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Challenge Copilot: RAG Q&A Bot using LLM/API Intergration path

Join this online live build to create a simple RAG (Retrieval-Augmented Generation) chatbot that answers questions about the Building AI Application Challenge—using the official challenge content as its knowledge base.

We’ll copy the challenge details into a text file, index it with LlamaIndex, generate grounded answers via an LLM API (LLM/API Integration path), and ship a clean Q&A UI using Gradio. You’ll leave with a working template you can reuse for any document-based assistant.

Register Here https://nas.io/artificialintelligence/events/join-biggest-tech-community-developers-founders-mentors-1767887684165

You’ll build:

  • `challenge_context.txt` → indexed knowledge base (LlamaIndex)
  • RAG Q&A flow (retrieve → answer with LLM API)
  • Gradio web UI (+ optional sources)

Best for: Challenge participants, beginners, and anyone who wants an end-to-end RAG demo fast.
Prereqs: Python basics + an LLM API key (OpenAI/Bedrock/etc.).

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