qa-and-rag-ai-assistant/IMPLEMENTATION_SUMMARY.md

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 - 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 - 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 - 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 - 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 - 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 - COMPLETELY REWRITTEN

New content:

• Complete setup instructions
• Database schema documentation
• API endpoints reference
• Usage flow diagram
• Development guide
• Troubleshooting section

Database Schema

Users Table

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

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:

   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:

   user = await session.execute(select(User).where(User.token == token))
   

6. Bot updates user:

   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:

   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

python init_db.py
# Choose option 1 to create tables

2. Verify Tables

docker exec rag_ai_postgres psql -U postgres -d rag_ai_assistant -c "\dt"
# Should show: users, profiles

3. Test Database Connection

.venv/bin/python database/database.py
# Should create test user and retrieve it

4. Start Application

# 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

# 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

uv pip install -r requirements.txt

Issue: "the greenlet library is required"

Solution: Already added to requirements.txt

uv pip install greenlet==3.0.3

Issue: "Connection refused" to PostgreSQL

Solution: Start Docker services

docker-compose up -d
docker ps  # Verify postgres is running

Issue: Old table structure

Solution: Reset database

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!