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CLAUDE.md

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+# EmbodiChain — Developer Reference
+
+EmbodiChain is an **end-to-end, GPU-accelerated, modular platform** for building generalized Embodied Intelligence, developed by DexForce Technology Co., Ltd. It provides a simulation lab, gym environments, RL training infrastructure, and agentic frameworks for robot learning research.
+
+- **License**: Apache 2.0
+- **Repository**: https://github.com/DexForce/EmbodiChain
+
+---
+
+## Project Structure
+
+```
+EmbodiChain/
+├── embodichain/                  # Main Python package
+│   ├── agents/                   # AI agents
+│   │   ├── hierarchy/            # LLM-based hierarchical agents (task, code, validation)
+│   │   ├── mllm/                 # Multimodal LLM prompt scaffolding
+│   │   └── rl/                   # RL agents: PPO algo, rollout buffer, actor-critic models
+│   ├── data/                     # Assets, datasets, constants, enums
+│   ├── lab/                      # Simulation lab
+│   │   ├── gym/                  # OpenAI Gym-compatible environments
+│   │   │   ├── envs/             # BaseEnv, EmbodiedEnv, RLEnv
+│   │   │   │   ├── managers/     # Observation, event, reward, record, dataset managers
+│   │   │   │   │   └── randomization/  # Physics, geometry, spatial, visual randomizers
+│   │   │   │   ├── tasks/        # Task implementations (tableware, RL, special)
+│   │   │   │   ├── action_bank/  # Configurable action primitives
+│   │   │   │   └── wrapper/      # Env wrappers (e.g. no_fail)
+│   │   │   └── utils/            # Gym registration, misc helpers
+│   │   ├── sim/                  # Simulation core
+│   │   │   ├── objects/          # Robot, RigidObject, Articulation, Light, Gizmo, SoftObject
+│   │   │   ├── sensors/          # Camera, StereoCamera, BaseSensor
+│   │   │   ├── robots/           # Robot-specific configs and params (dexforce_w1, cobotmagic)
+│   │   │   ├── planners/         # Motion planners (TOPPRA, motion generator)
+│   │   │   └── solvers/          # IK solvers (SRS, OPW, pink, pinocchio, pytorch)
+│   │   ├── devices/              # Real-device controllers
+│   │   └── scripts/              # Entry-point scripts (run_env, run_agent)
+│   ├── toolkits/                 # Standalone tools
+│   │   ├── graspkit/pg_grasp/    # Parallel-gripper grasp sampling
+│   │   └── urdf_assembly/        # URDF builder utilities
+│   └── utils/                    # Shared utilities
+│       ├── configclass.py        # @configclass decorator
+│       ├── logger.py             # Project logger
+│       ├── math/                 # Tensor math helpers
+│       └── warp/kinematics/      # GPU kinematics via Warp
+├── configs/                      # Agent configs and task prompts (text/YAML)
+├── docs/                         # Sphinx documentation source + build
+│   └── source/                   # .md doc pages (overview, quick_start, features, resources)
+├── tests/                        # Test suite
+├── .github/                      # CI workflows and issue/PR templates
+├── setup.py                      # Package setup
+└── VERSION                       # Package version file
+```
+
+---
+
+## Code Style
+
+### Formatting
+
+- **Formatter**: `black==24.3.0` — run before every commit.
+  ```bash
+  black .
+  ```
+
+### File Headers
+
+Every source file begins with the Apache 2.0 copyright header:
+
+```python
+# ----------------------------------------------------------------------------
+# Copyright (c) 2021-2026 DexForce Technology Co., Ltd.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# ...
+# ----------------------------------------------------------------------------
+```
+
+### Type Annotations
+
+- Use full type hints on all public APIs.
+- Use `from __future__ import annotations` at the top of every file.
+- Use `TYPE_CHECKING` guards for circular-import-safe imports.
+- Prefer `Union[A, B]` or `A | B` (Python 3.10+ union syntax is acceptable).
+
+### Configuration Pattern (`@configclass`)
+
+All configuration objects use the `@configclass` decorator (similar to Isaac Lab's pattern):
+
+```python
+from embodichain.utils import configclass
+from dataclasses import MISSING
+
+@configclass
+class MyManagerCfg:
+    param_a: float = 1.0
+    param_b: str = MISSING  # required — must be set by caller
+```
+
+### Functor / Manager Pattern
+
+Managers (observation, event, reward, randomization) use a `Functor`/`FunctorCfg` pattern:
+
+- **Function-style**: a plain function with signature `(env, env_ids, ...) -> None`.
+- **Class-style**: a class inheriting `Functor`, with `__init__(cfg, env)` and `__call__(env, env_ids, ...)`.
+- Registered in a manager config via `FunctorCfg(func=..., params={...})`.
+
+```python
+from embodichain.lab.gym.envs.managers import Functor, FunctorCfg
+
+class my_randomizer(Functor):
+    def __init__(self, cfg: FunctorCfg, env):
+        super().__init__(cfg, env)
+
+    def __call__(self, env, env_ids, my_param: float = 0.5):
+        ...
+```
+
+### Docstrings
+
+Use Google-style docstrings with Sphinx directives:
+
+```python
+def my_function(env, env_ids, scale: float = 1.0) -> None:
+    """Short one-line summary.
+
+    Longer description if needed.
+
+    .. attention::
+        Note a non-obvious behavior here.
+
+    .. tip::
+        Helpful usage hint.
+
+    Args:
+        env: The environment instance.
+        env_ids: Target environment IDs.
+        scale: Scaling factor applied to the result.
+
+    Returns:
+        Description if not None.
+
+    Raises:
+        ValueError: If the entity type is unsupported.
+    """
+```
+
+### Module Exports
+
+Define `__all__` in every public module to declare the exported API:
+
+```python
+__all__ = ["MyClass", "my_function"]
+```
+
+### Documentation
+
+- Docs are built with **Sphinx** using **Markdown** source files (`docs/source/`).
+- Build locally:
+  ```bash
+  pip install -r docs/requirements.txt
+  cd docs && make html
+  # Preview at docs/build/html/index.html
+  ```
+- If you encounter locale errors: `export LC_ALL=C.UTF-8; export LANG=C.UTF-8`
+
+---
+
+## Contributing Guide
+
+### Bug Reports
+
+Use the **Bug Report** issue template (`.github/ISSUE_TEMPLATE/bug.md`). Title format: `[Bug Report] Short description`.
+
+Include:
+- Clear description of the bug
+- Minimal reproduction steps and stack trace
+- System info: commit hash, OS, GPU model, CUDA version, GPU driver version
+- Confirm you checked for duplicate issues
+
+### Feature Requests / Proposals
+
+Use the **Proposal** issue template (`.github/ISSUE_TEMPLATE/proposal.md`). Title format: `[Proposal] Short description`.
+
+Include:
+- Description of the feature and its core capabilities
+- Motivation and problem it solves
+- Any related existing issues
+
+### Pull Requests
+
+1. **Fork** the repository and create a focused branch.
+2. **Keep PRs small** — one logical change per PR.
+3. **Format** the code with `black==24.3.0` before submitting.
+4. **Update documentation** for any public API changes.
+5. **Add tests** that prove your fix or feature works.
+6. **Submit** using the PR template (`.github/PULL_REQUEST_TEMPLATE.md`):
+   - Summarize changes and link the related issue (`Fixes #123`).
+   - Specify the type of change (bug fix / enhancement / new feature / breaking change / docs).
+   - Attach before/after screenshots for visual changes.
+   - Complete the checklist:
+     - [ ] `black .` has been run
+     - [ ] Documentation updated
+     - [ ] Tests added
+     - [ ] Dependencies updated (if applicable)
+
+> It is recommended to open an issue and discuss the design before opening a large PR.
+
+### Adding a New Robot
+
+Refer to `embodichain/lab/sim/robots/` for existing examples (`dexforce_w1`, `cobotmagic`). Each robot needs: a config (`cfg.py`), parameters (`params.py`), types (`types.py`), and utilities (`utils.py`).
+
+### Adding a New Task Environment
+
+Refer to `embodichain/lab/gym/envs/tasks/` for existing examples. Tasks subclass `EmbodiedEnv` or `BaseAgentEnv` and implement `_setup_scene`, `_reset_idx`, and evaluation logic.
+
+---
+
+## Unit Tests
+
+### Structure
+
+Tests live in `tests/` and mirror the source tree:
+
+```text
+tests/
+├── toolkits/
+│   └── test_pg_grasp.py
+├── gym/
+│   └── action_bank/
+│       └── test_configurable_action.py
+└── sim/
+    ├── objects/
+    │   ├── test_light.py
+    │   └── test_rigid_object_group.py
+    ├── sensors/
+    │   ├── test_camera.py
+    │   └── test_stereo.py
+    └── planners/
+        └── test_motion_generator.py
+```
+
+Place new test files at `tests/<subpackage>/test_<module>.py`, matching the layout of `embodichain/`.
+
+### Two accepted styles
+
+**pytest style** — for pure-Python logic with no test ordering dependency:
+
+```python
+# ----------------------------------------------------------------------------
+# Copyright (c) 2021-2026 DexForce Technology Co., Ltd.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# ...
+# ----------------------------------------------------------------------------
+
+from embodichain.my_module import my_function
+
+
+def test_expected_output():
+    result = my_function(input_value)
+    assert result == expected_value
+
+
+def test_edge_case():
+    result = my_function(edge_input)
+    assert result is not None
+```
+
+**`unittest.TestCase` style** — when tests must run in a specific order or share `setUp`/`tearDown` state:
+
+```python
+# ----------------------------------------------------------------------------
+# Copyright (c) 2021-2026 DexForce Technology Co., Ltd.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# ...
+# ----------------------------------------------------------------------------
+
+import unittest
+from embodichain.my_module import MyClass
+
+
+class TestMyClass(unittest.TestCase):
+    def setUp(self):
+        self.obj = MyClass(param=1.0)
+
+    def tearDown(self):
+        pass
+
+    def test_basic_behavior(self):
+        result = self.obj.run()
+        self.assertEqual(result, expected)
+
+    def test_raises_on_bad_input(self):
+        self.assertRaises(ValueError, self.obj.run, bad_input)
+
+
+if __name__ == "__main__":
+    unittest.main()
+```
+
+### Conventions
+
+- **File header**: include the standard Apache 2.0 copyright block (same as all source files).
+- **Naming**: test files are `test_<module>.py`; test functions/methods are `test_<scenario>`.
+- **Simulation-dependent tests**: tests that require a running `SimulationManager` (GPU, sensors, robots) must initialize and teardown the sim inside `setUp`/`tearDown` or a pytest fixture. Keep them isolated from pure-logic tests.
+- **No magic numbers**: define expected values as named constants or comments explaining their origin.
+- **`if __name__ == "__main__"`**: include this block for tests that support optional visual/interactive output (pass `is_visual=True` manually when debugging).
+
+### Running tests
+
+```bash
+# Run all tests
+pytest tests/
+
+# Run a specific file
+pytest tests/toolkits/test_pg_grasp.py
+
+# Run a specific test function
+pytest tests/toolkits/test_pg_grasp.py::test_antipodal_score_selector
+
+# Run with verbose output
+pytest -v tests/
+```

CONTRIBUTING.md

@@ -36,6 +36,67 @@ We welcome pull requests for bug fixes, new features, and documentation improvem
     *   Include a summary of the changes and link to any relevant issues (e.g., `Fixes #123`).
     *   Ensure all checks pass.
 
+## Using Claude Code for Contributions
+
+[Claude Code](https://docs.anthropic.com/en/docs/claude-code/overview) is an AI-powered CLI that can assist you throughout the contribution workflow — from understanding the codebase to writing, reviewing, and debugging code.
+
+### Setup
+
+Install Claude Code and authenticate:
+
+```bash
+npm install -g @anthropic-ai/claude-code
+claude
+```
+
+A `CLAUDE.md` file is present at the root of this repository. Claude Code reads it automatically at startup to load project conventions, structure, and style rules, so it is context-aware from the first prompt.
+
+### Suggested workflows
+
+**Explore the codebase before making changes**
+
+```
+> Explain how the Functor/Manager pattern works in embodichain/lab/gym/envs/managers/
+> What is the difference between EmbodiedEnv and RLEnv?
+> Show me an example of how a randomization functor is registered in a task config.
+```
+
+**Implement a new feature**
+
+```
+> I want to add a new observation functor that returns the end-effector velocity.
+  Which existing functor should I model it after?
+> Generate the functor following the project style, with a proper docstring and type hints.
+```
+
+**Validate style and formatting before submitting**
+
+```
+> Review my changes in embodichain/lab/gym/envs/managers/randomization/visual.py
+  for style issues, missing type hints, and docstring completeness.
+```
+
+**Write or update tests**
+
+```
+> Write a pytest test for the randomize_emission_light function in
+  embodichain/lab/gym/envs/managers/randomization/visual.py.
+```
+
+**Understand a bug**
+
+```
+> I'm getting a KeyError in observation_manager.py at line 42 when env_ids is None.
+  What could cause this and how should it be fixed?
+```
+
+### Tips
+
+*   Always run `black .` after Claude Code generates or edits Python files — Claude Code can do this for you if you ask.
+*   Claude Code respects the `CLAUDE.md` conventions. If you notice it deviating (wrong docstring style, missing `__all__`, etc.), point it out and it will correct the output.
+*   For large features, break the work into small, focused tasks and handle them one at a time.
+*   Claude Code can help draft your PR description and populate the PR checklist once your changes are ready.
+
 ## Contribute specific robots
 
 TODO: Add instructions for contributing new robot models and its configurations.