SQL-LLM-Agent

Overview

SQL-LLM-Agent is a cutting-edge project that leverages OpenAI's GPT-3.5, the LangChain framework, and an Agentic RAG (Retrieval-Augmented Generation) pipeline to transform the way we interact with databases. This system is designed to translate natural language queries into SQL commands, enabling seamless interaction with a MySQL database. It also includes advanced features like transaction tracking, automated actions.

Features

• AI-Powered SQL Query Generation: Translates natural language input into SQL queries using GPT-3.5.
• Agentic RAG Pipeline: Combines retrieval and generation techniques for accurate and context-aware responses.
• MySQL Integration: Securely connects to a MySQL database and executes queries.
• User-Friendly Interaction: Allows non-technical users to interact with databases using simple, natural language queries.
• Error Handling: Robust handling of errors during query execution, ensuring reliability.
• Future Capabilities: Transaction and wallet tracking, and potential automated actions like ordering food.

  Project Structure

SQL-LLM-Agent/
├── agents/
│   ├── __init__.py
│   ├── query_agent.py
├── db/
│   ├── __init__.py
│   ├── connection.py
│   ├── executor.py
├── models/
│   ├── llm_model.py
├── prompts/
│   ├── prompt_template.py
├── utils/
│   ├── error_handling.py
│   ├── validation.py
├── tests/
│   ├── test_agent.py
│   ├── test_db.py
│   ├── test_models.py
├── README.md
├── requirements.txt
└── main.py 

Getting Started

Prerequisites

• Python 3.10+
• MySQL: Ensure that a MySQL server is running and accessible.
• API Keys: Obtain an API key from OpenAI for GPT-3.5.

Installation

Clone the repository:

git clone https://github.com/your-username/SQL-LLM-Agent.git
cd SQL-LLM-Agent

Install the required dependencies:

pip install -r requirements.txt

Set up environment variables:

export OPENAI_API_KEY='your-openai-api-key'
export MYSQL_USER='your-mysql-username'
export MYSQL_PASSWORD='your-mysql-password'
export MYSQL_DB='your-database-name'
export MYSQL_HOST='localhost'

Usage

Start the Application:

python utils.py

Interacting with the Agent:

• You can input natural language queries, like “What is the total value of all items in stock?”
• The agent will generate the corresponding SQL query, execute it, and return the results.

Future Enhancements

• Advanced Error Handling & Monitoring: Implementing more granular error handling and logging for better debugging and system monitoring.
• Sophisticated NLP Capabilities: Enhancing natural language processing to handle a wider range of queries.
• User-Friendly Interface: Developing a web or desktop interface with query history, result visualization, and export options.
• Automated Actions: Enabling the agent to perform tasks like ordering food or managing transactions through voice or text commands.

Contributing

• Contributions are welcome! If you’d like to help improve this project, please fork the repository and create a pull request with your changes.

License

This project is licensed under the MIT License.

Contact

For any questions or suggestions, feel free to reach out to me via LinkedIn https://www.linkedin.com/in/satyam-sharma-6632a61b4/ or open an issue in this repository.

Demo

https://www.linkedin.com/posts/satyam-sharma-6632a61b4_openai-langchain-ai-activity-7197948980297699329-zzSi?utm_source=share&utm_medium=member_desktop