Files
resolutionflow/backend
Michael Chihlas 882f67f42e feat: AI chat session conclusion + survey completion & management
AI Assistant - Conclude Session:
- 3-step modal: select outcome (resolved/escalated/paused), add notes, AI-generated summary
- AI generates structured ticket notes from conversation transcript (PSA-ready format)
- Copy to clipboard for pasting into ticketing systems
- "Resume in New Chat" for paused sessions (pre-loads context into new chat)
- Backend: POST /chats/{id}/conclude endpoint, conclusion_summary/outcome/concluded_at fields
- Migration 048: add conclusion fields to assistant_chats

Survey Completion Flow:
- Email-to-self option after submission (branded HTML email with formatted responses)
- Finish button navigates to /survey/thank-you page
- Thank you page with close-window message and feedback email callout
- Already-submitted state updated with same messaging
- Backend: POST /survey/email-copy public endpoint

Survey Admin Management:
- Read/unread indicators (cyan dot, bold name, auto-mark on expand)
- Unread count stat card
- Per-row context menu: mark read/unread, archive/unarchive, delete
- Bulk actions bar: select all, mark read/unread, archive, delete
- Show Archived toggle to filter archived responses
- Backend: 7 new admin endpoints (read, unread, archive, unarchive, delete, bulk)
- Migration 049: add is_read, archived_at to survey_responses

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-05 20:00:28 -05:00
..

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 Endpoints

Authentication

  • POST /api/v1/auth/register - Register new user
  • POST /api/v1/auth/login - Login (form data)
  • POST /api/v1/auth/login/json - Login (JSON body)
  • POST /api/v1/auth/refresh - Refresh token
  • GET /api/v1/auth/me - Get current user
  • POST /api/v1/auth/logout - Logout

Trees

  • GET /api/v1/trees - List all trees
  • GET /api/v1/trees/categories - List categories
  • GET /api/v1/trees/search?q=query - Search trees
  • GET /api/v1/trees/{id} - Get specific tree
  • POST /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 sessions
  • GET /api/v1/sessions/{id} - Get specific session
  • POST /api/v1/sessions - Start new session
  • PUT /api/v1/sessions/{id} - Update session
  • POST /api/v1/sessions/{id}/complete - Complete session
  • POST /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