Welcome to the GitHub repository for our tutorial on building a natural language SQL chatbot using GPT-4! This project guides you through the development of a chatbot that can interpret natural language queries, generate SQL queries, and fetch results from a SQL database, all in an intuitive and user-friendly way. It utilizes the power of OpenAI's GPT-4 model, integrated with a Streamlit GUI for an enhanced interaction experience.
🟡 This original repository serves as supporting material for the YouTube video tutorial I invite you to check his great youtube channel.
- Natural Language Processing: Uses GPT-4 to interpret and respond to user queries in natural language.
- SQL Query Generation: Dynamically generates SQL queries based on the user's natural language input.
- Database Interaction: Connects to a SQL database to retrieve query results, demonstrating practical database interaction.
- Streamlit GUI: Features a user-friendly interface built with Streamlit, making it easy for users of all skill levels.
- Python-based: Entirely coded in Python, showcasing best practices in software development with modern technologies.
The chatbot works by taking a user's natural language query, converting it into a SQL query using GPT-4, executing the query on a SQL database, and then presenting the results back to the user in natural language. This process involves several steps of data processing and interaction with the OpenAI API and a SQL database, all seamlessly integrated into a Streamlit application.
Consider the following diagram to understand how the different chains and components are built:
Ensure you have Python installed on your machine. Then clone this repository:
git clone [repository-link]
cd [repository-directory]
Install the required packages:
pip install -r requirements.txt
Create your own .env file with the necessary variables, including your OpenAI API key:
OPENAI_API_KEY=[your-openai-api-key]
To launch the Streamlit app and interact with the chatbot:
streamlit run app.py
As this repository accompanies the YouTube video tutorial, we are primarily focused on providing a comprehensive learning experience. Contributions for bug fixes or typos are welcome.
This project is licensed under the MIT License - see the LICENSE file for details.
Happy Coding! 🚀👨💻🤖 and Thank You Alejandro