Michael Chihlas
d6218f2e07
The test_db fixture calls Base.metadata.create_all on a fresh test DB. That only creates tables for models that have been imported (and thus registered with Base.metadata) by the time the fixture runs. app.main imports app.core.database (which gives us Base) but does NOT eagerly import the model modules — most are pulled in lazily inside scheduler functions (archive_stale_ai_sessions etc.) and route modules. At fixture-setup time, only the handful of models touched by those eager imports are on the metadata, so any test that exercises PSA, network diagrams, ratings, escalations, etc. fails with \`UndefinedTableError: relation "X" does not exist\` and a cascade of 500s on every endpoint that queries the missing table. Adding \`from app import models as _models\` (rather than the bare \`import app.models\` which would shadow the \`app\` FastAPI instance imported just above) pulls in app/models/__init__.py, which itself imports every model module — registering all ~60 tables with Base.metadata before create_all runs. Verified locally: tests/test_psa_writeback_phase4.py went from 1 failed / 6 errors → 4 failed / 3 passed (the cascading errors were masking the actual passes). Co-Authored-By: Claude Opus 4.7 <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.