0xshre/rag-evaluation

A QA RAG system that uses a custom chromadb to retrieve relevant passages and then uses an LLM to generate the answer.

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Experimental

This project helps evaluate and improve question-answering systems built using Retrieval-Augmented Generation (RAG). You feed in documents and questions, and it generates answers while also providing a detailed report on how accurate and relevant the answers are. It's for data scientists and AI engineers who are developing or fine-tuning RAG-based chatbots or knowledge retrieval tools.

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Use this if you are building or evaluating a RAG-based question-answering system and need to understand its performance in terms of answer quality and context utilization.

Not ideal if you are looking for a ready-to-use, off-the-shelf chatbot without needing to delve into RAG system performance metrics.

AI-development Natural-Language-Processing Knowledge-retrieval ML-evaluation Question-Answering-systems

No License Stale 6m No Package No Dependents

Maintenance 0 / 25

Adoption 6 / 25

Maturity 8 / 25

Community 15 / 25

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rag-evaluation and gc-qa-rag rag-evaluation and lm-rag-techniques

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