{"data":{"slug":"jina-ai-serve","name":"serve","tagline":"Build multimodal AI applications with cloud-native stack","github_url":"https://github.com/jina-ai/serve","owner":"jina-ai","repo":"serve","owner_avatar_url":"https://avatars.githubusercontent.com/u/60539444?v=4","primary_language":"Python","stars":21861,"forks":2240,"topics":["cloud-native","cncf","deep-learning","docker","fastapi","framework","generative-ai","grpc","jaeger","kubernetes","llmops","machine-learning","microservice","mlops","multimodal","neural-search","opentelemetry","orchestration","pipeline","prometheus"],"archived":false,"github_pushed_at":"2025-03-24T13:59:54+00:00","maintenance_label":"Dormant","stars_delta_30d":-2,"url":"https://www.graphcanon.com/tools/jina-ai-serve","markdown_url":"https://www.graphcanon.com/tools/jina-ai-serve.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/jina-ai-serve","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=jina-ai-serve","description":"☁️ Build multimodal AI applications with cloud-native stack","homepage_url":"https://jina.ai/serve","license":"Apache-2.0","open_issues":26,"watchers":212,"ai_summary":"Jina AI Serve is a framework for building multimodal AI applications using a cloud-native stack, supporting deep learning, microservices, and orchestration.","readme_excerpt":"## Install \n\n```bash\npip install jina\n```\n\nSee guides for [Apple Silicon](https://jina.ai/serve/get-started/install/apple-silicon-m1-m2/) and [Windows](https://jina.ai/serve/get-started/install/windows/).\n\n---\n\n### Cloud Deployment\n\n#### Containerize Services\n\n1. Structure your Executor:\n```\nTextToImage/\n├── executor.py\n├── config.yml\n├── requirements.txt\n```\n\n2. Configure:\n```yaml","github_created_at":"2020-02-13T17:04:44+00:00","created_at":"2026-07-07T17:41:30.776391+00:00","updated_at":"2026-09-20T04:29:55.392361+00:00","categories":[{"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"},{"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":"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":"cloud-native","name":"cloud-native"},{"slug":"cncf","name":"cncf"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"docker","name":"docker"},{"slug":"fastapi","name":"fastapi"},{"slug":"framework","name":"framework"},{"slug":"generative-ai","name":"generative-ai"},{"slug":"grpc","name":"grpc"}],"trust":{"provenance":{"is_fork":false,"github_id":240315046,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-18T08:19:39.653Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":542,"last_release_at":"2024-11-12T08:26:45Z","stars_delta_30d":-2,"open_issues_delta_30d":-1},"security_summary":{"status":"ok","scanner":"osv@v1","low_count":0,"high_count":0,"last_scan_at":"2026-09-18T08:19:41.855Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-18T08:19:38.567Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-09-18T08:19:38.567Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-09-18T08:19:38.567Z"}},"decision_facts":{"hosting":null,"pricing":{"model":"freemium","summary":"Serve is free to use, but additional services or support might be available for a fee."},"requirements":{"notes":["Installation requires Python and pip.","Supports Apple Silicon and Windows installations."],"min_ram_gb":4,"requires_docker":true},"constraints":{"min_ram_gb":4,"pricing_model":"freemium","requires_docker":true},"when_to_use":["Use Serve when you need to build applications that integrate multiple types of data, such as text, images, and audio, into a single AI application.","Consider Serve if you are working in a cloud-native environment and want to leverage technologies like Kubernetes, Docker, and GRPC for deploying and scaling your AI applications."],"when_not_to_use":["Avoid Serve if your project does not require multimodal capabilities and you are looking for a simpler serving solution.","Do not use Serve if you are not comfortable with cloud-native technologies and prefer a more traditional deployment approach."],"source":"enrich:decision_facts","observed_at":"2026-09-18T10:56:32.998Z"},"constraint_facets":{"min_ram_gb":4,"pricing_model":"freemium","requires_docker":true},"decision_summary":[{"label":"Pricing","value":"freemium - Serve is free to use, but additional services or support might be available for a fee."},{"label":"Requirements","value":"Min 4 GB RAM; Requires Docker; Installation requires Python and pip.; Supports Apple Silicon and Windows installations."},{"label":"Adopt for","value":"Serve is a Python-based framework for building multimodal AI applications using a cloud-native stack, supporting deep learning, microservices, and orchestration."},{"label":"License detail","value":"Serve is available under the Apache-2.0 license, allowing for free use, modification, and distribution."}]}}