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RAG with Vector Search and MCP for Knowledge Access
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Linked challenge: Human-Robot Team Collaboration
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Linked challenge
Human-Robot Team Collaboration
Prompt source
Original prompt text with formatting preserved for inspection.
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Implement a RAG system using a vector database (e.g., in-memory FAISS) that stores simulated robot manuals, previous human troubleshooting logs, and assembly blueprints. Describe how AutoGen agents will query this knowledge base using GPT-5 for context-aware information retrieval during assembly and error resolution. Detail how this will be exposed via an MCP tool.
Adaptation plan
Keep the source stable, then change the prompt in a predictable order so the next run is easier to evaluate.
Keep stable
Hold the task contract and output shape stable so generated implementations remain comparable.
Tune next
Update libraries, interfaces, and environment assumptions to match the stack you actually run.
Verify after
Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.