🤖 Advanced AI Telegram Bot

A powerful AI-driven Telegram bot that brings cutting-edge artificial intelligence features to your fingertips.

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✨ Features

💬	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

🚀 Quick Start

# 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

📋 Commands

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

💡 Inline Features

The bot offers powerful inline mode capabilities:

Inline AI Responses

Type @YourBot your question? in any chat to quickly get AI responses without leaving the conversation.

Inline Image Generation

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

1. AI Responses: Type @YourBot What is quantum computing? in any chat
2. Image Generation: Type @YourBot image beautiful sunset over mountains.
3. Select the result when it appears to send it to the chat
4. For complex queries, wait a few seconds and you'll see "Still generating..." which will update with your response
5. 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
6. You can use this in private chats, group conversations, or channels

🏗️ Project Structure

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

🧠 Architecture

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

🛠️ Setup Guide

System Requirements

• Python 3.8 or higher
• MongoDB (local or cloud instance)
• Telegram Bot Token from BotFather
• 1GB+ RAM recommended for image generation

Detailed Installation

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\activate

2. Install Dependencies

# Install required packages
pip install -r requirements.txt

# Verify installations
pip list

3. 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.space

4. Database Setup

# Start MongoDB (if using local instance)
mongod --dbpath /path/to/data/db

# The bot will automatically create required collections

5. Running the Bot

# Start the bot
python run.py

# For production deployment
# Consider using systemd, Docker, or PM2

🔧 Advanced Configuration

Docker Deployment

# Build the Docker image
docker build -t advai-telegram-bot .

# Run the container
docker run -d --name advai-bot advai-telegram-bot

Environment 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/"

💻 Technologies

• 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

🤝 Contributing

Contributions are welcome! Check out our Contributing Guide to get started.

Development Workflow

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Commit your changes: git commit -m 'Add amazing feature'
4. Push to the branch: git push origin feature/amazing-feature
5. Open a Pull Request

📝 License

This project is licensed under the MIT License - see the LICENSE file for details.

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👥 Maintainers

• TechyCSR
• Ankit
• Aarushi

Made with ❤️ by TechyCSR
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