Adaptive RAGs

1. RAG trained on LLM and Prompt Engineering content

This RAG performs the following operation:

• Loads the Open AI Model.
• Load and Index the document into a Memory Vector Store.
• Routes the question to the LLM Model if found relevant, otherwise perform a Web Search.
• Retrieve the indexed document from the Vector Store.
• Decide whether the retieved document is relevant to the question or not.
• If the document is relevant then ask model to generate answers for the question using the given context document.
• If the document is irrelevant, transform the question to get a better question/query and then re-grade the document with the updated question.
• Once the answer is generated, check the model for Hallucination and check how relevant the answer is to the question.

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2. RAG trained on Coding Interviews content