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vllm-omni/vllm_omni/engine/__init__.py
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2025-11-28 11:03:52 +08:00

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Python

"""
Engine components for vLLM-omni.
"""
from typing import Any, Optional
import msgspec
from vllm.v1.engine import EngineCoreRequest
class PromptEmbedsPayload(msgspec.Struct):
"""Serialized prompt embeddings payload for direct transfer.
data: raw bytes of the tensor in row-major order
shape: [seq_len, hidden_size]
dtype: torch dtype name (e.g., "float16", "float32")
"""
data: bytes
shape: list[int]
dtype: str
class AdditionalInformationEntry(msgspec.Struct):
"""One entry of additional_information.
Two supported forms are encoded:
- tensor: data/shape/dtype
- list: a Python list (msgspec-serializable)
Exactly one of (tensor_data, list_data) should be non-None.
"""
# Tensor form
tensor_data: Optional[bytes] = None
tensor_shape: Optional[list[int]] = None
tensor_dtype: Optional[str] = None
# List form
list_data: Optional[list[Any]] = None
class AdditionalInformationPayload(msgspec.Struct):
"""Serialized dictionary payload for additional_information.
Keys are strings; values are encoded as AdditionalInformationEntry.
"""
entries: dict[str, AdditionalInformationEntry]
class OmniEngineCoreRequest(EngineCoreRequest):
"""Engine core request for omni models with embeddings support.
Extends the base EngineCoreRequest with support for prompt embeddings
and additional information payloads, enabling direct transfer of
pre-computed embeddings between pipeline stages.
Attributes:
prompt_embeds: Optional serialized prompt embeddings payload for
direct transfer between stages
additional_information: Optional serialized additional information
dictionary containing tensors or lists to pass along with the request
"""
# Optional prompt embeddings (direct-transfer version)
prompt_embeds: Optional[PromptEmbedsPayload] = None
# Optional additional information dictionary (serialized)
additional_information: Optional[AdditionalInformationPayload] = None