step3_reasoning_parser.py 4 KB
Newer Older
Song's avatar
Song committed
1
2
3
4
5
6
7
8
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project

from collections.abc import Sequence

import regex as re
from transformers import PreTrainedTokenizerBase

9
from vllm.entrypoints.openai.protocol import ChatCompletionRequest, DeltaMessage
Song's avatar
Song committed
10
from vllm.logger import init_logger
11
from vllm.reasoning import ReasoningParser
Song's avatar
Song committed
12
13
14
15
16
17
18
19

logger = init_logger(__name__)


class Step3ReasoningParser(ReasoningParser):
    """
    Reasoning parser for Step3 model.

20
    The Step3 model uses </think> token to denote the end of reasoning
Song's avatar
Song committed
21
22
23
    text. This parser extracts all content before </think> as reasoning content.
    """

24
25
    def __init__(self, tokenizer: PreTrainedTokenizerBase, *args, **kwargs):
        super().__init__(tokenizer, *args, **kwargs)
Song's avatar
Song committed
26
27
        self.think_end_token = "</think>"

28
        self.reasoning_regex = re.compile(rf"(.*?){self.think_end_token}", re.DOTALL)
Song's avatar
Song committed
29
30
31
32

        if not self.model_tokenizer:
            raise ValueError(
                "The model tokenizer must be passed to the ReasoningParser "
33
34
                "constructor during construction."
            )
Song's avatar
Song committed
35
36
37
38
39

        self.think_end_token_id = self.vocab.get(self.think_end_token)
        if self.think_end_token_id is None:
            raise RuntimeError(
                "Step3 reasoning parser could not locate think end "
40
41
                "token in the tokenizer!"
            )
Song's avatar
Song committed
42
43
44
45
46
47
48
49
50

    def extract_reasoning_content_streaming(
        self,
        previous_text: str,
        current_text: str,
        delta_text: str,
        previous_token_ids: Sequence[int],
        current_token_ids: Sequence[int],
        delta_token_ids: Sequence[int],
51
    ) -> DeltaMessage | None:
Song's avatar
Song committed
52
53
54
55
56
57
58
59
60
        """
        Extract reasoning content from a delta message.
        Handles streaming output where previous + delta = current.
        Uses token IDs for faster processing.
        For text "abc</think>xyz":
        - 'abc' goes to reasoning_content
        - 'xyz' goes to content
        """
        # Skip single special token
61
        if len(delta_token_ids) == 1 and delta_token_ids[0] == self.think_end_token_id:
Song's avatar
Song committed
62
63
64
65
66
67
            return None

        if self.think_end_token_id in delta_token_ids:
            # </think> in delta, extract reasoning content and remaining content
            end_index = delta_text.find(self.think_end_token)
            reasoning_content = delta_text[:end_index]
68
69
70
71
72
            content = delta_text[end_index + len(self.think_end_token) :]
            return DeltaMessage(
                reasoning_content=reasoning_content,
                content=content if content else None,
            )
Song's avatar
Song committed
73
74
75
76
77
78
79
80
        elif self.think_end_token_id in previous_token_ids:
            # </think> already seen in previous text, everything is content
            return DeltaMessage(content=delta_text)
        else:
            # No </think> seen yet, everything is reasoning
            return DeltaMessage(reasoning_content=delta_text)

    def extract_reasoning_content(
81
        self, model_output: str, request: ChatCompletionRequest
82
    ) -> tuple[str | None, str | None]:
Song's avatar
Song committed
83
84
85
86
87
88
89
90
91
92
        # Check if the model output contains the </think> token
        if self.think_end_token not in model_output:
            # If no </think> token, everything is reasoning content
            return model_output, None
        else:
            # Find the first occurrence of </think>
            end_index = model_output.find(self.think_end_token)
            reasoning_content = model_output[:end_index]

            # Content after </think> token
93
            content = model_output[end_index + len(self.think_end_token) :]
Song's avatar
Song committed
94
95
96
97
98
99
100
101
102
103
104
105
106

            if len(content) == 0:
                content = None

            return reasoning_content, content

    def is_reasoning_end(self, input_ids: list[int]) -> bool:
        return self.think_end_token_id in input_ids

    def extract_content_ids(self, input_ids: list[int]) -> list[int]:
        if self.think_end_token_id not in input_ids[:-1]:
            return []
        else:
107
            return input_ids[input_ids.index(self.think_end_token_id) + 1 :]