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S ) )Sequence)OptionalUnion)PreTrainedTokenizerBase)ChatCompletionRequest DeltaMessage) init_logger)ReasoningParserReasoningParserManagerZqwen3c s e Zd ZdZdef fdd Zdee defddZ dee dee fd d
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edf fddZde dedeee ee f fddZ ZS )Qwen3ReasoningParserau
Reasoning parser for the Qwen3 model.
The Qwen3 model uses ... tokens to denote reasoning text
within its output. The model provides a strict switch to disable reasoning
output via the 'enable_thinking=False' parameter. This parser extracts the
reasoning content enclosed by and tokens from the model's
output.
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dd S )NzzzZThe model tokenizer must be passed to the ReasoningParser constructor during construction.zPQwen3 reasoning parser could not locate think start/end tokens in the tokenizer!) super__init__think_start_tokenthink_end_tokenZmodel_tokenizer
ValueErrorZvocabgetthink_start_token_idthink_end_token_id RuntimeError)selfr __class__ q/home/app/PaddleOCR-VL-test/.venv_paddleocr/lib/python3.10/site-packages/vllm/reasoning/qwen3_reasoning_parser.pyr s
z Qwen3ReasoningParser.__init__ input_idsreturnc C s
| j |v S )N)r r r r r r is_reasoning_end/ s
z%Qwen3ReasoningParser.is_reasoning_endc C s. | j |dd vr g S ||| j d d S )z:
Extract the content after the end tokens
N )r indexr r r r extract_content_ids2 s z(Qwen3ReasoningParser.extract_content_ids
previous_text current_text
delta_textprevious_token_idscurrent_token_idsdelta_token_idsNc C s t |dkr|d | j| jfv rdS | j|v rN| j|v r?|| j}|d| }||t | j d } t|| r;| dS ddS | j|v rIt|dS t|dS | j|v r| j|v r|| j}
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Extract reasoning content from a delta message.
Handles streaming output where previous + delta = current.
Uses token IDs for faster processing.
For text abcxyz:
- 'abc' goes to reasoning_content
- 'xyz' goes to content
r r N)reasoning_contentcontent)r* )r) )lenr r findr r r ) r r# r$ r% r& r' r( Z end_indexr) r* start_indexr r r #extract_reasoning_content_streaming; sD
z8Qwen3ReasoningParser.extract_reasoning_content_streaming model_outputrequestc C st | j |vs
| j|vrd|fS || j }|d r |d n|d }| j|vr)d|fS || j\}}}|p5d}||fS )a
Extract reasoning content from the model output.
For text abcxyz:
- 'abc' goes to reasoning_content
- 'xyz' goes to content
Returns:
tuple[Optional[str], Optional[str]]: reasoning content and content
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