WorldForge¶
A harness framework for building world-model-based workflows for physical AI systems.
WorldForge is the application builder's counterpart to model-training stacks like Stable World Model: it helps roboticists and physical-AI builders compose, evaluate, and benchmark workflows built on top of world models — so they can pick the best provider and configuration for a task — rather than train the models. The whole framework is organized around one backbone loop: planning and scoring action candidates with an action-conditioned predictive world model, in latent space.
Get started Read the introduction
Where to go next¶
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Quick Start
Install WorldForge, create a world, and run the mock provider end to end.
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CLI Reference
Look up an exact CLI command or optional-runtime smoke.
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Architecture
See module responsibilities and the planning pipelines.
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Provider Authoring
Add or promote a provider adapter against the capability contracts.
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Documentation Map
Follow the complete reader path across every section.
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Evidence And Evaluation
Understand how claims map to deterministic, reproducible evidence.