From jeremylongshore-claude-code-plugins-plus-skills
Configures FastAPI endpoints for ML model serving, inference, MLOps pipelines, monitoring, and production optimization. Generates production-ready code and best practices for ML deployment APIs.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin langchain-py-packThis skill is limited to using the following tools:
This skill provides automated assistance for fastapi ml endpoint tasks within the ML Deployment domain.
Generates Flask APIs for ML model serving and deployment, including MLOps pipelines, inference, monitoring, and production configurations with step-by-step guidance.
Deploys trained ML models to production via REST APIs, Docker containers, Kubernetes clusters, with data validation, error handling, and performance monitoring.
Builds production ML systems with PyTorch 2.x, TensorFlow, and modern frameworks for model serving, feature engineering, A/B testing, monitoring, and infrastructure.
Share bugs, ideas, or general feedback.
This skill provides automated assistance for fastapi ml endpoint tasks within the ML Deployment domain.
This skill activates automatically when you:
Example: Basic Usage Request: "Help me with fastapi ml endpoint" Result: Provides step-by-step guidance and generates appropriate configurations
| Error | Cause | Solution |
|---|---|---|
| Configuration invalid | Missing required fields | Check documentation for required parameters |
| Tool not found | Dependency not installed | Install required tools per prerequisites |
| Permission denied | Insufficient access | Verify credentials and permissions |
Part of the ML Deployment skill category. Tags: mlops, serving, inference, monitoring, production