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LongLive & StreamEdit

This folder contains the StreamEdit implementation built on LongLive v1.0 codebase.

Most files are inherited from the upstream LongLive repository. The implementation of StreamEdit is mainly located in:

  • inference_edit_streamedit.py: command-line entry point for StreamEdit video editing.
  • inference_edit_streamedit.sh: example editing commands.
  • pipeline/edit_causal_inference.py: dual-branch editing pipeline adapted to the LongLive streaming generator.
  • pipeline/__init__.py: exposes EditCausalInferencePipeline.
  • wan/modules/model.py and wan/modules/causal_model.py: attention-level support for grounding, boosting, query/key blending, source KV injection, and mask-aware cache usage.

The original LongLive training, inference, and interactive inference files are kept for code compatibility and attribution. For full upstream documentation, please refer to the original LongLive repository.

Quick Run

Install dependencies from the top-level requirements.txt, then prepare checkpoints:

huggingface-cli download Wan-AI/Wan2.1-T2V-1.3B --local-dir wan_models/Wan2.1-T2V-1.3B
huggingface-cli download Efficient-Large-Model/LongLive --local-dir longlive_models

Run the provided editing examples:

bash inference_edit_streamedit.sh

For first-frame visual prompting, the example script uses --triple_first_frame by default to better align with LongLive's sink token design.

Acknowledgements

This folder is based on LongLive, which is licensed under Apache-2.0. Please keep the upstream license and cite LongLive when using this implementation.