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 # 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!