68 lines
2.3 KiB
Python
68 lines
2.3 KiB
Python
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import json
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import re
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from typing import List
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from sglang.srt.function_call.base_format_detector import BaseFormatDetector
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from sglang.srt.function_call.core_types import (
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StreamingParseResult,
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StructureInfo,
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_GetInfoFunc,
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)
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from sglang.srt.function_call.ebnf_composer import EBNFComposer
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from sglang.srt.openai_api.protocol import Tool
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class Qwen25Detector(BaseFormatDetector):
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"""
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Detector for Qwen 2.5 models.
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Assumes function call format:
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<tool_call>{"name":"xxx", "arguments":{...}}</tool_call>
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"""
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def __init__(self):
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"""
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Initializes the detector with necessary state variables.
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"""
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super().__init__()
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self.bot_token = "<tool_call>"
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self.eot_token = "</tool_call>"
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def has_tool_call(self, text: str) -> bool:
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"""Check if the text contains a Qwen 2.5 format tool call."""
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return self.bot_token in text
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def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
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"""
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One-time parsing: Detects and parses tool calls in the provided text.
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:param text: The complete text to parse.
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:param tools: List of available tools.
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:return: ParseResult indicating success or failure, consumed text, leftover text, and parsed calls.
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"""
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idx = text.find(self.bot_token)
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normal_text = text[:idx].strip() if idx != -1 else text
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if self.bot_token not in text:
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return StreamingParseResult(normal_text=normal_text, calls=[])
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pattern = rf"{self.bot_token}(.*?){self.eot_token}"
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match_result_list = re.findall(pattern, text, re.DOTALL)
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calls = []
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for match_result in match_result_list:
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match_result = json.loads(match_result)
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calls.extend(self.parse_base_json(match_result, tools))
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return StreamingParseResult(normal_text=normal_text, calls=calls)
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def structure_info(self) -> _GetInfoFunc:
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return lambda name: StructureInfo(
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begin='<tool_call>{"name":"' + name + '", "arguments":',
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end="}</tool_call>",
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trigger="<tool_call>",
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)
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def build_ebnf(self, tools: List[Tool]):
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return EBNFComposer.build_ebnf(
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tools,
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bot_token=self.bot_token,
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eot_token=self.eot_token,
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function_format="json",
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)
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