A developer encountered two significant bugs while building an agentic Retrieval-Augmented Generation (RAG) assistant. The first bug involved internal citation markers leaking into user-facing answers due to how streaming token chunks split the markers, requiring a buffering solution to ensure complete markers were processed. The second bug, initially appearing as a state-storage issue, was actually an architectural problem where the backend's idle spin-down caused the application to lose all context, necessitating a re-upload of documents for each new session. AI
IMPACT Highlights potential trust issues in RAG systems due to subtle bugs in streaming and state management.
RANK_REASON Developer blog post detailing bugs in a custom-built AI application.
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