AI SQLBrain Streamlit App Using OpenAI LLM Agents

Leveraging the power of OpenAI's Language Model Agents to create an intelligent SQL query assistant.

Introduction

Welcome to the AI SQL Brain App repository! This project leverages the power of OpenAI's Language Model Agents to create an intelligent SQL query assistant. With this app, you can interact with a natural language interface to generate SQL queries, making it easier for both beginners and experienced SQL users to work with databases.

Streamlit URL

Access Demo: https://ai-sqlbrain-app-using-llm-agents.streamlit.app/

Features

• Natural Language Interface: Communicate with the app using everyday language to construct SQL queries.
• OpenAI Language Model Integration: Utilizes OpenAI's advanced language model to understand and generate SQL code.
• Interactive Query Builder: Step-by-step guidance for building complex SQL queries.
• Database Connection: Connect to your database to execute SQL queries directly.

Getting Started

To get started with the AI SQL Brain App, follow these steps:

1. Clone the Repository: Clone this repository to your local machine using the following command:

   git clone https://github.com/christinestraub/AI-SQLBrain-App-Using-LLM-Agents.git

2. Set Up Dependencies: Make sure you have the necessary dependencies installed. This may include Python, Flask, and other libraries. You can typically install them using pip:

   pip install -r requirements.txt

3. Configuration: Configure your database connection settings in the config.py file.

4. Start the Application: Run the Flask app to start the AI SQL Brain App:

   streamlit run main.py

5. Access the App: Open your web browser and navigate to http://localhost:5000 to use the AI SQL Brain App.

Usage

Once you access the application, you can interact with the AI SQL Brain App in the following ways:

1. Enter your query in natural language.
2. Follow the app's prompts to clarify your query step by step.
3. Review and modify the generated SQL query.
4. Execute the query on your connected database.

The app will provide real-time feedback and suggestions to help you construct accurate SQL queries.