faiza-faisal/Physical-AI-and-Humanoid-Robotics-Textbook

Physical AI & Humanoid Robotics Textbook - RAG Chatbot

An intelligent chatbot powered by Retrieval-Augmented Generation (RAG) that answers questions about Physical AI and Humanoid Robotics using advanced language models.

🌟 Features

• —Smart Question Answering: Get accurate answers from the textbook content
• —Multiple AI Providers: Support for both Cohere and Hugging Face models
• —Vector Search: Efficient document retrieval using ChromaDB
• —Clean Interface: User-friendly Streamlit web interface

🚀 Quick Start

1. 1.Select your preferred AI provider (Cohere recommended)
2. 2.Choose a model from the dropdown
3. 3.Type your question
4. 4.Get instant, context-aware answers!

🔑 Configuration

This Space requires API keys to function. Add them in Space Settings → Repository Secrets:

• —COHERE_API_KEY: Get from Cohere Dashboard
• —HF_TOKEN: (Optional) Get from Hugging Face Settings

📚 Supported Topics

• —ROS2 (Robot Operating System 2)
• —Simulation & Digital Twins
• —Hardware Basics
• —VLA (Vision-Language-Action) Systems
• —Advanced AI Control
• —Humanoid Robot Design

🛠️ Technology Stack

• —Framework: Streamlit
• —LLM Integration: LangChain
• —Vector Database: ChromaDB
• —Embeddings: Cohere embed-english-v3.0
• —AI Models: Cohere Command R+, Hugging Face models

💡 Sample Questions

• —"What is ROS2 and why is it important?"
• —"Explain digital twins in robotics"
• —"What are VLA systems?"
• —"How do humanoid robots work?"

🔒 Security

• —API tokens are stored securely as Space secrets
• —Never exposed in code or logs
• —Follow security best practices

📖 About the Textbook

This chatbot is based on a comprehensive textbook covering Physical AI and Humanoid Robotics, including theoretical foundations and practical implementations.

Built with ❤️ using Streamlit, LangChain, and Cohere