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How to ask the built-in assistant to diagnose a failed training run with Yolo Web Agent Starter

Use the Agent MVP to read evidence about a training job, then approve or reject any task it proposes.

Credentials. If you enable an external LLM, your question, object context, and tool results are sent to that service, and the API key must be entered in Settings and never shared in logs.

Who it is forA user whose training job failed and who wants a plain explanation with the evidence behind it, without the assistant starting work on its own.

The problemReading logs and config snapshots across several pages is slow, and an automated assistant that launches jobs could waste compute.

The outcomeA diagnostic answer backed by tool evidence, and optionally a confirmed training or evaluation task that the user approved before it ran.

What you need first

  • macOS or Linux
  • Python 3.11 or 3.12
  • Node.js 20 or newer
  • A set of images to label, or the built-in tiny demo generator

Steps

  1. Start the workbench with ./run-all.sh, then open the training page and click 询问助手 on the failed run to bind it to the assistant.
  2. Keep the default Mock / rule mode, or open Settings, then Agent LLM, enable a provider, enter the base URL, model, and key, test the connection, and save.
  3. Tick 仅查询 (query only) if you want a read-only answer, then ask why the run failed and wait for the async run to finish.
  4. Review the tool evidence and reasoning record, and if the assistant proposes a task, check its object, parameters, and expected output before choosing 确认执行 or rejecting it.
  5. If the run fails or is cancelled, retry it, which keeps the original mode, object, and read-only permission.

Prompt for your agent

In the YoloWebAgentStarter repo at <repo path>, bind the Training Assistant to training run <run ID> and ask for the likely cause of the failure in read-only mode. Verify that the answer cites tool evidence and that no task is submitted. Return the cause and the evidence list.

Caveat. A successful connection test does not prove the model can complete the full tool-calling workflow, so check a real diagnosis before relying on the assistant.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for fengzhizi715/YoloWebAgentStarter and "Ask the built-in assistant to diagnose a failed training run"

Add Deduped to Claude Code once

claude mcp add --transport http deduped https://dedupedai.com/mcp

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