[shouche]

I have been using elastic index for a while now. The best way I have found is to use a hybrid search - match all with embedding + exact+fuzzy match combination as a way to boost results.

Reranking also provide a significant improvement to the response quality.

Another way to improve results for domain specific RAG systems is to use some heuristics to boost results. E.g., penalize results that contain certain negative keywords or boost results with certain patterns.

For RAG, given the limited context size and potential hallucinations, best prompt + best data will provide you with best response.

Prompts can be improved greatly to get the LLM to throw a good response with reduced hallucinations. A lot of techniques are seen on Twitter and can be explored to find a good fit.

I improve my prompts using a GPT assistant that significantly improve the response quality. https://chat.openai.com/g/g-haH111AXX-prompt-optimizer