Build full-stack chat archive system with AI categorization and integrations

[Copilot]

Implements a production-ready chat archive system with AI-powered categorization, external integrations (Slack, Notion), and comprehensive search capabilities.

Backend (FastAPI + PostgreSQL)

• Authentication: JWT-based auth with bcrypt password hashing, token expiration
• Message Management: CRUD operations, full-text search, filtering by source/category/tags/date
• AI Categorization: OpenAI GPT-3.5 integration for automatic message categorization into 8 predefined categories
• Tag System: Many-to-many relationship with color coding, composite indexes for performance
• Slack Integration: Channel listing, bulk message import with deduplication by source_id
• Notion Sync: Export messages to Notion database with proper property mapping
• Logging: Structured logging with logging module (no print statements), exception tracking with exc_info=True

Frontend (React + Vite)

• Pages: Authentication (login/register), Messages (list/create/search), Tags (CRUD), Integrations (Slack/Notion)
• Search Interface: Multi-field filtering (content, category, source, channel, tags, date range)
• Tag Management: Visual tag creation with color picker, inline tag display
• Auth Flow: JWT stored in localStorage, protected routes with redirect, global auth context

Infrastructure

• Docker: Production (docker-compose.yml) and dev (docker-compose.dev.yml) configs with hot reload
• Database: PostgreSQL 15 with health checks, named volumes for persistence
• Nginx: Reverse proxy for frontend with API proxying at /api
• Scripts: Helper scripts for start/stop/dev/logs operations

API Examples

# Auto-categorization on message creation
POST /api/messages/
{
  "content": "Bug in login form validation",
  "author": "user@example.com"
}
# Returns message with category: "Bug Report"

# Advanced search
POST /api/messages/search
{
  "query": "authentication",
  "category": "Technical",
  "tag_ids": [1, 2],
  "start_date": "2024-01-01T00:00:00"
}

Security & Quality

• Database: Composite index on message_tags(message_id, tag_id), parameterized queries via ORM
• Error Handling: Specific exception types (SlackApiError, HTTPException), no bare except clauses
• Text Processing: Word-boundary text truncation for Notion titles
• Documentation: Architecture, deployment (multi-cloud), security best practices, quick start guide (6 docs, 1800+ lines)
• Testing: Basic test suite with SQLite in-memory DB, FastAPI TestClient
• Security Scan: CodeQL analysis passed (0 vulnerabilities)

Configuration

Environment variables for optional features:

• OPENAI_API_KEY: Enable AI categorization
• SLACK_BOT_TOKEN: Enable Slack import (requires channels:read, channels:history, users:read scopes)
• NOTION_API_KEY + NOTION_DATABASE_ID: Enable Notion sync
• SECRET_KEY: JWT signing (must be changed in production)

System works without external API keys (manual message entry only).

Original prompt

Create a full-stack chat archive system with:

• FastAPI backend with PostgreSQL database
• React frontend with search, filtering, and tagging
• AI-powered auto-categorization using OpenAI API
• Slack integration for importing messages
• Notion API integration for syncing data
• Docker setup for easy deployment
• Authentication and user management

---

✨ Let Copilot coding agent set things up for you — coding agent works faster and does higher quality work when set up for your repo.

[issdandavis]

@githubcopilot just do it