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A RAG Pipeline with Gemini Pro

A pipeline that stores PDF documents in a vector store ChromaDB and does document retrieval before sending off to Gemini to process the context and provide us with a suitable response.

Reranking with a cross-encoder was used to rerank the documents to hopefully provide a more accurate answer by first selecting better documents to use as context for the LLM.

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