{"id":"ddb98785-706e-4592-97f6-a5a7255150f8","shortId":"TXhEGh","kind":"skill","title":"Generate drift and quality reports for ML and LLM pipelines with Evidently","tagline":"Produce repeatable drift and quality reports after data, model, or prompt changes so regressions are visible before rollout.","description":"# Generate drift and quality reports for ML and LLM pipelines with Evidently\n\nProduce repeatable drift and quality reports after data, model, or prompt changes so regressions are visible before rollout.\n\n## Prerequisites\n\nPython 3.9+, pip, datasets or eval outputs for comparison\n\n## Installation\n\nUse the upstream install or setup path that matches your environment:\n- pip install evidently\n- conda install -c conda-forge evidently\n- uv run --with evidently evidently ui --demo-projects all\n- pip install virtualenv\n\nRequirements and caveats from upstream:\n- Evidently is an open-source Python library to evaluate, test, and monitor ML and LLM systems—from experiments to production.\n- 🛠️ Python interface for custom metrics.\n- View interactive Reports in Python or export as JSON, Python dictionary, HTML, or view in monitoring UI.\n\nBasic usage or getting-started notes:\n- |![Report example](https://github.com/evidentlyai/docs/blob/eb1630cdd80d31d55921ff4d34fc7b5e6e9c9f90/images/concepts/report_test_preview.gif)|\n- |![Dashboard example](https://github.com/evidentlyai/docs/blob/eb1630cdd80d31d55921ff4d34fc7b5e6e9c9f90/images/dashboard_llm_tabs.gif)|\n- To install Evidently using the Conda installer, run:\n\n- Source: https://github.com/evidentlyai/evidently\n- Extracted from upstream docs: https://raw.githubusercontent.com/evidentlyai/evidently/HEAD/README.md\n\n## Documentation\n\n- https://docs.evidentlyai.com/\n\n## Source\n\n- [Agent Skill 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