review-interface

You can generate a self-contained HTML annotation interface that runs entirely in the browser from a single file, requiring no server setup. It produces a single HTML file with inline CSS/JS to load JSONL data and review agent traces.

The best way to build a UI for human review of LLM outputs is to use a tool that generates a self-contained HTML file. This interface supports configurable annotation controls, progress tracking, and result exports for quality assessment.

Yes, you can load JSONL data into a custom annotation tool for side-by-side comparisons. The interface supports reviewing LLM outputs, agent execution traces, and data labeling tasks directly in the browser.

Yes, the generated HTML annotation interface supports both progress tracking and result export. It produces a single HTML file with inline CSS/JS to help you track annotation progress and export labeled results for audits.

To audit AI outputs and traces locally without a backend, generate a self-contained HTML annotation interface. It runs entirely in the browser from a single file, loading JSONL data to facilitate quality assessment and audit workflows.