>I rewrote a simple RAG ingestion pipeline from Python to Go

I also wrote a RAG pipeline in Go, using OpenSearch for hybrid search (full-text + semantic) and the OpenAI API. I reused OpenSearch because our product was already using it for other purposes, and it supports vector search.

For me, the hardest part was figuring out all the additional settings and knobs in OpenSearch to achieve around 90% successful retrieval, as well as determining the right prompt and various settings for the LLM. I've found that these settings can be very sensitive to the type of data you're applying RAG to. I'm not sure if there's a Python library that solves this out of the box without requiring manual tuning too