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TorchReview Copilot Demo Script
60-90 Second Walkthrough
- Open the Hugging Face Space and introduce TorchReview Copilot as an AI-powered code review and improvement system built with PyTorch.
- Point to the problem statement: manual code review is slow, inconsistent, and hard to scale.
- Select the
Fix the invoice total syntax regressionexample to show the app loading a broken code sample together with the context window. - Highlight the Live Triage Radar, the ML quality score, and the RL-ready reward score.
- Explain that the PyTorch layer uses CodeBERTa embeddings to compare the input against known code-quality patterns from the OpenEnv task catalog.
- Scroll to the three-step improvement plan and call out the progression: syntax and bug fixes, edge cases, then scalability.
- Switch to the performance example to show the confidence profile and reward changing for a different class of issue.
- Close by noting that OpenEnv still powers deterministic validation under the hood, so the demo remains grounded in measurable task outcomes.