Simplify AI workflows with flyte
Coordinate data, models, and compute with flyte, a tool for founders building AI workflows, backed by 7.1k+ GitHub stars
7,138 stars845 forksGoQuality 9/10Updated 7/14/2026100% free ยท open source Flyte helps founders coordinate data, models, and compute to build resilient AI workflows
docker run -p 30080:30080 -v $(pwd):/flyte -w /flyte flyteorg/flyte:latest deck
- โขWhen building AI-powered products that require dynamic workflow orchestration
- โขWhen needing to integrate multiple data sources and machine learning models
- โขWhen requiring a scalable and fault-tolerant workflow management system
- 1Create a new Flyte workflow by defining a Python function with the @task decorator
- 2Use the flytekit SDK to define and manage workflows, such as creating a new workflow with flytekit.Workflow
- 3Run the workflow locally with the command docker run -p 30080:30080 -v $(pwd):/flyte -w /flyte flyteorg/flyte:latest deck
- 4Use the Flyte Deck UI to visualize and manage workflows, accessible at http://localhost:30080
- 5Define workflow dependencies and inputs using the @input and @output decorators
Ready-to-paste prompt python -c 'from flytekit import task, workflow; @task def my_task(x: int) -> int: return x + 1; @workflow def my_workflow(x: int) -> int: return my_task(x=x)'
Heads up: Ensure you have Docker installed and configured on your system, as Flyte relies on Docker for workflow execution
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