85a65e7f51
Signed-off-by: taohui <taohui3@gmail.com> Signed-off-by: Tao Hui <taohui3@gmail.com> Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com> Co-authored-by: Chauncey <chaunceyjiang@gmail.com>
59 lines
2.0 KiB
Python
59 lines
2.0 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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from collections.abc import Sequence
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from transformers import PreTrainedTokenizerBase
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from vllm.entrypoints.openai.protocol import ChatCompletionRequest, DeltaMessage
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from vllm.logger import init_logger
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from vllm.reasoning import ReasoningParser
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logger = init_logger(__name__)
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class IdentityReasoningParser(ReasoningParser):
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"""
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Identity reasoning parser.
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This parser does not attempt to parse or strip out reasoning tokens.
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It treats the entire model output as content and ignores reasoning.
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"""
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def __init__(self, tokenizer: PreTrainedTokenizerBase, *args, **kwargs):
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super().__init__(tokenizer, *args, **kwargs)
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if not self.model_tokenizer:
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raise ValueError(
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"The model tokenizer must be passed to the ReasoningParser "
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"constructor during construction."
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)
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def is_reasoning_end(self, input_ids: list[int]) -> bool:
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# Always return True, since we never treat reasoning specially
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return True
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def extract_content_ids(self, input_ids: list[int]) -> list[int]:
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# Identity: return all tokens as content
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return input_ids
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def extract_reasoning_content_streaming(
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self,
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previous_text: str,
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current_text: str,
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delta_text: str,
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previous_token_ids: Sequence[int],
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current_token_ids: Sequence[int],
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delta_token_ids: Sequence[int],
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) -> DeltaMessage | None:
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# Just wrap delta_text as content, ignore reasoning
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if delta_text:
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return DeltaMessage(content=delta_text)
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return None
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def extract_reasoning_content(
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self, model_output: str, request: ChatCompletionRequest
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) -> tuple[str | None, str | None]:
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# No reasoning separation: return None for reasoning_content,
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# and full model_output as content
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return None, model_output
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