DebugAI: Diagnose failed LLM outputs
Debug failed LLM calls with root-cause diagnoses
What it does
DebugAI is a Python SDK and web workbench for debugging and fixing failed LLM outputs. Wrap your LLM client or paste a bad response to get the failure type, severity, evidence, root cause, pipeline stage, and a suggested fix you can ship. It helps teams repair prompts, RAG systems, tool calls, and AI workflows faster.
Does the same job
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Hey HN, I just built an experimental VSCode extension called LLM Debugger. It’s a proof-of-concept that lets a large language model take charge of debugging. Instead of only looking at the static code, the LLM also gets to see the live runtime state—actual variable values, function calls, branch decisions, and more. The idea is to give it enough context to help diagnose issues faster and even generate synthetic data from running programs. Here’s what it does: * Active Debugging: It integrates with Node.js debug sessions to gather runtime info (like variable states and stack traces). *…
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