A powerful AI-driven Telegram bot that brings cutting-edge artificial intelligence features to your fingertips.
| 💬 | AI Chat Natural conversations powered by GPT-4o | 🎨 | Image Generation Create stunning images from text descriptions |
| 🔊 | Voice Processing Two-way voice message and text conversion | 📝 | Text Extraction Extract text from any image with OCR |
| 🌐 | Multi-language Support Communicate in your preferred language | 👥 | Group Integration Full AI functionality in group chats |
| 📱 | Inline Mode Generate AI responses and images in any chat | ⚡ | Fast Response Optimized for quick, efficient interactions |
📱 Try it now: t.me/AdvChatGptBot
# Clone repository git clone https://github.com/TechyCSR/AdvAITelegramBot.git # Navigate to directory cd AdvAITelegramBot # Set up virtual environment python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate # Install dependencies pip install -r requirements.txt # Configure your bot cp config.example.py config.py # Edit config.py with your API credentials # Launch! python run.py| Command | Description |
|---|---|
/start | 🏁 Start a conversation with the bot |
/help | ❓ Get help and see available commands |
/generate [prompt] | 🎨 Generate an image from text |
/newchat | 🔄 Clear conversation history |
/settings | ⚙️ Adjust bot preferences |
/rate | ⭐ Rate your experience |
/clear_cache | 🧹 Clear your stored images |
The bot offers powerful inline mode capabilities:
Type @YourBot your question? in any chat to quickly get AI responses without leaving the conversation.
Type @YourBot image your description. to generate and share images instantly in any chat.
Pro Tip: End your AI queries with . or ? and your image prompts with . to trigger generation. If the response takes time, simply add a space every 5-7 seconds to refresh the query without losing your prompt.
How to use inline mode effectively
- AI Responses: Type
@YourBot What is quantum computing?in any chat - Image Generation: Type
@YourBot image beautiful sunset over mountains. - Select the result when it appears to send it to the chat
- For complex queries, wait a few seconds and you'll see "Still generating..." which will update with your response
- If no response appears: Add a space after your prompt every 5-7 seconds to refresh the query while maintaining your place in the generation queue
- You can use this in private chats, group conversations, or channels
Click to expand folder structure
AdvAITelegramBot/ ├── modules/ # Core application modules │ ├── core/ # Core infrastructure components │ │ ├── database.py # DatabaseService with connection pooling │ │ └── service_container.py # Dependency injection container │ ├── models/ # Data models and services │ │ ├── ai_res.py # AI conversation functionality │ │ ├── user_db.py # User data operations │ │ ├── inline_ai_response.py # Inline mode AI responses │ │ └── image_service.py # Image generation and management │ ├── user/ # User interaction modules │ │ ├── start.py # Bot start and onboarding │ │ ├── settings.py # User settings management │ │ ├── help.py # Help and documentation │ │ ├── commands.py # Command handling │ │ ├── assistant.py # Assistant mode settings │ │ ├── lang_settings.py # Language preferences │ │ └── user_support.py # User support functionality │ ├── group/ # Group chat functionality │ │ ├── group_info.py # Group information │ │ ├── group_settings.py # Group configuration │ │ └── new_group.py # New group handling │ ├── image/ # Image processing components │ │ ├── img_to_text.py # OCR and text extraction │ │ ├── image_generation.py # Image generation from prompts │ │ └── inline_image_generation.py # Inline mode image generation │ ├── speech/ # Voice processing components │ │ ├── voice_to_text.py # Speech recognition │ │ └── text_to_voice.py # Text-to-speech conversion │ ├── chatlogs.py # Logging user interactions │ ├── feedback_nd_rating.py # User feedback system │ ├── lang.py # Language translation │ └── maintenance.py # Maintenance utilities ├── database/ # Database configuration ├── generated_images/ # Local storage for generated images ├── sessions/ # Pyrogram session files ├── logs/ # Application logs ├── assets/ # Static assets ├── ImgGenModel/ # Image generation models ├── run.py # Main application entry point ├── config.py # Configuration settings ├── requirements.txt # Python dependencies ├── Dockerfile # Container configuration └── LICENSE # MIT License The bot employs a modern, modular architecture with several key design patterns:
- 💉 Service Container: Centralized dependency injection for clean, testable code
- 🔄 Singleton Database Service: Efficient MongoDB connection pooling
- 📊 Model-View Pattern: Separation of data and presentation layers
- 🔄 Async Processing: Non-blocking operations for inline queries and image generation
- Python 3.8 or higher
- MongoDB (local or cloud instance)
- Telegram Bot Token from BotFather
- 1GB+ RAM recommended for image generation
1. Environment Setup
# Make sure you have Python 3.8+ installed python --version # Create and activate virtual environment python -m venv .venv source .venv/bin/activate # On Windows: .venv\Scripts\activate2. Install Dependencies
# Install required packages pip install -r requirements.txt # Verify installations pip list3. Configuration
Create a config.py file with your credentials:
BOT_TOKEN = "your_telegram_bot_token" # From BotFather API_KEY = "your_telegram_api_key" # From my.telegram.org API_HASH = "your_telegram_api_hash" # From my.telegram.org DATABASE_URL = "mongodb://localhost:27017/" ADMINS = [123456789] # Your Telegram user ID OCR_KEY = "your_ocr_space_api_key" # From ocr.space4. Database Setup
# Start MongoDB (if using local instance) mongod --dbpath /path/to/data/db # The bot will automatically create required collections5. Running the Bot
# Start the bot python run.py # For production deployment # Consider using systemd, Docker, or PM2Docker Deployment
# Build the Docker image docker build -t advai-telegram-bot . # Run the container docker run -d --name advai-bot advai-telegram-botEnvironment Variables
You can use environment variables instead of config.py:
export BOT_TOKEN="your_telegram_bot_token" export API_KEY="your_telegram_api_key" export API_HASH="your_telegram_api_hash" export DATABASE_URL="mongodb://localhost:27017/"- Pyrogram: Modern Telegram client library
- MongoDB: NoSQL database for user data
- GPT-4o: Advanced language model
- OCR.space: Text extraction API
- Various Image Generators: High-quality AI image creation
Contributions are welcome! Check out our Contributing Guide to get started.
Development Workflow
- Fork the repository
- Create a feature branch:
git checkout -b feature/amazing-feature - Commit your changes:
git commit -m 'Add amazing feature' - Push to the branch:
git push origin feature/amazing-feature - Open a Pull Request
This project is licensed under the MIT License - see the LICENSE file for details.