refactor: Implement RAG Pipeline for AI Chatbot to Replace Full-Context Injection

[priyansh-narang2308]

Overview

The chatbot currently injects the full documentation into the system prompt using INCLUDE_DOCS_CONTEXT. This works for testing, but it’s inefficient, slow, and wastes tokens.

Goal

Replace full-doc injection with a RAG setup to reduce tokens and improve response time.

Plan

• Parse all .md files from user_docs
• Split content into logical chunks
• Generate embeddings per chunk
• Store them in a simple local vector index
• On each query:
  • Run semantic search
  • Fetch top 3–5 relevant chunks
  • Inject only those into the prompt

Acceptance

• INCLUDE_DOCS_CONTEXT is removed or rerouted to RAG
• Token usage drops noticeably
• Project-specific answers still work