
items.append({
"source_type": source_type,
"source_ref": source_ref,
"text": text,
"summary": summary,
})
# Strip all PROMOTE blocks from display content — engineers see facts in
# the What-we-know panel, not as raw markers in the chat.
cleaned = re.sub(r"\[PROMOTE\]\s*[\s\S]*?\s*\[/PROMOTE\]", "", ai_content).strip()
return cleaned, items or None
def _assign_stable_task_lane_ids(
prev_lane: dict[str, Any] | None,
questions: list[dict[str, Any]] | None,
actions: list[dict[str, Any]] | None,
) -> tuple[list[dict[str, Any]], list[dict[str, Any]]]:
"""Assign stable UUIDs to task-lane items, preserving them across turns.
The model often re-emits the same question/action across multiple turns
(it is told to keep `_(not yet completed)_` items alive). When the
question text matches a prior turn's, we keep the prior UUID so any
`session_facts.source_ref` pointing at it stays valid.
Match key:
- Questions: exact `text`
- Actions: exact `label`
Returns the questions/actions lists augmented with an `id` field.
"""
prev_questions = (prev_lane or {}).get("questions") or []
prev_actions = (prev_lane or {}).get("actions") or []
prev_q_ids: dict[str, str] = {
str(q.get("text") or "").strip(): str(q["id"])
for q in prev_questions
if isinstance(q, dict) and q.get("id") and q.get("text")
}
prev_a_ids: dict[str, str] = {
str(a.get("label") or "").strip(): str(a["id"])
for a in prev_actions
if isinstance(a, dict) and a.get("id") and a.get("label")
}
out_questions: list[dict[str, Any]] = []
for q in questions or []:
text = str(q.get("text") or "").strip()
existing = prev_q_ids.get(text) if text else None
out_questions.append({
**q,
"id": existing or str(_uuid.uuid4()),
})
out_actions: list[dict[str, Any]] = []
for a in actions or []:
label = str(a.get("label") or "").strip()
existing = prev_a_ids.get(label) if label else None
out_actions.append({
**a,
"id": existing or str(_uuid.uuid4()),
})
return out_questions, out_actions
def _parse_suggest_fix_marker(
ai_content: str,
) -> tuple[str, dict[str, Any] | None]:
"""Extract a single [SUGGEST_FIX]...[/SUGGEST_FIX] JSON block from AI response.
The block contains:
{"title": "...", "description": "...", "confidence": 0..100,
"script_template_slug": "..." | null,
"ai_drafted_script": "..." | null,
"ai_drafted_parameters": {...} | null}
Per FLOWPILOT-MIGRATION.md Section 8.2. Only the LAST block in the response
is honored — if the model emits multiple, only its final view of the fix
matters; earlier ones in the same turn are stale even before persistence.
Returns (cleaned_content, fix_dict_or_None). Marker stripped from display.
"""
blocks = list(re.finditer(r"\[SUGGEST_FIX\]\s*([\s\S]*?)\s*\[/SUGGEST_FIX\]", ai_content))
if not blocks:
return ai_content, None
# Take the last block — most-recent intent wins within a single turn.
last = blocks[-1]
raw = last.group(1).strip()
if raw.startswith("```"):
raw = re.sub(r"^```(?:json)?\s*", "", raw)
raw = re.sub(r"\s*```$", "", raw)
try:
data = json.loads(raw)
except (json.JSONDecodeError, ValueError) as e:
logger.warning("Failed to parse [SUGGEST_FIX] block: %s", e)
return re.sub(r"\[SUGGEST_FIX\]\s*[\s\S]*?\s*\[/SUGGEST_FIX\]", "", ai_content).strip(), None
if not isinstance(data, dict):
return re.sub(r"\[SUGGEST_FIX\]\s*[\s\S]*?\s*\[/SUGGEST_FIX\]", "", ai_content).strip(), None
title = (data.get("title") or "").strip()
description = (data.get("description") or "").strip()
confidence = data.get("confidence")
if not title or not description or not isinstance(confidence, (int, float)):
logger.warning("[SUGGEST_FIX] missing required fields, dropping")
return re.sub(r"\[SUGGEST_FIX\]\s*[\s\S]*?\s*\[/SUGGEST_FIX\]", "", ai_content).strip(), None
confidence_int = max(0, min(100, int(round(float(confidence)))))
parsed = {
"title": title[:200],
"description": description,
"confidence_pct": confidence_int,
"script_template_slug": (data.get("script_template_slug") or None),
"ai_drafted_script": (data.get("ai_drafted_script") or None),
"ai_drafted_parameters": data.get("ai_drafted_parameters") if isinstance(data.get("ai_drafted_parameters"), dict) else None,
}
cleaned = re.sub(r"\[SUGGEST_FIX\]\s*[\s\S]*?\s*\[/SUGGEST_FIX\]", "", ai_content).strip()
return cleaned, parsed
def _parse_fix_outcome_marker(
ai_content: str,
) -> tuple[str, dict[str, Any] | None]:
"""Extract a single [FIX_OUTCOME]...[/FIX_OUTCOME] JSON block.
Block shape:
{"fix_id": "<uuid>", "outcome": "success"|"failure"|"partial",
"reason": "<one-line>"}
Emitted by the AI when the engineer clearly indicates in chat that a
prior suggested fix worked, didn't work, or was partially applied.
The marker PROPOSES an outcome — the engineer confirms via the UI.
Only the last block in a response is honored.
"""
blocks = list(re.finditer(
r"\[FIX_OUTCOME\]\s*([\s\S]*?)\s*\[/FIX_OUTCOME\]", ai_content,
))
if not blocks:
return ai_content, None
last = blocks[-1]
raw = last.group(1).strip()
if raw.startswith("```"):
raw = re.sub(r"^```(?:json)?\s*", "", raw)
raw = re.sub(r"\s*```$", "", raw)
cleaned = re.sub(
r"\[FIX_OUTCOME\]\s*[\s\S]*?\s*\[/FIX_OUTCOME\]", "", ai_content,
).strip()
try:
data = json.loads(raw)
except (json.JSONDecodeError, ValueError) as e:
logger.warning("Failed to parse [FIX_OUTCOME] block: %s", e)
return cleaned, None
if not isinstance(data, dict):
return cleaned, None
fix_id = str(data.get("fix_id") or "").strip()
outcome = str(data.get("outcome") or "").strip().lower()
reason = str(data.get("reason") or "").strip()
if not fix_id or outcome not in {"success", "failure", "partial"}:
logger.warning("[FIX_OUTCOME] missing/invalid fields, dropping")
return cleaned, None
return cleaned, {"fix_id": fix_id, "outcome": outcome, "reason": reason}
async def _persist_suggested_fix(
*,
db: AsyncSession,
session: AISession,
fix: dict[str, Any],
) -> None:
"""Supersede the prior active fix and insert the new one. Bumps state_version.
A session has at most one active suggested fix (`superseded_at IS NULL`).
Emitting [SUGGEST_FIX] is the only way to introduce a new one; the
engineer's user_decision is recorded via the decision endpoint.
"""
now = datetime.now(timezone.utc)
# Mark any prior active rows for this session as superseded.
await db.execute(
update(SessionSuggestedFix)
.where(
SessionSuggestedFix.session_id == session.id,
SessionSuggestedFix.superseded_at.is_(None),
)
.values(superseded_at=now)
)
# Resolve script_template_slug → script_template_id if provided.
script_template_id = None
slug = fix.get("script_template_slug")
if slug:
result = await db.execute(
select(ScriptTemplate).where(ScriptTemplate.slug == slug)
)
tpl = result.scalar_one_or_none()
if tpl is not None:
script_template_id = tpl.id
else:
logger.warning(
"SUGGEST_FIX referenced unknown script_template_slug=%r"
"treating as no template match", slug,
)
new_fix = SessionSuggestedFix(
session_id=session.id,
account_id=session.account_id,
title=fix["title"],
description=fix["description"],
confidence_pct=fix["confidence_pct"],
script_template_id=script_template_id,
ai_drafted_script=fix.get("ai_drafted_script"),
ai_drafted_parameters=fix.get("ai_drafted_parameters"),
)
db.add(new_fix)
# Bump preview-cache version atomically with the supersession+insert.
await db.execute(
update(AISession)
.where(AISession.id == session.id)
.values(state_version=AISession.state_version + 1)
)
await db.flush()
async def _record_ai_outcome_proposal(
*,
db: AsyncSession,
session: AISession,
proposal: dict[str, Any],
) -> None:
"""Persist the AI's proposed outcome on the active fix.
Writes to session_suggested_fixes.ai_outcome_proposal. Frontend polls
the active fix and renders the AI-confirming banner state when this is
non-null. Does NOT mutate the fix's status — the engineer's confirmation
click via PATCH /outcome is what changes the status.
Drops silently when the fix_id isn't a valid UUID or doesn't belong to
this session.
"""
try:
fix_uuid = UUID(proposal["fix_id"])
except (ValueError, KeyError, TypeError):
logger.warning("[FIX_OUTCOME] invalid fix_id, dropping")
return
await db.execute(
update(SessionSuggestedFix)
.where(
SessionSuggestedFix.id == fix_uuid,
SessionSuggestedFix.session_id == session.id,
)
.values(ai_outcome_proposal=proposal)
)
await db.flush()
async def _persist_promote_items(
*,
db: AsyncSession,
session: AISession,
user_id: UUID,
items: list[dict[str, Any]],
) -> None:
"""Persist parsed [PROMOTE] items as session_facts. Failures are logged.
A malformed PROMOTE must never break the chat response — the engineer
still gets the AI's analysis; the missing fact can be added manually.
"""
if not items:
return
service = FactSynthesisService(db)
for item in items:
try:
await service.create_fact(
session_id=session.id,
account_id=session.account_id,
user_id=user_id,
source_type=item["source_type"],
text=item["text"],
summary=item["summary"],
source_ref=item["source_ref"],
)
except ValueError:
# Validation failure (e.g. empty text after strip, or
# source_ref-on-ai_synthesis race). Log and continue — losing
# one fact is better than aborting the whole chat turn.
logger.warning(
"Skipping invalid PROMOTE item for session %s: %r",
session.id, item, exc_info=True,
)
except Exception:
logger.exception(
"Failed to persist PROMOTE item for session %s", session.id
)
async def create_chat_session(
user_id: UUID,
account_id: UUID,
@@ -642,14 +251,10 @@ async def send_chat_message(
if session.status == "paused":
session.status = "active"
# Check for fork, actions, questions, promote, and suggest_fix markers
# in branch response too
# Check for fork, actions, and questions markers in branch response too
branch_display, branch_fork_data = _parse_fork_marker(ai_content)
branch_display, branch_actions_data = _parse_actions_marker(branch_display)
branch_display, branch_questions_data = _parse_questions_marker(branch_display)
branch_display, branch_promote_items = _parse_promote_marker(branch_display)
branch_display, branch_suggest_fix = _parse_suggest_fix_marker(branch_display)
branch_display, branch_outcome_proposal = _parse_fix_outcome_marker(branch_display)
if branch_display != ai_content:
# Store stripped content in branch history
msgs[-1] = {"role": "assistant", "content": branch_display}
@@ -683,42 +288,15 @@ async def send_chat_message(
except Exception:
logger.exception("Failed to create fork within branch for session %s", session.id)
# Persist task lane state on session — assign stable UUIDs so any
# PROMOTE marker emitted later can reference the same items.
# Persist task lane state on session
if branch_questions_data or branch_actions_data:
stable_qs, stable_as = _assign_stable_task_lane_ids(
session.pending_task_lane,
branch_questions_data,
branch_actions_data,
)
session.pending_task_lane = {
"questions": stable_qs,
"actions": stable_as,
"questions": branch_questions_data or [],
"actions": branch_actions_data or [],
}
else:
session.pending_task_lane = None
# Persist any PROMOTE items emitted in this turn. Done AFTER the
# task-lane write so source_refs to brand-new items would still
# land on persisted UUIDs (the model can also reference IDs from
# the previous turn, which were already persisted).
if branch_promote_items:
await _persist_promote_items(
db=db, session=session, user_id=user_id, items=branch_promote_items,
)
# Persist a [SUGGEST_FIX] if the branch turn included one.
if branch_suggest_fix:
await _persist_suggested_fix(
db=db, session=session, fix=branch_suggest_fix,
)
# Persist a [FIX_OUTCOME] proposal if the branch turn included one.
if branch_outcome_proposal is not None:
await _record_ai_outcome_proposal(
db=db, session=session, proposal=branch_outcome_proposal,
)
suggested_flows = extract_suggested_flows(
await rag_search(query=message, account_id=account_id, db=db, limit=8)
)
@@ -765,22 +343,9 @@ async def send_chat_message(
# Check for questions marker in AI response
display_content, questions_data = _parse_questions_marker(display_content)
# Check for promote markers — facts the AI is surfacing to What we know.
display_content, promote_items = _parse_promote_marker(display_content)
# Check for a [SUGGEST_FIX] marker — supersedes the prior active fix.
display_content, suggest_fix_data = _parse_suggest_fix_marker(display_content)
# Check for a [FIX_OUTCOME] proposal — AI confirms a prior fix's outcome.
display_content, outcome_proposal = _parse_fix_outcome_marker(display_content)
logger.info(
"Marker parsing results — actions: %s, questions: %s, fork: %s, "
"promote: %d, suggest_fix: %s, outcome_proposal: %s, "
"raw_length: %d, display_length: %d",
"Marker parsing results — actions: %s, questions: %s, fork: %s, raw_length: %d, display_length: %d",
bool(actions_data), bool(questions_data), bool(fork_data),
len(promote_items or []), bool(suggest_fix_data),
bool(outcome_proposal),
len(ai_content), len(display_content),
)
@@ -845,36 +410,15 @@ async def send_chat_message(
logger.exception("Failed to create fork for session %s", session_id)
# Fork failed but chat message still sent — don't break the response
# Persist task lane state on session — assign stable UUIDs so any PROMOTE
# marker (this turn or a later one) can reference the same items.
# Persist task lane state on session
if questions_data or actions_data:
stable_qs, stable_as = _assign_stable_task_lane_ids(
session.pending_task_lane, questions_data, actions_data,
)
session.pending_task_lane = {
"questions": stable_qs,
"actions": stable_as,
"questions": questions_data or [],
"actions": actions_data or [],
}
else:
session.pending_task_lane = None
# Persist any PROMOTE items emitted in this turn. Done after task-lane
# assignment so source_refs the model invented this turn already exist.
if promote_items:
await _persist_promote_items(
db=db, session=session, user_id=user_id, items=promote_items,
)
# Persist a [SUGGEST_FIX] if this turn included one — supersedes prior fix.
if suggest_fix_data:
await _persist_suggested_fix(db=db, session=session, fix=suggest_fix_data)
# Persist a [FIX_OUTCOME] proposal if this turn included one.
if outcome_proposal is not None:
await _record_ai_outcome_proposal(
db=db, session=session, proposal=outcome_proposal,
)
suggested_flows = extract_suggested_flows(rag_results)
return display_content, suggested_flows, session, fork_metadata, actions_data, questions_data

View File

@@ -27,7 +27,6 @@ markers =
slow: marks tests as slow (deselect with '-m "not slow"')
integration: marks tests as integration tests
unit: marks tests as unit tests
rls: opt-in RLS migration and policy tests (run with RUN_RLS_TESTS=1)
# Ignore paths
testpaths = tests

View File

@@ -3,7 +3,7 @@
# Testing
pytest==7.4.3
pytest-asyncio==0.24.0
pytest-asyncio==0.23.0
httpx>=0.27.0
pytest-cov==4.1.0

View File

@@ -1,375 +0,0 @@
#!/usr/bin/env python3
"""
Seed Phase 9 QA fixtures: 4 ai_sessions + matching suggested_fixes that
exercise the five Phase 9 components which gate on a backend-emitted
`SUGGEST_FIX` action and don't fire reliably in normal local sessions.
Usage:
cd backend
python -m scripts.seed_phase9_qa_fixtures
python -m scripts.seed_phase9_qa_fixtures --reset # delete & recreate
Targets the super-admin from `seed_test_users.py`
(admin@resolutionflow.example.com) and their account. UUIDs are
deterministic (UUID5 over a fixed namespace) so re-runs are idempotent
without --reset.
Sessions created:
| # | Title | Phase 9 component reached when… |
|---|---------------------------------|-------------------------------------------------------|
| A | Phase 9 QA — no-template path | ChatTabStrip + ScriptBuilderTab + ProposalBanner |
| B | Phase 9 QA — drafted-script | InlineNoTemplateDialog + ProposalBanner |
| C | Phase 9 QA — template match | TemplateMatchPanel + ProposalBanner |
| D | Phase 9 QA — verify state | EscalateInterceptDialog (with new "partial" choice) |
Run /qa, then in the browser go to /pilot, click each session in the
sidebar, and exercise its Phase 9 surface. The session URLs are printed
at the end.
"""
import argparse
import asyncio
import sys
import uuid
from datetime import datetime, timedelta, timezone
from sqlalchemy import text
from sqlalchemy.ext.asyncio import create_async_engine
from app.core.config import settings
ADMIN_EMAIL = "admin@resolutionflow.example.com"
# Deterministic UUIDs so re-running the seeder updates rather than duplicates.
NS = uuid.UUID("00000000-0000-0000-0000-000000000901")
SESSION_A = uuid.uuid5(NS, "session-A-no-template")
SESSION_B = uuid.uuid5(NS, "session-B-drafted-script")
SESSION_C = uuid.uuid5(NS, "session-C-template-match")
SESSION_D = uuid.uuid5(NS, "session-D-verify-state")
FIX_A = uuid.uuid5(NS, "fix-A")
FIX_B = uuid.uuid5(NS, "fix-B")
FIX_C = uuid.uuid5(NS, "fix-C")
FIX_D = uuid.uuid5(NS, "fix-D")
CATEGORY_QA = uuid.uuid5(NS, "category-qa-fixtures")
TEMPLATE_QA = uuid.uuid5(NS, "template-qa-fixtures")
DRAFTED_SCRIPT = """\
# Phase 9 QA fixture — AI-drafted PowerShell to flush DNS and
# restart the FortiClient service. Not for production use.
ipconfig /flushdns
Restart-Service -Name "FortiSslvpnDaemon" -Force
Get-Service -Name "FortiSslvpnDaemon" | Format-Table -AutoSize
"""
TEMPLATE_BODY = """\
# Phase 9 QA fixture — canned template that the AI matches against.
param([string]$ServiceName = "FortiSslvpnDaemon")
Restart-Service -Name $ServiceName -Force
Get-Service -Name $ServiceName | Select-Object Status, Name
"""
async def main(reset: bool = False) -> None:
db_url = (
settings.ADMIN_DATABASE_URL
if hasattr(settings, "ADMIN_DATABASE_URL") and settings.ADMIN_DATABASE_URL
else settings.DATABASE_URL
)
engine = create_async_engine(db_url, echo=False)
now = datetime.now(timezone.utc)
async with engine.begin() as conn:
# ─── Locate the admin user + account ───────────────────────────
row = (
await conn.execute(
text(
"SELECT id, account_id FROM users WHERE email = :email LIMIT 1"
),
{"email": ADMIN_EMAIL},
)
).first()
if row is None:
print(
f"ERROR: user {ADMIN_EMAIL!r} not found. Run "
"`python -m scripts.seed_test_users` first.",
file=sys.stderr,
)
sys.exit(2)
user_id, account_id = row
if reset:
await conn.execute(
text(
"DELETE FROM session_suggested_fixes WHERE id = ANY(:ids)"
),
{"ids": [FIX_A, FIX_B, FIX_C, FIX_D]},
)
await conn.execute(
text("DELETE FROM ai_sessions WHERE id = ANY(:ids)"),
{"ids": [SESSION_A, SESSION_B, SESSION_C, SESSION_D]},
)
await conn.execute(
text("DELETE FROM script_templates WHERE id = :id"),
{"id": TEMPLATE_QA},
)
await conn.execute(
text("DELETE FROM script_categories WHERE id = :id"),
{"id": CATEGORY_QA},
)
# ─── Script category + template (for Session C) ────────────────
await conn.execute(
text(
"""
INSERT INTO script_categories (id, name, slug, sort_order, is_active, created_at, updated_at)
VALUES (:id, 'QA Fixtures', 'qa-fixtures', 999, true, :now, :now)
ON CONFLICT (id) DO NOTHING
"""
),
{"id": CATEGORY_QA, "now": now},
)
await conn.execute(
text(
"""
INSERT INTO script_templates (
id, category_id, account_id, created_by, name, slug,
description, script_body, language, parameters_schema,
default_values, validation_rules, tags, complexity,
requires_elevation, requires_modules, created_at, updated_at
)
VALUES (
:id, :cat_id, :acct_id, :user_id,
'QA Fixture: Restart Forti Service',
'qa-fixture-restart-forti-service',
'Phase 9 QA fixture template for TemplateMatchPanel testing.',
:body, 'powershell',
'{}'::jsonb, '{}'::jsonb, '{}'::jsonb, '[]'::jsonb,
'beginner', false, '[]'::jsonb,
:now, :now
)
ON CONFLICT (id) DO NOTHING
"""
),
{
"id": TEMPLATE_QA,
"cat_id": CATEGORY_QA,
"acct_id": account_id,
"user_id": user_id,
"body": TEMPLATE_BODY,
"now": now,
},
)
# ─── 4 sessions ────────────────────────────────────────────────
# `canAct` in the chat header gates Resolve/Escalate on
# `messages.length >= 2`, so each fixture seeds two synthetic
# conversation messages — enough to enable the buttons that drive
# the Phase 9 surfaces.
seed_messages = (
'['
'{"role":"user","content":"QA fixture: see seed_phase9_qa_fixtures.py"},'
'{"role":"assistant","content":"This session is a Phase 9 QA fixture. The suggested fix below is pre-seeded — drive it from the UI."}'
']'
)
sessions = [
(SESSION_A, "Phase 9 QA — no-template path"),
(SESSION_B, "Phase 9 QA — drafted-script path"),
(SESSION_C, "Phase 9 QA — template-match path"),
(SESSION_D, "Phase 9 QA — verify state (Escalate intercept)"),
]
for sid, title in sessions:
await conn.execute(
text(
"""
INSERT INTO ai_sessions (
id, user_id, account_id, session_type, title,
intake_type, intake_content, status, confidence_tier,
confidence_score, conversation_messages,
total_input_tokens, total_output_tokens, step_count,
is_branching, state_version,
handoff_count, total_active_seconds, total_parked_seconds,
created_at, updated_at
)
VALUES (
:id, :user_id, :acct_id, 'chat', :title,
'free_text', '{"text": "QA fixture session"}'::jsonb,
'active', 'discovery',
0.0, (:msgs)::jsonb,
0, 0, 0,
false, 0,
0, 0, 0,
:now, :now
)
ON CONFLICT (id) DO UPDATE SET
title = EXCLUDED.title,
status = EXCLUDED.status,
conversation_messages = EXCLUDED.conversation_messages,
updated_at = EXCLUDED.updated_at
"""
),
{
"id": sid,
"user_id": user_id,
"acct_id": account_id,
"title": title,
"msgs": seed_messages,
"now": now,
},
)
# ─── 4 suggested fixes ─────────────────────────────────────────
# Fix A — no template, no draft → ChatTabStrip + ScriptBuilderTab
await _upsert_fix(
conn, fix_id=FIX_A, session_id=SESSION_A, account_id=account_id,
title="Restart the FortiClient daemon and flush DNS",
description=(
"Error -8 on FortiClient SSL VPN typically clears after a "
"service restart on the endpoint. No matching template; "
"no AI draft yet — engineer should choose Build Template "
"or One-Off in the Script Builder tab."
),
confidence_pct=72,
script_template_id=None,
ai_drafted_script=None,
status="proposed",
applied_at=None,
now=now,
)
# Fix B — drafted script, no template → InlineNoTemplateDialog
await _upsert_fix(
conn, fix_id=FIX_B, session_id=SESSION_B, account_id=account_id,
title="Run AI-drafted PowerShell to recover SSL VPN",
description=(
"AI drafted a session-specific script because no library "
"template matched. Inline dialog should offer Save-as-template, "
"Run-once, or Discard."
),
confidence_pct=68,
script_template_id=None,
ai_drafted_script=DRAFTED_SCRIPT,
status="proposed",
applied_at=None,
now=now,
)
# Fix C — template match → TemplateMatchPanel
await _upsert_fix(
conn, fix_id=FIX_C, session_id=SESSION_C, account_id=account_id,
title="Match: QA Fixture Restart Forti Service",
description=(
"AI matched an existing library template. The match panel "
"should render with the parameterization preview and an "
"explicit 'I ran this' action."
),
confidence_pct=88,
script_template_id=TEMPLATE_QA,
ai_drafted_script=None,
status="proposed",
applied_at=None,
now=now,
)
# Fix D — applied_at set, status='proposed' → verify state.
# Hitting Escalate from this state opens EscalateInterceptDialog.
await _upsert_fix(
conn, fix_id=FIX_D, session_id=SESSION_D, account_id=account_id,
title="Verifying: post-apply tunnel reconnect",
description=(
"Engineer marked the fix as Applied; we're now in the "
"verify window. Clicking Escalate from here should open "
"the EscalateInterceptDialog with the four outcome choices "
"(worked / didn't / partial / never-applied)."
),
confidence_pct=80,
script_template_id=None,
ai_drafted_script=DRAFTED_SCRIPT,
status="proposed",
applied_at=now - timedelta(minutes=2),
now=now,
)
await engine.dispose()
print()
print("=" * 64)
print(" Phase 9 QA fixtures ready.")
print("=" * 64)
print()
print(f" Sign in as : {ADMIN_EMAIL}")
print(f" Then visit : http://docker-01:5173/pilot")
print(f" Pick from the History sidebar:")
print(f" A. Phase 9 QA — no-template path (ChatTabStrip + ScriptBuilderTab)")
print(f" B. Phase 9 QA — drafted-script path (InlineNoTemplateDialog)")
print(f" C. Phase 9 QA — template-match path (TemplateMatchPanel)")
print(f" D. Phase 9 QA — verify state (EscalateInterceptDialog)")
print()
print(f" Re-run with --reset to wipe and recreate.")
print()
async def _upsert_fix(
conn,
*,
fix_id: uuid.UUID,
session_id: uuid.UUID,
account_id: uuid.UUID,
title: str,
description: str,
confidence_pct: int,
script_template_id: uuid.UUID | None,
ai_drafted_script: str | None,
status: str,
applied_at: datetime | None,
now: datetime,
) -> None:
await conn.execute(
text(
"""
INSERT INTO session_suggested_fixes (
id, session_id, account_id, title, description,
confidence_pct, script_template_id, ai_drafted_script,
status, applied_at, created_at
)
VALUES (
:id, :sid, :acct, :title, :desc,
:conf, :tmpl, :draft,
:status, :applied, :now
)
ON CONFLICT (id) DO UPDATE SET
title = EXCLUDED.title,
description = EXCLUDED.description,
confidence_pct = EXCLUDED.confidence_pct,
script_template_id = EXCLUDED.script_template_id,
ai_drafted_script = EXCLUDED.ai_drafted_script,
status = EXCLUDED.status,
applied_at = EXCLUDED.applied_at,
superseded_at = NULL
"""
),
{
"id": fix_id,
"sid": session_id,
"acct": account_id,
"title": title,
"desc": description,
"conf": confidence_pct,
"tmpl": script_template_id,
"draft": ai_drafted_script,
"status": status,
"applied": applied_at,
"now": now,
},
)
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Seed Phase 9 QA fixtures.")
parser.add_argument(
"--reset",
action="store_true",
help="Delete and recreate the fixtures.",
)
args = parser.parse_args()
asyncio.run(main(reset=args.reset))

View File

@@ -161,8 +161,8 @@ async def main() -> None:
if cfg["plan"] is not None:
await conn.execute(
text("""
INSERT INTO subscriptions (id, account_id, plan, status, cancel_at_period_end, created_at, updated_at)
VALUES (:id, :aid, :plan, 'active', false, :now, :now)
INSERT INTO subscriptions (id, account_id, plan, status, created_at, updated_at)
VALUES (:id, :aid, :plan, 'active', :now, :now)
"""),
{"id": uuid.uuid4(), "aid": account_id, "plan": cfg["plan"], "now": now},
)

View File

@@ -4,8 +4,8 @@ Pytest configuration and fixtures for integration tests.
Provides test database setup, client fixtures, and authentication helpers.
"""
import os
from typing import AsyncGenerator
import asyncio
from typing import AsyncGenerator, Generator
import pytest
import sqlalchemy as sa
from httpx import AsyncClient, ASGITransport
@@ -14,55 +14,30 @@ from sqlalchemy.pool import NullPool
from app.main import app
from app.core.database import Base, get_db
from app.core.admin_database import get_admin_db
from app.core.config import settings
# Disable invite code requirement for tests
settings.REQUIRE_INVITE_CODE = False
# Test database URL — NEVER reuse DATABASE_URL. The test_db fixture does
# `DROP SCHEMA public CASCADE` on every test; if DATABASE_URL (which normally
# points at the dev/prod DB) leaked into this value, running `pytest tests/`
# would silently nuke the dev database. Only DATABASE_TEST_URL is honored,
# and the safety assertion below refuses to run against a DB whose name
# doesn't contain "test".
# Test database URL (separate from production)
# Use DATABASE_TEST_URL env var if set (e.g. inside Docker where host is 'db'),
# otherwise fall back to localhost for local development.
import os
TEST_DATABASE_URL = os.environ.get(
"DATABASE_TEST_URL",
"postgresql+asyncpg://postgres:postgres@localhost:5432/resolutionflow_test",
"DATABASE_URL",
os.environ.get(
"DATABASE_TEST_URL",
"postgresql+asyncpg://postgres:postgres@localhost:5432/patherly_test",
),
)
# Belt-and-suspenders: refuse to run tests against a DB whose name doesn't
# contain "test". Parses the last path segment of the URL (everything after
# the final '/', with query string stripped) so credentials / hosts that
# happen to contain "test" can't bypass the check.
_test_db_name = TEST_DATABASE_URL.rsplit("/", 1)[-1].split("?", 1)[0].lower()
assert "test" in _test_db_name, (
f"Refusing to run tests against database {_test_db_name!r}"
f"the DB name must contain 'test'. Set DATABASE_TEST_URL to a dedicated "
f"test database (e.g. resolutionflow_test)."
)
_RUN_RLS_TESTS = os.environ.get("RUN_RLS_TESTS") == "1"
_RLS_ISOLATION_FILE = "test_rls_isolation.py"
def pytest_collection_modifyitems(config, items):
"""Keep migration-managed RLS checks out of the default create_all suite."""
if _RUN_RLS_TESTS:
return
selected = []
deselected = []
for item in items:
item_path = getattr(item, "path", None) or getattr(item, "fspath", None)
if item_path and str(item_path).endswith(_RLS_ISOLATION_FILE):
deselected.append(item)
else:
selected.append(item)
if deselected:
config.hook.pytest_deselected(items=deselected)
items[:] = selected
@pytest.fixture(scope="session")
def event_loop() -> Generator:
"""Create an instance of the default event loop for each test case."""
loop = asyncio.get_event_loop_policy().new_event_loop()
yield loop
loop.close()
@pytest.fixture
@@ -156,11 +131,6 @@ async def client(test_db: AsyncSession):
yield test_db
app.dependency_overrides[get_db] = override_get_db
# Endpoints that use get_admin_db (register, admin routes, service accounts)
# must also hit the test DB; otherwise they leak into the real admin DB.
# RLS is not enabled in the test schema (create_all, not alembic), so sharing
# the same session is safe.
app.dependency_overrides[get_admin_db] = override_get_db
transport = ASGITransport(app=app)
async with AsyncClient(transport=transport, base_url="http://test") as ac:

View File

@@ -1,536 +0,0 @@
"""Integration tests for PATCH /ai-sessions/{sid}/suggested-fixes/{fid}/outcome.
Fixture style follows test_session_suggested_fixes_api.py:
client, test_user, auth_headers, test_db
"""
from __future__ import annotations
from unittest.mock import AsyncMock, call, patch
import pytest
from httpx import AsyncClient
from sqlalchemy import select
from app.api.endpoints.session_suggested_fixes import _clear_preview_cache_for_tests
from app.models.ai_session import AISession
from app.models.session_suggested_fix import SessionSuggestedFix
@pytest.fixture(autouse=True)
def _isolate_preview_cache():
_clear_preview_cache_for_tests()
yield
_clear_preview_cache_for_tests()
# ── shared helper ────────────────────────────────────────────────────────────
async def _make_session_with_fix(test_db, user) -> tuple[str, str]:
"""Create an AISession + active proposed SessionSuggestedFix.
Returns (session_id_str, fix_id_str).
"""
session = AISession(
user_id=user["user_data"]["id"],
account_id=user["user_data"]["account_id"],
session_type="chat",
intake_type="free_text",
intake_content={"text": "outcome test"},
status="active",
confidence_tier="discovery",
conversation_messages=[],
)
test_db.add(session)
await test_db.flush()
fix = SessionSuggestedFix(
session_id=session.id,
account_id=session.account_id,
title="Reset credential cache",
description="Clear stale credentials from the domain cache.",
confidence_pct=82,
)
test_db.add(fix)
await test_db.commit()
await test_db.refresh(fix)
return str(session.id), str(fix.id)
# ── tests ────────────────────────────────────────────────────────────────────
@pytest.mark.asyncio
async def test_patch_outcome_marks_success(
client: AsyncClient, test_user, auth_headers, test_db
):
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
r = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
headers=auth_headers,
json={"outcome": "applied_success"},
)
assert r.status_code == 200, r.text
body = r.json()
assert body["status"] == "applied_success"
assert body["verified_at"] is not None
@pytest.mark.asyncio
async def test_patch_outcome_partial_requires_notes(
client: AsyncClient, test_user, auth_headers, test_db
):
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
r = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
headers=auth_headers,
json={"outcome": "applied_partial"},
)
assert r.status_code == 400
assert "notes" in r.text.lower()
@pytest.mark.asyncio
async def test_partial_to_success_allowed(
client: AsyncClient, test_user, auth_headers, test_db
):
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
r1 = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
headers=auth_headers,
json={"outcome": "applied_partial", "notes": "ran cred clear only"},
)
assert r1.status_code == 200, r1.text
r2 = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
headers=auth_headers,
json={"outcome": "applied_success"},
)
assert r2.status_code == 200
assert r2.json()["status"] == "applied_success"
@pytest.mark.asyncio
async def test_terminal_outcome_is_locked(
client: AsyncClient, test_user, auth_headers, test_db
):
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
r1 = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
headers=auth_headers,
json={"outcome": "applied_failed", "notes": "no change"},
)
assert r1.status_code == 200
r2 = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
headers=auth_headers,
json={"outcome": "applied_success"},
)
assert r2.status_code == 409
@pytest.mark.asyncio
async def test_partial_notes_can_be_updated(
client: AsyncClient, test_user, auth_headers, test_db
):
"""partial→partial with new notes updates the stored notes."""
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
r1 = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
json={"outcome": "applied_partial", "notes": "ran cred clear only"},
headers=auth_headers,
)
assert r1.status_code == 200
assert r1.json()["partial_notes"] == "ran cred clear only"
r2 = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
json={"outcome": "applied_partial", "notes": "also finished the rebuild; not verified yet"},
headers=auth_headers,
)
assert r2.status_code == 200
assert r2.json()["partial_notes"] == "also finished the rebuild; not verified yet"
@pytest.mark.asyncio
async def test_dismissed_sets_no_timestamps(
client: AsyncClient, test_user, auth_headers, test_db
):
"""dismissed outcome does not stamp applied_at or verified_at."""
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
r = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
json={"outcome": "dismissed"},
headers=auth_headers,
)
assert r.status_code == 200
body = r.json()
assert body["status"] == "dismissed"
assert body["applied_at"] is None
assert body["verified_at"] is None
@pytest.mark.asyncio
async def test_applied_at_auto_stamped_on_first_outcome(
client: AsyncClient, test_user, auth_headers, test_db
):
"""If applied_at is null when the engineer sets outcome, server stamps it."""
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
r = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
json={"outcome": "applied_success"},
headers=auth_headers,
)
assert r.status_code == 200
body = r.json()
assert body["applied_at"] is not None
assert body["verified_at"] is not None
@pytest.mark.asyncio
async def test_failed_outcome_stores_notes_as_failure_reason(
client: AsyncClient, test_user, auth_headers, test_db
):
"""applied_failed stores notes under failure_reason (not partial_notes)."""
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
r = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
json={"outcome": "applied_failed", "notes": "user reports no change"},
headers=auth_headers,
)
assert r.status_code == 200
body = r.json()
assert body["failure_reason"] == "user reports no change"
assert body["partial_notes"] is None
# ── state_version bump ────────────────────────────────────────────────────────
@pytest.mark.asyncio
async def test_outcome_patch_bumps_state_version(
client: AsyncClient, test_user, auth_headers, test_db
):
"""PATCH /outcome must increment ai_sessions.state_version (like record_decision)."""
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
# Capture the initial state_version from DB.
from uuid import UUID
result = await test_db.execute(
select(AISession).where(AISession.id == UUID(session_id))
)
session_obj = result.scalar_one()
initial_version = session_obj.state_version
r = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
json={"outcome": "applied_success"},
headers=auth_headers,
)
assert r.status_code == 200
await test_db.refresh(session_obj)
assert session_obj.state_version == initial_version + 1, (
"Outcome patch must bump state_version so preview cache is invalidated"
)
# ── outcome propagation into preview bundle ───────────────────────────────────
@pytest.mark.asyncio
async def test_resolution_note_preview_reflects_outcome_after_patch(
client: AsyncClient, test_user, auth_headers, test_db
):
"""End-to-end: preview before outcome != preview after outcome; new preview
bundle includes failure_reason; state_version was bumped between the two.
The LLM is stubbed so the test is deterministic. The stub returns whatever
the user-message content is, which means the captured call args reflect
what the bundle actually contained.
"""
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
distinct_failure_reason = "DISTINCT-FAILURE-REASON-XYZZY-42"
calls_made: list[str] = []
async def fake_generate_text(system_prompt, messages, max_tokens):
user_content = messages[0]["content"]
calls_made.append(user_content)
# Return markdown that includes the user-message bundle verbatim so we
# can assert the bundle shape without inspecting mock internals.
return (
f"## Problem\ntest\n\n## What we confirmed\n(none)\n\n"
f"## Root cause\ntest\n\n## Resolution\nBUNDLE_CONTENT={user_content}",
100,
50,
)
fake_provider = AsyncMock()
fake_provider.generate_text = AsyncMock(side_effect=fake_generate_text)
with patch(
"app.services.resolution_note_generator.get_ai_provider",
return_value=fake_provider,
):
# Preview A — before any outcome recorded (status = "proposed").
r_a = await client.post(
f"/api/v1/ai-sessions/{session_id}/resolution-note/preview",
headers=auth_headers,
)
assert r_a.status_code == 200
markdown_a = r_a.json()["markdown"]
version_a = r_a.json()["state_version"]
assert r_a.json()["from_cache"] is False
# Record an applied_failed outcome with a distinctive reason.
r_patch = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
json={"outcome": "applied_failed", "notes": distinct_failure_reason},
headers=auth_headers,
)
assert r_patch.status_code == 200
# Preview B — must be a cache miss because state_version changed.
r_b = await client.post(
f"/api/v1/ai-sessions/{session_id}/resolution-note/preview",
headers=auth_headers,
)
assert r_b.status_code == 200
markdown_b = r_b.json()["markdown"]
version_b = r_b.json()["state_version"]
assert r_b.json()["from_cache"] is False, (
"Preview after outcome patch must be a cache miss (state_version changed)"
)
# State version increased between the two previews.
assert version_b > version_a, (
f"state_version should have increased; got {version_a}{version_b}"
)
# Markdown differs between the two previews.
assert markdown_a != markdown_b, (
"Regenerated preview after outcome patch should differ from pre-outcome preview"
)
# The bundle passed to the LLM for preview B includes the outcome fields.
assert len(calls_made) == 2, f"Expected 2 LLM calls (one per preview); got {len(calls_made)}"
bundle_b = calls_made[1]
assert "applied_failed" in bundle_b, (
"Bundle for second preview should include 'Outcome status: applied_failed'"
)
assert distinct_failure_reason in bundle_b, (
"Bundle for second preview should include the failure_reason text"
)
# ── Apply endpoint ─────────────────────────────────────────────────────────
@pytest.mark.asyncio
async def test_apply_stamps_applied_at(
client: AsyncClient, test_user, auth_headers, test_db
):
"""POST /apply stamps applied_at and bumps state_version."""
from uuid import UUID
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
result = await test_db.execute(
select(AISession).where(AISession.id == UUID(session_id))
)
session_obj = result.scalar_one()
initial_version = session_obj.state_version
r = await client.post(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/apply",
headers=auth_headers,
)
assert r.status_code == 200, r.text
body = r.json()
assert body["applied_at"] is not None, "applied_at must be set after /apply"
assert body["status"] == "proposed", "status must remain 'proposed' after /apply"
await test_db.refresh(session_obj)
assert session_obj.state_version == initial_version + 1, (
"/apply must bump state_version so preview cache is invalidated"
)
@pytest.mark.asyncio
async def test_apply_is_idempotent(
client: AsyncClient, test_user, auth_headers, test_db
):
"""Second POST /apply returns 200 with applied_at unchanged (no double-bump)."""
from uuid import UUID
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
r1 = await client.post(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/apply",
headers=auth_headers,
)
assert r1.status_code == 200, r1.text
applied_at_first = r1.json()["applied_at"]
result = await test_db.execute(
select(AISession).where(AISession.id == UUID(session_id))
)
session_obj = result.scalar_one()
version_after_first = session_obj.state_version
r2 = await client.post(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/apply",
headers=auth_headers,
)
assert r2.status_code == 200, r2.text
assert r2.json()["applied_at"] == applied_at_first, (
"applied_at must not change on second /apply call"
)
await test_db.refresh(session_obj)
assert session_obj.state_version == version_after_first, (
"state_version must not be bumped a second time on idempotent /apply"
)
@pytest.mark.asyncio
async def test_apply_rejects_non_proposed(
client: AsyncClient, test_user, auth_headers, test_db
):
"""POST /apply returns 409 when fix status is 'applied_success'."""
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
# Advance the fix to a terminal status via the outcome endpoint.
r_outcome = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
headers=auth_headers,
json={"outcome": "applied_success"},
)
assert r_outcome.status_code == 200
r = await client.post(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/apply",
headers=auth_headers,
)
assert r.status_code == 409, r.text
@pytest.mark.asyncio
async def test_apply_rejects_dismissed(
client: AsyncClient, test_user, auth_headers, test_db
):
"""POST /apply returns 409 when fix status is 'dismissed'."""
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
r_outcome = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
headers=auth_headers,
json={"outcome": "dismissed"},
)
assert r_outcome.status_code == 200
r = await client.post(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/apply",
headers=auth_headers,
)
assert r.status_code == 409, r.text
# ── AI outcome proposal: clear / reject ───────────────────────────────────────
async def _make_session_with_fix_and_proposal(test_db, user) -> tuple[str, str]:
"""Create an AISession + fix with a populated ai_outcome_proposal."""
from uuid import UUID as _UUID
session = AISession(
user_id=user["user_data"]["id"],
account_id=user["user_data"]["account_id"],
session_type="chat",
intake_type="free_text",
intake_content={"text": "proposal clear test"},
status="active",
confidence_tier="discovery",
conversation_messages=[],
)
test_db.add(session)
await test_db.flush()
fix = SessionSuggestedFix(
session_id=session.id,
account_id=session.account_id,
title="Flush DNS cache",
description="Run ipconfig /flushdns on the affected host.",
confidence_pct=74,
ai_outcome_proposal={"fix_id": str(session.id), "outcome": "success", "reason": "User confirmed resolved"},
)
test_db.add(fix)
await test_db.commit()
await test_db.refresh(fix)
return str(session.id), str(fix.id)
@pytest.mark.asyncio
async def test_outcome_patch_clears_ai_proposal(
client: AsyncClient, test_user, auth_headers, test_db
):
"""PATCH /outcome clears ai_outcome_proposal regardless of which outcome is written."""
session_id, fix_id = await _make_session_with_fix_and_proposal(test_db, test_user)
# Verify the proposal is set before the patch.
from uuid import UUID
result = await test_db.execute(
select(SessionSuggestedFix).where(SessionSuggestedFix.id == UUID(fix_id))
)
fix_before = result.scalar_one()
assert fix_before.ai_outcome_proposal is not None
r = await client.patch(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/outcome",
headers=auth_headers,
json={"outcome": "applied_success"},
)
assert r.status_code == 200, r.text
body = r.json()
assert body["ai_outcome_proposal"] is None, (
"PATCH /outcome must clear ai_outcome_proposal on any terminal action"
)
@pytest.mark.asyncio
async def test_delete_ai_proposal_clears_field(
client: AsyncClient, test_user, auth_headers, test_db
):
"""DELETE /ai-outcome-proposal clears the field without changing status."""
session_id, fix_id = await _make_session_with_fix_and_proposal(test_db, test_user)
r = await client.delete(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/ai-outcome-proposal",
headers=auth_headers,
)
assert r.status_code == 200, r.text
body = r.json()
assert body["ai_outcome_proposal"] is None, (
"DELETE /ai-outcome-proposal must clear the field"
)
assert body["status"] == "proposed", (
"DELETE /ai-outcome-proposal must not change fix status"
)
@pytest.mark.asyncio
async def test_delete_ai_proposal_when_none_is_idempotent(
client: AsyncClient, test_user, auth_headers, test_db
):
"""DELETE /ai-outcome-proposal returns 200 even when the field is already null."""
session_id, fix_id = await _make_session_with_fix(test_db, test_user)
# Fix created by _make_session_with_fix has ai_outcome_proposal=None.
r = await client.delete(
f"/api/v1/ai-sessions/{session_id}/suggested-fixes/{fix_id}/ai-outcome-proposal",
headers=auth_headers,
)
assert r.status_code == 200, r.text
assert r.json()["ai_outcome_proposal"] is None

View File

@@ -1,91 +0,0 @@
"""Unit tests for the [FIX_OUTCOME] marker parser."""
from __future__ import annotations
from app.services.unified_chat_service import _parse_fix_outcome_marker
def test_parses_success_outcome():
ai = (
"Great news — that confirms the root cause.\n\n"
"[FIX_OUTCOME]\n"
'{"fix_id":"11111111-1111-1111-1111-111111111111",'
'"outcome":"success","reason":"user said the fix worked"}\n'
"[/FIX_OUTCOME]\n"
)
cleaned, parsed = _parse_fix_outcome_marker(ai)
assert "[FIX_OUTCOME]" not in cleaned
assert "confirms the root cause" in cleaned
assert parsed == {
"fix_id": "11111111-1111-1111-1111-111111111111",
"outcome": "success",
"reason": "user said the fix worked",
}
def test_parses_failure_outcome():
ai = (
"[FIX_OUTCOME]\n"
'{"fix_id":"22222222-2222-2222-2222-222222222222",'
'"outcome":"failure","reason":"user reports still broken"}\n'
"[/FIX_OUTCOME]"
)
cleaned, parsed = _parse_fix_outcome_marker(ai)
assert "[FIX_OUTCOME]" not in cleaned
assert parsed["outcome"] == "failure"
def test_missing_marker_returns_none():
ai = "no marker here"
cleaned, parsed = _parse_fix_outcome_marker(ai)
assert cleaned == ai
assert parsed is None
def test_invalid_json_is_dropped():
ai = "[FIX_OUTCOME]\nnot-json\n[/FIX_OUTCOME]"
cleaned, parsed = _parse_fix_outcome_marker(ai)
assert "[FIX_OUTCOME]" not in cleaned
assert parsed is None
def test_unknown_outcome_rejected():
ai = (
"[FIX_OUTCOME]\n"
'{"fix_id":"33333333-3333-3333-3333-333333333333",'
'"outcome":"maybe","reason":"x"}\n'
"[/FIX_OUTCOME]"
)
_, parsed = _parse_fix_outcome_marker(ai)
assert parsed is None
def test_last_block_wins_when_multiple():
ai = (
"[FIX_OUTCOME]\n"
'{"fix_id":"44444444-4444-4444-4444-444444444444",'
'"outcome":"failure","reason":"first"}\n'
"[/FIX_OUTCOME]\n"
"[FIX_OUTCOME]\n"
'{"fix_id":"55555555-5555-5555-5555-555555555555",'
'"outcome":"success","reason":"second"}\n'
"[/FIX_OUTCOME]"
)
cleaned, parsed = _parse_fix_outcome_marker(ai)
assert "[FIX_OUTCOME]" not in cleaned
assert parsed["fix_id"] == "55555555-5555-5555-5555-555555555555"
assert parsed["outcome"] == "success"
def test_parses_partial_outcome():
ai = (
"[FIX_OUTCOME]\n"
'{"fix_id":"66666666-6666-6666-6666-666666666666",'
'"outcome":"partial","reason":"user ran cred clear only"}\n'
"[/FIX_OUTCOME]"
)
_, parsed = _parse_fix_outcome_marker(ai)
assert parsed == {
"fix_id": "66666666-6666-6666-6666-666666666666",
"outcome": "partial",
"reason": "user ran cred clear only",
}

View File

@@ -1,120 +0,0 @@
"""Integration tests for PATCH /ai-sessions/{sid}/suggested-fixes/{fid}/script."""
from __future__ import annotations
import pytest
from httpx import AsyncClient
from sqlalchemy import select
from uuid import UUID, uuid4
from app.models.ai_session import AISession
from app.models.session_suggested_fix import SessionSuggestedFix
async def _make_session_with_fix(
test_db, user, *, status: str = "proposed", with_script: bool = False,
) -> tuple[str, str]:
"""Create a pilot session + suggested fix for tests. Returns (sid, fid)."""
session = AISession(
id=uuid4(),
user_id=user["user_data"]["id"],
account_id=user["user_data"]["account_id"],
session_type="tshoot",
intake_type="psa_ticket",
intake_content={},
title="QA",
status="active",
confidence_tier="exploring",
confidence_score=0.0,
)
test_db.add(session)
await test_db.flush()
fix = SessionSuggestedFix(
id=uuid4(),
session_id=session.id,
account_id=user["user_data"]["account_id"],
title="QA: test fix",
description="desc",
confidence_pct=80,
status=status,
ai_drafted_script="pre-existing" if with_script else None,
)
test_db.add(fix)
await test_db.commit()
return str(session.id), str(fix.id)
@pytest.mark.asyncio
async def test_patch_script_happy_path(
client: AsyncClient, test_user, auth_headers, test_db
):
sid, fid = await _make_session_with_fix(test_db, test_user)
r = await client.patch(
f"/api/v1/ai-sessions/{sid}/suggested-fixes/{fid}/script",
json={"ai_drafted_script": "Write-Host 'hello'"},
headers=auth_headers,
)
assert r.status_code == 200, r.text
body = r.json()
assert body["ai_drafted_script"] == "Write-Host 'hello'"
assert body["applied_at"] is None # draft != apply
assert body["status"] == "proposed"
@pytest.mark.asyncio
async def test_patch_script_bumps_state_version(
client: AsyncClient, test_user, auth_headers, test_db
):
sid, fid = await _make_session_with_fix(test_db, test_user)
before = await test_db.scalar(
select(AISession.state_version).where(AISession.id == UUID(sid))
)
r = await client.patch(
f"/api/v1/ai-sessions/{sid}/suggested-fixes/{fid}/script",
json={"ai_drafted_script": "echo hi"},
headers=auth_headers,
)
assert r.status_code == 200
after = await test_db.scalar(
select(AISession.state_version).where(AISession.id == UUID(sid))
)
assert after == (before or 0) + 1
@pytest.mark.asyncio
async def test_patch_script_rejects_terminal_fix(
client: AsyncClient, test_user, auth_headers, test_db
):
sid, fid = await _make_session_with_fix(test_db, test_user, status="applied_success")
r = await client.patch(
f"/api/v1/ai-sessions/{sid}/suggested-fixes/{fid}/script",
json={"ai_drafted_script": "echo hi"},
headers=auth_headers,
)
assert r.status_code == 409
@pytest.mark.asyncio
async def test_patch_script_rejects_empty_body(
client: AsyncClient, test_user, auth_headers, test_db
):
sid, fid = await _make_session_with_fix(test_db, test_user)
r = await client.patch(
f"/api/v1/ai-sessions/{sid}/suggested-fixes/{fid}/script",
json={"ai_drafted_script": ""},
headers=auth_headers,
)
assert r.status_code == 422 # pydantic min_length=1
@pytest.mark.asyncio
async def test_patch_script_404_on_wrong_session(
client: AsyncClient, test_user, auth_headers, test_db
):
_, fid = await _make_session_with_fix(test_db, test_user)
wrong_sid = str(uuid4())
r = await client.patch(
f"/api/v1/ai-sessions/{wrong_sid}/suggested-fixes/{fid}/script",
json={"ai_drafted_script": "echo hi"},
headers=auth_headers,
)
assert r.status_code == 404

View File

@@ -1,96 +0,0 @@
from __future__ import annotations
import uuid
import pytest
from sqlalchemy import select
from app.models.device_type import DeviceType
from app.models.user import User
from app.core.service_account import PLATFORM_ACCOUNT_ID
async def _login_headers(client, email: str, password: str) -> dict[str, str]:
response = await client.post(
"/api/v1/auth/login/json",
json={"email": email, "password": password},
)
assert response.status_code == 200
token = response.json()["access_token"]
return {"Authorization": f"Bearer {token}"}
@pytest.mark.asyncio
async def test_device_types_include_platform_and_account_custom(client, test_db, auth_headers, test_user):
result = await test_db.execute(select(User).where(User.email == test_user["email"]))
user = result.scalar_one()
test_db.add(
DeviceType(
id=uuid.uuid4(),
slug="platform-router",
label="Platform Router",
category="network",
is_system=True,
account_id=PLATFORM_ACCOUNT_ID,
sort_order=0,
)
)
await test_db.commit()
create_response = await client.post(
"/api/v1/device-types/",
json={
"slug": "tenant-appliance",
"label": "Tenant Appliance",
"category": "network",
"sort_order": 3,
},
headers=auth_headers,
)
assert create_response.status_code == 201
assert create_response.json()["account_id"] == str(user.account_id)
list_response = await client.get("/api/v1/device-types/", headers=auth_headers)
assert list_response.status_code == 200
payload = list_response.json()
slugs = {item["slug"] for item in payload}
assert "platform-router" in slugs
assert "tenant-appliance" in slugs
@pytest.mark.asyncio
async def test_network_diagrams_are_account_scoped(client, test_db, auth_headers, test_user):
other_user = {
"email": "other-network@example.com",
"password": "TestPassword123!",
"name": "Other Network User",
}
register_response = await client.post("/api/v1/auth/register", json=other_user)
assert register_response.status_code in (200, 201)
other_headers = await _login_headers(client, other_user["email"], other_user["password"])
owner_result = await test_db.execute(select(User).where(User.email == test_user["email"]))
owner = owner_result.scalar_one()
create_response = await client.post(
"/api/v1/network-diagrams/",
json={
"name": "HQ Core",
"client_name": "Acme",
"description": "Primary topology",
"nodes": [],
"edges": [],
},
headers=auth_headers,
)
assert create_response.status_code == 201
diagram = create_response.json()
assert diagram["account_id"] == str(owner.account_id)
own_get = await client.get(f"/api/v1/network-diagrams/{diagram['id']}", headers=auth_headers)
assert own_get.status_code == 200
other_get = await client.get(f"/api/v1/network-diagrams/{diagram['id']}", headers=other_headers)
assert other_get.status_code == 404

View File

@@ -1,277 +0,0 @@
"""API + service tests for Phase 5 inline Script Generator integration.
Covers:
- TemplateExtractionService: well-formed, fallback on bad output, missing-key fallback.
- /suggested-fixes/{fix_id}/decision side effects:
* one_off returns rendered_script, no draft_templates row.
* draft_template returns rendered_script + draft_template_id, draft persisted.
* build_template returns redirect_path.
* dismissed (Phase 3) still works.
- 400 when ai_drafted_script is missing for a non-template fix.
"""
from __future__ import annotations
from unittest.mock import AsyncMock, patch
import pytest
from httpx import AsyncClient
from sqlalchemy import select
from app.api.endpoints.session_suggested_fixes import _clear_preview_cache_for_tests
from app.models.ai_session import AISession
from app.models.draft_template import DraftTemplate
from app.models.session_suggested_fix import SessionSuggestedFix
from app.services.template_extraction_service import (
_fallback,
_parse_response,
extract_parameters,
)
@pytest.fixture(autouse=True)
def _isolate_preview_cache():
_clear_preview_cache_for_tests()
yield
_clear_preview_cache_for_tests()
async def _make_session_with_fix(
test_db, user, *, with_template_id: bool = False, with_drafted_script: bool = True,
) -> tuple[AISession, SessionSuggestedFix]:
session = AISession(
user_id=user["user_data"]["id"],
account_id=user["user_data"]["account_id"],
session_type="chat",
intake_type="free_text",
intake_content={"text": "phase 5 test"},
status="active",
confidence_tier="discovery",
conversation_messages=[],
)
test_db.add(session)
await test_db.flush()
fix = SessionSuggestedFix(
session_id=session.id,
account_id=session.account_id,
title="Reset cached creds",
description="Clearing the cached credential...",
confidence_pct=85,
ai_drafted_script=(
'cmdkey /delete:"outlook.office365.com"\n'
'Restart-Process -Name OUTLOOK'
) if with_drafted_script else None,
ai_drafted_parameters={"target_user": "jsmith"} if with_drafted_script else None,
)
test_db.add(fix)
await test_db.commit()
await test_db.refresh(session)
await test_db.refresh(fix)
return session, fix
# ── TemplateExtractionService: parse + fallback ───────────────────────────
class TestParseResponse:
def test_well_formed(self):
raw = (
'{"parameters": [{"key":"host","label":"Host","type":"text",'
'"inferred_from":"session fact"}],'
'"templated_body":"Get-Service -ComputerName {{ host }}"}'
)
result = _parse_response(raw)
assert result is not None
assert len(result["parameters"]) == 1
assert result["parameters"][0]["key"] == "host"
assert result["templated_body"].endswith("{{ host }}")
def test_strips_fences(self):
raw = '```json\n{"parameters": [], "templated_body": "x"}\n```'
result = _parse_response(raw)
assert result is not None and result["parameters"] == []
def test_invalid_key_dropped(self):
# Capital letters and dashes in key names violate snake_case — drop.
raw = (
'{"parameters":[{"key":"BadKey-Name","type":"text"}],'
'"templated_body":"x"}'
)
result = _parse_response(raw)
assert result is not None and result["parameters"] == []
def test_unknown_type_falls_back_to_text(self):
raw = (
'{"parameters":[{"key":"x","type":"weird"}],"templated_body":"x"}'
)
result = _parse_response(raw)
assert result is not None and result["parameters"][0]["type"] == "text"
def test_malformed_json_returns_none(self):
assert _parse_response("not json") is None
def test_non_dict_returns_none(self):
assert _parse_response('["a","b"]') is None
@pytest.mark.asyncio
async def test_extract_parameters_round_trip_failure_uses_fallback():
"""Templated_body referencing an undeclared placeholder triggers fallback."""
fake_provider = AsyncMock()
fake_provider.generate_json = AsyncMock(return_value=(
# Declares parameter `host` but the body references `port` too.
'{"parameters":[{"key":"host","label":"Host","type":"text"}],'
'"templated_body":"Get-Service -ComputerName {{ host }} -Port {{ port }}"}',
100, 50,
))
with patch(
"app.services.template_extraction_service.get_ai_provider",
return_value=fake_provider,
):
result = await extract_parameters(
script_body="Get-Service -ComputerName srv01 -Port 8080",
)
fb = _fallback("Get-Service -ComputerName srv01 -Port 8080")
assert result == fb
@pytest.mark.asyncio
async def test_extract_parameters_llm_exception_uses_fallback():
fake_provider = AsyncMock()
fake_provider.generate_json = AsyncMock(side_effect=RuntimeError("boom"))
with patch(
"app.services.template_extraction_service.get_ai_provider",
return_value=fake_provider,
):
result = await extract_parameters(script_body="echo hello")
assert result == _fallback("echo hello")
# ── Decision endpoint: one_off ─────────────────────────────────────────────
@pytest.mark.asyncio
async def test_one_off_returns_rendered_script_no_draft(
client: AsyncClient, test_user, auth_headers, test_db
):
session, fix = await _make_session_with_fix(test_db, test_user)
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/suggested-fixes/{fix.id}/decision",
headers=auth_headers,
json={"decision": "one_off"},
)
assert r.status_code == 200
body = r.json()
assert body["user_decision"] == "one_off"
assert body["rendered_script"] is not None
assert "cmdkey" in body["rendered_script"]
assert body["draft_template_id"] is None
assert body["redirect_path"] is None
# No draft_templates row should have been created.
rows = (
await test_db.execute(select(DraftTemplate).where(DraftTemplate.source_session_id == session.id))
).scalars().all()
assert list(rows) == []
# ── Decision endpoint: draft_template ─────────────────────────────────────
@pytest.mark.asyncio
async def test_draft_template_creates_draft_with_extracted_params(
client: AsyncClient, test_user, auth_headers, test_db
):
session, fix = await _make_session_with_fix(test_db, test_user)
fake_provider = AsyncMock()
fake_provider.generate_json = AsyncMock(return_value=(
'{"parameters":[{"key":"target_user","label":"Target User","type":"text",'
'"inferred_from":"session fact"}],'
'"templated_body":"cmdkey /delete:\\"outlook.office365.com\\"\\n'
'Restart-Process -Name OUTLOOK"}',
80, 60,
))
with patch(
"app.services.template_extraction_service.get_ai_provider",
return_value=fake_provider,
):
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/suggested-fixes/{fix.id}/decision",
headers=auth_headers,
json={"decision": "draft_template"},
)
assert r.status_code == 200
body = r.json()
assert body["user_decision"] == "draft_template"
assert body["rendered_script"] is not None
assert body["draft_template_id"] is not None
assert body["redirect_path"] is None
drafts = (
await test_db.execute(select(DraftTemplate).where(DraftTemplate.source_session_id == session.id))
).scalars().all()
drafts = list(drafts)
assert len(drafts) == 1
draft = drafts[0]
assert draft.status == "pending"
assert draft.proposed_name == fix.title
proposed = draft.proposed_parameters.get("parameters") if isinstance(draft.proposed_parameters, dict) else None
assert isinstance(proposed, list) and len(proposed) == 1
assert proposed[0]["key"] == "target_user"
# ── Decision endpoint: build_template ─────────────────────────────────────
@pytest.mark.asyncio
async def test_build_template_returns_redirect_path(
client: AsyncClient, test_user, auth_headers, test_db
):
session, fix = await _make_session_with_fix(test_db, test_user)
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/suggested-fixes/{fix.id}/decision",
headers=auth_headers,
json={"decision": "build_template"},
)
assert r.status_code == 200
body = r.json()
assert body["redirect_path"] is not None
assert str(session.id) in body["redirect_path"]
assert str(fix.id) in body["redirect_path"]
# ── Decision endpoint: 400 when no drafted script ─────────────────────────
@pytest.mark.asyncio
async def test_one_off_without_drafted_script_returns_400(
client: AsyncClient, test_user, auth_headers, test_db
):
"""A template-matched fix takes the dedicated /scripts/generate path; trying
to one_off it via this endpoint without an ai_drafted_script must surface
a clear client-error, not silently render nothing."""
session, fix = await _make_session_with_fix(test_db, test_user, with_drafted_script=False)
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/suggested-fixes/{fix.id}/decision",
headers=auth_headers,
json={"decision": "one_off"},
)
assert r.status_code == 400
assert "ai_drafted_script" in r.json()["detail"]
# ── Decision endpoint: edited script overrides ai_drafted_script ──────────
@pytest.mark.asyncio
async def test_edited_script_overrides_ai_drafted(
client: AsyncClient, test_user, auth_headers, test_db
):
session, fix = await _make_session_with_fix(test_db, test_user)
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/suggested-fixes/{fix.id}/decision",
headers=auth_headers,
json={
"decision": "one_off",
"edited_script": "Get-Service -Name Dnscache",
},
)
assert r.status_code == 200
assert r.json()["rendered_script"] == "Get-Service -Name Dnscache"

View File

@@ -1,295 +0,0 @@
"""API tests for the FlowPilot Phase 6 post-resolve templatization flow.
Covers:
- GET /api/v1/draft-templates list with pending_only filter.
- POST /{id}/accept → creates script_templates row with provenance fields,
marks draft accepted + promoted_template_id set.
- POST /{id}/reject → marks rejected.
- 409 when accepting or rejecting a non-pending draft.
- Category validation (400 on unknown category_id).
- GET/PATCH /accounts/me/preferences round-trip.
"""
from __future__ import annotations
from datetime import datetime, timezone
from uuid import UUID
import pytest
from httpx import AsyncClient
from sqlalchemy import select
from app.models.account_settings import AccountSettings
from app.models.ai_session import AISession
from app.models.draft_template import DraftTemplate
from app.models.script_template import ScriptCategory, ScriptTemplate
async def _make_draft(
test_db,
user,
*,
proposed_name: str = "Test draft",
status_: str = "pending",
with_psa_ticket: bool = False,
) -> tuple[AISession, DraftTemplate]:
session = AISession(
user_id=user["user_data"]["id"],
account_id=user["user_data"]["account_id"],
session_type="chat",
intake_type="free_text",
intake_content={"text": "phase 6 test"},
status="resolved",
confidence_tier="discovery",
conversation_messages=[],
psa_ticket_id="48307" if with_psa_ticket else None,
)
test_db.add(session)
await test_db.flush()
draft = DraftTemplate(
account_id=user["user_data"]["account_id"],
source_session_id=session.id,
source_user_id=user["user_data"]["id"],
script_body='Do-Something -Target {{ target_name }}\n',
proposed_parameters={
"parameters": [
{"key": "target_name", "label": "Target Name", "type": "text"},
],
},
proposed_name=proposed_name,
status=status_,
)
test_db.add(draft)
await test_db.commit()
await test_db.refresh(draft)
return session, draft
async def _make_category(test_db) -> ScriptCategory:
cat = ScriptCategory(
name="Phase 6 Test Category",
slug=f"phase-6-test-{datetime.now(timezone.utc).timestamp()}",
description="test",
is_active=True,
)
test_db.add(cat)
await test_db.commit()
await test_db.refresh(cat)
return cat
# ── List ─────────────────────────────────────────────────────────────────
@pytest.mark.asyncio
async def test_list_pending_only_default(
client: AsyncClient, test_user, auth_headers, test_db
):
await _make_draft(test_db, test_user, proposed_name="pending-a", status_="pending")
await _make_draft(test_db, test_user, proposed_name="accepted-b", status_="accepted")
r = await client.get("/api/v1/draft-templates", headers=auth_headers)
assert r.status_code == 200
drafts = r.json()["drafts"]
names = {d["proposed_name"] for d in drafts}
assert "pending-a" in names
assert "accepted-b" not in names
@pytest.mark.asyncio
async def test_list_with_pending_only_false_includes_all(
client: AsyncClient, test_user, auth_headers, test_db
):
await _make_draft(test_db, test_user, proposed_name="pending-c", status_="pending")
await _make_draft(test_db, test_user, proposed_name="rejected-d", status_="rejected")
r = await client.get(
"/api/v1/draft-templates?pending_only=false", headers=auth_headers,
)
assert r.status_code == 200
names = {d["proposed_name"] for d in r.json()["drafts"]}
assert {"pending-c", "rejected-d"}.issubset(names)
# ── Accept ───────────────────────────────────────────────────────────────
@pytest.mark.asyncio
async def test_accept_creates_template_with_provenance(
client: AsyncClient, test_user, auth_headers, test_db
):
session, draft = await _make_draft(test_db, test_user, with_psa_ticket=True)
cat = await _make_category(test_db)
r = await client.post(
f"/api/v1/draft-templates/{draft.id}/accept",
headers=auth_headers,
json={
"name": "Do Something On Target",
"category_id": str(cat.id),
"description": "promoted from phase 6 test",
"parameters_schema": {
"parameters": [
{"key": "target_name", "label": "Target", "field_type": "text"},
],
},
},
)
assert r.status_code == 201
body = r.json()
assert body["draft_id"] == str(draft.id)
assert body["promoted_template_id"] is not None
assert body["template_slug"] == "do-something-on-target"
# Draft row is now accepted with the promoted template ID set.
await test_db.refresh(draft)
assert draft.status == "accepted"
assert draft.promoted_template_id == UUID(body["promoted_template_id"])
assert draft.resolved_at is not None
# New template row exists with provenance fields populated.
tpl_result = await test_db.execute(
select(ScriptTemplate).where(ScriptTemplate.id == UUID(body["promoted_template_id"]))
)
tpl = tpl_result.scalar_one()
assert tpl.source_session_id == session.id
assert tpl.source_user_id == UUID(test_user["user_data"]["id"])
assert tpl.source_ticket_ref == "CW #48307"
assert tpl.script_body == draft.script_body # edited_body was not supplied
@pytest.mark.asyncio
async def test_accept_with_edited_body_overrides_draft(
client: AsyncClient, test_user, auth_headers, test_db
):
_, draft = await _make_draft(test_db, test_user)
cat = await _make_category(test_db)
r = await client.post(
f"/api/v1/draft-templates/{draft.id}/accept",
headers=auth_headers,
json={
"name": "Edited Body Test",
"category_id": str(cat.id),
"parameters_schema": {"parameters": []},
"edited_body": 'Write-Host "edited final version"\n',
},
)
assert r.status_code == 201
tpl = (
await test_db.execute(
select(ScriptTemplate).where(
ScriptTemplate.id == UUID(r.json()["promoted_template_id"])
)
)
).scalar_one()
assert tpl.script_body == 'Write-Host "edited final version"\n'
@pytest.mark.asyncio
async def test_accept_rejects_unknown_category(
client: AsyncClient, test_user, auth_headers, test_db
):
_, draft = await _make_draft(test_db, test_user)
bogus_cat = "00000000-0000-0000-0000-000000000000"
r = await client.post(
f"/api/v1/draft-templates/{draft.id}/accept",
headers=auth_headers,
json={
"name": "x",
"category_id": bogus_cat,
"parameters_schema": {"parameters": []},
},
)
assert r.status_code == 400
@pytest.mark.asyncio
async def test_accept_already_accepted_returns_409(
client: AsyncClient, test_user, auth_headers, test_db
):
_, draft = await _make_draft(test_db, test_user, status_="accepted")
cat = await _make_category(test_db)
r = await client.post(
f"/api/v1/draft-templates/{draft.id}/accept",
headers=auth_headers,
json={
"name": "x",
"category_id": str(cat.id),
"parameters_schema": {"parameters": []},
},
)
assert r.status_code == 409
# ── Reject ───────────────────────────────────────────────────────────────
@pytest.mark.asyncio
async def test_reject_marks_draft_rejected(
client: AsyncClient, test_user, auth_headers, test_db
):
_, draft = await _make_draft(test_db, test_user)
r = await client.post(
f"/api/v1/draft-templates/{draft.id}/reject", headers=auth_headers,
)
assert r.status_code == 200
assert r.json()["status"] == "rejected"
await test_db.refresh(draft)
assert draft.status == "rejected"
assert draft.resolved_at is not None
@pytest.mark.asyncio
async def test_reject_already_accepted_returns_409(
client: AsyncClient, test_user, auth_headers, test_db
):
_, draft = await _make_draft(test_db, test_user, status_="accepted")
r = await client.post(
f"/api/v1/draft-templates/{draft.id}/reject", headers=auth_headers,
)
assert r.status_code == 409
# ── Preferences ──────────────────────────────────────────────────────────
@pytest.mark.asyncio
async def test_get_preferences_empty_by_default(
client: AsyncClient, auth_headers,
):
r = await client.get("/api/v1/accounts/me/preferences", headers=auth_headers)
assert r.status_code == 200
assert r.json()["preferences"] == {}
@pytest.mark.asyncio
async def test_patch_preferences_merges_keys(
client: AsyncClient, test_user, auth_headers, test_db
):
# First write: one key.
r = await client.patch(
"/api/v1/accounts/me/preferences",
headers=auth_headers,
json={"preferences": {"templatize_prompt_enabled": False}},
)
assert r.status_code == 200
assert r.json()["preferences"]["templatize_prompt_enabled"] is False
# Second write: different key — first must be preserved (merge semantics).
r2 = await client.patch(
"/api/v1/accounts/me/preferences",
headers=auth_headers,
json={"preferences": {"cw_resolved_status_id": 42}},
)
assert r2.status_code == 200
prefs = r2.json()["preferences"]
assert prefs["templatize_prompt_enabled"] is False
assert prefs["cw_resolved_status_id"] == 42
# Stored on the account_settings row.
stored = (
await test_db.execute(
select(AccountSettings.preferences).where(
AccountSettings.account_id == UUID(test_user["user_data"]["account_id"])
)
)
).scalar_one()
assert stored["templatize_prompt_enabled"] is False
assert stored["cw_resolved_status_id"] == 42

View File

@@ -1,184 +0,0 @@
"""Guardrail: literal output payloads must not live in any LLM system prompt.
This test exists because the same anti-pattern bit us twice in the same
day: a worked example with literal content (Outlook + jsmith + literal
JSON; full DNS troubleshooting tree) sitting inside a `*_PROMPT` constant
caused Claude to recite that content on unrelated tickets, making the
task lane look like it was leaking previous-session data.
The fix is structural: every output example in a system prompt must use
`<placeholder>` or `<...>` syntax, never literal field values, command
names, hostnames, or usernames that the model could parrot. Format
examples that need real-looking content live in few-shot messages
(separate file, separate code path, model treats them as past behavior),
not in system prompts.
Failure messages here name the constant + line; fix by replacing the
literal payload with a placeholder schema, or by moving the example
out of the system prompt entirely.
See CLAUDE.md → Critical Lessons → "Don't put literal payloads in
system prompts" for the longer rationale.
"""
from __future__ import annotations
import importlib
import inspect
import pkgutil
import re
from typing import Iterator
import pytest
# Modules to scan. We deliberately import the modules (not just walk source
# files) so we get the actual string values of `*_PROMPT` constants — which
# may be assembled from concat / .format() / f-strings.
_MODULE_PACKAGES = ("app.services", "app.core")
def _iter_prompt_constants() -> Iterator[tuple[str, str, str]]:
"""Yield (module_name, constant_name, value) for every uppercase string
constant whose name ends in `_PROMPT` (or `_SCHEMA`/`_PROTOCOL`/`_FORMAT`
— same anti-pattern risk).
Skips modules that fail to import to keep the test resilient when an
individual module has unrelated breakage.
"""
suffixes = ("_PROMPT", "_SCHEMA", "_PROTOCOL", "_FORMAT", "_CONTEXT")
for pkg_name in _MODULE_PACKAGES:
pkg = importlib.import_module(pkg_name)
for mod_info in pkgutil.iter_modules(pkg.__path__, prefix=f"{pkg_name}."):
try:
mod = importlib.import_module(mod_info.name)
except Exception:
continue
for name, value in inspect.getmembers(mod):
if not name.isupper() or not name.endswith(suffixes):
continue
if not isinstance(value, str):
continue
yield mod_info.name, name, value
# ── The forbidden patterns ──────────────────────────────────────────────────
# A literal username pattern that Claude has historically parroted across
# unrelated tickets. The list isn't exhaustive — it's the exact strings
# we've seen leak. Add to it if a new one shows up in production.
_FORBIDDEN_LITERAL_TOKENS: tuple[str, ...] = (
"jsmith", # leaked from an Outlook/AD example
"DC01", # leaked from an intake-form example
"ADSync", # leaked from a commands-array example
"Dnscache", # leaked from a DNS troubleshooting tree example
"google.com", # leaked from a DNS troubleshooting tree example
"Outlook keeps", "Teams drops", # specific phrasings from a worked Outlook/WiFi example
)
# Marker-with-payload patterns. A `[QUESTIONS]\n[{...JSON with real field values...}]`
# block in a prompt is the highest-risk shape — the model treats it as a
# canonical response template. We allow placeholder content (anything inside
# angle brackets `<...>` is treated as a placeholder, not a literal).
#
# Restrictions on the regex (to avoid false positives where the marker name
# appears in prose like "include [QUESTIONS] markers"):
# - opening tag must be at start of string OR preceded by newline/whitespace
# AND followed by newline+JSON-ish content
# - block content must START with `[` or `{` after optional whitespace,
# so prose blocks (like the closing-tag-distance regex match across
# markdown headings) are excluded
_MARKER_BLOCK_RE = re.compile(
r"(?:^|\n)\[(QUESTIONS|ACTIONS|SUGGEST_FIX|FIX_OUTCOME|PROMOTE|FORK|TREE_UPDATE|STEPS_UPDATE|INTAKE_FORM|METADATA|DELTA)\]"
r"\s*\n" # forced newline before content
r"(\s*[\[{][\s\S]*?)" # content must start with [ or {
r"\s*\n\[/\1\]"
)
# Heuristic: only flag JSON VALUES, not JSON KEYS. Keys are followed by `:`,
# values come after `: ` (object value) or are bare strings inside an array.
# The shape we're defending against is `{"text": "Is this user on a laptop?"}` —
# the value `"Is this user on a laptop?"` is a literal payload the model will
# recite. Keys like `"text"` are part of the schema and must stay literal.
#
# Matches a quoted string that has at least 3 chars, no angle brackets, and
# is followed by a JSON value-terminator (`,` `]` `}`) — i.e. NOT followed
# by `:` (which would mark it as a key).
_QUOTED_VALUE_RE = re.compile(
r'"([^"<>][^"<>]{2,}?)"\s*(?=[,\]\}])'
)
# Substrings that, if PRESENT in the candidate value, indicate it's a
# placeholder marker rather than literal output. Be strict — broad markers
# like "?" alone would whitelist any sentence ending in a question mark,
# defeating the test's purpose.
_PLACEHOLDER_HINTS = ("...", "snake_case", "kebab-case", "<", "TODO")
# Schema enum-like values that are part of the format spec, not parrotable text.
_ALLOWED_ENUM_VALUES = frozenset({
"text", "password", "select", "boolean", "number", "textarea", "multi_text",
"powershell", "bash", "cmd", "python",
"question", "diagnostic_check", "user_note", "ai_synthesis",
"decision", "action", "solution", "procedure_step", "section_header", "procedure_end",
"step", "warning",
})
def _block_has_literal_payload(block_body: str) -> tuple[bool, str | None]:
"""Return (True, offending_string) if the marker block looks like literal output."""
for m in _QUOTED_VALUE_RE.finditer(block_body):
s = m.group(1).strip()
if not s:
continue
# Pure placeholder hints — accept.
if any(h in s for h in _PLACEHOLDER_HINTS):
continue
# Pipe-separated enum like `text|password|select` — schema spec.
if "|" in s:
continue
# Single-word enum value we explicitly allow.
if s in _ALLOWED_ENUM_VALUES:
continue
# JSON ellipsis-style placeholders, ".." etc.
if all(c in "._" for c in s):
continue
return True, s
return False, None
# ── Tests ──────────────────────────────────────────────────────────────────
def test_no_known_leaked_literal_tokens_in_prompts() -> None:
"""Constants must not contain strings the model has historically parroted.
Adding a new entry to _FORBIDDEN_LITERAL_TOKENS after a production leak is
the right way to extend coverage — keep this list as the audit trail.
"""
failures: list[str] = []
for module_name, const_name, value in _iter_prompt_constants():
for token in _FORBIDDEN_LITERAL_TOKENS:
if token in value:
failures.append(
f"{module_name}.{const_name} contains forbidden literal token "
f"{token!r} — replace with a <placeholder>. See CLAUDE.md → "
f"'Don't put literal payloads in system prompts'."
)
assert not failures, "\n".join(failures)
def test_marker_blocks_in_prompts_use_placeholders_not_literal_payloads() -> None:
"""Every marker block in a system prompt must contain placeholders only.
A block like `[QUESTIONS]\\n[{"text": "Is this user on a laptop or desktop?"}]\\n[/QUESTIONS]`
will be recited verbatim by Claude on unrelated tickets. Use angle-bracket
placeholders instead: `[{"text": "<one short, specific question>"}]`.
"""
failures: list[str] = []
for module_name, const_name, value in _iter_prompt_constants():
for m in _MARKER_BLOCK_RE.finditer(value):
marker = m.group(1)
body = m.group(2)
has_literal, offender = _block_has_literal_payload(body)
if has_literal:
failures.append(
f"{module_name}.{const_name}: [{marker}] block contains literal "
f"payload string {offender!r}. Replace with a <placeholder>. "
f"See CLAUDE.md → 'Don't put literal payloads in system prompts'."
)
assert not failures, "\n".join(failures)

View File

@@ -1,55 +0,0 @@
# backend/tests/test_psa_tickets.py
"""Routing and auth tests for new ticket management endpoints."""
import pytest
@pytest.mark.asyncio
async def test_create_ticket_requires_auth(client):
"""POST /tickets returns 401 without auth."""
response = await client.post(
"/api/v1/integrations/psa/tickets",
json={
"summary": "Test", "company_id": 1, "board_id": 1,
"status_id": 1, "priority_id": 1
},
)
assert response.status_code == 401
@pytest.mark.asyncio
async def test_list_resources_requires_auth(client):
response = await client.get("/api/v1/integrations/psa/tickets/1/resources")
assert response.status_code == 401
@pytest.mark.asyncio
async def test_search_tickets_returns_paginated_shape(client, auth_headers):
"""search endpoint returns TicketListResponse shape when no PSA connected."""
response = await client.get(
"/api/v1/integrations/psa/tickets/search",
headers=auth_headers,
)
# No PSA connection → 400 or 502; with PSA → 200
assert response.status_code in (200, 400, 502)
if response.status_code == 200:
data = response.json()
assert "items" in data
assert "total" in data
assert "page" in data
@pytest.mark.asyncio
async def test_update_status_requires_auth(client):
response = await client.patch(
"/api/v1/integrations/psa/tickets/1/status?status_id=5"
)
assert response.status_code == 401
@pytest.mark.asyncio
async def test_ai_parse_requires_auth(client):
response = await client.post(
"/api/v1/integrations/psa/tickets/ai-parse",
json={"prompt": "New ticket for Acme"},
)
assert response.status_code == 401

View File

@@ -1,281 +0,0 @@
"""API tests for the FlowPilot Phase 4 Resolve + Escalate writeback flow.
Covers:
- Local-only path when no PSA ticket is linked (markdown stored, status flipped,
no provider call).
- PSA post happy path (provider mocked).
- Status transition verified by re-fetch (happy path).
- Status verification failure surfaces 502 with a clear error body.
- 409 when trying to resolve an already-resolved session / escalate an
already-escalated one.
- Escalation parallel to resolution (same structure).
"""
from __future__ import annotations
import uuid
from unittest.mock import AsyncMock, patch
import pytest
from httpx import AsyncClient
from app.api.endpoints.session_suggested_fixes import _clear_preview_cache_for_tests
from app.models.account_settings import AccountSettings
from app.models.ai_session import AISession
from app.models.psa_connection import PsaConnection
from app.services.psa.types import NoteType, PSANote, PSATicket
@pytest.fixture(autouse=True)
def _isolate_preview_cache():
_clear_preview_cache_for_tests()
yield
_clear_preview_cache_for_tests()
async def _make_session(test_db, user, *, with_psa: bool = False) -> AISession:
session_kwargs: dict = dict(
user_id=user["user_data"]["id"],
account_id=user["user_data"]["account_id"],
session_type="chat",
intake_type="free_text",
intake_content={"text": "phase 4 test"},
status="active",
confidence_tier="discovery",
conversation_messages=[],
)
if with_psa:
# Fake connection — provider factory is patched in each test so we
# never touch a real CW instance.
from app.services.psa.encryption import encrypt_credentials
conn = PsaConnection(
account_id=user["user_data"]["account_id"],
provider="connectwise",
site_url="https://fake.cw.local",
company_id="TEST",
credentials_encrypted=encrypt_credentials({"public_key": "x", "private_key": "y"}),
is_active=True,
)
test_db.add(conn)
await test_db.flush()
session_kwargs["psa_connection_id"] = conn.id
session_kwargs["psa_ticket_id"] = "48291"
session = AISession(**session_kwargs)
test_db.add(session)
await test_db.commit()
await test_db.refresh(session)
return session
# ── Resolve: local-only ────────────────────────────────────────────────────
@pytest.mark.asyncio
async def test_resolve_local_only_when_no_psa_ticket(
client: AsyncClient, test_user, auth_headers, test_db
):
session = await _make_session(test_db, test_user, with_psa=False)
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/resolution-note/post",
headers=auth_headers,
json={"markdown": "## Problem\nx\n\n## Resolution\nfixed"},
)
assert r.status_code == 200
body = r.json()
assert body["outcome"] == "resolved_local"
assert body["session_status"] == "resolved"
assert body["external_id"] is None
await test_db.refresh(session)
assert session.status == "resolved"
assert session.resolution_note_markdown == "## Problem\nx\n\n## Resolution\nfixed"
assert session.resolved_at is not None
# ── Resolve: happy path (PSA post + status transition verified) ────────────
@pytest.mark.asyncio
async def test_resolve_posts_to_psa_and_verifies_status(
client: AsyncClient, test_user, auth_headers, test_db
):
session = await _make_session(test_db, test_user, with_psa=True)
# Configure the Resolved status ID so the transition is attempted.
await AccountSettings.set_setting(
test_db, session.account_id, "cw_resolved_status_id", 42,
)
await test_db.commit()
# Mock provider: post_note returns a fake note, update_ticket_status
# returns anything, get_ticket returns the new status_id (matches 42
# → verification passes).
fake_provider = AsyncMock()
fake_provider.post_note = AsyncMock(return_value=PSANote(
id="cw-note-777", text="...", note_type=NoteType.RESOLUTION, created_at=None,
))
fake_provider.update_ticket_status = AsyncMock(return_value=None)
fake_provider.get_ticket = AsyncMock(return_value=PSATicket(
id="48291", summary="t", status_id=42, status_name="Resolved",
))
with patch(
"app.services.psa_writeback_service.get_provider_for_connection",
return_value=fake_provider,
):
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/resolution-note/post",
headers=auth_headers,
json={"markdown": "## Problem\nx\n\n## Resolution\nfixed"},
)
assert r.status_code == 200
body = r.json()
assert body["outcome"] == "resolved"
assert body["external_id"] == "cw-note-777"
assert body["verified_status_id"] == 42
assert body["verified_status_name"] == "Resolved"
# post_note must have used the RESOLUTION note type
fake_provider.post_note.assert_awaited_once()
called_note_type = fake_provider.post_note.await_args.kwargs["note_type"]
assert called_note_type == NoteType.RESOLUTION
# ── Resolve: status verification failure → 502 ──────────────────────────────
@pytest.mark.asyncio
async def test_resolve_surfaces_status_verification_failure(
client: AsyncClient, test_user, auth_headers, test_db
):
"""CW silently rejecting a status change must NOT report silent success."""
session = await _make_session(test_db, test_user, with_psa=True)
await AccountSettings.set_setting(
test_db, session.account_id, "cw_resolved_status_id", 42,
)
await test_db.commit()
fake_provider = AsyncMock()
fake_provider.post_note = AsyncMock(return_value=PSANote(
id="cw-note-alpha", text="...", note_type=NoteType.RESOLUTION, created_at=None,
))
fake_provider.update_ticket_status = AsyncMock(return_value=None)
# get_ticket returns a DIFFERENT status_id — the transition didn't stick.
fake_provider.get_ticket = AsyncMock(return_value=PSATicket(
id="48291", summary="t", status_id=99, status_name="In Progress",
))
with patch(
"app.services.psa_writeback_service.get_provider_for_connection",
return_value=fake_provider,
):
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/resolution-note/post",
headers=auth_headers,
json={"markdown": "## Problem\nx\n\n## Resolution\nfixed"},
)
assert r.status_code == 502
assert "did not verify" in r.json()["detail"]
# ── Resolve: skip status transition when not configured ────────────────────
@pytest.mark.asyncio
async def test_resolve_skips_status_transition_when_unconfigured(
client: AsyncClient, test_user, auth_headers, test_db
):
"""No cw_resolved_status_id setting → post the note, don't touch status, not an error."""
session = await _make_session(test_db, test_user, with_psa=True)
# Deliberately no AccountSettings row.
fake_provider = AsyncMock()
fake_provider.post_note = AsyncMock(return_value=PSANote(
id="cw-note-beta", text="...", note_type=NoteType.RESOLUTION, created_at=None,
))
with patch(
"app.services.psa_writeback_service.get_provider_for_connection",
return_value=fake_provider,
):
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/resolution-note/post",
headers=auth_headers,
json={"markdown": "## Problem\nx\n\n## Resolution\nfixed"},
)
assert r.status_code == 200
body = r.json()
assert body["outcome"] == "resolved"
assert body["verified_status_id"] is None
assert body["status_transition_skipped_reason"] is not None
fake_provider.update_ticket_status.assert_not_called()
fake_provider.get_ticket.assert_not_called()
# ── Resolve: already-resolved → 409 ─────────────────────────────────────────
@pytest.mark.asyncio
async def test_resolve_rejects_already_resolved_session(
client: AsyncClient, test_user, auth_headers, test_db
):
session = await _make_session(test_db, test_user, with_psa=False)
session.status = "resolved"
await test_db.commit()
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/resolution-note/post",
headers=auth_headers,
json={"markdown": "..."},
)
assert r.status_code == 409
# ── Escalate: local-only + PSA parallels ────────────────────────────────────
@pytest.mark.asyncio
async def test_escalate_local_only_when_no_psa_ticket(
client: AsyncClient, test_user, auth_headers, test_db
):
session = await _make_session(test_db, test_user, with_psa=False)
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/escalation-package/post",
headers=auth_headers,
json={"markdown": "## Problem\nx\n\n## Suggested next steps\n- try X"},
)
assert r.status_code == 200
assert r.json()["outcome"] == "escalated_local"
await test_db.refresh(session)
assert session.status == "escalated"
assert session.escalation_package_markdown is not None
@pytest.mark.asyncio
async def test_escalate_posts_internal_note_to_psa(
client: AsyncClient, test_user, auth_headers, test_db
):
"""Escalation handoff posts as INTERNAL_ANALYSIS (not customer-visible)."""
session = await _make_session(test_db, test_user, with_psa=True)
fake_provider = AsyncMock()
fake_provider.post_note = AsyncMock(return_value=PSANote(
id="cw-note-esc", text="...", note_type=NoteType.INTERNAL_ANALYSIS, created_at=None,
))
with patch(
"app.services.psa_writeback_service.get_provider_for_connection",
return_value=fake_provider,
):
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/escalation-package/post",
headers=auth_headers,
json={"markdown": "## Problem\nx\n\n## Suggested next steps\n- try X"},
)
assert r.status_code == 200
body = r.json()
assert body["outcome"] == "escalated"
assert body["external_id"] == "cw-note-esc"
# Handoff packages are internal — must NOT be posted with RESOLUTION or DESCRIPTION flags.
called = fake_provider.post_note.await_args.kwargs
assert called["note_type"] == NoteType.INTERNAL_ANALYSIS

View File

@@ -11,57 +11,30 @@ Tests bypass FastAPI entirely — raw asyncpg connections only.
MUST FAIL before Task 10 (RLS migration) and PASS after it.
Run with:
RUN_RLS_TESTS=1 DB_APP_ROLE_PASSWORD=app_secret_change_me pytest tests/test_rls_isolation.py -v
DB_APP_ROLE_PASSWORD=app_secret_change_me pytest tests/test_rls_isolation.py -v
The test DB comes from DATABASE_TEST_URL, matching conftest.py.
The test DB is patherly_test (matches conftest.py default).
"""
import os
import subprocess
import sys
import uuid
from pathlib import Path
from urllib.parse import unquote, urlsplit
import asyncpg
import pytest
import pytest_asyncio
# All tests in this module use module-scoped async fixtures (admin_conn,
# seed_rls_test_data) which run on the module event loop. Without this marker,
# pytest-asyncio 0.23+ defaults tests to function-scoped loops, causing
# "Future attached to a different loop" errors on the asyncpg connections.
pytestmark = [
pytest.mark.asyncio(loop_scope="module"),
pytest.mark.rls,
]
pytestmark = pytest.mark.asyncio(loop_scope="module")
_DATABASE_TEST_URL = os.getenv(
"DATABASE_TEST_URL",
"postgresql+asyncpg://postgres:postgres@localhost:5432/resolutionflow_test",
)
_DATABASE_TEST_URL_ASYNCPG = _DATABASE_TEST_URL.replace(
"postgresql+asyncpg://",
"postgresql://",
1,
)
_DATABASE_TEST_URL_SYNC = _DATABASE_TEST_URL_ASYNCPG
_TEST_DB_PARTS = urlsplit(_DATABASE_TEST_URL_ASYNCPG)
_DB_HOST = os.getenv("TEST_DB_HOST", _TEST_DB_PARTS.hostname or "localhost")
_DB_PORT = int(os.getenv("TEST_DB_PORT", str(_TEST_DB_PARTS.port or 5432)))
_DB_NAME = os.getenv(
"TEST_DB_NAME",
unquote(_TEST_DB_PARTS.path.lstrip("/") or "resolutionflow_test"),
)
_ADMIN_USER = os.getenv(
"TEST_DB_ADMIN_USER",
unquote(_TEST_DB_PARTS.username or "postgres"),
)
_ADMIN_PASSWORD = os.getenv(
"TEST_DB_ADMIN_PASSWORD",
unquote(_TEST_DB_PARTS.password or "postgres"),
)
_DB_HOST = os.getenv("TEST_DB_HOST", "localhost")
_DB_PORT = int(os.getenv("TEST_DB_PORT", "5432"))
_DB_NAME = os.getenv("TEST_DB_NAME", "patherly_test") # matches conftest.py
_APP_PASSWORD = os.getenv("DB_APP_ROLE_PASSWORD", "app_secret_change_me")
_ADMIN_DSN = f"postgresql://postgres:postgres@{_DB_HOST}:{_DB_PORT}/{_DB_NAME}"
PLATFORM_ACCOUNT_ID = "00000000-0000-0000-0000-000000000001"
ACCOUNT_A_ID = "aaaaaaaa-aaaa-aaaa-aaaa-aaaaaaaaaaaa"
@@ -82,33 +55,23 @@ def _ensure_rls_schema():
the full migration-managed schema (including RLS policies) is in place.
"""
backend_dir = Path(__file__).parent.parent
env = os.environ.copy()
env["DATABASE_URL"] = _DATABASE_TEST_URL
env["DATABASE_URL_SYNC"] = _DATABASE_TEST_URL_SYNC
subprocess.run(
[sys.executable, "-m", "alembic", "upgrade", "head"],
cwd=backend_dir,
env=env,
check=True,
capture_output=True,
)
@pytest_asyncio.fixture(scope="module", loop_scope="module")
@pytest.fixture(scope="module")
async def admin_conn(_ensure_rls_schema):
"""Superuser asyncpg connection for fixture setup and teardown."""
conn = await asyncpg.connect(
host=_DB_HOST,
port=_DB_PORT,
database=_DB_NAME,
user=_ADMIN_USER,
password=_ADMIN_PASSWORD,
)
conn = await asyncpg.connect(_ADMIN_DSN)
yield conn
await conn.close()
@pytest_asyncio.fixture(scope="module", loop_scope="module", autouse=True)
@pytest.fixture(scope="module", autouse=True)
async def seed_rls_test_data(admin_conn):
"""
Create two isolated test accounts, one user per account, and one private
@@ -191,7 +154,7 @@ async def seed_rls_test_data(admin_conn):
await admin_conn.execute("DELETE FROM tree_tags WHERE slug = 'rls-global-tag'")
@pytest_asyncio.fixture(loop_scope="module")
@pytest.fixture
async def conn_a():
"""App-role connection, tenant context = Account A."""
conn = await asyncpg.connect(
@@ -205,7 +168,7 @@ async def conn_a():
await conn.close()
@pytest_asyncio.fixture(loop_scope="module")
@pytest.fixture
async def conn_b():
"""App-role connection, tenant context = Account B."""
conn = await asyncpg.connect(
@@ -219,7 +182,7 @@ async def conn_b():
await conn.close()
@pytest_asyncio.fixture(loop_scope="module")
@pytest.fixture
async def conn_no_context():
"""App-role connection with NO tenant context set."""
conn = await asyncpg.connect(
@@ -325,7 +288,7 @@ async def test_flow_proposals_account_a_cannot_see_account_b(conn_a):
# Phase 2 fixtures
# ---------------------------------------------------------------------------
@pytest_asyncio.fixture(scope="module", loop_scope="module")
@pytest.fixture(scope="module")
async def session_row_ids(admin_conn):
"""
Insert one `sessions` row and one `ai_sessions` row for each of
@@ -681,15 +644,13 @@ async def test_psa_post_log_account_a_cannot_see_account_b(conn_a, session_row_i
async def test_step_library_account_a_cannot_see_account_b_private_steps(admin_conn, conn_a):
"""Private/non-public steps owned by Account B must not be visible to Account A."""
user_b_id = await _get_user_b_id(admin_conn)
private_step_id = str(uuid.uuid4())
await admin_conn.execute(f"""
INSERT INTO step_library (
id, account_id, created_by, title, step_type, content,
id, account_id, title, step_type, content,
visibility, is_active, created_at, updated_at
) VALUES (
'{private_step_id}', '{ACCOUNT_B_ID}', '{user_b_id}',
'RLS Private Step', 'action',
'{private_step_id}', '{ACCOUNT_B_ID}', 'RLS Private Step', 'action',
'{{}}'::jsonb, 'private', TRUE, NOW(), NOW()
)
""")
@@ -707,15 +668,13 @@ async def test_step_library_account_a_cannot_see_account_b_private_steps(admin_c
async def test_step_library_account_a_can_see_account_b_public_steps(admin_conn, conn_a):
"""Public steps owned by Account B MUST be visible to Account A (cross-tenant visibility)."""
user_b_id = await _get_user_b_id(admin_conn)
public_step_id = str(uuid.uuid4())
await admin_conn.execute(f"""
INSERT INTO step_library (
id, account_id, created_by, title, step_type, content,
id, account_id, title, step_type, content,
visibility, is_active, created_at, updated_at
) VALUES (
'{public_step_id}', '{ACCOUNT_B_ID}', '{user_b_id}',
'RLS Public Step', 'action',
'{public_step_id}', '{ACCOUNT_B_ID}', 'RLS Public Step', 'action',
'{{}}'::jsonb, 'public', TRUE, NOW(), NOW()
)
""")
@@ -769,11 +728,10 @@ async def test_step_ratings_account_a_cannot_see_account_b(admin_conn, conn_a):
step_id = str(uuid.uuid4())
await admin_conn.execute(f"""
INSERT INTO step_library (
id, account_id, created_by, title, step_type, content,
id, account_id, title, step_type, content,
visibility, is_active, created_at, updated_at
) VALUES (
'{step_id}', '{ACCOUNT_B_ID}', '{user_b_id}',
'Phase3 RLS Step', 'action',
'{step_id}', '{ACCOUNT_B_ID}', 'Phase3 RLS Step', 'action',
'{{}}'::jsonb, 'private', TRUE, NOW(), NOW()
)
""")
@@ -810,11 +768,10 @@ async def test_step_usage_log_account_a_cannot_see_account_b(admin_conn, conn_a)
step_id = str(uuid.uuid4())
await admin_conn.execute(f"""
INSERT INTO step_library (
id, account_id, created_by, title, step_type, content,
id, account_id, title, step_type, content,
visibility, is_active, created_at, updated_at
) VALUES (
'{step_id}', '{ACCOUNT_B_ID}', '{user_b_id}',
'Phase3 Usage Step', 'action',
'{step_id}', '{ACCOUNT_B_ID}', 'Phase3 Usage Step', 'action',
'{{}}'::jsonb, 'private', TRUE, NOW(), NOW()
)
""")
@@ -1014,10 +971,10 @@ async def test_script_builder_sessions_account_a_cannot_see_account_b(admin_conn
session_id = str(uuid.uuid4())
await admin_conn.execute(f"""
INSERT INTO script_builder_sessions (
id, user_id, account_id, language, origin, created_at, updated_at
id, user_id, account_id, language, created_at, updated_at
) VALUES (
'{session_id}', '{user_b_id}', '{ACCOUNT_B_ID}',
'powershell', 'standalone', NOW(), NOW()
'powershell', NOW(), NOW()
)
""")
try:
@@ -1044,24 +1001,22 @@ async def test_ai_session_steps_account_a_cannot_see_account_b(admin_conn, conn_
ai_session_id = str(uuid.uuid4())
await admin_conn.execute(f"""
INSERT INTO ai_sessions (
id, user_id, account_id, session_type, intake_type,
intake_content, status, confidence_tier, confidence_score,
id, user_id, account_id, flow_type, status, confidence_tier,
created_at, updated_at
) VALUES (
'{ai_session_id}', '{user_b_id}', '{ACCOUNT_B_ID}',
'guided', 'free_text', '{{}}'::jsonb, 'active', 'guided', 0.0,
NOW(), NOW()
'troubleshooting', 'active', 'guided', NOW(), NOW()
)
""")
step_id = str(uuid.uuid4())
await admin_conn.execute(f"""
INSERT INTO ai_session_steps (
id, session_id, account_id, step_order, step_type, content,
id, session_id, account_id, step_type, content,
created_at
) VALUES (
'{step_id}', '{ai_session_id}', '{ACCOUNT_B_ID}',
1, 'question', '{{"text": "Phase4 RLS test step"}}'::jsonb, NOW()
'question', 'Phase4 RLS test step', NOW()
)
""")
try:
@@ -1085,11 +1040,11 @@ async def test_notifications_account_a_cannot_see_account_b(admin_conn, conn_a):
notif_id = str(uuid.uuid4())
await admin_conn.execute(f"""
INSERT INTO notifications (
id, user_id, account_id, event, title, body,
id, user_id, account_id, type, title, message,
is_read, created_at
) VALUES (
'{notif_id}', '{user_b_id}', '{ACCOUNT_B_ID}',
'test_event', 'Phase4 RLS Test', 'RLS isolation test notification',
'info', 'Phase4 RLS Test', 'RLS isolation test notification',
FALSE, NOW()
)
""")
@@ -1100,3 +1055,4 @@ async def test_notifications_account_a_cannot_see_account_b(admin_conn, conn_a):
assert len(rows) == 0, "Account A should not see Account B notifications"
finally:
await admin_conn.execute(f"DELETE FROM notifications WHERE id = '{notif_id}'")

View File

@@ -1,176 +0,0 @@
"""Integration tests for inline pilot_inline script_builder_session behavior.
Covers:
- Idempotent get-or-create for (user, ai_session_id) on origin='pilot_inline'
- Authorization: ai_session_id must belong to current user
- list_sessions + count_user_sessions default-scope to 'standalone'
"""
from __future__ import annotations
import pytest
from httpx import AsyncClient
from sqlalchemy import select, func
from uuid import uuid4
from app.models.ai_session import AISession
from app.models.script_builder_session import ScriptBuilderSession
async def _make_pilot_session(test_db, user) -> str:
"""Helper: create a minimal pilot session owned by `user`.
Matches the existing pattern used by test_fix_outcome_endpoint.py.
`user` is the dict returned by the test_user fixture:
{"email": ..., "password": ..., "user_data": {"id": ..., "account_id": ..., ...}}
"""
user_id = user["user_data"]["id"]
account_id = user["user_data"]["account_id"]
session = AISession(
id=uuid4(), user_id=user_id, account_id=account_id,
session_type="tshoot", intake_type="psa_ticket",
intake_content={}, title="QA",
status="active", confidence_tier="exploring", confidence_score=0.0,
)
test_db.add(session)
await test_db.commit()
return str(session.id)
@pytest.mark.asyncio
async def test_inline_create_is_idempotent(
client: AsyncClient, test_user, auth_headers, test_db
):
"""Second create with same (user, ai_session_id) returns the existing row."""
ai_session_id = await _make_pilot_session(test_db, test_user)
r1 = await client.post(
"/api/v1/scripts/builder/sessions",
json={"language": "powershell", "origin": "pilot_inline",
"ai_session_id": ai_session_id},
headers=auth_headers,
)
assert r1.status_code in (200, 201), r1.text
first_id = r1.json()["id"]
r2 = await client.post(
"/api/v1/scripts/builder/sessions",
json={"language": "powershell", "origin": "pilot_inline",
"ai_session_id": ai_session_id},
headers=auth_headers,
)
assert r2.status_code in (200, 201)
assert r2.json()["id"] == first_id
# DB confirms only one row
row_count = await test_db.scalar(
select(func.count()).select_from(ScriptBuilderSession).where(
ScriptBuilderSession.user_id == test_user["user_data"]["id"],
ScriptBuilderSession.origin == "pilot_inline",
)
)
assert row_count == 1
@pytest.mark.asyncio
async def test_inline_requires_ai_session_id(
client: AsyncClient, auth_headers
):
"""origin='pilot_inline' without ai_session_id is rejected."""
r = await client.post(
"/api/v1/scripts/builder/sessions",
json={"language": "powershell", "origin": "pilot_inline"},
headers=auth_headers,
)
assert r.status_code == 400
assert "ai_session_id" in r.text.lower()
@pytest.mark.asyncio
async def test_inline_ai_session_must_belong_to_caller(
client: AsyncClient, test_user, auth_headers, test_db
):
"""ai_session_id pointing at another user's session is rejected."""
# Create pilot session owned by a DIFFERENT user
from app.models.user import User
from app.models.account import Account
other_account = Account(id=uuid4(), name="other", display_code="OTH-0001")
test_db.add(other_account)
await test_db.flush()
other_user = User(
id=uuid4(), email="other@example.com",
password_hash="x", name="Other", role="engineer",
is_super_admin=False, is_team_admin=False, is_active=True,
is_service_account=False, must_change_password=False,
account_id=other_account.id, account_role="engineer",
)
test_db.add(other_user)
await test_db.flush()
# Build user dict in the same shape as the test_user fixture
other_user_dict = {
"user_data": {"id": str(other_user.id), "account_id": str(other_account.id)}
}
other_session_id = await _make_pilot_session(test_db, other_user_dict)
r = await client.post(
"/api/v1/scripts/builder/sessions",
json={"language": "powershell", "origin": "pilot_inline",
"ai_session_id": other_session_id},
headers=auth_headers,
)
assert r.status_code in (403, 404), r.text
@pytest.mark.asyncio
async def test_list_sessions_excludes_inline(
client: AsyncClient, test_user, auth_headers, test_db
):
"""GET /scripts/builder/sessions returns only standalone rows."""
ai_session_id = await _make_pilot_session(test_db, test_user)
# Create one inline session
await client.post(
"/api/v1/scripts/builder/sessions",
json={"language": "powershell", "origin": "pilot_inline",
"ai_session_id": ai_session_id},
headers=auth_headers,
)
# Create one standalone session
await client.post(
"/api/v1/scripts/builder/sessions",
json={"language": "powershell"},
headers=auth_headers,
)
r = await client.get("/api/v1/scripts/builder/sessions", headers=auth_headers)
assert r.status_code == 200
body = r.json()
# Depending on response shape, this may be a list or {"sessions": [...]}.
items = body if isinstance(body, list) else body.get("sessions", body.get("items", []))
# Response schema does not surface `origin`; len==1 is the only meaningful guard:
# inline row would push this to 2.
assert len(items) == 1
@pytest.mark.asyncio
async def test_inline_sessions_do_not_count_against_cap(
client: AsyncClient, test_user, auth_headers, test_db
):
"""Creating 5 pilot_inline sessions does not block a subsequent standalone."""
# Create 5 distinct pilot sessions and attach inline builder sessions to each
for _ in range(5):
ai_session_id = await _make_pilot_session(test_db, test_user)
r = await client.post(
"/api/v1/scripts/builder/sessions",
json={"language": "powershell", "origin": "pilot_inline",
"ai_session_id": ai_session_id},
headers=auth_headers,
)
assert r.status_code in (200, 201), r.text
# A standalone create should still succeed — inline sessions don't count
r = await client.post(
"/api/v1/scripts/builder/sessions",
json={"language": "powershell"},
headers=auth_headers,
)
assert r.status_code in (200, 201), r.text

View File

@@ -1,455 +0,0 @@
"""API + service tests for the FlowPilot Phase 2 "What we know" facts surface.
Covers:
- /api/v1/ai-sessions/{id}/facts CRUD
- Editability rule (403 on PATCH for question/diagnostic_check facts)
- /facts/promote with `proposed_text` (no LLM call) and via synthesis (mocked)
- state_version increments on every fact write
- Stable-UUID assignment for pending_task_lane items
- [PROMOTE] marker parser shape
"""
from __future__ import annotations
import uuid
from unittest.mock import AsyncMock, patch
import pytest
from httpx import AsyncClient
from sqlalchemy import select
from app.models.ai_session import AISession
from app.models.session_fact import SessionFact
from app.services.fact_synthesis_service import FactSynthesisService
from app.services.unified_chat_service import (
_assign_stable_task_lane_ids,
_parse_promote_marker,
)
# ── Fixtures ────────────────────────────────────────────────────────────────
async def _make_session(test_db, user, *, pending_task_lane=None) -> AISession:
session = AISession(
user_id=user["user_data"]["id"],
account_id=user["user_data"]["account_id"],
session_type="chat",
intake_type="free_text",
intake_content={"text": "test"},
status="active",
confidence_tier="discovery",
conversation_messages=[],
pending_task_lane=pending_task_lane,
)
test_db.add(session)
await test_db.commit()
await test_db.refresh(session)
return session
# ── [PROMOTE] marker parser ─────────────────────────────────────────────────
class TestPromoteMarkerParser:
def test_no_marker_returns_unchanged(self):
text = "Just an analysis sentence."
cleaned, items = _parse_promote_marker(text)
assert cleaned == text
assert items is None
def test_single_block(self):
ref = uuid.uuid4()
text = (
"Some analysis.\n\n"
f'[PROMOTE]\n{{"source_type":"question","source_ref":"{ref}",'
'"text":"OWA login confirmed working","summary":"rules out tenant"}\n'
"[/PROMOTE]"
)
cleaned, items = _parse_promote_marker(text)
assert cleaned == "Some analysis."
assert items is not None and len(items) == 1
assert items[0]["source_type"] == "question"
assert items[0]["source_ref"] == ref
assert items[0]["text"] == "OWA login confirmed working"
assert items[0]["summary"] == "rules out tenant"
def test_multiple_blocks(self):
text = (
'[PROMOTE]\n{"source_type":"question","source_ref":null,'
'"text":"a","summary":"x"}\n[/PROMOTE]\n'
'[PROMOTE]\n{"source_type":"diagnostic_check","source_ref":null,'
'"text":"b","summary":"y"}\n[/PROMOTE]'
)
cleaned, items = _parse_promote_marker(text)
assert items is not None and len(items) == 2
assert items[0]["text"] == "a"
assert items[1]["text"] == "b"
assert "[PROMOTE]" not in cleaned
def test_ai_synthesis_strips_source_ref(self):
# The model should not provide source_ref for synthesis facts —
# the parser drops it defensively even if the model does.
ref = uuid.uuid4()
text = (
f'[PROMOTE]\n{{"source_type":"ai_synthesis","source_ref":"{ref}",'
'"text":"Combined finding","summary":"synth"}\n[/PROMOTE]'
)
_, items = _parse_promote_marker(text)
assert items is not None and items[0]["source_ref"] is None
def test_invalid_source_type_dropped(self):
text = (
'[PROMOTE]\n{"source_type":"bogus","text":"x"}\n[/PROMOTE]\n'
'[PROMOTE]\n{"source_type":"question","source_ref":null,"text":"good"}\n[/PROMOTE]'
)
_, items = _parse_promote_marker(text)
assert items is not None and len(items) == 1
assert items[0]["text"] == "good"
def test_missing_text_dropped(self):
text = '[PROMOTE]\n{"source_type":"question","source_ref":null,"text":""}\n[/PROMOTE]'
_, items = _parse_promote_marker(text)
assert items is None # empty list collapses to None
def test_invalid_uuid_drops_ref_keeps_item(self):
text = '[PROMOTE]\n{"source_type":"question","source_ref":"not-a-uuid","text":"keep"}\n[/PROMOTE]'
_, items = _parse_promote_marker(text)
assert items is not None and items[0]["source_ref"] is None
assert items[0]["text"] == "keep"
def test_malformed_json_dropped(self):
text = "[PROMOTE]\nnot json at all\n[/PROMOTE]"
cleaned, items = _parse_promote_marker(text)
assert items is None
# Block is still stripped from display so the engineer doesn't see it.
assert "[PROMOTE]" not in cleaned
# ── Stable-UUID assignment ──────────────────────────────────────────────────
class TestAssignStableTaskLaneIds:
def test_empty_prev_assigns_fresh_uuids(self):
qs, acts = _assign_stable_task_lane_ids(
None,
[{"text": "Q1", "context": "c1"}],
[{"label": "A1", "command": "cmd"}],
)
assert len(qs) == 1 and uuid.UUID(qs[0]["id"])
assert len(acts) == 1 and uuid.UUID(acts[0]["id"])
def test_prev_uuid_preserved_on_text_match(self):
qid = str(uuid.uuid4())
prev = {
"questions": [{"id": qid, "text": "Same text"}],
"actions": [],
}
qs, _ = _assign_stable_task_lane_ids(prev, [{"text": "Same text"}], [])
assert qs[0]["id"] == qid
def test_prev_uuid_replaced_when_text_changes(self):
qid = str(uuid.uuid4())
prev = {"questions": [{"id": qid, "text": "Original"}], "actions": []}
qs, _ = _assign_stable_task_lane_ids(prev, [{"text": "Different"}], [])
assert qs[0]["id"] != qid
def test_action_label_match_preserves_uuid(self):
aid = str(uuid.uuid4())
prev = {"questions": [], "actions": [{"id": aid, "label": "Run X"}]}
_, acts = _assign_stable_task_lane_ids(prev, [], [{"label": "Run X"}])
assert acts[0]["id"] == aid
# ── FactSynthesisService.create_fact validation ─────────────────────────────
@pytest.mark.asyncio
async def test_create_fact_rejects_source_ref_for_user_note(test_db, test_user):
session = await _make_session(test_db, test_user)
svc = FactSynthesisService(test_db)
with pytest.raises(ValueError, match="source_ref must be None"):
await svc.create_fact(
session_id=session.id,
account_id=session.account_id,
user_id=session.user_id,
source_type="user_note",
text="x",
source_ref=uuid.uuid4(),
)
@pytest.mark.asyncio
async def test_create_fact_rejects_invalid_source_type(test_db, test_user):
session = await _make_session(test_db, test_user)
svc = FactSynthesisService(test_db)
with pytest.raises(ValueError, match="Invalid source_type"):
await svc.create_fact(
session_id=session.id,
account_id=session.account_id,
user_id=session.user_id,
source_type="not_a_type",
text="x",
)
@pytest.mark.asyncio
async def test_create_fact_bumps_state_version(test_db, test_user):
session = await _make_session(test_db, test_user)
initial_version = session.state_version
svc = FactSynthesisService(test_db)
await svc.create_fact(
session_id=session.id,
account_id=session.account_id,
user_id=session.user_id,
source_type="user_note",
text="A confirmed observation",
)
await test_db.commit()
await test_db.refresh(session)
assert session.state_version == initial_version + 1
# ── Endpoint tests ──────────────────────────────────────────────────────────
@pytest.mark.asyncio
async def test_list_facts_empty(client: AsyncClient, test_user, auth_headers, test_db):
session = await _make_session(test_db, test_user)
resp = await client.get(
f"/api/v1/ai-sessions/{session.id}/facts",
headers=auth_headers,
)
assert resp.status_code == 200
assert resp.json()["facts"] == []
@pytest.mark.asyncio
async def test_create_user_note_fact(client: AsyncClient, test_user, auth_headers, test_db):
session = await _make_session(test_db, test_user)
resp = await client.post(
f"/api/v1/ai-sessions/{session.id}/facts",
headers=auth_headers,
json={"text": "Customer is on a laptop", "summary": "endpoint type"},
)
assert resp.status_code == 201
body = resp.json()
assert body["source_type"] == "user_note"
assert body["editable"] is True
assert body["source_ref"] is None
assert body["text"] == "Customer is on a laptop"
@pytest.mark.asyncio
async def test_patch_user_note_succeeds(client: AsyncClient, test_user, auth_headers, test_db):
session = await _make_session(test_db, test_user)
create = await client.post(
f"/api/v1/ai-sessions/{session.id}/facts",
headers=auth_headers,
json={"text": "original"},
)
fact_id = create.json()["id"]
patch_resp = await client.patch(
f"/api/v1/ai-sessions/{session.id}/facts/{fact_id}",
headers=auth_headers,
json={"text": "edited", "summary": "new label"},
)
assert patch_resp.status_code == 200
assert patch_resp.json()["text"] == "edited"
assert patch_resp.json()["source_summary"] == "new label"
@pytest.mark.asyncio
async def test_patch_question_fact_returns_403(client: AsyncClient, test_user, auth_headers, test_db):
"""Question/check-sourced facts must be edited at the source item, not the card."""
session = await _make_session(test_db, test_user)
# Insert a question-sourced fact directly so the editability rule applies.
fact = SessionFact(
session_id=session.id,
account_id=session.account_id,
text="Pre-existing question fact",
source_type="question",
source_ref=uuid.uuid4(),
created_by=session.user_id,
)
test_db.add(fact)
await test_db.commit()
await test_db.refresh(fact)
resp = await client.patch(
f"/api/v1/ai-sessions/{session.id}/facts/{fact.id}",
headers=auth_headers,
json={"text": "trying to edit"},
)
assert resp.status_code == 403
@pytest.mark.asyncio
async def test_delete_fact_soft_deletes(client: AsyncClient, test_user, auth_headers, test_db):
session = await _make_session(test_db, test_user)
create = await client.post(
f"/api/v1/ai-sessions/{session.id}/facts",
headers=auth_headers,
json={"text": "to be removed"},
)
fact_id = create.json()["id"]
del_resp = await client.delete(
f"/api/v1/ai-sessions/{session.id}/facts/{fact_id}",
headers=auth_headers,
)
assert del_resp.status_code == 204
# Listed facts should not include the soft-deleted one.
list_resp = await client.get(
f"/api/v1/ai-sessions/{session.id}/facts",
headers=auth_headers,
)
assert list_resp.status_code == 200
assert all(f["id"] != fact_id for f in list_resp.json()["facts"])
# Row still exists in DB (deleted_at set), proving it was soft-deleted.
row = (
await test_db.execute(
select(SessionFact).where(SessionFact.id == uuid.UUID(fact_id))
)
).scalar_one()
assert row.deleted_at is not None
@pytest.mark.asyncio
async def test_promote_with_proposed_text(client: AsyncClient, test_user, auth_headers, test_db):
qid = uuid.uuid4()
session = await _make_session(
test_db, test_user,
pending_task_lane={
"questions": [{"id": str(qid), "text": "Is OWA working?"}],
"actions": [],
},
)
resp = await client.post(
f"/api/v1/ai-sessions/{session.id}/facts/promote",
headers=auth_headers,
json={
"source_type": "question",
"source_ref": str(qid),
"proposed_text": "OWA confirmed working for jsmith",
"proposed_summary": "rules out tenant/license",
},
)
assert resp.status_code == 201
body = resp.json()
assert body["source_type"] == "question"
assert body["source_ref"] == str(qid)
assert body["editable"] is False # question-sourced facts are read-only at the card
@pytest.mark.asyncio
async def test_promote_via_synthesis(client: AsyncClient, test_user, auth_headers, test_db):
qid = uuid.uuid4()
session = await _make_session(
test_db, test_user,
pending_task_lane={
"questions": [{"id": str(qid), "text": "Is the user on a laptop?"}],
"actions": [],
},
)
# Mock the LLM call to avoid hitting the network in tests.
fake_provider = AsyncMock()
fake_provider.generate_json = AsyncMock(return_value=(
'{"text": "User confirmed on a laptop", "summary": "endpoint type"}',
50, 20,
))
with patch(
"app.services.fact_synthesis_service.get_ai_provider",
return_value=fake_provider,
):
resp = await client.post(
f"/api/v1/ai-sessions/{session.id}/facts/promote",
headers=auth_headers,
json={
"source_type": "question",
"source_ref": str(qid),
"raw_input": "Yes, it's a Lenovo X1 Carbon",
},
)
assert resp.status_code == 201
assert resp.json()["text"] == "User confirmed on a laptop"
assert resp.json()["source_summary"] == "endpoint type"
@pytest.mark.asyncio
async def test_promote_synthesis_returning_null_returns_422(
client: AsyncClient, test_user, auth_headers, test_db
):
"""When the synthesizer judges the input has no fact, the endpoint surfaces 422."""
qid = uuid.uuid4()
session = await _make_session(
test_db, test_user,
pending_task_lane={
"questions": [{"id": str(qid), "text": "Is OWA working?"}],
"actions": [],
},
)
fake_provider = AsyncMock()
fake_provider.generate_json = AsyncMock(return_value=(
'{"text": null, "summary": null}', 30, 10,
))
with patch(
"app.services.fact_synthesis_service.get_ai_provider",
return_value=fake_provider,
):
resp = await client.post(
f"/api/v1/ai-sessions/{session.id}/facts/promote",
headers=auth_headers,
json={
"source_type": "question",
"source_ref": str(qid),
"raw_input": "unknown",
},
)
assert resp.status_code == 422
@pytest.mark.asyncio
async def test_promote_rejects_both_or_neither_inputs(
client: AsyncClient, test_user, auth_headers, test_db
):
session = await _make_session(test_db, test_user)
# Neither
resp = await client.post(
f"/api/v1/ai-sessions/{session.id}/facts/promote",
headers=auth_headers,
json={"source_type": "question"},
)
assert resp.status_code == 400
# Both
resp2 = await client.post(
f"/api/v1/ai-sessions/{session.id}/facts/promote",
headers=auth_headers,
json={
"source_type": "question",
"proposed_text": "x",
"raw_input": "y",
},
)
assert resp2.status_code == 400
@pytest.mark.asyncio
async def test_state_version_bumps_on_create_via_endpoint(
client: AsyncClient, test_user, auth_headers, test_db
):
session = await _make_session(test_db, test_user)
initial = session.state_version
await client.post(
f"/api/v1/ai-sessions/{session.id}/facts",
headers=auth_headers,
json={"text": "a"},
)
# Reload — refresh fetches the latest persisted row.
await test_db.refresh(session)
assert session.state_version == initial + 1

View File

@@ -1,356 +0,0 @@
"""API + service tests for the FlowPilot Phase 3 suggested-fix + preview surface.
Covers:
- /api/v1/ai-sessions/{id}/suggested-fixes/active (200 + 404)
- /api/v1/ai-sessions/{id}/suggested-fixes/{fix_id}/decision (one_off,
draft_template, build_template, dismissed; 409 on dismissing a superseded
fix; state_version bump)
- /api/v1/ai-sessions/{id}/resolution-note/preview (LLM mocked; cache hit on
same state_version, miss after a fact write)
- [SUGGEST_FIX] marker parser shape
- _persist_suggested_fix supersession + state_version bump
"""
from __future__ import annotations
import uuid
from datetime import datetime, timezone
from unittest.mock import AsyncMock, patch
import pytest
from httpx import AsyncClient
from sqlalchemy import select
from app.api.endpoints.session_suggested_fixes import _clear_preview_cache_for_tests
from app.models.ai_session import AISession
from app.models.session_suggested_fix import SessionSuggestedFix
from app.services.unified_chat_service import (
_parse_suggest_fix_marker,
_persist_suggested_fix,
)
@pytest.fixture(autouse=True)
def _isolate_preview_cache():
_clear_preview_cache_for_tests()
yield
_clear_preview_cache_for_tests()
async def _make_session(test_db, user) -> AISession:
session = AISession(
user_id=user["user_data"]["id"],
account_id=user["user_data"]["account_id"],
session_type="chat",
intake_type="free_text",
intake_content={"text": "phase 3 test"},
status="active",
confidence_tier="discovery",
conversation_messages=[],
)
test_db.add(session)
await test_db.commit()
await test_db.refresh(session)
return session
# ── [SUGGEST_FIX] parser ────────────────────────────────────────────────────
class TestSuggestFixParser:
def test_no_marker(self):
cleaned, fix = _parse_suggest_fix_marker("just analysis")
assert cleaned == "just analysis"
assert fix is None
def test_well_formed_block(self):
text = (
"Analysis sentence.\n\n"
'[SUGGEST_FIX]\n'
'{"title": "Reset password", "description": "Stale credential.", '
'"confidence": 87, "script_template_slug": "reset-cw"}\n'
'[/SUGGEST_FIX]'
)
cleaned, fix = _parse_suggest_fix_marker(text)
assert cleaned == "Analysis sentence."
assert fix is not None
assert fix["title"] == "Reset password"
assert fix["confidence_pct"] == 87
assert fix["script_template_slug"] == "reset-cw"
assert fix["ai_drafted_script"] is None
def test_confidence_clamped_and_rounded(self):
text = (
'[SUGGEST_FIX]\n{"title":"x","description":"y","confidence":120.7}\n[/SUGGEST_FIX]'
)
_, fix = _parse_suggest_fix_marker(text)
assert fix is not None and fix["confidence_pct"] == 100
text2 = (
'[SUGGEST_FIX]\n{"title":"x","description":"y","confidence":-3}\n[/SUGGEST_FIX]'
)
_, fix2 = _parse_suggest_fix_marker(text2)
assert fix2 is not None and fix2["confidence_pct"] == 0
def test_only_last_block_wins(self):
# Stale early block plus a final intent — the parser keeps the LAST one.
text = (
'[SUGGEST_FIX]\n{"title":"old","description":"o","confidence":50}\n[/SUGGEST_FIX]\n'
'[SUGGEST_FIX]\n{"title":"new","description":"n","confidence":80}\n[/SUGGEST_FIX]'
)
cleaned, fix = _parse_suggest_fix_marker(text)
assert fix is not None and fix["title"] == "new"
assert "[SUGGEST_FIX]" not in cleaned
def test_missing_required_field_dropped(self):
text = '[SUGGEST_FIX]\n{"title":"only title"}\n[/SUGGEST_FIX]'
cleaned, fix = _parse_suggest_fix_marker(text)
assert fix is None
# Marker still stripped from display.
assert "[SUGGEST_FIX]" not in cleaned
def test_malformed_json_dropped(self):
text = "[SUGGEST_FIX]\nnot json\n[/SUGGEST_FIX]"
cleaned, fix = _parse_suggest_fix_marker(text)
assert fix is None
assert "[SUGGEST_FIX]" not in cleaned
# ── _persist_suggested_fix ──────────────────────────────────────────────────
@pytest.mark.asyncio
async def test_persist_supersedes_prior_active_and_bumps_state_version(test_db, test_user):
session = await _make_session(test_db, test_user)
initial_version = session.state_version
# Insert an existing active fix so we can verify supersession.
existing = SessionSuggestedFix(
session_id=session.id,
account_id=session.account_id,
title="Old fix",
description="prior",
confidence_pct=60,
)
test_db.add(existing)
await test_db.commit()
await _persist_suggested_fix(
db=test_db,
session=session,
fix={
"title": "New fix",
"description": "current best",
"confidence_pct": 88,
"script_template_slug": None,
"ai_drafted_script": None,
"ai_drafted_parameters": None,
},
)
await test_db.commit()
await test_db.refresh(existing)
await test_db.refresh(session)
assert existing.superseded_at is not None
assert session.state_version == initial_version + 1
# Exactly one active row remains — and it's the new one.
result = await test_db.execute(
select(SessionSuggestedFix).where(
SessionSuggestedFix.session_id == session.id,
SessionSuggestedFix.superseded_at.is_(None),
)
)
actives = list(result.scalars().all())
assert len(actives) == 1
assert actives[0].title == "New fix"
# ── /suggested-fixes/active endpoint ────────────────────────────────────────
@pytest.mark.asyncio
async def test_get_active_returns_404_when_none(client: AsyncClient, test_user, auth_headers, test_db):
session = await _make_session(test_db, test_user)
r = await client.get(
f"/api/v1/ai-sessions/{session.id}/suggested-fixes/active",
headers=auth_headers,
)
assert r.status_code == 404
@pytest.mark.asyncio
async def test_get_active_returns_active_fix(client: AsyncClient, test_user, auth_headers, test_db):
session = await _make_session(test_db, test_user)
fix = SessionSuggestedFix(
session_id=session.id,
account_id=session.account_id,
title="Active fix",
description="d",
confidence_pct=72,
)
test_db.add(fix)
await test_db.commit()
r = await client.get(
f"/api/v1/ai-sessions/{session.id}/suggested-fixes/active",
headers=auth_headers,
)
assert r.status_code == 200
body = r.json()
assert body["title"] == "Active fix"
assert body["confidence_pct"] == 72
assert body["superseded_at"] is None
# ── /decision endpoint ─────────────────────────────────────────────────────
@pytest.mark.asyncio
async def test_record_decision_persists_and_bumps_state_version(
client: AsyncClient, test_user, auth_headers, test_db
):
session = await _make_session(test_db, test_user)
initial_version = session.state_version
fix = SessionSuggestedFix(
session_id=session.id,
account_id=session.account_id,
title="x",
description="y",
confidence_pct=50,
)
test_db.add(fix)
await test_db.commit()
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/suggested-fixes/{fix.id}/decision",
headers=auth_headers,
json={"decision": "draft_template"},
)
assert r.status_code == 200
assert r.json()["user_decision"] == "draft_template"
await test_db.refresh(session)
assert session.state_version == initial_version + 1
@pytest.mark.asyncio
async def test_dismissed_supersedes_the_fix(
client: AsyncClient, test_user, auth_headers, test_db
):
session = await _make_session(test_db, test_user)
fix = SessionSuggestedFix(
session_id=session.id,
account_id=session.account_id,
title="x",
description="y",
confidence_pct=50,
)
test_db.add(fix)
await test_db.commit()
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/suggested-fixes/{fix.id}/decision",
headers=auth_headers,
json={"decision": "dismissed"},
)
assert r.status_code == 200
await test_db.refresh(fix)
assert fix.superseded_at is not None
@pytest.mark.asyncio
async def test_dismiss_already_superseded_returns_409(
client: AsyncClient, test_user, auth_headers, test_db
):
session = await _make_session(test_db, test_user)
fix = SessionSuggestedFix(
session_id=session.id,
account_id=session.account_id,
title="x",
description="y",
confidence_pct=50,
superseded_at=datetime.now(timezone.utc),
)
test_db.add(fix)
await test_db.commit()
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/suggested-fixes/{fix.id}/decision",
headers=auth_headers,
json={"decision": "dismissed"},
)
assert r.status_code == 409
# ── /resolution-note/preview endpoint ──────────────────────────────────────
@pytest.mark.asyncio
async def test_preview_uses_state_version_cache(
client: AsyncClient, test_user, auth_headers, test_db
):
session = await _make_session(test_db, test_user)
fake_provider = AsyncMock()
fake_provider.generate_text = AsyncMock(return_value=(
"## Problem\nx\n\n## What we confirmed\n(none)\n\n## Root cause\ny\n\n## Resolution\nz",
100, 50,
))
with patch(
"app.services.resolution_note_generator.get_ai_provider",
return_value=fake_provider,
):
# First call — cache miss, generates fresh.
r1 = await client.post(
f"/api/v1/ai-sessions/{session.id}/resolution-note/preview",
headers=auth_headers,
)
assert r1.status_code == 200
assert r1.json()["from_cache"] is False
assert fake_provider.generate_text.await_count == 1
# Second call, no state change — must hit the cache (no extra LLM call).
r2 = await client.post(
f"/api/v1/ai-sessions/{session.id}/resolution-note/preview",
headers=auth_headers,
)
assert r2.status_code == 200
assert r2.json()["from_cache"] is True
assert r2.json()["markdown"] == r1.json()["markdown"]
assert fake_provider.generate_text.await_count == 1
@pytest.mark.asyncio
async def test_preview_invalidates_after_fact_write(
client: AsyncClient, test_user, auth_headers, test_db
):
"""A new fact bumps state_version → next preview is a fresh generation, not cached."""
session = await _make_session(test_db, test_user)
fake_provider = AsyncMock()
fake_provider.generate_text = AsyncMock(return_value=(
"## Problem\nx\n\n## What we confirmed\n(none)\n\n## Root cause\ny\n\n## Resolution\nz",
100, 50,
))
with patch(
"app.services.resolution_note_generator.get_ai_provider",
return_value=fake_provider,
):
await client.post(
f"/api/v1/ai-sessions/{session.id}/resolution-note/preview",
headers=auth_headers,
)
assert fake_provider.generate_text.await_count == 1
# Add a fact — bumps state_version on the session.
await client.post(
f"/api/v1/ai-sessions/{session.id}/facts",
headers=auth_headers,
json={"text": "a confirmed observation"},
)
# Next preview must regenerate (cache key includes state_version).
r = await client.post(
f"/api/v1/ai-sessions/{session.id}/resolution-note/preview",
headers=auth_headers,
)
assert r.status_code == 200
assert r.json()["from_cache"] is False
assert fake_provider.generate_text.await_count == 2

View File

@@ -1,5 +1,4 @@
name: resolutionflow
services:
db:
image: pgvector/pgvector:pg16
@@ -9,7 +8,7 @@ services:
POSTGRES_PASSWORD: postgres
POSTGRES_DB: resolutionflow
ports:
- "${POSTGRES_PORT:-5433}:5432"
- "${POSTGRES_PORT:-5432}:5432"
volumes:
- rf_postgres_data:/var/lib/postgresql/data
healthcheck:
@@ -23,51 +22,53 @@ services:
context: ./backend
dockerfile: Dockerfile.dev
container_name: resolutionflow_backend
command: uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
ports:
- "8000:8000"
volumes:
- ${REPO_ROOT}/backend:/app
- ./backend:/app
environment:
- APP_NAME=ResolutionFlow
- DEBUG=true
- DATABASE_URL=postgresql+asyncpg://postgres:postgres@db:5432/resolutionflow
- DATABASE_URL_SYNC=postgresql://postgres:postgres@db:5432/resolutionflow
# Dedicated test database — pytest will refuse to run against any DB
# whose name doesn't contain 'test' (conftest.py safety assertion).
- DATABASE_TEST_URL=postgresql+asyncpg://postgres:postgres@db:5432/resolutionflow_test
- SECRET_KEY=${SECRET_KEY}
- ALGORITHM=HS256
- ACCESS_TOKEN_EXPIRE_MINUTES=15
- REFRESH_TOKEN_EXPIRE_DAYS=7
- REQUIRE_INVITE_CODE=true
- FEEDBACK_EMAIL=feedback@resolutionflow.com
- AI_PROVIDER=anthropic
- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
- GOOGLE_AI_API_KEY=${GOOGLE_AI_API_KEY:-}
- ENABLE_MCP_MICROSOFT_LEARN=true
- FRONTEND_URL=http://docker-01:5173
- CORS_ORIGINS=["http://localhost:5173","http://127.0.0.1:5173","http://docker-01:5173","http://100.64.78.44:5173"]
- GOOGLE_AI_API_KEY=${GOOGLE_AI_API_KEY}
- CORS_ORIGINS=["http://localhost:3000","http://localhost:5173","http://127.0.0.1:3000","http://127.0.0.1:5173","http://46.202.92.250:5173","http://46.202.92.250:3000","https://resolutionflow.com","https://www.resolutionflow.com"]
depends_on:
db:
condition: service_healthy
labels:
- "traefik.enable=true"
- "traefik.http.routers.rf-api.rule=Host(`dev.resolutionflow.com`) && PathPrefix(`/api`)"
- "traefik.http.routers.rf-api.entrypoints=websecure"
- "traefik.http.routers.rf-api.tls.certresolver=letsencrypt"
- "traefik.http.services.rf-api.loadbalancer.server.port=8000"
frontend:
build:
context: ./frontend
dockerfile: Dockerfile.dev
container_name: resolutionflow_frontend
command: npm run dev -- --host 0.0.0.0 --port 5173
ports:
- "5173:5173"
volumes:
- ${REPO_ROOT}/frontend:/app
- ./frontend:/app
- /app/node_modules
environment:
- VITE_API_URL=http://docker-01:8000
- CHOKIDAR_USEPOLLING=true
- VITE_API_URL=https://dev.resolutionflow.com/
depends_on:
- backend
labels:
- "traefik.enable=true"
- "traefik.http.routers.rf-frontend.rule=Host(`dev.resolutionflow.com`)"
- "traefik.http.routers.rf-frontend.middlewares=dev-auth"
- "traefik.http.middlewares.dev-auth.basicauth.users=chihlasm:$$apr1$$dJXUAZ3Y$$SsJm.K8fOjCeNMe4B70Bi0"
- "traefik.http.routers.rf-frontend.entrypoints=websecure"
- "traefik.http.routers.rf-frontend.tls.certresolver=letsencrypt"
- "traefik.http.services.rf-frontend.loadbalancer.server.port=5173"
volumes:
rf_postgres_data:
rf_postgres_data:

View File

@@ -1,163 +0,0 @@
# FlowPilot & ResolutionAssist
> ResolutionFlow offers two AI-driven troubleshooting modes that share the same session backend but present very different interaction styles. Both work standalone and become richer when paired with a PSA connection.
---
## At a glance
| | **FlowPilot** | **ResolutionAssist** |
|---|---|---|
| **Style** | Guided, structured | Conversational, freeform |
| **Entry** | `/pilot` | `/assistant` |
| **Interaction** | Questions → Actions → Resolution, one step at a time | Natural chat with inline questions/actions |
| **Best for** | Reproducible workflows, low-context engineers, handoffs | Exploratory problems, quick lookups, rubber-ducking |
| **Lifecycle** | Active → Paused → Resolved / Escalated / Abandoned | Active → Resolved / Abandoned (lightweight) |
| **Confidence tracking** | Yes — drives tier transitions | No — always responsive to user direction |
| **Navigation guard** | Yes — prevents accidental loss | No — free to leave and return |
Both modes share the `ai_sessions` table (discriminated by `session_type`), the same multimodal AI backend (image uploads, markdown, cached prompts), and the same `[QUESTIONS]` / `[ACTIONS]` / `[FORK]` marker vocabulary that renders inline TaskLane elements.
---
## FlowPilot — guided troubleshooting
FlowPilot is a wizard-style AI engineer that walks you through a problem one diagnostic step at a time. It runs on confidence tiers:
- **Discovery** (confidence < 0.4) — asking broad, open-ended questions to characterize the problem
- **Exploring** (0.40.8) — proposing targeted actions and narrowing hypotheses
- **Guided** (≥ 0.8) — recommending a specific fix with steps to verify
### The FlowPilot session flow
1. **Intake.** You start from `/pilot` or from the dashboard "New Session" button. The intake screen accepts free-text description, PSA ticket context, screenshots, or log pastes.
2. **Preference check.** Before suggesting any fix, the AI asks whether you want a **GUI** or **script** approach. This is enforced in the system prompt so you never get steps you can't execute.
3. **Step-by-step progression.** Each AI response is either a question (with clickable options), an action (with "Done" / "Didn't work" buttons), a `[FORK]` (two distinct paths to try), or a final resolution suggestion. You respond, the AI updates its confidence, and the next step is generated.
4. **Action bar.** The session header always shows **Pause & Leave**, **Resolve**, **Escalate**, **Share Update**, and **Close**. Pausing freezes the session; resuming restores the full context.
5. **Resolve / Escalate.** *Resolve* marks the ticket fixed and generates a clean summary of what worked. *Escalate* packages the problem summary and steps tried into an **escalation package** that the next engineer (or the PSA ticket) inherits.
### Why FlowPilot exists
- **New engineers** get senior-engineer-level diagnostic rigor without needing the experience to know what to ask next.
- **Documented resolutions** — every step is captured, so the generated note on the ticket is substantive (not just "fixed it").
- **Handoff-friendly** — escalation packages mean the next person doesn't start from zero.
---
## ResolutionAssist — conversational AI
ResolutionAssist is a chat with an expert IT systems engineer. It's less structured than FlowPilot but still surfaces interactive elements when the AI wants structured input.
### The ResolutionAssist flow
1. **Open a chat.** From `/assistant` or the dashboard. Sessions show up in the left sidebar just like any messaging app.
2. **Send a message.** Freeform prose. Attach up to 3 images per message (screenshots, error dialogs, network diagrams). Paste logs, code, or PowerShell output.
3. **AI responds.** The response is prose, but any `[QUESTIONS]` or `[ACTIONS]` blocks render as a **TaskLane** — a side panel with clickable options and action buttons. You can answer via chat or click the TaskLane elements.
4. **Branching (`[FORK]`).** If the AI proposes two paths ("check cable or restart switch?"), the fork renders as a choice. Picking one continues the conversation down that path.
5. **Resume later.** Unlike FlowPilot, there's no navigation guard. Leave mid-conversation; every message is stored.
### Why ResolutionAssist exists
- **Unstructured problems** — "I have no idea where to start, here's a screenshot" works great.
- **Reference lookups** — "what's the right PowerShell command to check Exchange health" is faster in chat than through an intake form.
- **Senior engineers** — when you already know what you're doing and just want a second opinion or a syntax check.
---
## Without a PSA connection
Both modes work standalone. Without ConnectWise connected:
- Sessions live entirely in ResolutionFlow. They're listed in your session history, searchable, and shareable via public share links (`/shared/sessions/:token`).
- Summaries generated on Resolve are saved to the session record but **not** written anywhere else. You can copy/paste into whatever ticketing or documentation system you use.
- Escalating a FlowPilot session routes the escalation package to another ResolutionFlow engineer on your team — not to an external PSA ticket.
- No ticket context is injected into the AI prompt, so the AI starts cold with only what you provide in the intake or first message.
**Standalone use cases:**
- Evaluating ResolutionFlow before committing to a PSA integration
- Troubleshooting internal IT issues that aren't client-facing
- Teams using a PSA ResolutionFlow doesn't integrate with yet
- Knowledge-base research ("what are my options for X") that don't map to a ticket
---
## With a PSA connection (ConnectWise)
When ConnectWise is connected, both modes become ticket-aware and write back to the PSA as a first-class client.
### FlowPilot + PSA
**Starting from a ticket:**
- Click a ticket row (from `/tickets` or the dashboard queue) and pick "Start FlowPilot." The ticket's problem description, recent notes, configurations, company details, and related tickets are auto-injected into the AI's context. No manual retyping.
- The session shows the linked ticket badge in the header.
**During the session:**
- **Share Update** — posts an interim note to the CW ticket with the current AI summary, so stakeholders can see progress without interrupting you.
- **Status changes** — the detail panel and session header let you move the ticket through statuses (New → In Progress → Waiting on Customer → Resolved) directly from ResolutionFlow. Status writes are verified against CW so you're never told "success" when CW silently rejected the change.
- **Resource assignment** — add yourself or a teammate as a co-assignee without touching the owner. If the ticket has no owner yet, assigning sets owner; if there's already an owner, you're added as an additional resource via a CW schedule entry.
**On Resolve:**
- Final summary is posted as a ticket note.
- Ticket status can auto-update to Resolved (per your team's settings).
**On Escalate:**
- The escalation package (problem summary + steps tried) is posted as a note.
- The ticket can be routed via CW's normal escalation rules.
- The next engineer picking up the ticket can auto-start a new session with the full escalation context pre-filled.
**Spin-off tickets (new):**
- During any session, if you discover a separate issue, the AI can propose `create_spin_off_ticket`. Accepting opens the New Ticket modal pre-filled with the current ticket's company and board, so a second ticket is one click away without leaving your session.
### ResolutionAssist + PSA
**Starting from a ticket:**
- Same ticket-context injection as FlowPilot. When opened with a linked ticket, the AI sees company, configs, notes, and related tickets.
- A "New Ticket" button appears in the header — lets you spawn a separate ticket mid-conversation (same flow as FlowPilot's spin-off).
**During the chat:**
- Ask the AI about the ticket directly: *"Summarize what's been tried," "What configs does this company have?"* — the AI already has that context loaded.
- `[ACTIONS]` can include `create_spin_off_ticket` when the AI detects a separate issue surfaced in the conversation.
**Writing back:**
- ResolutionAssist is a lighter-weight mode, so it doesn't auto-post on resolve. You can manually copy the conversation summary to a ticket note if useful.
- Status updates and resource assignment are done via the `/tickets` page rather than the chat UI.
---
## Choosing between them
| I want to… | Use |
|---|---|
| Walk through a known issue type with step-by-step rigor | **FlowPilot** |
| Document every action taken for audit or handoff | **FlowPilot** |
| Escalate with a full context package | **FlowPilot** |
| Ask a question, get an answer, move on | **ResolutionAssist** |
| Paste a screenshot and say "what's wrong here?" | **ResolutionAssist** |
| Stay on the ticket for 2 minutes, not 20 | **ResolutionAssist** |
| Troubleshoot without breaking flow to switch pages | Either, with the linked ticket panel open alongside |
The two modes aren't competitive. A common workflow is to start in ResolutionAssist to scope the problem, then kick off a FlowPilot session when you realize the issue is going to take real diagnosis. Both show up in the unified session history.
---
## Tickets page — the PSA hub
`/tickets` is the CW ticket manager built into ResolutionFlow. With a PSA connection:
- Search and filter tickets by assignment (me / unassigned / specific member via searchable picker), board, status, priority, company, open/closed.
- Slide-out detail panel shows notes, configurations, related tickets, and assignees — all fetched in parallel for fast hydration.
- From the detail panel: change status, add/remove assignees, post notes, or "Start FlowPilot" / "Open in ResolutionAssist" with full context.
- New Ticket modal offers both AI-parse ("Create a high-priority ticket for Acme — Outlook not syncing for jsmith") and a traditional form.
Without a PSA connection, `/tickets` is hidden from the sidebar entirely — there's nothing to show.
---
## Summary
- **FlowPilot** = guided, structured, lifecycle-heavy, ideal for resolvable issues and handoffs.
- **ResolutionAssist** = freeform chat, ideal for scoping and quick answers.
- **Without PSA** = both work, sessions live in ResolutionFlow, summaries are yours to export.
- **With PSA** = both become ticket-aware, write back to CW (notes, status, resources), and can spawn spin-off tickets mid-session.
The AI is the same under the hood. The difference is how much structure you want around the conversation — and how deeply the result needs to integrate with your ticketing system.

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# FlowPilot Migration Plan: Phase 0 Through Phase 7
## Summary
- Stay code-change-free until execution is explicitly requested.
- Implement in commit-sized phases, with Phase 0 as a prerequisite for AI-heavy Phases 2+.
- Use this repos existing `/api/v1/ai-sessions` API namespace instead of the docs generic `/sessions` path.
- Move the existing chat-first `AssistantChatPage` to `/pilot`; `/assistant` becomes a permanent redirect.
- Keep `ai_sessions.session_type` for compatibility, but the user-facing product becomes one FlowPilot surface.
## Phase 0: Prompt Caching Infrastructure
- Consolidate Anthropic prompt caching into `backend/app/core/ai_provider.py`, then route all Anthropic calls through that provider.
- Preserve the existing cached behavior from `assistant_chat_service`, but remove the private duplicate cached implementation once provider parity exists.
- Add cache-control blocks for static system prompt sections and stable tool/context prefixes; keep volatile user messages outside the cached prefix.
- Update one-shot AI generators and `/tickets/ai-parse` to separate stable context from changing request content.
- Instrument every Anthropic response with `cache_read_input_tokens` and `cache_creation_input_tokens`.
- Acceptance: two identical FlowPilot/provider-backed calls within 5 minutes show creation tokens on the first call and read tokens on the second.
## Phase 1: Schema + Route Rename
- Add Alembic migration after current repo head with:
- `session_facts`
- `session_suggested_fixes`
- `draft_templates`
- `account_settings`
- new artifact columns on `ai_sessions`
- provenance columns on `script_templates`
- Create `account_settings` as one lazy row per account:
- `account_id` primary key, FK to `accounts(id)` with cascade delete
- `preferences JSONB NOT NULL DEFAULT '{}'`
- timestamps
- `get_setting(key, default)` helper on the SQLAlchemy model
- `templatize_prompt_enabled` default read as `true` when the row/key is absent
- Apply RLS to all new tenant-scoped tables using the repos `app.current_account_id` policy pattern.
- Route `/pilot` and `/pilot/:sessionId` to the existing chat UI; redirect `/assistant` and `/assistant/:sessionId` permanently.
- Update sidebar, command palette, dashboard cards, session list links, and visible labels from “AI Assistant”/ResolutionAssist to “FlowPilot” where they describe the troubleshooting surface.
- Acceptance: `/pilot` renders the chat UI, `/assistant` redirects, RLS grep/check passes, and no Phase 2 UI is introduced yet.
## Phase 2: What We Know
- Add `FactSynthesisService` for conservative conversion of answers/check outputs into facts.
- Add fact APIs under `/api/v1/ai-sessions/{id}/facts`:
- list, create manual note, update editable fact, soft-delete, promote source item.
- Extend `unified_chat_service` marker parsing with `[PROMOTE]`; do not create a separate marker pipeline.
- Because current questions/checks live in `ai_sessions.pending_task_lane` JSON, Phase 2 must assign stable UUIDs to task-lane questions/actions/checks when they are first persisted. `session_facts.source_ref` points to those stable JSON item IDs; it remains polymorphic and unconstrained at the DB level.
- Add frontend task lane components under the new FlowPilot component namespace:
- `TaskLane`
- `WhatWeKnow`
- `WhatWeKnowItem`
- `AddNoteButton`
- moved/refactored Questions and Diagnostic Checks sections
- Place What We Know above Questions. Facts from questions/checks are read-only at the fact card level; manual and AI-synthesis facts are editable.
- Acceptance: answering a question or completing a check can promote a fact within 2 seconds; manual notes persist; page reload preserves facts; cross-account access is blocked.
## Phase 3: Suggested Fix + Resolve Preview
- Add suggested-fix APIs under `/api/v1/ai-sessions/{id}/suggested-fixes`:
- get active suggested fix
- record decision for one-off/draft-template/build-template/dismissed
- Extend `unified_chat_service` marker parsing with `[SUGGEST_FIX]`; supersede the prior active fix when a new one is persisted.
- Add `ResolutionNoteGeneratorService` that builds the fixed markdown shape:
- Problem
- What we confirmed
- Root cause
- Resolution
- Add preview endpoint at `/api/v1/ai-sessions/{id}/resolution-note/preview`.
- Generate the preview from `ai_sessions`, `session_facts`, active suggested fix, and linked script generations; redact sensitive script parameters.
- Cache preview output by session-state version or content hash; invalidate on fact/suggested-fix/script-generation writes.
- Add `SuggestedFix`, `ResolveButton`, and `ResolutionNotePreview` popover. Debounce preview refresh to 500ms.
- Acceptance: a session with facts and a suggested fix shows a four-section preview; editing a fact refreshes preview; human review confirms no unsupported claims.
## Phase 4: Resolve + Escalate Writebacks
- Add `EscalationPackageGeneratorService` with handoff-oriented markdown:
- Problem
- What weve confirmed
- What weve tried
- Current hypothesis
- Suggested next steps
- Add preview/post endpoints under `/api/v1/ai-sessions/{id}`:
- `/resolution-note/preview`
- `/resolution-note/post`
- `/escalation-package/preview`
- `/escalation-package/post`
- Extend PSA writeback service using the existing PSA provider registry and `post_note` seam.
- Implement “confirm and fire”: engineer edits preview, clicks Confirm & post, then server posts to PSA and stores result metadata.
- Ticket status transitions must verify by re-fetching status; failed verification is surfaced as an error, not silent success.
- Resolving without a linked PSA ticket stores markdown and marks the session resolved without external posting.
- Acceptance: ConnectWise test ticket receives the note/package, status verification works, and unlinked sessions resolve locally.
## Phase 5: Inline Script Generator Integration
- Add inline Script Generator components:
- `TemplateMatchPanel`
- `NoTemplateDialog`
- `ParameterizationPreview`
- For template matches, clicking the suggested fix opens the existing Script Generator flow with parameters prefilled from facts, ticket context, account/PSA config, and AI-suggested values.
- For no-template matches, show the three-option dialog:
- Run as one-off
- Run now, templatize after resolve
- Build as template now
- Persist the selected path on `session_suggested_fixes.user_decision`.
- Add `TemplateExtractionService` for converting concrete scripts into proposed parameter schemas and templated bodies.
- Link every script generation back to `ai_sessions` via existing `script_generations.ai_session_id`.
- `Cmd+K → script` opens the inline generator from the FlowPilot session; no Resolve keyboard shortcut is added.
- Acceptance: matched templates prefill parameters; no-match flow shows three options; all options produce the correct session/template side effects.
## Phase 6: Post-Resolve Templatize Prompt
- Add `TemplatizePrompt` after successful Resolve only when:
- the account setting allows prompts
- the session has pending `draft_templates`
- the user chose “Run now, templatize after resolve”
- Accept flow creates a real `script_templates` row with:
- `source_session_id`
- `source_user_id`
- `source_ticket_ref`
- accepted parameter schema/body edits
- Skip flow marks the draft rejected.
- “Dont ask me again for this team” writes `{"templatize_prompt_enabled": false}` to `account_settings.preferences`.
- Script Library shows a pending-drafts badge/count for the account.
- Acceptance: accept creates a visible template with provenance; skip creates no template; disabled prompt is respected on the next resolve.
## Phase 7: Polish
- Match the authoritative mockup HTML for spacing, colors, typography, and component structure; use PNGs for visual target confirmation.
- Add loading states for fact synthesis, preview generation, template extraction, PSA post/verify, and script generation.
- Add empty states for:
- no facts
- no questions
- no checks
- no suggested fix
- no pending draft templates
- Add keyboard shortcuts except Resolve:
- `Cmd+K` command palette
- `Cmd+Enter` send composer
- `Cmd+G` script generator
- At widths below 1200px, collapse the task lane into a bottom drawer.
- Use existing design tokens where present; add missing tokens only if needed to match the mockups.
- Acceptance: major screens visually compare within the docs tolerance, no horizontal scroll at 1280px, mobile task lane works, and shortcuts do not conflict with browser reload.
## Public Interfaces
- New backend routes use `/api/v1/ai-sessions/{id}/...`, not `/api/v1/sessions/{id}/...`.
- Existing chat creation/message APIs remain compatible.
- `session_type` remains queryable and stored, but frontend routing no longer sends chat sessions to `/assistant`.
- New persistent entities:
- `session_facts`
- `session_suggested_fixes`
- `draft_templates`
- `account_settings`
- New persisted artifact columns on `ai_sessions` store resolution/escalation markdown and PSA post metadata.
## Test Plan
- Migration tests:
- fresh DB upgrade succeeds
- downgrade succeeds if the repo expects reversible migrations
- new tables have RLS enabled/forced
- tenant policy includes `app.current_account_id`
- Backend tests:
- fact CRUD and promotion authorization
- suggested-fix supersession and decision persistence
- preview generation cache invalidation
- Resolve/Escalate local-only behavior without PSA
- PSA status verification failure path
- draft-template accept/reject behavior
- Frontend tests:
- route redirects
- task lane rendering and persistence
- inline editing and preview refresh
- script generator option flows
- templatize prompt settings behavior
- responsive drawer behavior
- Manual QA:
- run through one ConnectWise linked Resolve
- run through one Escalate
- run one template-match script path
- run one no-template draft-template path through post-resolve save
## Assumptions
- Phase 0 is included and must be complete before Phase 2 begins.
- No Resolve keyboard shortcut in this migration.
- Templatize prompt defaults to enabled.
- Resolution notes use engineer review plus Confirm & post, not supervisor staging.
- Existing component folders may be renamed opportunistically, but behavior and route migration matter more than directory-name purity.
- No backfill of What We Know for old sessions.
- Team Wiki compilation, SharePoint integration, marketplace sharing, and confidence-tier UI are out of scope.

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