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Telegram AI Chatbot

A feature-rich Telegram chatbot powered by Google’s Gemini AI, designed to engage users with insightful and thought-provoking conversations. This bot leverages Flask for handling webhooks, SQLite for maintaining chat history, and includes robust rate limiting and error handling to ensure a smooth user experience.

Table of Contents

Features

  • AI-Powered Conversations: Utilizes Google’s Gemini 1.5-flash model to generate intelligent and engaging responses.
  • Persistent Chat History: Stores user interactions in a SQLite database for context-aware conversations.
  • Rate Limiting: Ensures fair usage by limiting the number of requests per user.
  • Multithreading: Handles multiple user requests concurrently for improved performance.
  • Webhook Integration: Uses Flask to manage Telegram webhooks securely.
  • Error Handling & Logging: Comprehensive logging for monitoring and troubleshooting.
  • Customizable AI Persona: Configured to behave as Albert, a distinguished astrophysicist with a unique communication style.

Prerequisites

  • Python 3.7 or higher
  • A Telegram account
  • Telegram Bot Token
  • Google Gemini API Key
  • Hosting service (e.g., Heroku, AWS, etc.) to run the Flask app and expose a public URL

Installation

  1. Clone the Repository

  2. Create a Virtual Environment

    python3 -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

  3. Install Dependencies

    pip install -r requirements.txt

  4. Set Up Environment Variables

    Create a .env file in the root directory and add the following variables:

    TELEGRAM_BOT_TOKEN=your_telegram_bot_token
GEMINI_API_KEY=your_gemini_api_key
WEBHOOK_URL_BASE=https://your-domain.com
PORT=5000  # Or any other port you prefer

Configuration

The bot requires several environment variables to function correctly. Ensure you have the following variables set in your .env file:

  • TELEGRAM_BOT_TOKEN: Your Telegram bot token obtained from BotFather.
  • GEMINI_API_KEY: Your API key for Google’s Gemini AI.
  • WEBHOOK_URL_BASE: The base URL where your Flask app is hosted (e.g., https://your-domain.com).
  • PORT: The port on which the Flask app will run (default is 5000).

Example .env file:

TELEGRAM_BOT_TOKEN=123456789:ABCDEFGHIJKLMNOPQRSTUVWXYZ
GEMINI_API_KEY=your_gemini_api_key
WEBHOOK_URL_BASE=https://your-domain.com
PORT=5000

Usage

  1. Initialize the Database

    The database is automatically initialized when you run the bot for the first time. It creates a chat_history.db SQLite database to store user interactions.

  2. Run the Bot

    python your_bot_script.py

    Replace your_bot_script.py with the name of your Python script containing the bot code.

  3. Set Up Webhook

    The bot automatically sets up the webhook using the WEBHOOK_URL_BASE and BOT_TOKEN. Ensure that your hosting service correctly points to the webhook URL.

  4. Interact with the Bot

    Open Telegram, find your bot by its username, and start interacting!

Architecture

Main Components

  • Flask App: Handles incoming webhook requests from Telegram.
  • Telebot: Manages Telegram bot interactions and messaging.
  • SQLite Database: Stores chat history for each user to maintain context.
  • Google Generative AI (Gemini): Generates AI-powered responses based on user input and chat history.
  • Rate Limiter: Controls the number of requests a user can make within a specific timeframe to prevent abuse.
  • Thread Pool Executor: Manages concurrent processing of user messages.
  • Logging: Captures errors and warnings for monitoring and debugging.

Workflow

  1. Webhook Reception: Telegram sends updates to the Flask webhook route.
  2. Message Queuing: Incoming messages are placed in a thread-safe queue.
  3. Worker Threads: Multiple worker threads process messages concurrently.
  4. Input Validation: Validates user input for length and content.
  5. Rate Limiting: Checks if the user has exceeded the request limit.
  6. AI Response Generation: Fetches chat history and generates a response using Gemini AI.
  7. Response Delivery: Sends the formatted response back to the user via Telegram.

Logging

The bot is configured to log errors and warnings to a file named bot_errors.log. This helps in monitoring the bot’s performance and troubleshooting issues.

logging.basicConfig(filename='bot_errors.log', level=logging.ERROR)

License

This project is licensed under the MIT License.

Developed with ❤️ by Jacob