[Bug Fix] Fix reasoning parser when continue_final_message=true (#17065)
Co-authored-by: Xinyuan Tong <115166877+JustinTong0323@users.noreply.github.com>
This commit is contained in:
@@ -1,5 +1,6 @@
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from typing import Dict, Optional, Tuple, Type
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from sglang.srt.entrypoints.openai.protocol import ChatCompletionRequest
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from sglang.srt.parser.harmony_parser import HarmonyParser
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@@ -24,6 +25,8 @@ class BaseReasoningFormatDetector:
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think_end_token: str,
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force_reasoning: bool = False,
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stream_reasoning: bool = True,
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continue_final_message: bool = False,
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previous_content: str = "",
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):
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self.think_start_token = think_start_token
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self.think_end_token = think_end_token
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@@ -33,6 +36,19 @@ class BaseReasoningFormatDetector:
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self._buffer = ""
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self.stripped_think_start = False
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self.continue_final_message = continue_final_message
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if self.continue_final_message:
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self.previous_content = previous_content
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self.previous_count = len(previous_content)
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else:
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self.previous_content = ""
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self.previous_count = 0
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if self.think_start_token in self.previous_content:
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self._in_reasoning = True
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if self.think_end_token in self.previous_content:
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self._in_reasoning = False
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def detect_and_parse(self, text: str) -> StreamingParseResult:
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"""
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One-time parsing: Detects and parses reasoning sections in the provided text.
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@@ -46,18 +62,25 @@ class BaseReasoningFormatDetector:
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# The text is considered to be in a reasoning block.
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processed_text = text.replace(self.think_start_token, "").strip()
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if self.think_end_token not in processed_text:
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if (
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self.think_end_token not in processed_text
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and self.think_end_token not in self.previous_content
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):
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# Assume reasoning was truncated before `</think>` token
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return StreamingParseResult(reasoning_text=processed_text)
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# Extract reasoning content
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splits = processed_text.split(self.think_end_token, maxsplit=1)
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reasoning_text = splits[0]
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normal_text = splits[1].strip()
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if self.think_end_token in processed_text:
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splits = processed_text.split(self.think_end_token, maxsplit=1)
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reasoning_text = splits[0]
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normal_text = splits[1].strip()
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return StreamingParseResult(
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normal_text=normal_text, reasoning_text=reasoning_text
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)
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return StreamingParseResult(
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normal_text=normal_text, reasoning_text=reasoning_text
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)
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else:
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# think_end_token is in self.previous_content for continue_final_message=True case
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return StreamingParseResult(normal_text=processed_text)
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def parse_streaming_increment(self, new_text: str) -> StreamingParseResult:
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"""
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@@ -137,13 +160,21 @@ class DeepSeekR1Detector(BaseReasoningFormatDetector):
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If True, streams reasoning content as it arrives.
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"""
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def __init__(self, stream_reasoning: bool = True, force_reasoning: bool = True):
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def __init__(
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self,
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stream_reasoning: bool = True,
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force_reasoning: bool = True,
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continue_final_message: bool = False,
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previous_content: str = "",
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):
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# DeepSeek-R1 is assumed to be reasoning until `</think>` token
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super().__init__(
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"<think>",
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"</think>",
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force_reasoning=True,
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stream_reasoning=stream_reasoning,
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continue_final_message=continue_final_message,
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previous_content=previous_content,
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)
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# https://github.com/sgl-project/sglang/pull/3202#discussion_r1950153599
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@@ -184,12 +215,20 @@ class Qwen3Detector(BaseReasoningFormatDetector):
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If True, streams reasoning content as it arrives.
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"""
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def __init__(self, stream_reasoning: bool = True, force_reasoning: bool = False):
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def __init__(
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self,
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stream_reasoning: bool = True,
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force_reasoning: bool = False,
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continue_final_message: bool = False,
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previous_content: str = "",
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):
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super().__init__(
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"<think>",
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"</think>",
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force_reasoning=force_reasoning,
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stream_reasoning=stream_reasoning,
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continue_final_message=continue_final_message,
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previous_content=previous_content,
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)
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@@ -202,12 +241,20 @@ class KimiDetector(BaseReasoningFormatDetector):
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and the rest of the text as `normal_text`.
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"""
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def __init__(self, stream_reasoning: bool = True, force_reasoning: bool = False):
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def __init__(
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self,
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stream_reasoning: bool = True,
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force_reasoning: bool = False,
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continue_final_message: bool = False,
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previous_content: str = "",
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):
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super().__init__(
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"◁think▷",
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"◁/think▷",
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force_reasoning=False,
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stream_reasoning=stream_reasoning,
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continue_final_message=continue_final_message,
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previous_content=previous_content,
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)
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@@ -216,12 +263,20 @@ class GptOssDetector(BaseReasoningFormatDetector):
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Detector for T4-style reasoning format (GPT-OSS), using the HarmonyParser.
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"""
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def __init__(self, stream_reasoning: bool = True, force_reasoning: bool = True):
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def __init__(
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self,
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stream_reasoning: bool = True,
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force_reasoning: bool = True,
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continue_final_message: bool = False,
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previous_content: str = "",
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):
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super().__init__(
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"<|channel|>analysis<|message|>",
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"<|end|>",
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force_reasoning=force_reasoning,
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stream_reasoning=stream_reasoning,
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continue_final_message=continue_final_message,
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previous_content=previous_content,
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)
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self.parser = HarmonyParser()
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@@ -274,13 +329,21 @@ class MiniMaxAppendThinkDetector(BaseReasoningFormatDetector):
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Append `<think>` token to the beginning of the text.
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"""
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def __init__(self, stream_reasoning: bool = True, force_reasoning: bool = False):
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def __init__(
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self,
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stream_reasoning: bool = True,
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force_reasoning: bool = False,
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continue_final_message: bool = False,
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previous_content: str = "",
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):
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# scheduler.py need `reasoning_parser.detector.think_end_token`
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super().__init__(
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"<think>",
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"</think>",
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force_reasoning=force_reasoning,
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stream_reasoning=stream_reasoning,
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continue_final_message=continue_final_message,
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previous_content=previous_content,
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)
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self.is_first_chunk = False
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@@ -301,12 +364,20 @@ class NanoV3Detector(BaseReasoningFormatDetector):
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"""
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def __init__(self, stream_reasoning: bool = True, force_reasoning: bool = False):
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def __init__(
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self,
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stream_reasoning: bool = True,
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force_reasoning: bool = False,
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continue_final_message: bool = False,
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previous_content: str = "",
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):
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super().__init__(
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"<think>",
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"</think>",
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force_reasoning=force_reasoning,
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stream_reasoning=stream_reasoning,
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continue_final_message=continue_final_message,
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previous_content=previous_content,
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)
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@@ -342,6 +413,7 @@ class ReasoningParser:
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model_type: Optional[str] = None,
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stream_reasoning: bool = True,
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force_reasoning: Optional[bool] = None,
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request: ChatCompletionRequest = None,
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):
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if not model_type:
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raise ValueError("Model type must be specified")
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@@ -359,6 +431,15 @@ class ReasoningParser:
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if force_reasoning is not None:
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kwargs["force_reasoning"] = force_reasoning
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if (
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request is not None
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and isinstance(request, ChatCompletionRequest)
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and request.continue_final_message
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and request.messages[-1].role == "assistant"
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):
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kwargs["continue_final_message"] = True
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kwargs["previous_content"] = request.messages[-1].content
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self.detector = detector_class(**kwargs)
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def parse_non_stream(self, full_text: str) -> Tuple[Optional[str], Optional[str]]:
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