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| license: apache-2.0 | |
| title: '# Website RAG Chatbot' | |
| sdk: gradio | |
| emoji: 📊 | |
| colorFrom: green | |
| colorTo: yellow | |
| pinned: false | |
| # Website RAG Chatbot | |
| This project implements a Retrieval-Augmented Generation (RAG) system using Langchain, Google's Generative AI, and Gradio. It creates a chatbot interface that answers questions based on information retrieved from a pre-processed set of web pages. | |
| ## Features | |
| - Web-based chatbot interface using Gradio | |
| - RAG system powered by Langchain and Google's Generative AI | |
| - Local FAISS vector store for efficient information retrieval | |
| - Customizable UI with CSS styling | |
| ## Prerequisites | |
| - Python 3.9 or higher | |
| - Google API key for access to Generative AI models | |
| - Langchain API key | |
| - Pre-processed FAISS index (stored in `./Vector_DB/faiss_index`) | |
| ## Installation | |
| 1. Clone this repository: | |
| ``` | |
| git clone | |
| cd website-rag-chatbot | |
| ``` | |
| 2. Install the required packages: | |
| ``` | |
| pip install -r requirements.txt | |
| ``` | |
| 3. Set up your environment variables: | |
| Create a `.env` file in the project root and add the following: | |
| ``` | |
| GOOGLE_API_KEY=your_google_api_key | |
| LANGCHAIN_API_KEY=your_langchain_api_key | |
| ``` | |
| ## Usage | |
| To run the chatbot locally: | |
| ``` | |
| python app.py | |
| ``` | |
| This will start the Gradio interface, typically accessible at `http://localhost:7860`. | |
| ## Deployment | |
| This project is configured for deployment to Google Cloud Run. | |
| 1. Build the Docker image: | |
| ``` | |
| docker build -t website-rag-chatbot . | |
| ``` | |
| 2. Tag and push the image to Google Container Registry: | |
| ``` | |
| docker tag website-rag-chatbot gcr.io/your-project-id/website-rag-chatbot | |
| docker push gcr.io/your-project-id/website-rag-chatbot | |
| ``` | |
| 3. Deploy to Cloud Run: | |
| ``` | |
| gcloud run deploy website-rag-chatbot --image gcr.io/your-project-id/website-rag-chatbot --platform managed | |
| ``` | |
| Remember to set the necessary environment variables in the Cloud Run configuration. | |
| ## Project Structure | |
| - `app.py`: Main application file containing the Gradio interface and RAG logic | |
| - `Dockerfile`: Configuration for containerizing the application | |
| - `requirements.txt`: List of Python package dependencies | |
| - `Vector_DB/faiss_index`: Pre-processed FAISS index (not included in repository) | |
| ## Contributing | |
| Contributions are welcome! Please feel free to submit a Pull Request. | |
| ## License | |
| This project is licensed under the MIT License - see the LICENSE file for details. | |
| ## Acknowledgments | |
| - Langchain for the RAG framework | |
| - Google for the Generative AI models | |
| - Gradio for the easy-to-use interface building | |
| ## Contact | |
| Created by Yash Kavaiya - feel free to contact me! | |
| - GitHub: [https://github.com/Yash-Kavaiya](https://github.com/Yash-Kavaiya) | |
| - LinkedIn: [https://linkedin.com/in/Yash-Kavaiya](https://linkedin.com/in/Yash-Kavaiya) |