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Data Pipeline Agent

Workflow agent for multi-step data processing. Extract, transform, validate, and load — with checkpoints at each step.

agentworkflowpipelineetl
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A workflow agent for multi-step data processing. It implements an ETL pattern — extract, transform, validate, and load — with checkpoints so you can resume from any step.

What's included

  • ETL workflow — extract, transform, validate, and load steps
  • Checkpoint pattern — state saved at each step for resumability
  • Workflow agent — orchestrates the pipeline with error handling
  • Step isolation — each stage can be retried or resumed independently

When to use this

Pick the Data Pipeline Agent example when you want to:

  • Build data processing workflows with clear stages
  • Implement checkpointing for fault-tolerant pipelines
  • See how workflow agents handle multi-step ETL

Project structure

├── agents/
│   └── pipeline.py             # ETL workflow agent with checkpoints
├── main.py                     # Entry point — serve(agents)
├── pyproject.toml
└── reminix.config.toml

Quick start

Deploy the project and run the pipeline workflow. It will execute extract, transform, validate, and load steps, checkpointing state at each stage.