Michael Chihlas
52f6d0308f
GET /api/v1/analytics/flowpilot/escalations?period={7d,30d,90d}
Computes the in-product wedge metric for Escalation Mode: average / median /
p95 seconds between SessionHandoff.claimed_at and the first ai_session_step
created on the same session after that timestamp. Account-scoped, role-gated
to engineer-or-admin.
The metric is intentionally NOT called "minutes recovered" — that's the
two-metric framing locked by /codex review: this in-product number must be
paired with manual baseline (the verbal-handoff stopwatch from The Assignment)
to produce the savings claim. Schema's `metric_definition` field surfaces the
disclaimer in every response so callers don't oversell it.
Implementation notes:
- Uses correlated scalar subquery for first-step-after-claim per handoff,
aggregates avg/median/p95 in Python (~1k rows/account/month is well within
budget; cleaner than percentile_cont gymnastics in SQL)
- Excludes unclaimed handoffs (claimed_at IS NULL)
- Counts claimed-but-no-action handoffs in n_handoffs_claimed but not in
n_handoffs_with_action — surfaces the conversion-rate signal
- Floors negative deltas at 0 to handle clock-drift edge cases
Tests cover happy path, zero-data, claimed-but-no-action accounting, period
window filtering, multi-handoff aggregation, multi-tenant isolation (Phase 4
RLS landmine pattern), viewer-role 403 gate, and period validation. 9 tests,
all green. No regressions in existing handoff_manager / session_handoffs
suites.
First piece of the Approach A wedge build per
docs/plans/2026-04-27-escalation-mode-wedge-design.md. Unblocks the queue
stat-card and the analytics page.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Troubleshooting Decision Tree - Backend API
FastAPI backend for the Troubleshooting Decision Tree application.
Quick Start
1. Set up Python environment
cd backend
python -m venv venv
# Windows
venv\Scripts\activate
# macOS/Linux
source venv/bin/activate
pip install -r requirements.txt
2. Start PostgreSQL database
Using Docker:
docker-compose up -d
Or install PostgreSQL locally and create a database:
CREATE DATABASE decision_tree;
3. Configure environment
Copy the example env file and update as needed:
cp .env.example .env
4. Run database migrations
alembic upgrade head
5. Start the server
uvicorn app.main:app --reload --host 0.0.0.0 --port 8000
The API will be available at:
- API: http://localhost:8000
- Docs: http://localhost:8000/api/docs
- ReDoc: http://localhost:8000/api/redoc
API Endpoints
Authentication
POST /api/v1/auth/register- Register new userPOST /api/v1/auth/login- Login (form data)POST /api/v1/auth/login/json- Login (JSON body)POST /api/v1/auth/refresh- Refresh tokenGET /api/v1/auth/me- Get current userPOST /api/v1/auth/logout- Logout
Trees
GET /api/v1/trees- List all treesGET /api/v1/trees/categories- List categoriesGET /api/v1/trees/search?q=query- Search treesGET /api/v1/trees/{id}- Get specific treePOST /api/v1/trees- Create tree (engineer/admin)PUT /api/v1/trees/{id}- Update tree (engineer/admin)DELETE /api/v1/trees/{id}- Delete tree (admin)
Sessions
GET /api/v1/sessions- List user's sessionsGET /api/v1/sessions/{id}- Get specific sessionPOST /api/v1/sessions- Start new sessionPUT /api/v1/sessions/{id}- Update sessionPOST /api/v1/sessions/{id}/complete- Complete sessionPOST /api/v1/sessions/{id}/export- Export session
Development
Create new migration
alembic revision --autogenerate -m "description"
Run migrations
alembic upgrade head
Rollback migration
alembic downgrade -1
Project Structure
backend/
├── alembic/ # Database migrations
│ └── versions/
├── app/
│ ├── api/
│ │ ├── endpoints/ # API route handlers
│ │ ├── deps.py # Dependencies (auth, etc.)
│ │ └── router.py # Main router
│ ├── core/
│ │ ├── config.py # Settings
│ │ ├── database.py # DB connection
│ │ └── security.py # JWT, password hashing
│ ├── models/ # SQLAlchemy models
│ ├── schemas/ # Pydantic schemas
│ └── main.py # FastAPI app
├── tests/
├── alembic.ini
├── docker-compose.yml
├── requirements.txt
└── README.md