moja-clickhouse-agent 1.0.4

🚀 ClickHouse AI Agent - Intelligent database analysis and operations

🚀 Moja - ClickHouse AI Agent

A beautiful, intelligent CLI agent for ClickHouse database analysis and operations.

✨ Features

• 🤖 AI-Powered: Intelligent natural language interface for ClickHouse operations
• 📊 Data Analysis: Comprehensive table analysis with statistics and insights
• 📈 Visualizations: Create beautiful charts and graphs from query results
• 📥 Data Loading: Load CSV, JSON files into ClickHouse with auto-schema detection
• 📤 Data Export: Export query results to various formats (CSV, JSON, Parquet, Excel)
• 🔧 Database Management: Table optimization, system information, and more
• 🎨 Beautiful CLI: Rich, colorful interface with progress bars and tables

🛠️ Installation

Quick Install (Recommended)

Install globally with pipx for the best experience:

pipx install moja-clickhouse-agent

Then run:

moja

This will start the interactive onboarding flow to configure your database and AI provider.

Manual Installation

# Clone the repository
git clone https://github.com/vish/moja.git
cd moja

# Install dependencies
pip install -r requirements.txt

# Set up your configuration
export OPENROUTER_API_KEY="your-api-key"
export CLICKHOUSE_HOST="localhost"
export CLICKHOUSE_PORT="8123"

🚀 Quick Start

Interactive Chat Mode

moja chat

Execute Single Query

moja query "SELECT * FROM my_table LIMIT 10"

Analyze Table

moja analyze my_table --deep

Load Data

moja load-data data.csv my_table

🔧 Configuration

Create a .env file or use environment variables:

# ClickHouse Configuration
CLICKHOUSE_HOST=localhost
CLICKHOUSE_PORT=8123
CLICKHOUSE_USERNAME=default
CLICKHOUSE_PASSWORD=
CLICKHOUSE_DATABASE=default

# OpenRouter Configuration
OPENROUTER_API_KEY=your-api-key-here
OPENROUTER_MODEL=openai/gpt-4o-mini

🤖 AI Capabilities

Moja understands natural language commands like:

• "Show me all tables in the database"
• "Analyze the user_events table and find patterns"
• "Create a bar chart showing sales by month"
• "Load the CSV file into a new table"
• "Export the query results to Excel"

🏗️ Architecture

Built with modern Python tools:

• Typer: Beautiful CLI interface
• Rich: Colorful terminal output
• ClickHouse Connect: Fast database connectivity
• OpenRouter: AI model access
• Plotly: Interactive visualizations
• Pandas: Data manipulation

📖 Examples

Data Analysis

# Interactive session
python main.py chat

> "Analyze my sales_data table and show me the top products"
> "Create a line chart showing revenue trends over time"
> "Find any anomalies in the user behavior data"

Batch Operations

# Load multiple files
python main.py load-data sales_2023.csv sales_data
python main.py load-data users.json user_profiles

# Analyze and export
python main.py analyze sales_data --deep
python main.py query "SELECT * FROM sales_data WHERE revenue > 1000" --format csv --save results.csv

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📄 License

MIT License - see LICENSE file for details.

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Built with ❤️ for the ClickHouse community