- Add complete directory structure for multimodal and non-autoregressive processing - Include AsyncLLM, OmniEngine, and DiffusionEngine modules - Add processors, schedulers, executors, and output processors - Add API interfaces for Higress, Gradio, and ComfyUI - Add configuration management and CLI interface - Add comprehensive test structure and documentation - Add pyproject.toml with dependencies and project configuration - Add examples and documentation structure
34 lines
961 B
Python
34 lines
961 B
Python
"""
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vLLM-omni: Multi-modality models inference and serving with non-autoregressive structures.
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This package extends vLLM beyond traditional text-based, autoregressive generation
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to support multi-modality models with non-autoregressive structures and non-textual outputs.
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Architecture:
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- 🟡 Modified: vLLM components modified for multimodal support
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- 🔴 Added: New components for multimodal and non-autoregressive processing
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"""
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__version__ = "0.1.0"
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__author__ = "vLLM-omni Team"
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__email__ = "hsliuustc@gmail.com"
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# Main entry points
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from .async_llm import AsyncLLM
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from .omni_engine import OmniEngine
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from .diffusion_engine import DiffusionEngine
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__all__ = [
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# Version info
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"__version__",
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"__author__",
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"__email__",
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# Main components
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"AsyncLLM",
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"OmniEngine",
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"DiffusionEngine",
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# All other components are available through their respective modules
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# processors.*, schedulers.*, executors.*, etc.
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] |