{"data":{"slug":"guildai-guildai","name":"guildai","tagline":"Experiment tracking, ML developer tools","github_url":"https://github.com/guildai/guildai","owner":"guildai","repo":"guildai","owner_avatar_url":"https://avatars.githubusercontent.com/u/19977227?v=4","primary_language":"Python","stars":907,"forks":93,"topics":[],"archived":false,"github_pushed_at":"2025-04-29T19:09:51+00:00","maintenance_label":"Dormant","stars_delta_30d":3,"url":"https://www.graphcanon.com/tools/guildai-guildai","markdown_url":"https://www.graphcanon.com/tools/guildai-guildai.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/guildai-guildai","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=guildai-guildai","description":"Experiment tracking, ML developer tools","homepage_url":"https://guild.ai","license":"Apache-2.0","open_issues":241,"watchers":11,"ai_summary":"Guild AI is an open-source toolkit that automates and optimizes machine learning experiments by capturing results, supporting various optimization strategies, enabling remote execution on cloud accelerators, and facilitating archival to S3 or other storage solutions.","readme_excerpt":"# Guild AI\n\n\n\n\nThis is the source repository for Guild AI.\n\nGuild AI is an [open source](LICENSE.txt) toolkit that automates and\noptimizes machine learning experiments.\n\n- Run unmodified training scripts, capturing each run result as a unique\n  experiment\n- Automate trials using grid search, random search, and Bayesian\n  optimization\n- Compare and analyze runs to understand and improve models\n- Backup training related operations such as data preparation and test\n- Archive runs to S3 or other remote systems\n- Run operations remotely on cloud accelerators\n- Package and distribute models for easy reproducibility\n\nFor more on features, see [Guild AI - Features](https://guildai.org).\n\nImportant links:\n\n- **[Get Started with Guild AI](https://guildai.org/start)**\n- **[Get Help with Guild AI](https://guildai.org)**\n- **[Latest Release on PyPI](https://pypi.python.org/pypi/guildai)**\n- **[Documentation](https://guildai.org/docs/)**\n- **[Issues on GitHub](https://github.com/guildai/guildai/issues)**","github_created_at":"2017-09-27T18:57:50+00:00","created_at":"2026-07-11T23:25:38.816078+00:00","updated_at":"2026-09-27T06:00:29.299669+00:00","categories":[{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"automation","name":"automation"},{"slug":"bayesian-optimization","name":"bayesian-optimization"},{"slug":"experiment-tracking","name":"experiment tracking"},{"slug":"grid-search","name":"grid search"},{"slug":"ml-developer-tools","name":"ml developer tools"},{"slug":"optimization","name":"optimization"},{"slug":"random-search","name":"random search"}],"trust":{"provenance":{"is_fork":false,"github_id":105057392,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-27T06:00:28.529Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":515,"last_release_at":"2022-05-11T01:13:36Z","stars_delta_30d":3,"open_issues_delta_30d":4},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":138,"high_count":0,"last_scan_at":"2026-07-11T23:25:40.907Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-27T06:00:28.990Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-09-27T06:00:28.990Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-09-27T06:00:28.990Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["You require automation for running multiple experiment configurations to compare different models effectively.","Your workflow involves archiving experiment runs on cloud storage systems like S3, simplifying version control and data management.","Grid search, random search, or Bayesian optimization strategies are integral parts of your ML development process.","Remote execution on cloud accelerators is necessary to boost experiment performance and resource utilization."],"when_not_to_use":["If your project exclusively uses languages other than Python for machine learning tasks, Guild AI's capabilities may not be fully leveraged due to language-specific functionalities.","Your model development does not require intricate optimization methods or trial automation provided by this toolkit.","The need for experimentation tracking and archiving on cloud solutions is limited or you prefer manual handling of experiment data."],"source":"enrich:decision_facts","observed_at":"2026-07-17T04:14:25.811Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Guild AI is geared towards Python developers who need to manage various types of experiments and utilize optimization methods like grid search, random search, and Bayesian optimization."}]}}