Practical solutions to answer inconsistency in RAG systems
The problem of answer inconsistency in the RAG system is mainly caused by the disconnect between the retrieved content and the generated answers.Ragas provides aFaithfulness Assessment (Faithfulness)function can effectively solve this problem:
- Evaluate the process:Verify the context dependency of the answer in two steps, first identifying the core statements in the answer and then verifying that these statements are supported by the retrieved content
- Realization method:Call Ragas' faithfulness indicator API, passing in the question, answer, and context triples
- Optimization Recommendations:When the score is lower than 0.8, it is recommended to adjust the retrieval strategy or enhance the context-dependent cues of the generated models
- Advanced Tips:Can be used in conjunction with context_relevancy metrics to co-diagnose and distinguish between retrieval and generation problems
Typical implementation examples can be referenced through the meal analysis case in the article, which has a faithfulness score of 0.83 indicating that the system performs well but still has room for optimization.
This answer comes from the articleRagas: assessing RAG recall QA accuracy and answer correlationThe
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