{"data":{"slug":"migoxlab-dingo","name":"dingo","tagline":"Dingo: A Comprehensive AI Data, Model and Application Quality Evaluation Tool","github_url":"https://github.com/MigoXLab/dingo","owner":"MigoXLab","repo":"dingo","owner_avatar_url":"https://avatars.githubusercontent.com/u/216983961?v=4","primary_language":"Python","stars":722,"forks":74,"topics":["agent-as-a-judge","common-crawl","data-agent","data-evaluation","data-quality","data-quality-assessment","data-quality-report","data-validation","dataquality","datascience","deepseek","hallucination","hallucination-detection","llm","llm-as-a-judge","openai","opencompass","qwen","spark","vlm"],"archived":false,"github_pushed_at":"2026-07-10T11:30:45+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/migoxlab-dingo","markdown_url":"https://www.graphcanon.com/tools/migoxlab-dingo.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/migoxlab-dingo","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=migoxlab-dingo","description":"Dingo: A Comprehensive AI Data, Model and Application Quality Evaluation Tool","homepage_url":"https://dingo.openxlab.org.cn/","license":"Apache-2.0","open_issues":4,"watchers":8,"ai_summary":"A Python-based toolset for evaluating the quality of data, models, and applications in AI. It targets areas like data validation, hallucination detection, and model evaluation through multi-agent systems.","readme_excerpt":"## Future Plans\n\n- [ ] **Agent-as-a-Judge** - Multi-agent debate patterns for bias reduction and complex reasoning\n- [ ] **SaaS Platform** - Hosted evaluation service with API access and dashboard\n- [ ] **Audio & Video Modalities** - Extend beyond text/image\n- [ ] **Diversity Metrics** - Statistical diversity assessment\n- [ ] **Real-time Monitoring** - Continuous quality checks in production pipelines\n\n---\n\n# License\n\nThis project uses the [Apache 2.0 Open Source License](LICENSE).\n\nThis project uses fasttext for some functionality including language detection. fasttext is licensed under the MIT License, which is compatible with our Apache 2.0 license and provides flexibility for various usage scenarios.","github_created_at":"2024-12-24T05:59:24+00:00","created_at":"2026-07-11T10:34:20.114675+00:00","updated_at":"2026-07-12T02:36:18.481291+00:00","categories":[{"slug":"data-retrieval","name":"Data & Retrieval","url":"https://www.graphcanon.com/categories/data-retrieval","markdown_url":"https://www.graphcanon.com/categories/data-retrieval.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/data-retrieval"},{"slug":"evaluation-observability","name":"Evaluation & Observability","url":"https://www.graphcanon.com/categories/evaluation-observability","markdown_url":"https://www.graphcanon.com/categories/evaluation-observability.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/evaluation-observability"}],"tags":[{"slug":"agent-as-a-judge","name":"agent-as-a-judge"},{"slug":"llm-as-a-judge","name":"llm-as-a-judge"},{"slug":"hallucination-detection","name":"hallucination-detection"},{"slug":"data-evaluation","name":"data-evaluation"},{"slug":"data-quality","name":"data-quality"}],"trust":{"provenance":{"is_fork":false,"github_id":907673924,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T10:34:20.822Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":2,"days_since_push":0,"last_release_at":"2026-05-29T10:30:27Z"},"security_summary":{"status":"ok","scanner":"osv@v1","low_count":0,"high_count":0,"last_scan_at":"2026-07-11T10:34:26.960Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-12T02:35:48.518Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-07-12T02:35:48.518Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-12T02:35:48.518Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"The tool currently offers free open-source options under an Apache 2.0 license with plans for future SaaS platform services that may come at a cost."},"requirements":null,"constraints":{"pricing_model":"freemium"},"when_to_use":["When evaluating the quality of data, models, or applications that require insights from multiple perspectives to detect nuances such as bias or hallucination.","For organizations aiming to implement real-time monitoring systems in AI production pipelines to ensure continuous quality checks."],"when_not_to_use":["If your project does not benefit from a multi-agent approach for evaluation, and simpler single-model approaches suffice.","In scenarios where immediate feedback is critical but Dingo's planned SaaS platform with API access and dashboard support are still under development."],"source":"enrich:decision_facts","observed_at":"2026-07-12T02:36:18.251Z"},"constraint_facets":{"pricing_model":"freemium"},"decision_summary":[{"label":"Pricing","value":"freemium - The tool currently offers free open-source options under an Apache 2.0 license with plans for future SaaS platform services that may come at a cost."},{"label":"Adopt for","value":"Dingo includes a unique focus on multi-agent debate patterns ('Agent-as-a-Judge') for bias reduction and complex reasoning in evaluation tasks."},{"label":"License detail","value":"Licensed under the Apache-2.0 license, it includes fasttext functionality for language detection, which itself is licensed under the MIT License."}]}}