Implement RAG using LangChain and HuggingFace embedding models
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Updated
Sep 14, 2024 - Jupyter Notebook
Implement RAG using LangChain and HuggingFace embedding models
Upload documents 📄 and get instant, accurate answers to your questions with InstaDoc: Intelligent QnA Powered by RAG. Enjoy quick summaries 📜 and precise Q&A, all through an intuitive interface. InstaDoc leverages advanced technologies 🚀 to help you understand your documents better and faster, making document analysis efficient and user-friendly
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The project involves developing a chatbot to enhance learning by answering common FAQs and providing hints within the scope of each sprint. Below is the deployed link demonstrating frontend and node backend. Flask app is not deployed due to size issue, please run locally and use google api key to check the functionality of our RAG based chatbot
Click below to visit my website
A RAG Model ChatBot for jamia Millia Islamia
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Repo for DermAssist: Your AI Assitant for Skin Problems. Powered by a vision model and a reliable RAG system.
In this end to end project I have built a RAG app using ObjectBox Vector Databse and LangChain. With Objectbox you can do OnDevice AI, without the data ever needing to leave the device.
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Description given in the README
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