feat(gym): add declarative expert program runtime

[yuecideng]

Description

Stack

• Layer: 6/14
• Base: feat/semantic-skill-runtime
• Depends on: feat(sim): add semantic runtime effects and parallelism #496
• Followed by: feat(agents): add strict expert program frontend #498
  Add the strict, versioned Expert Program configuration, decoder, loader, preflight compiler, lazy segment runtime, Gym demo bridge, simulation factory, settling policies, validators, and completion metadata.

The environment retains its normal env.step() cadence and dataset lifecycle. Expert Programs compile into the existing semantic/atomic runtime instead of creating a third workflow engine.

Refs #471
Refs #474

Type of change

• New feature (non-breaking change which adds functionality)

Screenshots

Not applicable.

Validation

• Focused coverage: tests/gym/envs/expert_program, demo, settling, registration, and run-env integration tests
• Final affected-suite regression on the stack tip: 1215 passed, 2 skipped, 8 deselected
• Changed Python files pass Black 26.3.1; the Sphinx build and rollout-report drift check pass at the stack tip

Checklist

• Changed Python files pass Black 26.3.1.
• Corresponding public/design documentation is included in this stack.
• Tests cover the affected behavior.
• No dependency update is required.

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[greptile-apps]

Greptile Summary

The PR adds a strict, versioned Expert Program frontend that compiles declarative programs into the existing semantic-skill runtime while preserving normal Gym stepping and dataset lifecycle.

• Adds schema decoding, loading, validation, and preflight compilation.
• Adds lazy sequential and parallel segment execution, simulation adapters, settling policies, validators, and completion metadata.
• Integrates Expert Programs with Gym configuration, demonstrations, environment launching, and public documentation.

Confidence Score: 5/5

The PR appears safe to merge because no blocking failure remains in the eligible follow-up review scope.

No blocking failure remains.

Important Files Changed

Filename	Overview
embodichain/lab/gym/envs/expert_program/decoder.py	Implements bounded, path-aware decoding with strict discriminator, field, numeric, and executable-value validation.
embodichain/lab/gym/envs/expert_program/compiler.py	Performs static preflight and lowers declarative sequential or parallel program structure into semantic runtime inputs.
embodichain/lab/gym/envs/expert_program/bridge.py	Adapts lazy Expert Program execution to demo segments, Gym actions, post-policies, validators, and completion metadata.
embodichain/lab/gym/envs/expert_program/simulation_environment.py	Connects simulation-backed scene, runtime, policy, and validation services to the Expert Program environment contract.
embodichain/lab/gym/envs/demo.py	Extends demonstration execution with richer segment lifecycle, runtime failure traces, and completion metadata.
embodichain/lab/sim/skills/runtime.py	Refines the canonical semantic runtime and row-local lifecycle used by Expert Program execution.
embodichain/lab/scripts/run_env.py	Adds launcher support for loading and applying an explicit Expert Program configuration.
embodichain/lab/gym/envs/settling.py	Adds reusable batched settling monitors and policies for segment post-processing.

Flowchart

%%{init: {'theme': 'neutral'}}%%
flowchart TD
A[JSON or YAML Expert Program] --> B[Strict decoder and loader]
B --> C[ExpertProgramCfg]
C --> D[Preflight compiler]
D --> E[Lazy program segments]
E --> F[Semantic SkillRuntime]
F --> G[Atomic action runtime]
G --> H[AtomicDemoBridge]
H --> I[Normal env.step cadence]
I --> J[Settling and validators]
J --> K[Completion and dataset metadata]

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[greptile-apps]

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