diff --git a/.github/workflows/collect-metrics.yml b/.github/workflows/collect-metrics.yml index c738033..ec1a43d 100644 --- a/.github/workflows/collect-metrics.yml +++ b/.github/workflows/collect-metrics.yml @@ -1,9 +1,10 @@ name: Collect GitHub Metrics on: - # Run weekly on Mondays at 00:00 UTC + # Run weekly on Mondays at 12:00 UTC (noon) + # Later timing ensures PyPI stats are available for the previous day schedule: - - cron: '0 0 * * 1' + - cron: '0 12 * * 1' # Allow manual trigger workflow_dispatch: diff --git a/catalog/public/data/github_metrics.json b/catalog/public/data/github_metrics.json index 7c0bb64..f063f05 100644 --- a/catalog/public/data/github_metrics.json +++ b/catalog/public/data/github_metrics.json @@ -1,175 +1,104 @@ { "repos": { - "vectorinstitute/retrieval-augmented-generation": { - "repo_id": "vectorinstitute/retrieval-augmented-generation", - "name": "retrieval-augmented-generation", - "timestamp": "2025-12-01T00:25:46.035801+00:00", - "stars": 31, - "forks": 21, - "watchers": 24, - "open_issues": 1, - "size": 49310, - "views_14d": 173, - "unique_visitors_14d": 23, - "clones_14d": 80, - "unique_cloners_14d": 41, - "language": "Jupyter Notebook", - "created_at": "2023-11-30T19:17:30Z", - "updated_at": "2025-11-27T03:46:35Z", - "topics": [ - "rag", - "retrieval-augmented-generation" - ] - }, - "VectorInstitute/mcp-goodnews": { - "repo_id": "VectorInstitute/mcp-goodnews", - "name": "mcp-goodnews", - "timestamp": "2025-12-01T00:25:46.803261+00:00", - "stars": 44, - "forks": 9, + "VectorInstitute/midst-toolkit": { + "repo_id": "VectorInstitute/midst-toolkit", + "name": "midst-toolkit", + "timestamp": "2025-12-03T19:17:46.684919+00:00", + "stars": 5, + "forks": 1, "watchers": 0, "open_issues": 1, - "size": 101, - "views_14d": 62, - "unique_visitors_14d": 42, - "clones_14d": 55, - "unique_cloners_14d": 39, - "language": "Python", - "created_at": "2025-03-18T18:06:25Z", - "updated_at": "2025-11-26T21:32:12Z", - "topics": [] - }, - "VectorInstitute/bias-in-the-picture-benchmark": { - "repo_id": "VectorInstitute/bias-in-the-picture-benchmark", - "name": "bias-in-the-picture-benchmark", - "timestamp": "2025-12-01T00:25:47.455817+00:00", - "stars": 3, - "forks": 0, - "watchers": 0, - "open_issues": 0, - "size": 9705, - "views_14d": 78, - "unique_visitors_14d": 10, - "clones_14d": 13, - "unique_cloners_14d": 11, + "size": 114921, + "views_14d": 673, + "unique_visitors_14d": 26, + "clones_14d": 692, + "unique_cloners_14d": 237, "language": "Python", - "created_at": "2025-11-21T16:57:41Z", - "updated_at": "2025-11-26T21:34:25Z", + "created_at": "2025-06-13T13:37:34Z", + "updated_at": "2025-12-02T22:11:24Z", "topics": [] }, - "VectorInstitute/humanibench": { - "repo_id": "VectorInstitute/humanibench", - "name": "humanibench", - "timestamp": "2025-12-01T00:25:48.028776+00:00", - "stars": 6, + "VectorInstitute/atomgen": { + "repo_id": "VectorInstitute/atomgen", + "name": "atomgen", + "timestamp": "2025-12-03T19:17:51.563667+00:00", + "stars": 8, "forks": 1, - "watchers": 1, - "open_issues": 0, - "size": 21607, - "views_14d": 199, - "unique_visitors_14d": 27, - "clones_14d": 59, - "unique_cloners_14d": 44, - "language": "Python", - "created_at": "2025-01-28T14:55:04Z", - "updated_at": "2025-11-27T21:43:32Z", - "topics": [ - "evaluation-framework", - "multimodal-large-language-models", - "vlm" - ] - }, - "VectorInstitute/kg-rag": { - "repo_id": "VectorInstitute/kg-rag", - "name": "kg-rag", - "timestamp": "2025-12-01T00:25:48.711394+00:00", - "stars": 20, - "forks": 10, "watchers": 2, "open_issues": 1, - "size": 44098, - "views_14d": 230, - "unique_visitors_14d": 78, - "clones_14d": 41, - "unique_cloners_14d": 25, + "size": 2579, + "views_14d": 14, + "unique_visitors_14d": 7, + "clones_14d": 76, + "unique_cloners_14d": 38, "language": "Python", - "created_at": "2024-12-11T17:22:56Z", - "updated_at": "2025-11-24T14:33:14Z", - "topics": [ - "knowledge-graph", - "llms", - "rag" - ] - }, - "VectorInstitute/recommender-systems": { - "repo_id": "VectorInstitute/recommender-systems", - "name": "recommender-systems", - "timestamp": "2025-12-01T00:25:49.429513+00:00", - "stars": 6, - "forks": 0, - "watchers": 30, - "open_issues": 1, - "size": 27200, - "views_14d": 0, - "unique_visitors_14d": 0, - "clones_14d": 5, - "unique_cloners_14d": 4, - "language": "Jupyter Notebook", - "created_at": "2022-06-09T21:10:48Z", - "updated_at": "2025-05-13T20:17:43Z", + "created_at": "2024-04-11T01:22:34Z", + "updated_at": "2025-11-24T21:04:24Z", "topics": [ - "recommender-system" + "ai-for-science", + "atomistic-machine-learning", + "atomistic-models", + "atomistic-simulations", + "fine-tuning", + "huggingface", + "machine-learning", + "materials-science", + "pretrained-models", + "pytorch", + "transformers" ] }, - "VectorInstitute/bias-mitigation-unlearning": { - "repo_id": "VectorInstitute/bias-mitigation-unlearning", - "name": "bias-mitigation-unlearning", - "timestamp": "2025-12-01T00:25:50.131268+00:00", - "stars": 3, - "forks": 2, - "watchers": 1, - "open_issues": 6, - "size": 383, - "views_14d": 29, - "unique_visitors_14d": 5, - "clones_14d": 4, - "unique_cloners_14d": 3, - "language": "Python", - "created_at": "2024-10-09T20:05:04Z", - "updated_at": "2025-09-01T03:13:59Z", - "topics": [] - }, "VectorInstitute/linguamark": { "repo_id": "VectorInstitute/linguamark", "name": "linguamark", - "timestamp": "2025-12-01T00:25:50.851232+00:00", + "timestamp": "2025-12-03T19:17:54.204508+00:00", "stars": 0, "forks": 0, "watchers": 0, "open_issues": 0, "size": 17052, - "views_14d": 29, + "views_14d": 35, "unique_visitors_14d": 4, - "clones_14d": 3, - "unique_cloners_14d": 3, + "clones_14d": 4, + "unique_cloners_14d": 4, "language": "Python", "created_at": "2025-06-09T17:34:32Z", "updated_at": "2025-11-25T20:14:47Z", "topics": [] }, + "VectorInstitute/anomaly-detection": { + "repo_id": "VectorInstitute/anomaly-detection", + "name": "anomaly-detection", + "timestamp": "2025-12-03T19:17:58.393338+00:00", + "stars": 8, + "forks": 0, + "watchers": 19, + "open_issues": 0, + "size": 15604, + "views_14d": 42, + "unique_visitors_14d": 21, + "clones_14d": 2, + "unique_cloners_14d": 2, + "language": "Jupyter Notebook", + "created_at": "2023-03-20T16:43:29Z", + "updated_at": "2025-07-29T21:42:49Z", + "topics": [ + "anomaly-detection" + ] + }, "VectorInstitute/cyclops": { "repo_id": "VectorInstitute/cyclops", "name": "cyclops", - "timestamp": "2025-12-01T00:25:51.437294+00:00", + "timestamp": "2025-12-03T19:18:03.862165+00:00", "stars": 87, "forks": 14, "watchers": 8, "open_issues": 20, "size": 26986, - "views_14d": 57, - "unique_visitors_14d": 35, - "clones_14d": 153, - "unique_cloners_14d": 120, + "views_14d": 42, + "unique_visitors_14d": 28, + "clones_14d": 174, + "unique_cloners_14d": 126, "language": "Python", "created_at": "2022-02-21T21:15:08Z", "updated_at": "2025-10-16T06:37:02Z", @@ -193,64 +122,66 @@ "physionet" ] }, - "VectorInstitute/finetuning-and-alignment": { - "repo_id": "VectorInstitute/finetuning-and-alignment", - "name": "finetuning-and-alignment", - "timestamp": "2025-12-01T00:25:52.097101+00:00", - "stars": 11, - "forks": 3, + "VectorInstitute/recommender-systems": { + "repo_id": "VectorInstitute/recommender-systems", + "name": "recommender-systems", + "timestamp": "2025-12-03T19:18:08.732337+00:00", + "stars": 6, + "forks": 0, "watchers": 30, - "open_issues": 0, - "size": 27777, - "views_14d": 52, - "unique_visitors_14d": 8, - "clones_14d": 12, - "unique_cloners_14d": 12, + "open_issues": 1, + "size": 27200, + "views_14d": 0, + "unique_visitors_14d": 0, + "clones_14d": 3, + "unique_cloners_14d": 2, "language": "Jupyter Notebook", - "created_at": "2024-05-14T03:18:04Z", - "updated_at": "2025-11-27T02:38:26Z", + "created_at": "2022-06-09T21:10:48Z", + "updated_at": "2025-05-13T20:17:43Z", "topics": [ - "alignment", - "fine-tuning" + "recommender-system" ] }, - "VectorInstitute/diffusion-models": { - "repo_id": "VectorInstitute/diffusion-models", - "name": "diffusion-models", - "timestamp": "2025-12-01T00:25:52.803016+00:00", - "stars": 5, - "forks": 0, - "watchers": 10, - "open_issues": 1, - "size": 272452, - "views_14d": 18, - "unique_visitors_14d": 5, - "clones_14d": 8, - "unique_cloners_14d": 6, - "language": "Jupyter Notebook", - "created_at": "2024-06-12T17:52:14Z", - "updated_at": "2025-11-27T02:35:50Z", + "VectorInstitute/fed-rag": { + "repo_id": "VectorInstitute/fed-rag", + "name": "fed-rag", + "timestamp": "2025-12-03T19:18:14.623459+00:00", + "stars": 137, + "forks": 26, + "watchers": 6, + "open_issues": 50, + "size": 14133, + "views_14d": 161, + "unique_visitors_14d": 55, + "clones_14d": 160, + "unique_cloners_14d": 94, + "language": "Python", + "created_at": "2025-01-17T20:04:22Z", + "updated_at": "2025-11-26T21:02:01Z", "topics": [ - "diffusion-models", - "synthetic-data" + "deep-learning", + "federated-learning", + "llms", + "machine-learning", + "rag" ] }, "VectorInstitute/odyssey": { "repo_id": "VectorInstitute/odyssey", "name": "odyssey", - "timestamp": "2025-12-01T00:25:53.561528+00:00", + "timestamp": "2025-12-03T19:18:19.690361+00:00", "stars": 46, - "forks": 13, + "forks": 14, "watchers": 4, - "open_issues": 7, - "size": 106584, - "views_14d": 300, - "unique_visitors_14d": 33, - "clones_14d": 93, - "unique_cloners_14d": 50, + "open_issues": 8, + "size": 105566, + "views_14d": 406, + "unique_visitors_14d": 32, + "clones_14d": 115, + "unique_cloners_14d": 56, "language": "Python", "created_at": "2023-12-01T15:46:32Z", - "updated_at": "2025-11-27T10:08:06Z", + "updated_at": "2025-12-01T14:54:43Z", "topics": [ "electronic-health-record", "foundation-models", @@ -261,127 +192,35 @@ "transformers" ] }, - "VectorInstitute/crisp-nam": { - "repo_id": "VectorInstitute/crisp-nam", - "name": "crisp-nam", - "timestamp": "2025-12-01T00:25:54.159062+00:00", - "stars": 2, - "forks": 0, - "watchers": 0, - "open_issues": 0, - "size": 7170, - "views_14d": 39, - "unique_visitors_14d": 5, - "clones_14d": 5, - "unique_cloners_14d": 4, - "language": "Python", - "created_at": "2025-05-22T15:49:19Z", - "updated_at": "2025-11-25T20:44:42Z", - "topics": [] - }, - "VectorInstitute/FL4Health": { - "repo_id": "VectorInstitute/FL4Health", - "name": "FL4Health", - "timestamp": "2025-12-01T00:25:54.804801+00:00", - "stars": 48, - "forks": 15, - "watchers": 3, - "open_issues": 0, - "size": 234003, - "views_14d": 311, - "unique_visitors_14d": 52, - "clones_14d": 300, - "unique_cloners_14d": 137, - "language": "Python", - "created_at": "2022-09-16T12:54:29Z", - "updated_at": "2025-11-27T21:16:52Z", - "topics": [ - "deep-learning", - "distributed-learning", - "federated-learning", - "federated-learning-framework", - "healthcare", - "machine-learning" - ] - }, - "VectorInstitute/mmlearn": { - "repo_id": "VectorInstitute/mmlearn", - "name": "mmlearn", - "timestamp": "2025-12-01T00:25:55.470521+00:00", - "stars": 18, - "forks": 3, + "VectorInstitute/shared-encoder": { + "repo_id": "VectorInstitute/shared-encoder", + "name": "shared-encoder", + "timestamp": "2025-12-03T19:18:25.532404+00:00", + "stars": 9, + "forks": 1, "watchers": 4, - "open_issues": 7, - "size": 5293, - "views_14d": 9, - "unique_visitors_14d": 8, - "clones_14d": 55, - "unique_cloners_14d": 26, + "open_issues": 3, + "size": 157, + "views_14d": 10, + "unique_visitors_14d": 9, + "clones_14d": 8, + "unique_cloners_14d": 8, "language": "Python", - "created_at": "2024-08-07T18:50:11Z", - "updated_at": "2025-11-10T20:15:23Z", + "created_at": "2025-02-21T17:04:07Z", + "updated_at": "2025-10-02T02:00:56Z", "topics": [ "clip", - "contrastive-learning", - "i-jepa", - "multi-task-learning", + "mimic-cxr", + "multimodal", "multimodal-learning", - "zero-shot-classification", - "zero-shot-retrieval" - ] - }, - "VectorInstitute/atomgen": { - "repo_id": "VectorInstitute/atomgen", - "name": "atomgen", - "timestamp": "2025-12-01T00:25:56.118182+00:00", - "stars": 8, - "forks": 1, - "watchers": 2, - "open_issues": 0, - "size": 2577, - "views_14d": 27, - "unique_visitors_14d": 8, - "clones_14d": 80, - "unique_cloners_14d": 37, - "language": "Python", - "created_at": "2024-04-11T01:22:34Z", - "updated_at": "2025-11-24T21:04:24Z", - "topics": [ - "ai-for-science", - "atomistic-machine-learning", - "atomistic-models", - "atomistic-simulations", - "fine-tuning", - "huggingface", - "machine-learning", - "materials-science", - "pretrained-models", - "pytorch", - "transformers" + "quilt", + "shared-encoder" ] }, - "VectorInstitute/FLorist": { - "repo_id": "VectorInstitute/FLorist", - "name": "FLorist", - "timestamp": "2025-12-01T00:25:56.829118+00:00", - "stars": 10, - "forks": 1, - "watchers": 4, - "open_issues": 1, - "size": 5429, - "views_14d": 5, - "unique_visitors_14d": 5, - "clones_14d": 126, - "unique_cloners_14d": 51, - "language": "CSS", - "created_at": "2024-01-29T19:34:13Z", - "updated_at": "2025-11-24T20:31:52Z", - "topics": [] - }, "VectorInstitute/privacy-enhancing-techniques": { "repo_id": "VectorInstitute/privacy-enhancing-techniques", "name": "privacy-enhancing-techniques", - "timestamp": "2025-12-01T00:25:57.442292+00:00", + "timestamp": "2025-12-03T19:18:31.783295+00:00", "stars": 15, "forks": 9, "watchers": 16, @@ -403,104 +242,122 @@ "privacy" ] }, - "VectorInstitute/ai-deployment": { - "repo_id": "VectorInstitute/ai-deployment", - "name": "ai-deployment", - "timestamp": "2025-12-01T00:25:58.080016+00:00", - "stars": 8, - "forks": 29, - "watchers": 4, + "VectorInstitute/humanibench": { + "repo_id": "VectorInstitute/humanibench", + "name": "humanibench", + "timestamp": "2025-12-03T19:18:38.691241+00:00", + "stars": 6, + "forks": 1, + "watchers": 1, "open_issues": 0, - "size": 18502, - "views_14d": 20, - "unique_visitors_14d": 3, - "clones_14d": 25, - "unique_cloners_14d": 22, + "size": 21607, + "views_14d": 207, + "unique_visitors_14d": 26, + "clones_14d": 89, + "unique_cloners_14d": 61, "language": "Python", - "created_at": "2024-06-03T19:08:04Z", - "updated_at": "2025-11-27T02:32:45Z", + "created_at": "2025-01-28T14:55:04Z", + "updated_at": "2025-11-27T21:43:32Z", "topics": [ - "ai", - "deployment" + "evaluation-framework", + "multimodal-large-language-models", + "vlm" ] }, - "VectorInstitute/pmc-data-extraction": { - "repo_id": "VectorInstitute/pmc-data-extraction", - "name": "pmc-data-extraction", - "timestamp": "2025-12-01T00:25:58.798632+00:00", - "stars": 13, - "forks": 1, - "watchers": 1, - "open_issues": 6, - "size": 13482, - "views_14d": 36, - "unique_visitors_14d": 16, - "clones_14d": 9, - "unique_cloners_14d": 9, + "VectorInstitute/self-supervised-learning": { + "repo_id": "VectorInstitute/self-supervised-learning", + "name": "self-supervised-learning", + "timestamp": "2025-12-03T19:18:45.275901+00:00", + "stars": 3, + "forks": 0, + "watchers": 18, + "open_issues": 0, + "size": 84026, + "views_14d": 5, + "unique_visitors_14d": 1, + "clones_14d": 4, + "unique_cloners_14d": 4, "language": "Jupyter Notebook", - "created_at": "2024-09-12T17:32:48Z", - "updated_at": "2025-10-13T05:39:15Z", - "topics": [] + "created_at": "2023-08-17T15:25:42Z", + "updated_at": "2025-11-26T21:28:48Z", + "topics": [ + "contrastive-learning", + "masked-modelling", + "self-distillation", + "self-supervised-learning" + ] }, - "VectorInstitute/shared-encoder": { - "repo_id": "VectorInstitute/shared-encoder", - "name": "shared-encoder", - "timestamp": "2025-12-01T00:25:59.475032+00:00", - "stars": 9, + "VectorInstitute/FLorist": { + "repo_id": "VectorInstitute/FLorist", + "name": "FLorist", + "timestamp": "2025-12-03T19:18:52.108760+00:00", + "stars": 10, "forks": 1, "watchers": 4, - "open_issues": 3, - "size": 157, - "views_14d": 8, - "unique_visitors_14d": 7, - "clones_14d": 5, - "unique_cloners_14d": 5, + "open_issues": 1, + "size": 5675, + "views_14d": 11, + "unique_visitors_14d": 9, + "clones_14d": 269, + "unique_cloners_14d": 118, + "language": "CSS", + "created_at": "2024-01-29T19:34:13Z", + "updated_at": "2025-12-01T20:59:07Z", + "topics": [] + }, + "VectorInstitute/bias-in-the-picture-benchmark": { + "repo_id": "VectorInstitute/bias-in-the-picture-benchmark", + "name": "bias-in-the-picture-benchmark", + "timestamp": "2025-12-03T19:18:59.081331+00:00", + "stars": 3, + "forks": 0, + "watchers": 0, + "open_issues": 0, + "size": 9705, + "views_14d": 79, + "unique_visitors_14d": 11, + "clones_14d": 14, + "unique_cloners_14d": 12, "language": "Python", - "created_at": "2025-02-21T17:04:07Z", - "updated_at": "2025-10-02T02:00:56Z", - "topics": [ - "clip", - "mimic-cxr", - "multimodal", - "multimodal-learning", - "quilt", - "shared-encoder" - ] + "created_at": "2025-11-21T16:57:41Z", + "updated_at": "2025-11-26T21:34:25Z", + "topics": [] }, - "VectorInstitute/HV-Ai-C": { - "repo_id": "VectorInstitute/HV-Ai-C", - "name": "HV-Ai-C", - "timestamp": "2025-12-01T00:26:00.141731+00:00", - "stars": 73, - "forks": 22, - "watchers": 6, + "VectorInstitute/kg-rag": { + "repo_id": "VectorInstitute/kg-rag", + "name": "kg-rag", + "timestamp": "2025-12-03T19:19:05.330974+00:00", + "stars": 20, + "forks": 10, + "watchers": 2, "open_issues": 1, - "size": 223, - "views_14d": 93, - "unique_visitors_14d": 43, - "clones_14d": 14, - "unique_cloners_14d": 8, + "size": 44514, + "views_14d": 240, + "unique_visitors_14d": 83, + "clones_14d": 143, + "unique_cloners_14d": 67, "language": "Python", - "created_at": "2022-03-03T16:55:04Z", - "updated_at": "2025-11-10T06:49:37Z", + "created_at": "2024-12-11T17:22:56Z", + "updated_at": "2025-12-03T15:53:36Z", "topics": [ - "hvac-control", - "reinforcement-learning" + "knowledge-graph", + "llms", + "rag" ] }, "VectorInstitute/interpretability": { "repo_id": "VectorInstitute/interpretability", "name": "interpretability", - "timestamp": "2025-12-01T00:26:00.895530+00:00", + "timestamp": "2025-12-03T19:19:11.524417+00:00", "stars": 5, "forks": 0, "watchers": 7, "open_issues": 0, "size": 552929, - "views_14d": 143, - "unique_visitors_14d": 7, - "clones_14d": 14, - "unique_cloners_14d": 14, + "views_14d": 129, + "unique_visitors_14d": 6, + "clones_14d": 27, + "unique_cloners_14d": 19, "language": "Jupyter Notebook", "created_at": "2024-09-19T15:22:45Z", "updated_at": "2025-11-27T03:46:04Z", @@ -510,171 +367,314 @@ "machine-learning" ] }, - "VectorInstitute/self-supervised-learning": { - "repo_id": "VectorInstitute/self-supervised-learning", - "name": "self-supervised-learning", - "timestamp": "2025-12-01T00:26:01.616777+00:00", - "stars": 3, - "forks": 0, - "watchers": 18, - "open_issues": 0, - "size": 84026, - "views_14d": 5, - "unique_visitors_14d": 1, - "clones_14d": 3, - "unique_cloners_14d": 3, - "language": "Jupyter Notebook", - "created_at": "2023-08-17T15:25:42Z", - "updated_at": "2025-11-26T21:28:48Z", + "VectorInstitute/HV-Ai-C": { + "repo_id": "VectorInstitute/HV-Ai-C", + "name": "HV-Ai-C", + "timestamp": "2025-12-03T19:19:16.459865+00:00", + "stars": 74, + "forks": 22, + "watchers": 6, + "open_issues": 1, + "size": 223, + "views_14d": 98, + "unique_visitors_14d": 47, + "clones_14d": 16, + "unique_cloners_14d": 10, + "language": "Python", + "created_at": "2022-03-03T16:55:04Z", + "updated_at": "2025-12-03T19:07:08Z", "topics": [ - "contrastive-learning", - "masked-modelling", - "self-distillation", - "self-supervised-learning" + "hvac-control", + "reinforcement-learning" ] }, - "VectorInstitute/fed-rag": { - "repo_id": "VectorInstitute/fed-rag", - "name": "fed-rag", - "timestamp": "2025-12-01T00:26:02.328239+00:00", - "stars": 137, - "forks": 26, - "watchers": 6, - "open_issues": 50, - "size": 14126, - "views_14d": 173, - "unique_visitors_14d": 61, - "clones_14d": 177, - "unique_cloners_14d": 100, + "VectorInstitute/vector-inference": { + "repo_id": "VectorInstitute/vector-inference", + "name": "vector-inference", + "timestamp": "2025-12-03T19:19:21.417467+00:00", + "stars": 85, + "forks": 12, + "watchers": 7, + "open_issues": 5, + "size": 5897, + "views_14d": 305, + "unique_visitors_14d": 82, + "clones_14d": 238, + "unique_cloners_14d": 103, "language": "Python", - "created_at": "2025-01-17T20:04:22Z", - "updated_at": "2025-11-26T21:02:01Z", + "created_at": "2024-03-06T01:36:48Z", + "updated_at": "2025-12-02T17:32:32Z", "topics": [ - "deep-learning", - "federated-learning", - "llms", - "machine-learning", - "rag" + "inference", + "llm", + "llm-inference", + "reward-modeling", + "text-embedding", + "vllm", + "vlm" ] }, - "VectorInstitute/midst-toolkit": { - "repo_id": "VectorInstitute/midst-toolkit", - "name": "midst-toolkit", - "timestamp": "2025-12-01T00:26:02.935862+00:00", + "VectorInstitute/diffusion-models": { + "repo_id": "VectorInstitute/diffusion-models", + "name": "diffusion-models", + "timestamp": "2025-12-03T19:19:26.130791+00:00", "stars": 5, - "forks": 1, - "watchers": 0, + "forks": 0, + "watchers": 10, "open_issues": 1, - "size": 114381, - "views_14d": 636, - "unique_visitors_14d": 25, - "clones_14d": 473, - "unique_cloners_14d": 132, - "language": "Python", - "created_at": "2025-06-13T13:37:34Z", - "updated_at": "2025-11-28T18:44:31Z", + "size": 272452, + "views_14d": 23, + "unique_visitors_14d": 8, + "clones_14d": 11, + "unique_cloners_14d": 8, + "language": "Jupyter Notebook", + "created_at": "2024-06-12T17:52:14Z", + "updated_at": "2025-12-01T17:38:22Z", + "topics": [ + "diffusion-models", + "synthetic-data" + ] + }, + "VectorInstitute/pmc-data-extraction": { + "repo_id": "VectorInstitute/pmc-data-extraction", + "name": "pmc-data-extraction", + "timestamp": "2025-12-03T19:19:29.709204+00:00", + "stars": 13, + "forks": 1, + "watchers": 1, + "open_issues": 6, + "size": 13482, + "views_14d": 37, + "unique_visitors_14d": 15, + "clones_14d": 8, + "unique_cloners_14d": 8, + "language": "Jupyter Notebook", + "created_at": "2024-09-12T17:32:48Z", + "updated_at": "2025-10-13T05:39:15Z", "topics": [] }, - "VectorInstitute/anomaly-detection": { - "repo_id": "VectorInstitute/anomaly-detection", - "name": "anomaly-detection", - "timestamp": "2025-12-01T00:26:03.615906+00:00", + "VectorInstitute/ai-deployment": { + "repo_id": "VectorInstitute/ai-deployment", + "name": "ai-deployment", + "timestamp": "2025-12-03T19:19:33.241325+00:00", "stars": 8, - "forks": 0, - "watchers": 19, + "forks": 29, + "watchers": 4, "open_issues": 0, - "size": 15604, - "views_14d": 87, - "unique_visitors_14d": 27, - "clones_14d": 2, - "unique_cloners_14d": 2, + "size": 18502, + "views_14d": 25, + "unique_visitors_14d": 5, + "clones_14d": 26, + "unique_cloners_14d": 23, + "language": "Python", + "created_at": "2024-06-03T19:08:04Z", + "updated_at": "2025-11-27T02:32:45Z", + "topics": [ + "ai", + "deployment" + ] + }, + "VectorInstitute/bias-mitigation-unlearning": { + "repo_id": "VectorInstitute/bias-mitigation-unlearning", + "name": "bias-mitigation-unlearning", + "timestamp": "2025-12-03T19:19:36.643643+00:00", + "stars": 3, + "forks": 2, + "watchers": 1, + "open_issues": 6, + "size": 383, + "views_14d": 29, + "unique_visitors_14d": 5, + "clones_14d": 4, + "unique_cloners_14d": 3, + "language": "Python", + "created_at": "2024-10-09T20:05:04Z", + "updated_at": "2025-09-01T03:13:59Z", + "topics": [] + }, + "vectorinstitute/retrieval-augmented-generation": { + "repo_id": "vectorinstitute/retrieval-augmented-generation", + "name": "retrieval-augmented-generation", + "timestamp": "2025-12-03T19:19:40.366489+00:00", + "stars": 30, + "forks": 21, + "watchers": 24, + "open_issues": 1, + "size": 49310, + "views_14d": 184, + "unique_visitors_14d": 26, + "clones_14d": 98, + "unique_cloners_14d": 51, "language": "Jupyter Notebook", - "created_at": "2023-03-20T16:43:29Z", - "updated_at": "2025-07-29T21:42:49Z", + "created_at": "2023-11-30T19:17:30Z", + "updated_at": "2025-12-01T17:38:11Z", "topics": [ - "anomaly-detection" + "rag", + "retrieval-augmented-generation" ] }, - "VectorInstitute/masksql": { - "repo_id": "VectorInstitute/masksql", - "name": "masksql", - "timestamp": "2025-12-01T00:26:04.331881+00:00", - "stars": 1, + "VectorInstitute/crisp-nam": { + "repo_id": "VectorInstitute/crisp-nam", + "name": "crisp-nam", + "timestamp": "2025-12-03T19:19:44.741810+00:00", + "stars": 2, "forks": 0, "watchers": 0, - "open_issues": 3, - "size": 5468, - "views_14d": 202, - "unique_visitors_14d": 7, - "clones_14d": 109, - "unique_cloners_14d": 30, + "open_issues": 0, + "size": 7170, + "views_14d": 21, + "unique_visitors_14d": 4, + "clones_14d": 6, + "unique_cloners_14d": 5, "language": "Python", - "created_at": "2025-10-15T20:14:06Z", - "updated_at": "2025-11-24T15:17:01Z", + "created_at": "2025-05-22T15:49:19Z", + "updated_at": "2025-11-25T20:44:42Z", "topics": [] }, - "VectorInstitute/vbll": { - "repo_id": "VectorInstitute/vbll", - "name": "vbll", - "timestamp": "2025-12-01T00:26:05.009947+00:00", - "stars": 77, - "forks": 7, - "watchers": 2, - "open_issues": 4, - "size": 551, - "views_14d": 350, - "unique_visitors_14d": 49, - "clones_14d": 9, - "unique_cloners_14d": 8, + "VectorInstitute/mcp-goodnews": { + "repo_id": "VectorInstitute/mcp-goodnews", + "name": "mcp-goodnews", + "timestamp": "2025-12-03T19:19:50.234908+00:00", + "stars": 44, + "forks": 9, + "watchers": 0, + "open_issues": 1, + "size": 101, + "views_14d": 62, + "unique_visitors_14d": 42, + "clones_14d": 68, + "unique_cloners_14d": 50, "language": "Python", - "created_at": "2023-10-11T15:26:23Z", - "updated_at": "2025-11-11T10:51:53Z", + "created_at": "2025-03-18T18:06:25Z", + "updated_at": "2025-11-26T21:32:12Z", "topics": [] }, - "VectorInstitute/vector-inference": { - "repo_id": "VectorInstitute/vector-inference", - "name": "vector-inference", - "timestamp": "2025-12-01T00:26:05.639304+00:00", - "stars": 84, - "forks": 12, - "watchers": 7, - "open_issues": 5, - "size": 5883, - "views_14d": 325, - "unique_visitors_14d": 88, - "clones_14d": 147, - "unique_cloners_14d": 73, + "VectorInstitute/mmlearn": { + "repo_id": "VectorInstitute/mmlearn", + "name": "mmlearn", + "timestamp": "2025-12-03T19:19:55.407432+00:00", + "stars": 19, + "forks": 3, + "watchers": 4, + "open_issues": 7, + "size": 5296, + "views_14d": 18, + "unique_visitors_14d": 6, + "clones_14d": 62, + "unique_cloners_14d": 28, "language": "Python", - "created_at": "2024-03-06T01:36:48Z", - "updated_at": "2025-11-27T18:57:10Z", + "created_at": "2024-08-07T18:50:11Z", + "updated_at": "2025-12-02T13:31:50Z", "topics": [ - "inference", - "llm", - "llm-inference", - "reward-modeling", - "text-embedding", - "vllm", - "vlm" + "clip", + "contrastive-learning", + "i-jepa", + "multi-task-learning", + "multimodal-learning", + "zero-shot-classification", + "zero-shot-retrieval" ] }, + "VectorInstitute/finetuning-and-alignment": { + "repo_id": "VectorInstitute/finetuning-and-alignment", + "name": "finetuning-and-alignment", + "timestamp": "2025-12-03T19:19:59.310120+00:00", + "stars": 11, + "forks": 3, + "watchers": 30, + "open_issues": 0, + "size": 27777, + "views_14d": 27, + "unique_visitors_14d": 6, + "clones_14d": 18, + "unique_cloners_14d": 16, + "language": "Jupyter Notebook", + "created_at": "2024-05-14T03:18:04Z", + "updated_at": "2025-11-27T02:38:26Z", + "topics": [ + "alignment", + "fine-tuning" + ] + }, + "VectorInstitute/masksql": { + "repo_id": "VectorInstitute/masksql", + "name": "masksql", + "timestamp": "2025-12-03T19:20:02.916058+00:00", + "stars": 1, + "forks": 0, + "watchers": 0, + "open_issues": 2, + "size": 5529, + "views_14d": 161, + "unique_visitors_14d": 8, + "clones_14d": 190, + "unique_cloners_14d": 65, + "language": "Python", + "created_at": "2025-10-15T20:14:06Z", + "updated_at": "2025-12-03T15:52:15Z", + "topics": [] + }, "VectorInstitute/fair-sense-ai": { "repo_id": "VectorInstitute/fair-sense-ai", "name": "fair-sense-ai", - "timestamp": "2025-12-01T00:26:06.411908+00:00", + "timestamp": "2025-12-03T19:20:07.624416+00:00", "stars": 5, "forks": 2, "watchers": 0, "open_issues": 0, "size": 13906, - "views_14d": 53, - "unique_visitors_14d": 14, - "clones_14d": 5, - "unique_cloners_14d": 4, + "views_14d": 83, + "unique_visitors_14d": 20, + "clones_14d": 4, + "unique_cloners_14d": 3, "language": "Python", "created_at": "2025-01-08T20:10:48Z", "updated_at": "2025-08-29T07:22:56Z", "topics": [] + }, + "VectorInstitute/FL4Health": { + "repo_id": "VectorInstitute/FL4Health", + "name": "FL4Health", + "timestamp": "2025-12-03T19:20:12.913151+00:00", + "stars": 48, + "forks": 15, + "watchers": 3, + "open_issues": 4, + "size": 234664, + "views_14d": 276, + "unique_visitors_14d": 50, + "clones_14d": 358, + "unique_cloners_14d": 151, + "language": "Python", + "created_at": "2022-09-16T12:54:29Z", + "updated_at": "2025-11-27T21:16:52Z", + "topics": [ + "deep-learning", + "distributed-learning", + "federated-learning", + "federated-learning-framework", + "healthcare", + "machine-learning" + ] + }, + "VectorInstitute/vbll": { + "repo_id": "VectorInstitute/vbll", + "name": "vbll", + "timestamp": "2025-12-03T19:20:18.504534+00:00", + "stars": 78, + "forks": 7, + "watchers": 2, + "open_issues": 4, + "size": 551, + "views_14d": 297, + "unique_visitors_14d": 43, + "clones_14d": 8, + "unique_cloners_14d": 7, + "language": "Python", + "created_at": "2023-10-11T15:26:23Z", + "updated_at": "2025-12-02T04:43:16Z", + "topics": [] } }, - "last_updated": "2025-12-01T00:26:07.055850+00:00" -} \ No newline at end of file + "last_updated": "2025-12-03T19:20:23.222751+00:00" +} diff --git a/catalog/public/data/github_metrics_history.json b/catalog/public/data/github_metrics_history.json index 701ab13..9404be9 100644 --- a/catalog/public/data/github_metrics_history.json +++ b/catalog/public/data/github_metrics_history.json @@ -164,6 +164,24 @@ "created_at": "2025-06-13T13:37:34Z", "updated_at": "2025-11-28T18:44:31Z", "topics": [] + }, + { + "repo_id": "VectorInstitute/midst-toolkit", + "name": "midst-toolkit", + "timestamp": "2025-12-03T19:17:46.684919+00:00", + "stars": 5, + "forks": 1, + "watchers": 0, + "open_issues": 1, + "size": 114921, + "views_14d": 673, + "unique_visitors_14d": 26, + "clones_14d": 692, + "unique_cloners_14d": 237, + "language": "Python", + "created_at": "2025-06-13T13:37:34Z", + "updated_at": "2025-12-02T22:11:24Z", + "topics": [] } ] }, @@ -439,6 +457,36 @@ "pytorch", "transformers" ] + }, + { + "repo_id": "VectorInstitute/atomgen", + "name": "atomgen", + "timestamp": "2025-12-03T19:17:51.563667+00:00", + "stars": 8, + "forks": 1, + "watchers": 2, + "open_issues": 1, + "size": 2579, + "views_14d": 14, + "unique_visitors_14d": 7, + "clones_14d": 76, + "unique_cloners_14d": 38, + "language": "Python", + "created_at": "2024-04-11T01:22:34Z", + "updated_at": "2025-11-24T21:04:24Z", + "topics": [ + "ai-for-science", + "atomistic-machine-learning", + "atomistic-models", + "atomistic-simulations", + "fine-tuning", + "huggingface", + "machine-learning", + "materials-science", + "pretrained-models", + "pytorch", + "transformers" + ] } ] }, @@ -624,6 +672,26 @@ "topics": [ "anomaly-detection" ] + }, + { + "repo_id": "VectorInstitute/anomaly-detection", + "name": "anomaly-detection", + "timestamp": "2025-12-03T19:17:58.393338+00:00", + "stars": 8, + "forks": 0, + "watchers": 19, + "open_issues": 0, + "size": 15604, + "views_14d": 42, + "unique_visitors_14d": 21, + "clones_14d": 2, + "unique_cloners_14d": 2, + "language": "Jupyter Notebook", + "created_at": "2023-03-20T16:43:29Z", + "updated_at": "2025-07-29T21:42:49Z", + "topics": [ + "anomaly-detection" + ] } ] }, @@ -953,6 +1021,42 @@ "omop-cdm", "physionet" ] + }, + { + "repo_id": "VectorInstitute/cyclops", + "name": "cyclops", + "timestamp": "2025-12-03T19:18:03.862165+00:00", + "stars": 87, + "forks": 14, + "watchers": 8, + "open_issues": 20, + "size": 26986, + "views_14d": 42, + "unique_visitors_14d": 28, + "clones_14d": 174, + "unique_cloners_14d": 126, + "language": "Python", + "created_at": "2022-02-21T21:15:08Z", + "updated_at": "2025-10-16T06:37:02Z", + "topics": [ + "clinical-data", + "clinical-decision-support", + "clinical-research", + "data-drift", + "deep-learning", + "drift-detection", + "eicu-crd", + "electronic-health-record", + "electronic-medical-record", + "evaluation", + "healthcare", + "machine-learning", + "mimic-iii", + "mimic-iv", + "model-monitoring", + "omop-cdm", + "physionet" + ] } ] }, @@ -1138,6 +1242,26 @@ "topics": [ "recommender-system" ] + }, + { + "repo_id": "VectorInstitute/recommender-systems", + "name": "recommender-systems", + "timestamp": "2025-12-03T19:18:08.732337+00:00", + "stars": 6, + "forks": 0, + "watchers": 30, + "open_issues": 1, + "size": 27200, + "views_14d": 0, + "unique_visitors_14d": 0, + "clones_14d": 3, + "unique_cloners_14d": 2, + "language": "Jupyter Notebook", + "created_at": "2022-06-09T21:10:48Z", + "updated_at": "2025-05-13T20:17:43Z", + "topics": [ + "recommender-system" + ] } ] }, @@ -1359,6 +1483,30 @@ "machine-learning", "rag" ] + }, + { + "repo_id": "VectorInstitute/fed-rag", + "name": "fed-rag", + "timestamp": "2025-12-03T19:18:14.623459+00:00", + "stars": 137, + "forks": 26, + "watchers": 6, + "open_issues": 50, + "size": 14133, + "views_14d": 161, + "unique_visitors_14d": 55, + "clones_14d": 160, + "unique_cloners_14d": 94, + "language": "Python", + "created_at": "2025-01-17T20:04:22Z", + "updated_at": "2025-11-26T21:02:01Z", + "topics": [ + "deep-learning", + "federated-learning", + "llms", + "machine-learning", + "rag" + ] } ] }, @@ -1598,6 +1746,32 @@ "state-space-models", "transformers" ] + }, + { + "repo_id": "VectorInstitute/odyssey", + "name": "odyssey", + "timestamp": "2025-12-03T19:18:19.690361+00:00", + "stars": 46, + "forks": 14, + "watchers": 4, + "open_issues": 8, + "size": 105566, + "views_14d": 406, + "unique_visitors_14d": 32, + "clones_14d": 115, + "unique_cloners_14d": 56, + "language": "Python", + "created_at": "2023-12-01T15:46:32Z", + "updated_at": "2025-12-01T14:54:43Z", + "topics": [ + "electronic-health-record", + "foundation-models", + "healthcare", + "machine-learning", + "mimic-iv", + "state-space-models", + "transformers" + ] } ] }, @@ -1828,6 +2002,31 @@ "quilt", "shared-encoder" ] + }, + { + "repo_id": "VectorInstitute/shared-encoder", + "name": "shared-encoder", + "timestamp": "2025-12-03T19:18:25.532404+00:00", + "stars": 9, + "forks": 1, + "watchers": 4, + "open_issues": 3, + "size": 157, + "views_14d": 10, + "unique_visitors_14d": 9, + "clones_14d": 8, + "unique_cloners_14d": 8, + "language": "Python", + "created_at": "2025-02-21T17:04:07Z", + "updated_at": "2025-10-02T02:00:56Z", + "topics": [ + "clip", + "mimic-cxr", + "multimodal", + "multimodal-learning", + "quilt", + "shared-encoder" + ] } ] }, @@ -2058,6 +2257,31 @@ "ml", "privacy" ] + }, + { + "repo_id": "VectorInstitute/privacy-enhancing-techniques", + "name": "privacy-enhancing-techniques", + "timestamp": "2025-12-03T19:18:31.783295+00:00", + "stars": 15, + "forks": 9, + "watchers": 16, + "open_issues": 0, + "size": 35253, + "views_14d": 4, + "unique_visitors_14d": 3, + "clones_14d": 7, + "unique_cloners_14d": 5, + "language": "Jupyter Notebook", + "created_at": "2021-09-28T17:43:56Z", + "updated_at": "2025-07-30T00:00:30Z", + "topics": [ + "differential-privacy", + "encryption", + "federated-learning", + "machine-learning", + "ml", + "privacy" + ] } ] }, @@ -2270,6 +2494,29 @@ "self-distillation", "self-supervised-learning" ] + }, + { + "repo_id": "VectorInstitute/self-supervised-learning", + "name": "self-supervised-learning", + "timestamp": "2025-12-03T19:18:45.275901+00:00", + "stars": 3, + "forks": 0, + "watchers": 18, + "open_issues": 0, + "size": 84026, + "views_14d": 5, + "unique_visitors_14d": 1, + "clones_14d": 4, + "unique_cloners_14d": 4, + "language": "Jupyter Notebook", + "created_at": "2023-08-17T15:25:42Z", + "updated_at": "2025-11-26T21:28:48Z", + "topics": [ + "contrastive-learning", + "masked-modelling", + "self-distillation", + "self-supervised-learning" + ] } ] }, @@ -2437,6 +2684,24 @@ "created_at": "2024-01-29T19:34:13Z", "updated_at": "2025-11-24T20:31:52Z", "topics": [] + }, + { + "repo_id": "VectorInstitute/FLorist", + "name": "FLorist", + "timestamp": "2025-12-03T19:18:52.108760+00:00", + "stars": 10, + "forks": 1, + "watchers": 4, + "open_issues": 1, + "size": 5675, + "views_14d": 11, + "unique_visitors_14d": 9, + "clones_14d": 269, + "unique_cloners_14d": 118, + "language": "CSS", + "created_at": "2024-01-29T19:34:13Z", + "updated_at": "2025-12-01T20:59:07Z", + "topics": [] } ] }, @@ -2604,6 +2869,24 @@ "created_at": "2025-11-21T16:57:41Z", "updated_at": "2025-11-26T21:34:25Z", "topics": [] + }, + { + "repo_id": "VectorInstitute/bias-in-the-picture-benchmark", + "name": "bias-in-the-picture-benchmark", + "timestamp": "2025-12-03T19:18:59.081331+00:00", + "stars": 3, + "forks": 0, + "watchers": 0, + "open_issues": 0, + "size": 9705, + "views_14d": 79, + "unique_visitors_14d": 11, + "clones_14d": 14, + "unique_cloners_14d": 12, + "language": "Python", + "created_at": "2025-11-21T16:57:41Z", + "updated_at": "2025-11-26T21:34:25Z", + "topics": [] } ] }, @@ -2807,6 +3090,28 @@ "llms", "rag" ] + }, + { + "repo_id": "VectorInstitute/kg-rag", + "name": "kg-rag", + "timestamp": "2025-12-03T19:19:05.330974+00:00", + "stars": 20, + "forks": 10, + "watchers": 2, + "open_issues": 1, + "size": 44514, + "views_14d": 240, + "unique_visitors_14d": 83, + "clones_14d": 143, + "unique_cloners_14d": 67, + "language": "Python", + "created_at": "2024-12-11T17:22:56Z", + "updated_at": "2025-12-03T15:53:36Z", + "topics": [ + "knowledge-graph", + "llms", + "rag" + ] } ] }, @@ -2990,9 +3295,31 @@ "interpretability", "machine-learning" ] - } - ] - }, + }, + { + "repo_id": "VectorInstitute/interpretability", + "name": "interpretability", + "timestamp": "2025-12-03T19:19:11.524417+00:00", + "stars": 5, + "forks": 0, + "watchers": 7, + "open_issues": 0, + "size": 552929, + "views_14d": 129, + "unique_visitors_14d": 6, + "clones_14d": 27, + "unique_cloners_14d": 19, + "language": "Jupyter Notebook", + "created_at": "2024-09-19T15:22:45Z", + "updated_at": "2025-11-27T03:46:04Z", + "topics": [ + "ai", + "interpretability", + "machine-learning" + ] + } + ] + }, "VectorInstitute/vector-inference": { "name": "vector-inference", "snapshots": [ @@ -3229,6 +3556,32 @@ "vllm", "vlm" ] + }, + { + "repo_id": "VectorInstitute/vector-inference", + "name": "vector-inference", + "timestamp": "2025-12-03T19:19:21.417467+00:00", + "stars": 85, + "forks": 12, + "watchers": 7, + "open_issues": 5, + "size": 5897, + "views_14d": 305, + "unique_visitors_14d": 82, + "clones_14d": 238, + "unique_cloners_14d": 103, + "language": "Python", + "created_at": "2024-03-06T01:36:48Z", + "updated_at": "2025-12-02T17:32:32Z", + "topics": [ + "inference", + "llm", + "llm-inference", + "reward-modeling", + "text-embedding", + "vllm", + "vlm" + ] } ] }, @@ -3423,6 +3776,27 @@ "diffusion-models", "synthetic-data" ] + }, + { + "repo_id": "VectorInstitute/diffusion-models", + "name": "diffusion-models", + "timestamp": "2025-12-03T19:19:26.130791+00:00", + "stars": 5, + "forks": 0, + "watchers": 10, + "open_issues": 1, + "size": 272452, + "views_14d": 23, + "unique_visitors_14d": 8, + "clones_14d": 11, + "unique_cloners_14d": 8, + "language": "Jupyter Notebook", + "created_at": "2024-06-12T17:52:14Z", + "updated_at": "2025-12-01T17:38:22Z", + "topics": [ + "diffusion-models", + "synthetic-data" + ] } ] }, @@ -3590,6 +3964,24 @@ "created_at": "2024-09-12T17:32:48Z", "updated_at": "2025-10-13T05:39:15Z", "topics": [] + }, + { + "repo_id": "VectorInstitute/pmc-data-extraction", + "name": "pmc-data-extraction", + "timestamp": "2025-12-03T19:19:29.709204+00:00", + "stars": 13, + "forks": 1, + "watchers": 1, + "open_issues": 6, + "size": 13482, + "views_14d": 37, + "unique_visitors_14d": 15, + "clones_14d": 8, + "unique_cloners_14d": 8, + "language": "Jupyter Notebook", + "created_at": "2024-09-12T17:32:48Z", + "updated_at": "2025-10-13T05:39:15Z", + "topics": [] } ] }, @@ -3769,6 +4161,27 @@ "ai", "deployment" ] + }, + { + "repo_id": "VectorInstitute/ai-deployment", + "name": "ai-deployment", + "timestamp": "2025-12-03T19:19:33.241325+00:00", + "stars": 8, + "forks": 29, + "watchers": 4, + "open_issues": 0, + "size": 18502, + "views_14d": 25, + "unique_visitors_14d": 5, + "clones_14d": 26, + "unique_cloners_14d": 23, + "language": "Python", + "created_at": "2024-06-03T19:08:04Z", + "updated_at": "2025-11-27T02:32:45Z", + "topics": [ + "ai", + "deployment" + ] } ] }, @@ -3936,6 +4349,24 @@ "created_at": "2024-10-09T20:05:04Z", "updated_at": "2025-09-01T03:13:59Z", "topics": [] + }, + { + "repo_id": "VectorInstitute/bias-mitigation-unlearning", + "name": "bias-mitigation-unlearning", + "timestamp": "2025-12-03T19:19:36.643643+00:00", + "stars": 3, + "forks": 2, + "watchers": 1, + "open_issues": 6, + "size": 383, + "views_14d": 29, + "unique_visitors_14d": 5, + "clones_14d": 4, + "unique_cloners_14d": 3, + "language": "Python", + "created_at": "2024-10-09T20:05:04Z", + "updated_at": "2025-09-01T03:13:59Z", + "topics": [] } ] }, @@ -4115,6 +4546,27 @@ "rag", "retrieval-augmented-generation" ] + }, + { + "repo_id": "vectorinstitute/retrieval-augmented-generation", + "name": "retrieval-augmented-generation", + "timestamp": "2025-12-03T19:19:40.366489+00:00", + "stars": 30, + "forks": 21, + "watchers": 24, + "open_issues": 1, + "size": 49310, + "views_14d": 184, + "unique_visitors_14d": 26, + "clones_14d": 98, + "unique_cloners_14d": 51, + "language": "Jupyter Notebook", + "created_at": "2023-11-30T19:17:30Z", + "updated_at": "2025-12-01T17:38:11Z", + "topics": [ + "rag", + "retrieval-augmented-generation" + ] } ] }, @@ -4282,6 +4734,24 @@ "created_at": "2025-05-22T15:49:19Z", "updated_at": "2025-11-25T20:44:42Z", "topics": [] + }, + { + "repo_id": "VectorInstitute/crisp-nam", + "name": "crisp-nam", + "timestamp": "2025-12-03T19:19:44.741810+00:00", + "stars": 2, + "forks": 0, + "watchers": 0, + "open_issues": 0, + "size": 7170, + "views_14d": 21, + "unique_visitors_14d": 4, + "clones_14d": 6, + "unique_cloners_14d": 5, + "language": "Python", + "created_at": "2025-05-22T15:49:19Z", + "updated_at": "2025-11-25T20:44:42Z", + "topics": [] } ] }, @@ -4521,6 +4991,32 @@ "zero-shot-classification", "zero-shot-retrieval" ] + }, + { + "repo_id": "VectorInstitute/mmlearn", + "name": "mmlearn", + "timestamp": "2025-12-03T19:19:55.407432+00:00", + "stars": 19, + "forks": 3, + "watchers": 4, + "open_issues": 7, + "size": 5296, + "views_14d": 18, + "unique_visitors_14d": 6, + "clones_14d": 62, + "unique_cloners_14d": 28, + "language": "Python", + "created_at": "2024-08-07T18:50:11Z", + "updated_at": "2025-12-02T13:31:50Z", + "topics": [ + "clip", + "contrastive-learning", + "i-jepa", + "multi-task-learning", + "multimodal-learning", + "zero-shot-classification", + "zero-shot-retrieval" + ] } ] }, @@ -4700,6 +5196,27 @@ "alignment", "fine-tuning" ] + }, + { + "repo_id": "VectorInstitute/finetuning-and-alignment", + "name": "finetuning-and-alignment", + "timestamp": "2025-12-03T19:19:59.310120+00:00", + "stars": 11, + "forks": 3, + "watchers": 30, + "open_issues": 0, + "size": 27777, + "views_14d": 27, + "unique_visitors_14d": 6, + "clones_14d": 18, + "unique_cloners_14d": 16, + "language": "Jupyter Notebook", + "created_at": "2024-05-14T03:18:04Z", + "updated_at": "2025-11-27T02:38:26Z", + "topics": [ + "alignment", + "fine-tuning" + ] } ] }, @@ -4867,6 +5384,24 @@ "created_at": "2025-10-15T20:14:06Z", "updated_at": "2025-11-24T15:17:01Z", "topics": [] + }, + { + "repo_id": "VectorInstitute/masksql", + "name": "masksql", + "timestamp": "2025-12-03T19:20:02.916058+00:00", + "stars": 1, + "forks": 0, + "watchers": 0, + "open_issues": 2, + "size": 5529, + "views_14d": 161, + "unique_visitors_14d": 8, + "clones_14d": 190, + "unique_cloners_14d": 65, + "language": "Python", + "created_at": "2025-10-15T20:14:06Z", + "updated_at": "2025-12-03T15:52:15Z", + "topics": [] } ] }, @@ -5034,6 +5569,24 @@ "created_at": "2025-01-08T20:10:48Z", "updated_at": "2025-08-29T07:22:56Z", "topics": [] + }, + { + "repo_id": "VectorInstitute/fair-sense-ai", + "name": "fair-sense-ai", + "timestamp": "2025-12-03T19:20:07.624416+00:00", + "stars": 5, + "forks": 2, + "watchers": 0, + "open_issues": 0, + "size": 13906, + "views_14d": 83, + "unique_visitors_14d": 20, + "clones_14d": 4, + "unique_cloners_14d": 3, + "language": "Python", + "created_at": "2025-01-08T20:10:48Z", + "updated_at": "2025-08-29T07:22:56Z", + "topics": [] } ] }, @@ -5264,6 +5817,31 @@ "healthcare", "machine-learning" ] + }, + { + "repo_id": "VectorInstitute/FL4Health", + "name": "FL4Health", + "timestamp": "2025-12-03T19:20:12.913151+00:00", + "stars": 48, + "forks": 15, + "watchers": 3, + "open_issues": 4, + "size": 234664, + "views_14d": 276, + "unique_visitors_14d": 50, + "clones_14d": 358, + "unique_cloners_14d": 151, + "language": "Python", + "created_at": "2022-09-16T12:54:29Z", + "updated_at": "2025-11-27T21:16:52Z", + "topics": [ + "deep-learning", + "distributed-learning", + "federated-learning", + "federated-learning-framework", + "healthcare", + "machine-learning" + ] } ] }, @@ -5377,6 +5955,24 @@ "created_at": "2025-06-09T17:34:32Z", "updated_at": "2025-11-25T20:14:47Z", "topics": [] + }, + { + "repo_id": "VectorInstitute/linguamark", + "name": "linguamark", + "timestamp": "2025-12-03T19:17:54.204508+00:00", + "stars": 0, + "forks": 0, + "watchers": 0, + "open_issues": 0, + "size": 17052, + "views_14d": 35, + "unique_visitors_14d": 4, + "clones_14d": 4, + "unique_cloners_14d": 4, + "language": "Python", + "created_at": "2025-06-09T17:34:32Z", + "updated_at": "2025-11-25T20:14:47Z", + "topics": [] } ] }, @@ -5514,6 +6110,28 @@ "multimodal-large-language-models", "vlm" ] + }, + { + "repo_id": "VectorInstitute/humanibench", + "name": "humanibench", + "timestamp": "2025-12-03T19:18:38.691241+00:00", + "stars": 6, + "forks": 1, + "watchers": 1, + "open_issues": 0, + "size": 21607, + "views_14d": 207, + "unique_visitors_14d": 26, + "clones_14d": 89, + "unique_cloners_14d": 61, + "language": "Python", + "created_at": "2025-01-28T14:55:04Z", + "updated_at": "2025-11-27T21:43:32Z", + "topics": [ + "evaluation-framework", + "multimodal-large-language-models", + "vlm" + ] } ] }, @@ -5591,6 +6209,24 @@ "created_at": "2023-10-11T15:26:23Z", "updated_at": "2025-11-11T10:51:53Z", "topics": [] + }, + { + "repo_id": "VectorInstitute/vbll", + "name": "vbll", + "timestamp": "2025-12-03T19:20:18.504534+00:00", + "stars": 78, + "forks": 7, + "watchers": 2, + "open_issues": 4, + "size": 551, + "views_14d": 297, + "unique_visitors_14d": 43, + "clones_14d": 8, + "unique_cloners_14d": 7, + "language": "Python", + "created_at": "2023-10-11T15:26:23Z", + "updated_at": "2025-12-02T04:43:16Z", + "topics": [] } ] }, @@ -5659,6 +6295,27 @@ "hvac-control", "reinforcement-learning" ] + }, + { + "repo_id": "VectorInstitute/HV-Ai-C", + "name": "HV-Ai-C", + "timestamp": "2025-12-03T19:19:16.459865+00:00", + "stars": 74, + "forks": 22, + "watchers": 6, + "open_issues": 1, + "size": 223, + "views_14d": 98, + "unique_visitors_14d": 47, + "clones_14d": 16, + "unique_cloners_14d": 10, + "language": "Python", + "created_at": "2022-03-03T16:55:04Z", + "updated_at": "2025-12-03T19:07:08Z", + "topics": [ + "hvac-control", + "reinforcement-learning" + ] } ] }, @@ -5700,9 +6357,27 @@ "created_at": "2025-03-18T18:06:25Z", "updated_at": "2025-11-26T21:32:12Z", "topics": [] + }, + { + "repo_id": "VectorInstitute/mcp-goodnews", + "name": "mcp-goodnews", + "timestamp": "2025-12-03T19:19:50.234908+00:00", + "stars": 44, + "forks": 9, + "watchers": 0, + "open_issues": 1, + "size": 101, + "views_14d": 62, + "unique_visitors_14d": 42, + "clones_14d": 68, + "unique_cloners_14d": 50, + "language": "Python", + "created_at": "2025-03-18T18:06:25Z", + "updated_at": "2025-11-26T21:32:12Z", + "topics": [] } ] } }, - "last_updated": "2025-12-01T00:26:06.411908+00:00" -} \ No newline at end of file + "last_updated": "2025-12-03T19:20:18.504534+00:00" +} diff --git a/catalog/public/data/pypi_metrics.json b/catalog/public/data/pypi_metrics.json index e946ffd..cf6914c 100644 --- a/catalog/public/data/pypi_metrics.json +++ b/catalog/public/data/pypi_metrics.json @@ -5,11 +5,11 @@ "name": "cyclops", "package_name": "pycyclops", "type": "tool", - "timestamp": "2025-11-27T13:59:34.227902+00:00", - "downloads_last_day": 108, - "downloads_last_week": 439, - "downloads_last_month": 1839, - "total_downloads": 5179, + "timestamp": "2025-12-03T19:22:40.934525+00:00", + "downloads_last_day": 1, + "downloads_last_week": 192, + "downloads_last_month": 1633, + "total_downloads": 5162, "version": "0.2.12", "release_date": "2025-01-22T16:00:42" }, @@ -18,11 +18,11 @@ "name": "fed-rag", "package_name": "fed-rag", "type": "tool", - "timestamp": "2025-11-27T13:59:35.616226+00:00", - "downloads_last_day": 102, - "downloads_last_week": 110, - "downloads_last_month": 132, - "total_downloads": 2034, + "timestamp": "2025-12-03T19:22:44.750204+00:00", + "downloads_last_day": null, + "downloads_last_week": 149, + "downloads_last_month": 175, + "total_downloads": 1825, "version": "0.0.27", "release_date": "2025-06-18T04:08:33" }, @@ -31,11 +31,11 @@ "name": "hv-ai-c", "package_name": "hnp", "type": "tool", - "timestamp": "2025-11-27T13:59:36.822328+00:00", - "downloads_last_day": 11, - "downloads_last_week": 36, - "downloads_last_month": 65, - "total_downloads": 222, + "timestamp": "2025-12-03T19:22:48.386917+00:00", + "downloads_last_day": 12, + "downloads_last_week": 37, + "downloads_last_month": 84, + "total_downloads": 237, "version": "1.1.2", "release_date": "2023-03-08T05:07:41" }, @@ -44,24 +44,24 @@ "name": "vector-inference", "package_name": "vec-inf", "type": "tool", - "timestamp": "2025-11-27T13:59:38.103741+00:00", - "downloads_last_day": 1, - "downloads_last_week": 8, - "downloads_last_month": 183, - "total_downloads": 889, - "version": "0.7.2", - "release_date": "2025-11-04T23:24:41" + "timestamp": "2025-12-03T19:22:51.513664+00:00", + "downloads_last_day": 9, + "downloads_last_week": 113, + "downloads_last_month": 270, + "total_downloads": 989, + "version": "0.7.3", + "release_date": "2025-11-27T19:01:50" }, "aieng-rag-utils": { "repo_id": "vectorinstitute/retrieval-augmented-generation", "name": "retrieval-augmented-generation", "package_name": "aieng-rag-utils", "type": "bootcamp", - "timestamp": "2025-11-27T13:59:39.279837+00:00", + "timestamp": "2025-12-03T19:22:55.591891+00:00", "downloads_last_day": null, - "downloads_last_week": 3, - "downloads_last_month": 29, - "total_downloads": 419, + "downloads_last_week": null, + "downloads_last_month": 21, + "total_downloads": 346, "version": "1.0.0", "release_date": "2025-07-29T20:43:26" }, @@ -70,11 +70,11 @@ "name": "fair-sense-ai", "package_name": "fair-sense-ai", "type": "tool", - "timestamp": "2025-11-27T13:59:40.443723+00:00", - "downloads_last_day": 2, - "downloads_last_week": 12, - "downloads_last_month": 56, - "total_downloads": 802, + "timestamp": "2025-12-03T19:22:59.941732+00:00", + "downloads_last_day": null, + "downloads_last_week": 8, + "downloads_last_month": 27, + "total_downloads": 777, "version": "1.0.11", "release_date": "2025-06-21T18:46:37" }, @@ -83,27 +83,27 @@ "name": "fl4health", "package_name": "fl4health", "type": "tool", - "timestamp": "2025-11-27T13:59:41.649661+00:00", + "timestamp": "2025-12-03T19:23:05.019919+00:00", "downloads_last_day": 2, - "downloads_last_week": 61, - "downloads_last_month": 141, - "total_downloads": 1218, - "version": "0.4.0", - "release_date": "2025-07-15T20:39:30" + "downloads_last_week": 154, + "downloads_last_month": 284, + "total_downloads": 1305, + "version": "0.4.1", + "release_date": "2025-11-27T21:14:51" }, "vbll": { "repo_id": "VectorInstitute/vbll", "name": "vbll", "package_name": "vbll", "type": "applied-research", - "timestamp": "2025-11-27T13:59:42.858247+00:00", + "timestamp": "2025-12-03T19:23:10.152058+00:00", "downloads_last_day": 3, - "downloads_last_week": 138, - "downloads_last_month": 1468, - "total_downloads": 5203, + "downloads_last_week": 703, + "downloads_last_month": 1758, + "total_downloads": 5654, "version": "0.4.9", "release_date": "2025-05-14T17:35:57" } }, - "last_updated": "2025-11-27T13:59:44.040346+00:00" + "last_updated": "2025-12-03T19:23:14.974408+00:00" } diff --git a/catalog/public/data/pypi_metrics_history.json b/catalog/public/data/pypi_metrics_history.json index cdaa8fa..f015fcf 100644 --- a/catalog/public/data/pypi_metrics_history.json +++ b/catalog/public/data/pypi_metrics_history.json @@ -79,6 +79,19 @@ "total_downloads": 5179, "version": "0.2.12", "release_date": "2025-01-22T16:00:42" + }, + { + "repo_id": "VectorInstitute/cyclops", + "name": "cyclops", + "package_name": "pycyclops", + "type": "tool", + "timestamp": "2025-12-03T19:22:40.934525+00:00", + "downloads_last_day": 1, + "downloads_last_week": 192, + "downloads_last_month": 1633, + "total_downloads": 5162, + "version": "0.2.12", + "release_date": "2025-01-22T16:00:42" } ], "type": "tool" @@ -162,6 +175,19 @@ "total_downloads": 2034, "version": "0.0.27", "release_date": "2025-06-18T04:08:33" + }, + { + "repo_id": "VectorInstitute/fed-rag", + "name": "fed-rag", + "package_name": "fed-rag", + "type": "tool", + "timestamp": "2025-12-03T19:22:44.750204+00:00", + "downloads_last_day": null, + "downloads_last_week": 149, + "downloads_last_month": 175, + "total_downloads": 1825, + "version": "0.0.27", + "release_date": "2025-06-18T04:08:33" } ], "type": "tool" @@ -245,6 +271,19 @@ "total_downloads": 889, "version": "0.7.2", "release_date": "2025-11-04T23:24:41" + }, + { + "repo_id": "VectorInstitute/vector-inference", + "name": "vector-inference", + "package_name": "vec-inf", + "type": "tool", + "timestamp": "2025-12-03T19:22:51.513664+00:00", + "downloads_last_day": 9, + "downloads_last_week": 113, + "downloads_last_month": 270, + "total_downloads": 989, + "version": "0.7.3", + "release_date": "2025-11-27T19:01:50" } ], "type": "tool" @@ -328,6 +367,19 @@ "total_downloads": 802, "version": "1.0.11", "release_date": "2025-06-21T18:46:37" + }, + { + "repo_id": "VectorInstitute/fair-sense-ai", + "name": "fair-sense-ai", + "package_name": "fair-sense-ai", + "type": "tool", + "timestamp": "2025-12-03T19:22:59.941732+00:00", + "downloads_last_day": null, + "downloads_last_week": 8, + "downloads_last_month": 27, + "total_downloads": 777, + "version": "1.0.11", + "release_date": "2025-06-21T18:46:37" } ], "type": "tool" @@ -411,6 +463,19 @@ "total_downloads": 1218, "version": "0.4.0", "release_date": "2025-07-15T20:39:30" + }, + { + "repo_id": "VectorInstitute/FL4Health", + "name": "fl4health", + "package_name": "fl4health", + "type": "tool", + "timestamp": "2025-12-03T19:23:05.019919+00:00", + "downloads_last_day": 2, + "downloads_last_week": 154, + "downloads_last_month": 284, + "total_downloads": 1305, + "version": "0.4.1", + "release_date": "2025-11-27T21:14:51" } ], "type": "tool" @@ -471,6 +536,19 @@ "total_downloads": 419, "version": "1.0.0", "release_date": "2025-07-29T20:43:26" + }, + { + "repo_id": "vectorinstitute/retrieval-augmented-generation", + "name": "retrieval-augmented-generation", + "package_name": "aieng-rag-utils", + "type": "bootcamp", + "timestamp": "2025-12-03T19:22:55.591891+00:00", + "downloads_last_day": null, + "downloads_last_week": null, + "downloads_last_month": 21, + "total_downloads": 346, + "version": "1.0.0", + "release_date": "2025-07-29T20:43:26" } ] }, @@ -504,6 +582,19 @@ "total_downloads": 5203, "version": "0.4.9", "release_date": "2025-05-14T17:35:57" + }, + { + "repo_id": "VectorInstitute/vbll", + "name": "vbll", + "package_name": "vbll", + "type": "applied-research", + "timestamp": "2025-12-03T19:23:10.152058+00:00", + "downloads_last_day": 3, + "downloads_last_week": 703, + "downloads_last_month": 1758, + "total_downloads": 5654, + "version": "0.4.9", + "release_date": "2025-05-14T17:35:57" } ] }, @@ -524,9 +615,22 @@ "total_downloads": 222, "version": "1.1.2", "release_date": "2023-03-08T05:07:41" + }, + { + "repo_id": "VectorInstitute/HV-Ai-C", + "name": "hv-ai-c", + "package_name": "hnp", + "type": "tool", + "timestamp": "2025-12-03T19:22:48.386917+00:00", + "downloads_last_day": 12, + "downloads_last_week": 37, + "downloads_last_month": 84, + "total_downloads": 237, + "version": "1.1.2", + "release_date": "2023-03-08T05:07:41" } ] } }, - "last_updated": "2025-11-27T13:59:42.858247+00:00" + "last_updated": "2025-12-03T19:23:10.152058+00:00" } diff --git a/scripts/collect_pypi_metrics.py b/scripts/collect_pypi_metrics.py index 9d4338b..bf15ee4 100644 --- a/scripts/collect_pypi_metrics.py +++ b/scripts/collect_pypi_metrics.py @@ -107,7 +107,7 @@ def calculate_recent_downloads( Downloads for last day, last week, last month (without mirrors). """ - from datetime import datetime + from datetime import datetime, timedelta if not overall_data or "data" not in overall_data: return None, None, None @@ -121,12 +121,15 @@ def calculate_recent_downloads( return None, None, None today = datetime.now().date() + yesterday = today - timedelta(days=1) # Calculate downloads for different time periods + # For "last day", look at yesterday (most recent complete day) + # This avoids issues with incomplete data for the current day last_1_day = sum( d["downloads"] for d in without_mirrors - if (today - datetime.strptime(d["date"], "%Y-%m-%d").date()).days <= 1 + if datetime.strptime(d["date"], "%Y-%m-%d").date() == yesterday ) last_7_days = sum( d["downloads"]