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

[WinterSun23]

/assign

[Devpool-soc]

Alright @WinterSun23! Consider yourself officially assigned as now. If you are thinking, "Whoa, hold up, I didn't sign up for this," no worries, just yell "/unassign" and we can pretend this never happened. But if you are sticking around, just know your clock for this ticks out on: 2026-01-25. Don't screw it up :)

[IAmRiteshKoushik]

Hey @WinterSun23, we are yet to deactivate the bot for WoC. This issue is not a part of WoC anymore as the event has ended. Although, we appreciate the contribution :)