High-performance streaming video diffusion framework with pluggable model backends
Project description
flashdreams
A high-performance streaming inference framework for video diffusion models with a plugin architecture for model backends.
Features
- Streaming Inference -- Autoregressive chunk-wise video generation with per-rollout cache state for bounded VRAM and arbitrarily long rollouts
- Plugin Architecture -- Entry-point-based model discovery; third-party packages register runner configs that appear automatically in the CLI
- Multi-GPU -- Context parallelism via torchrun with automatic sharding across ranks
- Performance -- torch.compile support with CUDA graph capture and replay
- Serving -- WebRTC and gRPC integrations for real-time interactive applications
Supported Models
Wan 2.1/2.2, Cosmos Predict2, and more via first-party integration packages.
Installation
pip install flashdreams
Documentation
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