Chat with any CSV 📊

A Streamlit-based application that allows users to interact with CSV files through a conversational interface. Upload your CSV, ask questions about its contents, and get intelligent responses powered by a Large Language Model (LLM).

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Features

• CSV Upload: Upload and preview CSV files directly in the app.
• Intelligent Query Handling: Ask questions about your CSV's contents, and get accurate, AI-generated responses.
• Chat Interface: User-friendly chat interface for seamless interaction.
• LLM Integration: Utilizes Groq’s llama3-70b-8192 model for intelligent and contextual responses.

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How It Works

1. CSV Upload:

   • Users upload CSV files, which are displayed in the sidebar for preview.
   • Validates the CSV file to ensure it is not empty.

2. Question Answering:

   • Users input prompts through a chat interface.
   • The app processes the query using a CSV agent integrated with the Groq LLM.

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Installation

1. Clone the Repository:

   git clone https://github.com/Osama-Abo-Bakr/Chat-with-any-csv.git
   cd Chat-with-any-csv

2. Install Dependencies:

   • Create a virtual environment:

     python -m venv venv
     source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

   • Install required packages:

     pip install -r requirements.txt

3. Set Up Environment Variables:

   • Create a .env file in the project directory and add your credentials:

     GROQ_API_KEY=your_groq_api_key
     

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Usage

1. Run the Application:

   streamlit run app.py

2. Upload and Interact:

   • Use the sidebar to upload your CSV file.
   • Ask questions or provide prompts in the chat input.
   • View AI-generated responses based on the CSV data.

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Dependencies

• Streamlit: For building the interactive web application.
• LangChain: For integrating the conversational agent.
• Pandas: For reading and previewing CSV files.
• Groq: For large language model-based question answering.

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Future Improvements

• Add support for large CSV files with efficient processing.
• Enhance UI/UX with data visualization features.
• Enable exporting chat history for reference.
• Add support for additional file formats (e.g., Excel).

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Contributing

Contributions are welcome! Feel free to fork the repository and submit a pull request.

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License

This project is licensed under the MIT License. See the LICENSE file for details.

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Author

Osama Abo Bakr
GitHub: Osama-Abo-Bakr

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Acknowledgments

• Special thanks to the developers of Streamlit, LangChain, Pandas, and Groq for their amazing tools!