raptor-ml/raptor
Transform your pythonic research to an artifact that engineers can deploy easily.
Raptor helps data scientists and ML engineers take their Python-based machine learning research, often developed in notebooks, and easily transform it into reliable, scalable applications. It takes your existing data science code and generates production-ready artifacts, handling all the complex backend engineering like deployment to Kubernetes, data processing, and model serving. This allows data scientists to focus purely on model development and research.
161 stars.
Use this if you are a data scientist or ML engineer who wants to quickly deploy your Python models and features into a production environment without needing to become a backend engineering expert.
Not ideal if you are looking for a comprehensive MLOps platform to manage the entire ML resource lifecycle, as Raptor focuses specifically on bridging the gap between research and production deployment.
Stars
161
Forks
14
Language
Go
License
Apache-2.0
Category
Last pushed
Jan 31, 2026
Commits (30d)
0
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