Michael Chihlas
625dba7548
Adds the load-bearing structural feature of the FlowPilot migration: a
"What we know" panel that holds confirmed facts for a session, fed by AI
[PROMOTE] markers and engineer-added notes. Facts feed the resolution
note preview (Phase 3) and survive across turns via stable UUIDs assigned
to pending_task_lane items.
Backend:
- FactSynthesisService: create/update/soft-delete facts with atomic
state_version bumps; LLM-backed synthesize_from_question/check on the
fact_synthesis (Haiku) action tier per Section 6.6.
- /api/v1/ai-sessions/{id}/facts CRUD + /facts/promote (proposed_text or
via synthesis). PATCH returns 403 for question/diagnostic_check facts
(edit the source item instead, Section 7.3).
- unified_chat_service: [PROMOTE] marker parser (JSON-block per Section
8.1 spec drift note), stable-UUID assignment for pending_task_lane
questions/actions preserved by exact text/label match across turns.
- ASSISTANT_SYSTEM_PROMPT: documents [PROMOTE] format, when to/not to
emit, hallucination guardrails, source_ref handling.
- 17 tests covering parser, stable IDs, service validation, CRUD,
editability rule, both promote modes, 422 null-synthesis path,
state_version invariant.
Frontend:
- src/components/pilot/sections/{WhatWeKnow,WhatWeKnowItem,AddNoteButton}
— green-gradient section above Questions, dashed-circle check, inline
edit/delete gated by the server's editable flag.
- TaskLane gains a whatWeKnowSlot prop (existing assistant/ folder kept
per the doc's "rename is opportunistic" guidance).
- AssistantChatPage fetches facts on selectChat and refetches after each
chat send (so [PROMOTE]-synthesized facts appear immediately); auto-
opens the lane when facts exist.
Verification: end-to-end smoke against the local docker stack confirms
all five endpoints (list/create/patch/delete/promote) plus the 403
editability rule. pytest suite verifies the same with mocked LLM. Live
[PROMOTE] flow remains untested until used in the UI — the marker shape
is covered by parser tests.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
ResolutionFlow
Stop writing ticket notes. Start generating them.
ResolutionFlow is an AI-powered troubleshooting platform for MSP professionals. Engineers follow guided flows while an AI copilot assists — and documentation writes itself as a byproduct of the work.
Production: resolutionflow.com
Quick Start
# Prerequisites: Docker, Python 3.11+, Node.js 20+
# Start PostgreSQL
docker start patherly_postgres
# Backend
cd backend
source venv/bin/activate
pip install -r requirements.txt
alembic upgrade head
uvicorn app.main:app --reload
# Frontend (separate terminal)
cd frontend
npm install
npm run dev
- Frontend: http://localhost:5173
- Backend API: http://localhost:8000
- API Docs: http://localhost:8000/api/docs
See DEV-ENV.md for full environment setup (devserver, Docker, CORS).
Features
FlowPilot AI Copilot
Like having a senior engineer on every call. FlowPilot guides troubleshooting decisions, suggests next steps with context-aware intelligence, and automatically captures documentation as a byproduct of the session.
- Confidence-tiered model routing (fast responses for simple steps, deeper reasoning for complex decisions)
- AI-generated ticket summaries and session documentation
- Standalone assistant chat with RAG for open-ended troubleshooting
- Knowledge Flywheel: AI analyzes completed sessions and proposes new flows automatically
Guided Flows
- Troubleshooting Flows — Decision trees with branching paths for diagnosing issues
- Procedural Flows (Projects) — Step-by-step checklists for onboarding, migrations, deployments
- Maintenance Flows — Scheduled recurring tasks with batch execution across multiple targets
- Visual Flow Editor with drag-and-drop canvas, undo/redo, markdown support
- AI Flow Builder — describe what you need, get a complete flow generated
Auto-Documentation
Every session generates timestamped, detailed notes formatted for your PSA. Engineers never write another ticket note.
- Export to Markdown, plain text, or HTML
- Sensitive data redaction
- One-click push to ConnectWise PSA tickets
ConnectWise PSA Integration
- Post session documentation directly to ConnectWise tickets as internal notes
- Pull ticket details and client context into FlowPilot sessions
- Member mapping between ResolutionFlow and ConnectWise users
- Credentials encrypted at rest (Fernet), stored per-team
Team & Knowledge Management
- Role-based access (super_admin, team_admin, engineer, viewer)
- Shared flow library with categories, tags, folders, full-text search
- Step Library — reusable troubleshooting steps with ratings and reviews
- Session sharing via link (authenticated and public views)
- Escalation workflow with AI-enhanced briefing packages
- Flow proposals from AI analysis (review queue for team leads)
Tech Stack
| Layer | Technology |
|---|---|
| Frontend | React 19, TypeScript, Vite, Tailwind CSS v4 |
| State | Zustand (immer + zundo for undo/redo) |
| Routing | React Router v7 |
| Canvas | @xyflow/react (React Flow) + dagre |
| Backend | Python FastAPI, async SQLAlchemy 2.0 + asyncpg |
| Database | PostgreSQL 16 |
| Migrations | Alembic (75+ migrations) |
| Auth | JWT (python-jose) + bcrypt, refresh token rotation |
| AI | Anthropic Claude API (tiered model routing) |
| Embeddings | Voyage AI (semantic search) |
| Scheduling | APScheduler 3.x (async) |
| Analytics | PostHog |
| Hosting | Railway (auto-deploy on push to main) |
Project Structure
patherly/
├── backend/
│ ├── app/
│ │ ├── main.py # FastAPI entry point
│ │ ├── api/endpoints/ # Route handlers (35+ endpoints)
│ │ ├── core/ # Config, database, permissions, security
│ │ ├── models/ # SQLAlchemy models
│ │ ├── schemas/ # Pydantic schemas
│ │ └── services/psa/ # PSA provider abstraction layer
│ ├── alembic/ # Database migrations
│ └── tests/ # Integration tests (100+)
├── frontend/
│ ├── src/
│ │ ├── components/ # UI components by domain
│ │ ├── pages/ # Page components
│ │ ├── store/ # Zustand stores
│ │ └── types/ # TypeScript interfaces
├── docs/ # Design docs, plans, ConnectWise reference
├── brand-assets/ # SVGs, brand guide
├── CLAUDE.md # AI assistant project context
├── CURRENT-STATE.md # Detailed feature status
└── CHANGELOG.md # Release history
Running Tests
# Backend integration tests
cd backend
pytest --override-ini="addopts="
# Frontend build (stricter than tsc --noEmit)
cd frontend
npm run build
Documentation
| Document | Purpose |
|---|---|
| CLAUDE.md | Full project context for AI-assisted development |
| CURRENT-STATE.md | Detailed feature status |
| 03-DEVELOPMENT-ROADMAP.md | Development roadmap |
| UI-DESIGN-SYSTEM.md | Design system (Slate & Ice) |
| DEV-ENV.md | Development environment setup |
| CHANGELOG.md | Release history |
License
Proprietary. All rights reserved.