mirabdullahyaser/Retrieval-Augmented-Generation-Engine-with-LangChain-and-Streamlit
Powerful web application that combines Streamlit, LangChain, and Pinecone to simplify document analysis. Powered by OpenAI's GPT-3, RAG enables dynamic, interactive document conversations, making it ideal for efficient document retrieval and summarization.
Implements multi-document PDF ingestion with configurable vector storage backends—embeddings can persist in Pinecone or a local vector store—while maintaining conversation context across chat sessions. The architecture chains LangChain's text splitting and embedding utilities with Streamlit's session state for stateful question-answering, accepting OpenAI and Pinecone credentials via environment variables or a secrets configuration file.
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Jul 04, 2024
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