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RAG System and GPT-5 Integration for Recommendations
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Linked challenge: AI-Powered Quantum Link Integrity Monitor
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Linked challenge
AI-Powered Quantum Link Integrity Monitor
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Populate your PostgreSQL database with reference data like quantum network troubleshooting guides, security protocols, and mitigation strategies. Using LlamaIndex, build a Retrieval Augmented Generation (RAG) system that can semantically search this knowledge base. Integrate the GPT-5 API (via Fireworks) to take detected anomalies from your model, query the LlamaIndex RAG system for context, and generate comprehensive, actionable recommendations for network operators. Ensure the recommendations are relevant to the specific anomaly type (noise vs. eavesdropping).
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.