Update optimizing-rag-performance-in-librechat.md

This PR adds a detailed blog post written by Henk van Ess that covers how to optimize Retrieval-Augmented Generation (RAG) performance in LibreChat.

The guide walks through:

Improving vector database performance (PostgreSQL/pgvector)
Chunking strategies (CHUNK_SIZE / CHUNK_OVERLAP)
Embedding provider options (OpenAI, Azure, Ollama)
Retrieval settings (RAG_API_TOP_K)
Monitoring and server resource tips
It's designed to help developers fine-tune their LibreChat instances for speed and quality. All content is based on hands-on testing and is Markdown-formatted for blog use.

Looking forward to feedback — happy to revise if needed!

Author: voelspriet

pages/blog/optimizing-rag-performance-in-librechat.md

@@ -1,5 +1,3 @@
-Perfect — I’ve merged both versions of **"Manual: Optimizing RAG Performance in LibreChat"** into a single, cleaned-up, blog-ready Markdown guide. This merged version consolidates the extra detail from the second file (like index tuning and deeper PostgreSQL advice) into the original structure for clarity and completeness.
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 # Optimizing RAG Performance in LibreChat (Detailed Guide)
@@ -275,4 +273,3 @@ Test each change independently. Always monitor API logs and resource usage. If i
 
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-Would you like this in a `.md` file for PR submission? I can generate it and structure it inside a `blog/` folder with metadata.