8e9d22e0e0095b2e78d1dbaf39ebaf9b66ba18e6
Adds the dedicated 4-section handoff-context view that renders BEFORE
the FlowPilot session for senior techs picking up an escalated
session, then dissolves on "Start here". This is the wedge's
demonstrable magic moment — what the GTM Loom records.
- HandoffContextScreen.tsx: pure presentational, takes a HandoffResponse
plus onStartHere / onDismiss callbacks. Sections: header
(problem summary, domain, step count, escalated-time, priority badge),
"What's been tried" (engineer notes + step-count affordance), "AI
assessment" (likely_cause / suggested_steps / confidence badge), Start
here CTA. Confidence badge accepts both numeric (0..1) and string
("low"/"medium"/"high") shapes — backend currently emits the latter.
Renders an explicit "assessment unavailable" branch when
ai_assessment_data is null (the 5s timeout from 9bdd995 fired).
Honors prefers-reduced-motion (animate-fade-in vs animate-slide-up).
ARIA dialog + focus on the primary CTA. Esc dismisses when used as a
re-openable overlay; pre-claim, Start here is the only exit.
- FlowPilotSessionPage.tsx: on /pilot/:id?pickup=true, fetch the
handoff list via handoffsApi.listHandoffs (account-scoped via RLS,
no claim required) and find the latest unclaimed escalate handoff.
If found, render the magic-moment screen and skip the regular
loadSession (the senior isn't yet escalated_to_id, so GET would
404). Start here calls claimHandoff, drops the pickup query param,
dismisses the screen — the existing loadSession effect then fires
because the senior is now escalated_to_id. A "Context" toolbar
button on active sessions re-opens the screen as a dismissible
overlay (visible only when the senior arrived via the magic-moment
flow this session — handoff lookup on demand).
Verified end-to-end against the running dev stack: listHandoffs
returns the unclaimed handoff with full payload; claim flips session
status from escalated → active; subsequent GET succeeds. tsc -b clean.
Defers (TODO followups): suggested-step chips below the chat input
that prefill on click (requires threading through to
FlowPilotMessageBar); snapshot expansion to include the recent
diagnostic steps pre-claim; toolbar Context button on sessions where
the senior didn't arrive via magic-moment.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
fix: replace all remaining old brand tokens (text-brand-dark, border-brand-border, bg-white opacity)
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.
Description
Troubleshooting decision tree application for MSP engineers - automatically generates professional documentation from guided diagnostic workflows
Languages
Python
54.7%
TypeScript
43.5%
HTML
1.1%
CSS
0.6%