update docs

[gushiqiao]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @gushiqiao, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request aims to improve the deployment experience and resource management for the application. It simplifies how models are configured by consolidating multiple parameters into a single path and updates the associated documentation to guide users through the streamlined setup. Additionally, it enhances the Gradio demo's flexibility by adding specific CPU offloading controls for key model components.

Highlights

• Enhanced CPU Offloading: Introduced more granular CPU offloading options for T5, VAE, and CLIP components within the auto_configure function of the Gradio demo, allowing for potentially better resource management.
• Simplified Model Configuration: Streamlined the model configuration process in lightx2v_config.txt by replacing multiple model-related parameters (model_size, model_cls, i2v_model_path, t2v_model_path) with a single, unified model_path.
• Updated Documentation: Revised the Windows deployment guides (both English and Chinese versions) to reflect the simplified model configuration, update download links, and remove outdated or redundant instructions regarding model download options and initial setup.

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[gemini-code-assist]

Code Review

This pull request updates documentation and adds more CPU offloading options to the Gradio demos. My review focuses on improving code quality. I've identified a hardcoded debug setting that should be removed or made configurable to avoid performance issues. I've also pointed out significant code duplication in the new configurations and suggested a refactoring approach to improve maintainability. The documentation changes appear to simplify the setup process and look good.

[gemini-code-assist]

Hardcoding the profiling debug level is not recommended, especially with a high value like '2'. This can lead to performance degradation and verbose logging in production environments. This setting should be configurable, for example, through a command-line argument or an environment variable set outside the code, and should be disabled by default.

[gemini-code-assist]

Hardcoding the profiling debug level is not recommended, especially with a high value like '2'. This can lead to performance degradation and verbose logging in production environments. This setting should be configurable, for example, through a command-line argument or an environment variable set outside the code, and should be disabled by default.

[gemini-code-assist]

These three lines for CPU offloading are repeated in multiple configuration dictionaries within this function (e.g., lines 808-810, 821-823, 842-844, 852-854, and 863-865). To improve maintainability and reduce code duplication, consider defining a common dictionary for these offload settings and merging it into each configuration where needed. For example:

offload_components = {
    "t5_cpu_offload_val": True,
    "vae_cpu_offload_val": True,
    "clip_cpu_offload_val": True,
}

# Then in your rules:
{
    "cpu_offload_val": True,
    "use_tiling_vae_val": True,
    **offload_components,
}

[gemini-code-assist]

These three lines for CPU offloading are repeated in multiple configuration dictionaries within this function (e.g., lines 808-810, 821-823, 842-844, 852-854, and 863-865). To improve maintainability and reduce code duplication, consider defining a common dictionary for these offload settings and merging it into each configuration where needed. For example:

offload_components = {
    "t5_cpu_offload_val": True,
    "vae_cpu_offload_val": True,
    "clip_cpu_offload_val": True,
}

# Then in your rules:
{
    "cpu_offload_val": True,
    "use_tiling_vae_val": True,
    **offload_components,
}