Nice RAG trick for diverse content types (images / tables): generate + embed a text summary (for natural language search), but return full doc for LLM synthesis. Short write-up w/ 3 cookbooks below showing semi-structured and multi-modal RAG using this idea with the multi-vector retriever. Table summaries work nicely w/ the multi-vector retriever for semi-structured RAG. And I use LLaVA-7b (c/o @imhaotian) to generate image summaries. Also include a cookbook showing this full pipeline running private / local on my laptop w/ llama.cpp c/o @ggerganov, @ollama_ai, @nomic_ai embeddings, and @trychroma. Write-up: blog.langchain.dev/semi-stru…