Building a Self Hosted Question Answering Service using LangChain + Ray in 20 minutes

This blog post builds upon the previous part of a LangChain series to create a self-hosted LLM question-answering service using Ray and StableLM. The system queries search results from a semantic search engine, generates a prompt with the results, and feeds it to an LLM to generate an answer. The code uses a template to specify the LLM's behavior, including setting its "personality" and providing context for the question being asked. The chain is created using LangChain, which provides a powerful combination of Ray and StableLM capabilities. The blog post includes examples of how to use the system with Weights and Biases tracing and logging.

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