Physical AI RAG Chatbot for Humanoid Robotics
A Retrieval‑Augmented Generation chatbot that answers deep technical queries about humanoid robotics by indexing a curated corpus of papers, docs, and research.
The Problem
Engineers waste hours searching PDFs and research papers; generic chatbots hallucinate and lack domain expertise.
The Solution
Domain‑specific RAG system that indexes the robotics corpus into a vector store, retrieves relevant passages, and synthesises grounded answers with citations.
Architecture Overview
Ingestion pipeline → chunking & embeddings → vector DB → retrieval + re‑ranking → LLM synthesis (OpenAI) → streaming chat UI.
Tech Stack
Python
LangChain
OpenAI
ChromaDB
FastAPI
React
Key Features
- Domain‑specific retrieval over robotics literature
- Citation‑backed, low‑hallucination answers
- Streaming real‑time chat interface
- Re‑ranking for precision
Results
Research time cut from hours to seconds
Verifiable answers with source links
Adopted by the robotics research team for daily queries