chore: release v0.0.1

docs/source/en/user_guide/getting_started/hello_motrixlab.md

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+# Quick Start: Hello MotrixLab
+
+This tutorial demonstrates the MotrixLab workflow through a simple example - loading and training a cartpole environment:
+
+## Environment Preview
+
+We provide a simple script to visualize an environment without executing any training. This helps you verify that system dependencies are correctly configured:
+
+```bash
+uv run scripts/view.py --env cartpole
+```
+
+This will open a visualization window showing the cartpole physics simulation environment with random actions for demonstration.
+
+## Train Model
+
+Start training the cartpole balancing task:
+
+```bash
+uv run scripts/train.py --env cartpole
+```
+
+The training process will automatically:
+
+1. Automatically select training backend (JAX or PyTorch) based on hardware environment
+2. Create training environments
+3. Start PPO algorithm training
+
+Training results will be saved in the `runs/cartpole/` directory, including:
+
+-   Training checkpoints
+-   TensorBoard log files
+
+## Visualize Training Process
+
+If you want to observe the model's learning process during training, you can enable visualization rendering:
+
+```bash
+uv run scripts/train.py --env cartpole --render
+```
+
+### 🎮 Interactive Rendering Control
+
+> **Important Note**: Visualization significantly reduces training speed and is recommended mainly for debugging and demonstration purposes.
+
+During visualized training, you can use the **spacebar** to dynamically control rendering:
+
+-   **Enable Rendering**: Press spacebar to enable visualization and observe robot behavior
+-   **Disable Rendering**: Press spacebar again to disable rendering and improve training speed
+-   **Switch Anytime**: No need to restart the program; you can switch at any time during training
+
+This interactive control allows you to observe training effects when needed and enjoy fast training when not needed. This feature also works during inference.
+
+## View Training Results
+
+Use TensorBoard to view training progress:
+
+```bash
+uv run tensorboard --logdir runs/cartpole
+```
+
+## Test Trained Model
+
+After training is complete, test the trained policy:
+
+```bash
+# Automatically find best policy for testing (recommended)
+uv run scripts/play.py --env cartpole
+
+# Manually specify policy file for testing (if you need a specific version)
+uv run scripts/play.py --env cartpole --policy runs/cartpole/YOUR_RESULT_NUMBER/best_agent.pickle
+```
+
+> **Tip**: The system will automatically find the latest and best policy files in the `runs/cartpole/` directory. Usually, using the auto-discovery feature is sufficient.
+
+## That Completes Our Example
+
+Next, you can try modifying parameters to observe physical effects under different settings, or try other environments.
+
+## Next Steps
+
+-   Learn about the [Basic Framework](../tutorial/basic_frame.md)
+-   Study [Physics Environment Configuration](../tutorial/physics_environment.md)
+-   View more [Training Examples](../demo/cartpole.md)

docs/source/en/user_guide/getting_started/installation.md

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+# Installation Environment
+
+## Installation Requirements
+
+-   **Python Version**: {bdg-danger-line}`3.10.*`
+
+    | Python Version | Support Status |
+    | :------------: | :------------: |
+    |     ≤ 3.9      |       ❌       |
+    |      3.10      |       ✅       |
+    |     ≥ 3.11     |       ❌       |
+
+-   **Package Manager**: {bdg-danger-line}`UV`
+
+-   **System and Architecture**:
+
+    -   {bdg-danger-line}`Windows(x86_64)`
+    -   {bdg-danger-line}`Linux(x86_64)`
+
+    ```{note}
+    Features supported on each platform:
+
+    | Operating System | CPU Simulation | Interactive Viewer | GPU Simulation |
+    | :--------------: | :------------: | :----------------: | :------------: |
+    |      Linux       |       ✅       |         ✅          |    🛠️ In Development    |
+    |     Windows      |       ✅       |         ✅          |    🛠️ In Development    |
+    ```
+
+## Installation Method
+
+### Clone Project
+
+```bash
+git clone https://github.com/Motphys/MotrixLab.git
+cd MotrixLab
+```
+
+### Install Dependencies
+
+Use UV to install project dependencies:
+
+```bash
+# Install all dependencies
+uv sync --all-packages --all-extras
+```
+
+If you only need to install one training backend, you can choose to install a specific backend type:
+
+```bash
+# Install SKRL JAX (support Linux only)
+uv sync --all-packages --extra skrl-jax
+
+# Install SKRL PyTorch
+uv sync --all-packages --extra skrl-torch
+```