78 lines
2.1 KiB
Python
78 lines
2.1 KiB
Python
import enum
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from dataclasses import dataclass
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from typing import Any, Dict, List, Optional, Union
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import msgspec
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from vllm.lora.request import LoRARequest
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from vllm.multimodal import MultiModalDataDict, MultiModalPlaceholderDict
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from vllm.sampling_params import RequestOutputKind, SamplingParams
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@dataclass
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class DetokenizerRequest:
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request_id: str
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prompt: Optional[str]
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prompt_token_ids: List[int]
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skip_special_tokens: bool
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spaces_between_special_tokens: bool
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output_kind: RequestOutputKind
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stop: List[str]
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include_stop_str_in_output: bool
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@dataclass
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class EngineCoreRequest:
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# NOTE: prompt and prompt_token_ids should be DecoderOnlyInput,
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# but this object is currently not playing well with msgspec
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# due to circular imports and typing we have in data.py
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request_id: str
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#NOTE(Nick): I don't think we need to pass prompt here since it should
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# always be tokenized?
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prompt: Optional[str]
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prompt_token_ids: List[int]
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mm_data: Optional[MultiModalDataDict]
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mm_placeholders: Optional[MultiModalPlaceholderDict]
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mm_processor_kwargs: Optional[Dict[str, Any]]
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sampling_params: SamplingParams
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eos_token_id: Optional[int]
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arrival_time: float
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lora_request: Optional[LoRARequest]
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class EngineCoreOutput(msgspec.Struct,
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array_like=True,
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omit_defaults=True,
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gc=False):
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request_id: str
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new_token_ids: List[int]
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finished: bool
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finish_reason: Optional[str] = None
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stop_reason: Union[int, str, None] = None
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class EngineCoreOutputs(msgspec.Struct,
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array_like=True,
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omit_defaults=True,
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gc=False):
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#NOTE(Nick): We could consider ways to make this more compact,
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# e.g. columnwise layout and using an int enum for finish/stop reason
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# [num_reqs]
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outputs: List[EngineCoreOutput]
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class EngineCoreRequestType(enum.Enum):
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"""
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Request types defined as hex byte strings, so it can be sent over sockets
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without separate encoding step.
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"""
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ADD = b'\x00'
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ABORT = b'\x01'
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