Build a Self-Corrective RAG App with LangGraph Cloud
From the video description
In this tutorial, we create a Self-Corrective RAG application for answering questions about Pandas documentation using LangGraph Cloud. We implement ideas from both self-RAG and corrective RAG to flexibly handle model hallucinations. You'll see how to check for hallucinations after an answer is generated, and check for answer relevancy before returning the user question.
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Video by LangChain, played through YouTube.
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