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How to review generated CAD with QA reports and repair history with Multi Agent CAD

Inspect the brief, plan, generated Python, measurements, and repair steps behind each generated part.

Who it is forA mechanical engineer who must sign off on AI-generated geometry and needs to see how it was made before trusting it.

The problemA finished model alone does not show whether dimensions were checked or how failures were fixed, which makes review slow.

The outcomeA clear record of the structured brief, geometry plan, generated code, measurements, QA report, and repair history for one part.

What you need first

  • Python with conda or a Python 3.11 virtual environment
  • git to clone the repository
  • An API key for an OpenAI-compatible model endpoint, such as the default DashScope setup
  • Enough local disk and network access to run the model calls

Steps

  1. git clone https://github.com/Pan-Chera/Multi-Agent-CAD.git
  2. cd Multi-Agent-CAD
  3. conda env create -f environment.yml
  4. conda activate multi_agent_cad
  5. pip install --no-deps "aider-chat==0.82.3"
  6. export DASHSCOPE_API_KEY="your-key"
  7. Run python -m multi_agent_cad.graph with your brief, then open the run's QA report and repair history (inferred: check the output location set in multi_agent_cad/config.py)

Prompt for your agent

Use the Multi-Agent-CAD repo (github.com/Pan-Chera/Multi-Agent-CAD). Run the single-part workflow for the brief <part description>, then summarize the QA report and repair history and list any measurements that do not match the brief.

Caveat. The README describes audit artifacts but the exact output folder layout is in the single-part workflow documentation, so confirm where files land before relying on the path.

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