MurailoBot 🤖

A Telegram bot powered by Google's Gemini AI models that provides intelligent responses through the Telegram messaging platform, with sophisticated user profiling and image analysis capabilities.

Prerequisites

• Go 1.24+
• Telegram Bot Token (from @BotFather)
• Google Gemini API Key

Quick Start

1. Get the bot:

git clone https://github.com/edgard/murailobot.git
cd murailobot

2. Configure:

cp config.yaml.example config.yaml
# Edit config.yaml with your tokens and admin ID

3. Run:

make build
./murailobot

Configuration

Minimal config.yaml example:

telegram:
  token: "your-telegram-bot-token" # Required
  admin_user_id: 123456789 # Required

gemini:
  api_key: "your-gemini-api-key" # Required

For a complete configuration with all options and detailed documentation, see config.yaml.example.

Key configuration sections:

• telegram: Bot token and admin user ID
• database: SQLite database settings
• gemini: Google Gemini API settings
• logger: Logging configuration
• scheduler: Scheduled task settings with cron expressions
• messages: Customizable bot response templates

Docker

docker pull ghcr.io/edgard/murailobot:latest
docker run -v $(pwd)/config.yaml:/app/config.yaml ghcr.io/edgard/murailobot:latest

Both AMD64 and ARM64 architectures are supported.

Usage

Commands

• /start - Introduction to the bot
• /help - Show available commands
• /mrl_reset - Clear chat history and user profiles (admin only)
• /mrl_analyze - Analyze unprocessed messages and update profiles (admin only)
• /mrl_profiles - Show all user profiles in the database (admin only)
• /mrl_edit_user - Edit user profile fields (admin only)

Group Chat Usage

MurailoBot is designed to operate in Telegram group chats:

1. Add the bot to your group
2. Mention the bot (@your_bot_name) in your message to get a response
3. The bot will analyze the conversation context and respond appropriately
4. The bot can analyze both text and images when mentioned
5. Group messages are saved for context and profile generation

Key Features

• AI Conversation: Chat with Google's Gemini AI through Telegram group mentions
• Image Analysis: Process and understand photos shared in the group chat
• Context Management: Persistent conversation history with sophisticated context handling
• User Profiling: Advanced user profiling system with behavioral analysis
• Scheduled Tasks: Automated database maintenance using gocron v2
• Admin Commands: Protected administrative operations with proper access control
• Atomic Database Operations: Consistent data handling with transaction management
• Docker Support: Container images for both AMD64 and ARM64 architectures
• Robust Error Handling: Comprehensive error management with user-friendly messages
• Context-aware Timeouts: Prevent resource leaks in long-running AI operations

Technical Architecture

MurailoBot features a modular architecture with:

• Configuration: Viper-based with validation via go-playground/validator
• Logging: Structured logging using Go's slog
• Database: SQLite with embedded migrations and transaction management
• Scheduler: Task scheduling with gocron v2 for improved job management
• AI Integration: Google Gemini API with context timeout management
• Telegram API: Integration via go-telegram/bot with middleware support
• Middleware: Protection for administrative commands
• Component Lifecycle: Proper startup/shutdown with context management
• Error Handling: Consistent approach across components with structured logging

User Profiling System

MurailoBot includes a sophisticated user profiling system that:

• Automatically analyzes message patterns and content to build psychological profiles
• Maintains user information including aliases, locations, age ranges, and personality traits
• Preserves profile data between sessions and incrementally builds understanding
• Enhances AI responses with contextual user information
• Supports manual profile editing by administrators

The profiling system gathers insights by analyzing:

• Language patterns and word choice
• Emotional expressions and communication style
• Recurring themes in communications
• Cultural references and personal details
• Group interaction dynamics

Development

Building from Source

# Build the application
make build

# Run the application
make run

# Apply database migrations manually
make migrate

Environment Variables

All configuration options can also be set via environment variables with the BOT_ prefix:

export BOT_TELEGRAM_TOKEN="your-telegram-bot-token"
export BOT_GEMINI_API_KEY="your-gemini-api-key"
export BOT_TELEGRAM_ADMIN_USER_ID=123456789

Release Process

This project uses an automated release workflow. Here's how it works:

Automated Releases

When code is pushed to the master branch, the following happens automatically:

1. The CI workflow validates the code with tests and linting
2. Version is automatically bumped based on commit messages:
   • fix: or fix(scope): → patch bump
   • feat: or feat(scope): → minor bump
   • BREAKING CHANGE: in commit body → major bump
3. A new git tag is created with the new version
4. A GitHub release is generated with release notes
5. Binary artifacts are built for multiple platforms
6. Docker images are built and pushed to GitHub Container Registry

For Contributors

• No need to manually create version tags or releases
• Use Conventional Commits format for your commit messages
• The release type (patch, minor, major) is determined by your commit messages

All releases are available on the Releases page.

License

CC0 1.0 Universal - see LICENSE file

Links

• Google Gemini API
• Telegram Bot API