{"data":{"slug":"federatedai-fate","name":"FATE","tagline":"An Industrial Grade Federated Learning Framework","github_url":"https://github.com/FederatedAI/FATE","owner":"FederatedAI","repo":"FATE","owner_avatar_url":"https://avatars.githubusercontent.com/u/54675540?v=4","primary_language":"Python","stars":6084,"forks":1569,"topics":["algorithm","fate","federated-learning","machine-learning","privacy-preserving"],"archived":false,"github_pushed_at":"2024-11-19T08:19:11+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/federatedai-fate","markdown_url":"https://www.graphcanon.com/tools/federatedai-fate.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/federatedai-fate","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=federatedai-fate","description":"An Industrial Grade Federated Learning Framework","homepage_url":null,"license":"Apache-2.0","open_issues":21,"watchers":134,"ai_summary":null,"readme_excerpt":"## Getting Started\nFATE can be deployed on a single node or on multiple nodes. Choose the deployment approach which matches your environment.\n[Release version can be downloaded here.](https://github.com/FederatedAI/FATE/wiki/Download)\n\n---\n\n### Standalone deployment\n\n- Deploying FATE on a single node via PyPI, pre-built docker images or installers. It is for simple testing purposes. Refer to this [guide](./deploy/standalone-deploy/).\n\n---\n\n### Cluster deployment\nDeploying FATE to multiple nodes to achieve scalability, reliability and manageability.\n- [Cluster deployment by CLI](./deploy/cluster-deploy): Using CLI to deploy a FATE cluster.\n- [Docker-Compose deployment](./deploy/docker-compose): Using docker-compose to deploy FATE.\n\n---\n\n### Quick Start\n- [Training Demo with Only FATE Installed From Pypi](doc/2.0/fate/ml)\n- [Training Demo with Both FATE AND FATE-Flow Installed From Pypi](doc/2.0/fate/quick_start.md)","github_created_at":"2019-01-24T10:32:43+00:00","created_at":"2026-07-11T23:38:06.528654+00:00","updated_at":"2026-07-11T23:38:10.279599+00:00","categories":[{"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"},{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"},{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"}],"tags":[{"slug":"fate","name":"fate"},{"slug":"algorithm","name":"algorithm"},{"slug":"machine-learning","name":"machine-learning"},{"slug":"python","name":"python"},{"slug":"federated-learning","name":"federated-learning"},{"slug":"privacy-preserving","name":"privacy-preserving"}],"trust":{"provenance":{"is_fork":false,"github_id":167349656,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T23:38:07.816Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":599,"last_release_at":"2024-07-31T11:47:02Z"},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:38:08.633Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-11T23:38:07.266Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-07-11T23:38:07.266Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-11T23:38:07.266Z"}}}}