🏏 IPL Data Chatbot

The IPL Data Chatbot is an interactive web application built with Streamlit that allows users to query IPL (Indian Premier League) data from 2008 to 2024 using natural language. The chatbot uses OpenAI's GPT-4 to generate SQL queries dynamically and fetches data from a Snowflake database.

🌐 Try the IPL Data Chatbot Here

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✨ Features

• Natural Language Querying: Users can ask questions in plain English.
• Dynamic SQL Generation: Converts user queries into SQL using OpenAI GPT-4.
• Real-Time Data Fetching: Retrieves data from Snowflake and displays it in a user-friendly format.
• Data Export: Download query results as a CSV file.
• Query Validation: Ensures SQL queries are valid and data integrity is maintained.
• Insights and Summaries: Provides clear and concise summaries of query results.

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🛠️ Tech Stack

• Frontend: Streamlit
• Backend: Python
• Database: Snowflake
• AI Integration: OpenAI GPT-4
• Environment Variables: Managed using st.secrets in Streamlit.

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🚀 Getting Started

1. Prerequisites

Ensure you have the following installed:

• Python 3.8+
• Streamlit
• Snowflake Python Connector
• OpenAI Python Library (openai)

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2. Clone the Repository

git clone https://github.com/Kaustubhk28/sql-gpt.git

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⚙️ Configure Environment Variables

To securely configure the application, use the following steps:

Navigate to the .streamlit directory in the project.

Create a secrets.toml file with the following content:

[general] SNOWFLAKE_USER = "your_snowflake_username" SNOWFLAKE_PASSWORD = "your_snowflake_password" SNOWFLAKE_ACCOUNT = "your_snowflake_account" SNOWFLAKE_DATABASE = "your_snowflake_database" SNOWFLAKE_SCHEMA = "your_snowflake_schema" SNOWFLAKE_WAREHOUSE = "your_snowflake_warehouse" OPENAI_API_KEY = "your_openai_api_key"

Replace the placeholders (your_snowflake_username, your_openai_api_key, etc.) with your actual credentials.

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🚀 Run the Application Locally

To run the application on your local machine:

Start the app:

streamlit run app.py

Open your web browser and navigate to:

http://localhost:8501

The application should now be running locally!

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📁 Project Structure

Here’s a breakdown of the project structure:

ipl-data-chatbot/
├── app.py                # Main Streamlit application script
├── fetch_data.py         # Script for fetching data from Snowflake
├── langchain_utils.py    # Generates SQL queries using OpenAI GPT-4
├── requirements.txt      # Python dependencies
├── .streamlit/           
│   └── secrets.toml      # Environment variable configuration file
└── README.md             # Project documentation

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🔗 IPL Data Chatbot

💡 Features

Natural Language Querying: Ask questions like, "Which team scored the most runs in 2023?" Dynamic SQL Query Generation: Uses GPT-4 to convert natural language to SQL. Interactive Results: View, validate, and download query results as CSV. Secure Configuration: Sensitive credentials are stored securely using Streamlit's secrets.

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❤️ Acknowledgments

Streamlit: For creating a powerful framework for interactive web apps. OpenAI GPT-4: For natural language understanding and SQL generation. Snowflake: For efficient and scalable database management.