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This is a RAG application to chat with data in your PDF documents implemented using LangChain, OpenAI LLM, Faiss Vector Store and Streamlit for UI

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RAG-using-Langchain-Streamlit

This is a RAG application to chat with data in your PDF documents implemented using LangChain, OpenAI LLM and Embeddings, Faiss Vector Store and Streamlit for UI

Getting Started

  1. Clone the repository
git clone https://github.com/gdevakumar/RAG-using-Langchain-Streamlit.git
  1. Install the dependencies
cd RAG-using-Langchain-Streamlit && pip install -r requirements.txt
  1. Setup your OPENAI_API_KEY in .env file (RAG-using-LangChain-Streamlit/.env) and save

    OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>

  2. Run the application

streamlit run app.py

[Coming Soon] Similar applications with:

  • Vectorstores: Chroma, Weaviate, Qdrant
  • Embeddings: OpenSource HF Models
  • LLM: HF Open LLMs

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This is a RAG application to chat with data in your PDF documents implemented using LangChain, OpenAI LLM, Faiss Vector Store and Streamlit for UI

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