Welcome to Medical Q&A, your friendly chatbot companion for all things related to heart health! 🏥 This project uses cutting-edge technology to provide you with accurate information and support on your health journey. 💖
Powered by LangChain for seamless integration and leveraging the Retrieval-Augmented Generation (RAG) model, our chatbot ensures that you have access to the latest medical insights with ease. LangChain handles all aspects of text processing, from loading and splitting PDF documents to optimizing data storage and retrieval using vector embeddings.
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PDF Loader: Our chatbot comes equipped with a PDF loader that seamlessly loads and processes heart health documents, ensuring easy access to valuable medical information. 📚
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Text Splitter: To handle large documents with ease, our chatbot employs advanced text splitting techniques, breaking down complex information into manageable chunks for efficient processing. 🔍
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Vector Store: By harnessing the power of vector embeddings, our chatbot optimizes data storage, efficiently organizing and accessing information for lightning-fast responses to your queries while maintaining accuracy and relevancy. 💡
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Retrieval: Armed with a robust retrieval system, our chatbot swiftly fetches relevant data from the vector store, ensuring that you receive timely and accurate responses to your inquiries. 🎯
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Hugging Face LLM: Powered by a state-of-the-art language model from Hugging Face, our chatbot crafts responses that are not only informative but also engaging and natural-sounding, enhancing your interaction experience. 🤖
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Chatbot Interface: With a user-friendly interface, our chatbot provides a seamless experience, allowing you to effortlessly interact and engage with the wealth of medical knowledge at your fingertips. 💬
To get started with Medical Q&A, you'll need the following:
- Python 3.x
- Hugging Face Transformers library
- RAG model implementation (e.g., from Facebook's RAG GitHub repository)
- PDF for retrieval
- Other dependencies as specified in the project's requirements.txt file
- Install Dependencies: Ensure all required dependencies are installed. You can install them using pip
Interact with the Chatbot: Once the chatbot is running, interact with it by entering queries related to heart health. The chatbot will retrieve information from the PDF document and generate responses accordingly.
This project is licensed under the MIT License.
Feel free to share the love by giving the chatbot a star on GitHub! ⭐️