WebChatRAG is a tool that allows users to engage in conversations about the contents of a website using the state-of-the-art RAG (Retrieval-Augmented Generation) technique. Simply input a website URL, and start chatting with our language model!
- Website Content Extraction: Fetch content from any website by providing its URL.
- Natural Language Interaction: Engage in natural and meaningful conversations with the AI model about the website content.
- RAG Technique: Leveraging Retrieval-Augmented Generation, the model provides accurate and relevant responses based on both the website content and broader knowledge.
- GitHub Integration: Seamlessly integrate the tool into your GitHub projects for easy collaboration and deployment.
- Clone the repository:
git clone https://github.com/theQuert/WebChatRAG.git
cd WebChatRAG- Install dependencies:
pip install -r requirements.txt- Run the tool:
streamlit run src/app.py- Enter a website URL when prompted and start chatting with the AI model!
Contributions are welcome! If you have ideas for improvements or new features, feel free to open an issue or submit a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.
This project was made possible thanks to the incredible work of the OpenAI team and their advancements in natural language processing. Special thanks to the contributors and supporters of this project.
WebChatRAG is developed and maintained by theQuert. Connect with me on LinkedIn!
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