| Name | Version | Summary | date |
| cursus |
1.2.1 |
Automatic SageMaker Pipeline Generation from DAG Specifications |
2025-09-03 20:36:18 |
| graphreduce |
1.8.8 |
Leveraging graph data structures for complex feature engineering pipelines. |
2025-09-03 14:39:30 |
| outerbounds |
0.9.4 |
More Data Science, Less Administration |
2025-09-03 10:46:40 |
| h2o-mlops |
1.4.2 |
Python client for H2O MLOps. |
2025-09-03 08:36:29 |
| databricks-ml-bundle |
0.1.2 |
CLI tool to generate Databricks ML platform project structure with governance and best practices |
2025-09-03 06:10:53 |
| truss |
0.10.11 |
A seamless bridge from model development to model delivery |
2025-09-03 03:11:22 |
| wandb-generic |
1.1.0 |
A truly generic Python package for Weights & Biases integration with any ML/DL library or long-running function. |
2025-09-03 00:16:39 |
| apolo-all |
25.9.0 |
Combo package for installing all Apolo command line tools by 'pipx install apolo-all' command |
2025-09-01 16:45:02 |
| tora |
0.0.11 |
Python SDK for Tora ML experiment tracking platform |
2025-09-01 08:31:32 |
| zenml-nightly |
0.84.3.dev20250831 |
ZenML: Write production-ready ML code. |
2025-08-31 00:58:12 |
| extralit-server |
0.6.1 |
Open-source tool for accurate & fast scientific literature data extraction with LLM and human-in-the-loop. |
2025-08-29 07:41:53 |
| skewsentry |
0.1.1 |
Catch training ↔ serving feature skew before you ship to production |
2025-08-28 22:38:27 |
| pixeltable |
0.4.10 |
AI Data Infrastructure: Declarative, Multimodal, and Incremental |
2025-08-28 18:18:51 |
| bentoml |
1.4.22 |
BentoML: The easiest way to serve AI apps and models |
2025-08-27 01:21:19 |
| busysloths-mlox |
0.1.0.post89 |
Accelerate your ML journey—deploy production-ready MLOps in minutes, not months. |
2025-08-26 12:02:48 |
| superduper-chromadb |
0.10.0 |
SuperDuper Lance is a Python library that provides a high-level API for working with Lance vector search database. |
2025-08-26 10:30:57 |
| superduper-vllm |
0.10.0 |
Superduper allows users to work with self-hosted LLM models via [vLLM](https://github.com/vllm-project/vllm). |
2025-08-26 08:30:22 |
| superduper-transformers |
0.10.0 |
Transformers is a popular AI framework, and we have incorporated native support for Transformers to provide essential Large Language Model (LLM) capabilities. |
2025-08-26 08:30:18 |
| superduper-llamacpp |
0.10.0 |
Superduper allows users to work with self-hosted LLM models via [Llama.cpp](https://github.com/ggerganov/llama.cpp). |
2025-08-26 08:30:07 |
| superduper-sentence-transformers |
0.10.0 |
superduper allows users to work with self-hosted embedding models via [Sentence-Transformers](https://sbert.net). |
2025-08-26 08:30:05 |