{"data":{"slug":"jina-ai-clip-as-service","name":"clip-as-service","tagline":"-scalable embedding, reasoning, ranking for images and sentences with CLIP-","github_url":"https://github.com/jina-ai/clip-as-service","owner":"jina-ai","repo":"clip-as-service","owner_avatar_url":"https://avatars.githubusercontent.com/u/60539444?v=4","primary_language":"Python","stars":12829,"forks":2069,"topics":["bert","bert-as-service","clip-as-service","clip-model","cross-modal-retrieval","cross-modality","deep-learning","image2vec","multi-modality","neural-search","onnx","openai","pytorch","sentence-encoding","sentence2vec"],"archived":false,"github_pushed_at":"2024-01-23T10:33:43+00:00","maintenance_label":"Dormant","url":"https://www.graphcanon.com/tools/jina-ai-clip-as-service","markdown_url":"https://www.graphcanon.com/tools/jina-ai-clip-as-service.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/jina-ai-clip-as-service","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=jina-ai-clip-as-service","description":"🏄 Scalable embedding, reasoning, ranking for images and sentences with CLIP","homepage_url":"https://clip-as-service.jina.ai","license":"Other","open_issues":302,"watchers":215,"ai_summary":"CLIP-as-service offers scalable cross-modal retrieval using the CLIP model through a service-based architecture with server and client components.","readme_excerpt":"# pip install clip-client\nfrom clip_client import Client\n\nc = Client(\n    'grpcs://<your-inference-address>-grpc.wolf.jina.ai',\n    credential={'Authorization': '<your access token>'},\n)\n\nr = c.encode(\n    [\n        'First do it',\n        'then do it right',\n        'then do it better',\n        'https://picsum.photos/200',\n    ]\n)\nprint(r)\n```\n</td>\n</tr>\n</table>\n\n---\n\n## Install\n\nCLIP-as-service consists of two Python packages `clip-server` and `clip-client` that can be installed _independently_. Both require Python 3.7+.\n\n---\n\n### Install server\n\n<table>\n<tr>\n<td> Pytorch Runtime ⚡ </td>\n<td> ONNX Runtime ⚡⚡</td>\n<td> TensorRT Runtime ⚡⚡⚡ </td>\n</tr>\n<tr>\n<td>\n\n```bash\npip install clip-server\n```\n\n</td>\n<td>\n\n```bash\npip install \"clip-server[onnx]\"\n```\n\n</td>\n<td>\n\n```bash\npip install nvidia-pyindex \npip install \"clip-server[tensorrt]\"\n```\n</td>\n</tr>\n</table>\n\nYou can also [host the server on Google Colab](https://clip-as-service.jina.ai/hosting/colab/), leveraging its free GPU/TPU.\n\n---\n\n### Install client\n\n```bash\npip install clip-client\n```","github_created_at":"2018-11-12T10:48:50+00:00","created_at":"2026-07-11T23:10:44.224264+00:00","updated_at":"2026-07-12T07:52:07.109502+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":"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":"bert","name":"bert"},{"slug":"clip-as-service","name":"clip-as-service"},{"slug":"clip-model","name":"clip-model"},{"slug":"cross-modal-retrieval","name":"cross-modal-retrieval"},{"slug":"cross-modality","name":"cross-modality"},{"slug":"deep-learning","name":"deep-learning"},{"slug":"image2vec","name":"image2vec"},{"slug":"multi-modality","name":"multi-modality"}],"trust":{"provenance":{"is_fork":false,"github_id":157198623,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T23:10:46.514Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":900,"last_release_at":"2023-12-20T04:13:56Z"},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:10:47.021Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-12T03:03:23.172Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-07-12T03:03:23.172Z"},"license_spdx":{"value":"Other","source":"github.license","observed_at":"2026-07-12T03:03:23.172Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["- When you need to efficiently encode images and sentences into embeddings for tasks like neural search, where scalability is a priority.","- If your project involves multi-modality applications needing integration with different runtimes such as PyTorch, ONNX, or TensorRT."],"when_not_to_use":["- Avoid if your environment does not support Python 3.7+.","- The tool may be less suitable for small-scale projects where scalability and complex runtime configurations are unnecessary overheads."],"source":"enrich:decision_facts","observed_at":"2026-07-12T03:03:44.915Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Clip-as-service is a scalable cross-modal retrieval service using the CLIP model, offering server and client packages for Python. It requires Python 3.7+ and can use Pytorch, ONNX Runtime, or TensorRT runtimes."}]}}