# PostgreSQL Database Implementation Summary ## What Was Done Successfully migrated from in-memory fake_db dictionaries to PostgreSQL with async SQLAlchemy ORM. ## Files Modified ### 1. [database/database.py](database/database.py) - **COMPLETELY REWRITTEN** **Changes:** - ✅ Converted from synchronous to **async SQLAlchemy** (using `asyncpg` driver) - ✅ Added proper `User` model with: - Auto-increment `id` as primary key - Unique indexed `telegram_id` and `token` - `created_at` and `updated_at` timestamps - Composite index on `token` and `status` - ✅ Added `Profile` model with: - All fields from your Pydantic model - Email as unique indexed field - Timestamps - ✅ Created `get_db()` dependency for FastAPI - ✅ Added `init_db()` and `drop_db()` utility functions - ✅ Configured connection pooling and async engine ### 2. [app.py](app.py) - **MAJOR UPDATES** **Changes:** - ✅ Removed `profile_db = {}` in-memory dict - ✅ Added database imports and `Depends(get_db)` to all endpoints - ✅ Added `@app.on_event("startup")` to initialize DB on app start - ✅ Updated `/profile` POST endpoint: - Now saves to PostgreSQL `profiles` table - Handles create/update logic - Properly commits transactions - ✅ Updated `/profile/{email}` GET endpoint: - Queries from PostgreSQL - Converts DB model to Pydantic response - ✅ Updated `/login` endpoint: - Creates `User` record with pending status - Stores in PostgreSQL instead of dict - ✅ Updated `/check-auth/{token}` endpoint: - Queries user by token from PostgreSQL - Returns proper status - ✅ Updated `/database/tokens` endpoint: - Lists all users from database ### 3. [bot.py](bot.py) - **MAJOR REFACTORING** **Changes:** - ✅ Removed all references to `fake_db` - ✅ Removed `app.db = fake_db` synchronization code - ✅ Added proper database imports - ✅ Updated `/start` command handler: - Uses `AsyncSessionLocal()` for DB sessions - Queries user by token - Updates telegram_id, username, and status - Proper error handling with rollback - ✅ Added `init_db()` call in `start_bot()` ### 4. [requirements.txt](requirements.txt) - **CREATED** **New dependencies:** - FastAPI + Uvicorn - Pydantic with email support - SQLAlchemy 2.0 with async support - asyncpg (PostgreSQL async driver) - psycopg2-binary (backup driver) - greenlet (required for SQLAlchemy async) - aiogram 3.3.0 (Telegram bot) - minio (file storage) - python-dotenv - Testing: pytest, pytest-asyncio, httpx ### 5. [init_db.py](init_db.py) - **CREATED** **Purpose:** Interactive script to initialize or reset database **Features:** - Option 1: Create tables - Option 2: Drop and recreate (reset) - Safe with confirmation prompts ### 6. [README.md](README.md) - **COMPLETELY REWRITTEN** **New content:** - Complete setup instructions - Database schema documentation - API endpoints reference - Usage flow diagram - Development guide - Troubleshooting section ## Database Schema ### Users Table ```sql CREATE TABLE users ( id SERIAL PRIMARY KEY, telegram_id INTEGER NOT NULL UNIQUE, token VARCHAR(255) NOT NULL UNIQUE, username VARCHAR(100), status VARCHAR(50) NOT NULL DEFAULT 'pending', created_at TIMESTAMP NOT NULL DEFAULT NOW(), updated_at TIMESTAMP NOT NULL DEFAULT NOW() ); CREATE INDEX idx_token_status ON users(token, status); CREATE UNIQUE INDEX ix_users_telegram_id ON users(telegram_id); CREATE UNIQUE INDEX ix_users_token ON users(token); ``` ### Profiles Table ```sql CREATE TABLE profiles ( id SERIAL PRIMARY KEY, email VARCHAR(255) NOT NULL UNIQUE, name VARCHAR(255) NOT NULL, position VARCHAR(255) NOT NULL, competencies TEXT, experience TEXT, skills TEXT, country VARCHAR(100), languages VARCHAR(255), employment_format VARCHAR(100), rate VARCHAR(100), relocation VARCHAR(100), cv_url VARCHAR(500), created_at TIMESTAMP NOT NULL DEFAULT NOW(), updated_at TIMESTAMP NOT NULL DEFAULT NOW() ); CREATE UNIQUE INDEX ix_profiles_email ON profiles(email); ``` ## Architecture Benefits ### Before (In-Memory Dicts) ❌ Data lost on restart ❌ No persistence ❌ No concurrent access control ❌ No data validation at DB level ❌ No relationships or constraints ❌ No transaction safety ### After (PostgreSQL + SQLAlchemy) ✅ **Persistent** - Data survives restarts ✅ **ACID compliant** - Transaction safety ✅ **Concurrent** - Handle multiple requests ✅ **Indexed** - Fast queries on telegram_id, token, email ✅ **Constraints** - Unique tokens, emails ✅ **Timestamps** - Track created_at, updated_at ✅ **Async** - Non-blocking database operations ✅ **Pooling** - Efficient connection management ## How It Works Now ### Authentication Flow 1. User visits website → `GET /login` 2. FastAPI creates new `User` record in PostgreSQL: ```python User(telegram_id=0, token=uuid4(), status='pending') ``` 3. Returns Telegram bot URL with token 4. User clicks link → Opens bot → Sends `/start {token}` 5. Bot queries database for token: ```python user = await session.execute(select(User).where(User.token == token)) ``` 6. Bot updates user: ```python user.telegram_id = message.from_user.id user.username = message.from_user.username user.status = 'success' await session.commit() ``` 7. Website polls `/check-auth/{token}` → Gets auth status from DB ### Profile Management Flow 1. User submits profile → `POST /profile` 2. FastAPI uploads CV to MinIO 3. Checks if profile exists: ```python existing = await db.execute(select(Profile).where(Profile.email == email)) ``` 4. Updates existing or creates new profile 5. Commits to PostgreSQL ## Testing the Implementation ### 1. Initialize Database ```bash python init_db.py # Choose option 1 to create tables ``` ### 2. Verify Tables ```bash docker exec rag_ai_postgres psql -U postgres -d rag_ai_assistant -c "\dt" # Should show: users, profiles ``` ### 3. Test Database Connection ```bash .venv/bin/python database/database.py # Should create test user and retrieve it ``` ### 4. Start Application ```bash # Option A: Together python bot.py # Option B: Separate terminals uvicorn app:app --reload # In another terminal: python -c "from bot import start_bot; import asyncio; asyncio.run(start_bot())" ``` ### 5. Test Endpoints ```bash # Test login curl http://localhost:8000/login # Test check-auth curl http://localhost:8000/check-auth/{token} # Test tokens list curl http://localhost:8000/database/tokens ``` ## Common Issues & Solutions ### Issue: "No module named 'sqlalchemy'" **Solution:** Install dependencies ```bash uv pip install -r requirements.txt ``` ### Issue: "the greenlet library is required" **Solution:** Already added to requirements.txt ```bash uv pip install greenlet==3.0.3 ``` ### Issue: "Connection refused" to PostgreSQL **Solution:** Start Docker services ```bash docker-compose up -d docker ps # Verify postgres is running ``` ### Issue: Old table structure **Solution:** Reset database ```bash python init_db.py # Choose option 2 (reset) ``` ## Next Steps (Optional Improvements) 1. **Add foreign key relationship** between users and profiles 2. **Implement token expiration** (add expires_at column) 3. **Add database migrations** (Alembic) 4. **Add indexes** for common queries 5. **Implement connection pooling tuning** for production 6. **Add Redis caching** for frequently accessed data 7. **Implement soft deletes** (deleted_at column) 8. **Add audit logs** table for tracking changes 9. **Create database backup scripts** 10. **Add monitoring** with Prometheus/Grafana ## Code Quality Improvements Made - ✅ **Type hints** throughout database code - ✅ **Docstrings** on all major functions - ✅ **Error handling** with try/except and rollback - ✅ **Session management** using context managers - ✅ **Connection pooling** with proper configuration - ✅ **Index optimization** on frequently queried fields - ✅ **Async/await** pattern throughout - ✅ **Environment variables** for all config - ✅ **Dependency injection** with FastAPI Depends() ## Summary Your application now has a **production-ready database layer** with: - ✅ Proper ORM models - ✅ Async database operations - ✅ Transaction safety - ✅ Data persistence - ✅ Proper indexing - ✅ Error handling - ✅ Clean architecture All the logic for authentication tokens and profile storage has been successfully migrated from in-memory dictionaries to PostgreSQL!