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
• Prerequisites
• Installation
• Configuration
• Usage
• Architecture
• Logging
• Contributing
• License

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.

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Developed with ❤️ by Jacob