Produces the user-visible response.
The LLM takes the assembled context and user query to generate a natural language response. It synthesizes relevant information from the context, formats the answer appropriately, and delivers the final output to the user while staying grounded in the provided information.
This is the culmination of the RAG pipeline where value is delivered to the user. A well-performed answer generation produces responses that are correct (grounded in facts), complete, and clear, significantly reducing hallucinations compared to using the LLM alone.
Correctly uses context, admits uncertainty when appropriate
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Building a robust Answer Generation solution is challenging. Respeak's Enterprise RAG Platform handles this complexity for you.