Answer to: Improve the RAG chatbot result

I use an LLM to grade the retrieved documents (LLM reranking) to improve retrieval quality. You can use an LLM to evaluate whether the retrieved documents are relevant to the query. If none of the documents meet a predefined relevance threshold, you can trigger a web search tool, rewrite the query and retrieve again, or return “I don't know” instead of generating a potentially hallucinated answer. ChromaDB provides metadata filtering (https://docs.trychroma.com/docs/querying-collections/metadata-filtering), which can help improve retrieval precision. However, the filtering strategy depends on your specific use case and data structure. P.S. There are many practical RAG techniques discussed in this article: https://abdullin.com/ilya/how-to-build-best-rag/ You may find it helpful.