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}, "kind": "list", "text": "#3: Human Review\nCollect human feedback from subject matter experts\n- Custom evaluation criteria with editable fields directly in the UI\n- Flexible field types: binary, numeric, and string options\n- Keyboard shortcuts ← → to quickly navigate across datapoints", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", "groupRole": null, "confidence": null, "extraction": { "at": "2026-05-02 15:53:49.751+00", "model": "google/gemini-3.1-flash-lite-preview-20260303", "runId": null, "seconds": null, "promptVersion": null }, "componentId": "17379ead-882b-4b40-8aeb-8449039860cd", "parentComponentId": null }, { "bbox": { "h": 0.25, "w": 0.4, "x": 0.11, "y": 0.28 }, "kind": "list", "text": "#1: Setup Evaluators\nBuild custom metrics in UI / code\nDefine evaluators (i.e. metrics) to test and detect failure modes:\n- Code Evaluators: Create simple assertions and unit tests in Python or use external packages (Transformers, Scikit Learn, etc.)\n- LLM Evaluators: Evaluate semantic qualities like Toxicity, Coherence, Answer Faithfulness, etc. using other LLMs + your own policy/criteria\n- Human Evaluators: Create custom annotation fields and criteria for domain experts to review", "attrs": null, "canon": { "kind": { "name": "List", "slug": "list", "status": "active", "canonId": "019de52c-f94b-779b-a53b-fd4904a5f4d2", "version": 1, "description": "Bullet or numbered list." }, "tool": null, "subkind": { "name": "Bullet list", "slug": "bullet", "status": "active", "canonId": "019de52c-fc98-7169-a083-5cab805076ca", "version": 1, "description": null }, "framework": null }, "subkind": "bullet", 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