Lizhecheng02/RAG-ChatBot
A basic application using langchain, streamlit, and large language models to build a system for Retrieval-Augmented Generation (RAG) based on documents, also includes how to use Groq and deploy your own applications.
Implements vector embeddings via HuggingFace sentence transformers for semantic document retrieval, with LangChain's memory and retrieval chains orchestrating queries between PDF/doc/txt files and LLMs. Supports multiple LLM backends (OpenAI, Groq, Llama API) with configurable inference speeds, and provides comparison utilities to benchmark RAG responses against base model outputs, deployable directly to Streamlit Cloud.
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Jupyter Notebook
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Last pushed
May 09, 2024
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