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haipipe-end

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End-to-end ML endpoint deployment workflow

Software Engineering#workflow#deployment#endpoint#builder#inference#mlflow#haipipe-end
Authorjluo41
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Unified workflow to package a trained ModelInstance_Set into a production-ready Endpoint_Set, enabling seamless testing, design of five endpoint-inference function types (MetaFn, TrigFn, PostFn, Src2InputFn, Input2SrcFn), and deployment to Databricks or local environments.

Core Features & Use Cases

  • End-to-end lifecycle: packaging, testing, Fn design, and deployment across Databricks or local platforms.
  • Fn-type orchestration: supports all five Fn types with a guided builder workflow and YAML config.
  • Deployment orchestration: handles packaging, warmup, inference, and deployment steps in a repeatable process.

Quick Start

Run the haipipe-end workflow to package a trained endpoint, validate it with tests, and deploy to your chosen platform.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: haipipe-end
Download link: https://github.com/jluo41/Tools/archive/main.zip#haipipe-end

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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