ImadSaddik/RAG_With_Gemini

Providing useful context by using Retrieval Augmented Generation (RAG) to Gemini

24
/ 100
Experimental

Implements vector storage using ChromaDB with text chunking via LangChain, supporting data extraction from JSON and PDF sources. Provides a complete pipeline from embedding generation through the Gemini-Pro API to a Chainlit-based chat interface for querying retrieved context. Uses the free tier of Google's Gemini API to minimize costs while demonstrating production RAG patterns.

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No License Stale 6m No Package No Dependents
Maintenance 0 / 25
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Maturity 1 / 25
Community 18 / 25

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Category

gemini-langchain-rag

Last pushed

Jan 18, 2024

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Gemini LangChain RAG · 22 tools

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