Workflows
Algorithms
Algorithm developer guide
Workflows and algorithms
Every upload runs through a workflow you can see and change. Use the built-in algorithms, or write your own in Python.
What a workflow is, how it processes every upload, and how to choose the one your project uses.
Duplicate an official workflow, drop in an algorithm, publish it and test it on a real recording, without writing YAML.
Follow a run step by step, read its logs and outputs, and retry or rerun when something goes wrong.
The algorithms your workflow steps run: the built-in ones, grouped by what they do, and the ones your team writes.
Write an algorithm in Python in the browser, try it on a real recording, save it as a version and use it in a workflow.
How custom algorithms fit together, then a complete one written, tried on real data and saved in about ten minutes.
Teach the platform to read your own recording format, so every later step sees the same canonical recording.
Package an algorithm in any language as a container image that follows the same rules as a Python one.
Wire your algorithms and the built-in ones into a workflow, and understand exactly how each step runs, skips or stops.
Everything an algorithm can declare: decorator arguments, features, parameters, semantic types, facts, resources, exit states and versions.
Every public class, method and decorator argument of the embodiflow Python SDK, generated from the SDK itself.
Write, test and save algorithms from your own terminal, and manage workflows as files.
Let an AI assistant write, test and save algorithms and edit workflows, with the same checks the console uses.
What each algorithm and workflow error code means and what to do about it, in the same words the console uses.