[WIP] support MiniMax M2 model (#12129)
Signed-off-by: Xinyuan Tong <xinyuantong.cs@gmail.com> Signed-off-by: xuebi <xuebi@minimaxi.com> Co-authored-by: Xinyuan Tong <xinyuantong.cs@gmail.com> Co-authored-by: Xinyuan Tong <115166877+JustinTong0323@users.noreply.github.com> Co-authored-by: Roger Young <42564206+rogeryoungh@users.noreply.github.com> Co-authored-by: xuebi <xuebi@minimaxi.com>
This commit is contained in:
@@ -16,6 +16,7 @@ from sglang.srt.function_call.glm4_moe_detector import Glm4MoeDetector
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from sglang.srt.function_call.gpt_oss_detector import GptOssDetector
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from sglang.srt.function_call.kimik2_detector import KimiK2Detector
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from sglang.srt.function_call.llama32_detector import Llama32Detector
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from sglang.srt.function_call.minimax_m2 import MinimaxM2Detector
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from sglang.srt.function_call.mistral_detector import MistralDetector
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from sglang.srt.function_call.pythonic_detector import PythonicDetector
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from sglang.srt.function_call.qwen3_coder_detector import Qwen3CoderDetector
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@@ -49,6 +50,7 @@ class FunctionCallParser:
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"qwen25": Qwen25Detector,
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"qwen3_coder": Qwen3CoderDetector,
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"step3": Step3Detector,
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"minimax-m2": MinimaxM2Detector,
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}
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def __init__(self, tools: List[Tool], tool_call_parser: str):
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367
python/sglang/srt/function_call/minimax_m2.py
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367
python/sglang/srt/function_call/minimax_m2.py
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@@ -0,0 +1,367 @@
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import ast
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import html
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import json
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import logging
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import re
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from typing import Any, Dict, List, Tuple
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from sglang.srt.entrypoints.openai.protocol import Tool
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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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ToolCallItem,
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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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logger = logging.getLogger(__name__)
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def _safe_val(raw: str) -> Any:
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raw = html.unescape(raw.strip())
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try:
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return json.loads(raw)
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except Exception:
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try:
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return ast.literal_eval(raw)
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except Exception:
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return raw
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class MinimaxM2Detector(BaseFormatDetector):
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"""
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Detector for MiniMax M2 models.
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Assumes function call format:
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<minimax:tool_call>
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<invoke name="func1">
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<parameter name="param1">value1</parameter>
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<parameter name="param2">value2</parameter>
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</invoke>
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</minimax:tool_call>
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"""
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def __init__(self):
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super().__init__()
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self.tool_call_start_token: str = "<minimax:tool_call>"
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self.tool_call_end_token: str = "</minimax:tool_call>"
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self.tool_call_prefix: str = '<invoke name="'
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self.tool_call_function_end_token: str = "</invoke>"
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self.tool_call_regex = re.compile(
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r"<minimax:tool_call>(.*?)</minimax:tool_call>|<minimax:tool_call>(.*?)$",
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re.DOTALL,
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)
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self.tool_call_function_regex = re.compile(
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r"<invoke name=\"(.*?)</invoke>|<invoke name=\"(.*)$", re.DOTALL
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)
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self.tool_call_parameter_regex = re.compile(
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r"<parameter name=\"(.*?)</parameter>|<parameter name=\"(.*?)$", re.DOTALL
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)
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self._buf: str = ""
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# Streaming state variables
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self._current_function_name: str = ""
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self._current_parameters: Dict[str, Any] = {}
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self._streamed_parameters: Dict[str, str] = (
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{}
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) # Track what parameter content we've streamed
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self._in_tool_call: bool = False
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self._function_name_sent: bool = False
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def has_tool_call(self, text: str) -> bool:
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return self.tool_call_start_token in text
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def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
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normal, calls = self._extract(text, tools)
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return StreamingParseResult(normal_text=normal, calls=calls)
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def parse_streaming_increment(
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self, new_text: str, tools: List[Tool]
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) -> StreamingParseResult:
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self._buf += new_text
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normal = ""
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calls: List[ToolCallItem] = []
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# Build tool indices for validation
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if not hasattr(self, "_tool_indices"):
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self._tool_indices = self._get_tool_indices(tools)
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while True:
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# If we're not in a tool call and don't see a start token, return normal text
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if not self._in_tool_call and self.tool_call_start_token not in self._buf:
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normal += self._buf
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self._buf = ""
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break
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# Look for tool call start
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if not self._in_tool_call:
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s = self._buf.find(self.tool_call_start_token)
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if s == -1:
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normal += self._buf
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self._buf = ""
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break
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normal += self._buf[:s]
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self._buf = self._buf[s:]
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self._in_tool_call = True
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self._function_name_sent = False
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self._current_function_name = ""
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self._current_parameters = {}
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self._streamed_parameters = {}
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# Remove the start token
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self._buf = self._buf[len(self.tool_call_start_token) :]
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continue
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# We're in a tool call, try to parse function name if not sent yet
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if not self._function_name_sent:
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# Look for function name pattern: <invoke name=name>
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function_match = re.search(r"<invoke name=\"([^>]+)\">", self._buf)
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if function_match:
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function_name = function_match.group(1).strip()
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# Validate function name
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if function_name in self._tool_indices:
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self._current_function_name = function_name
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self._function_name_sent = True
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# Initialize tool call tracking
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if self.current_tool_id == -1:
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self.current_tool_id = 0
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# Ensure tracking arrays are large enough
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while len(self.prev_tool_call_arr) <= self.current_tool_id:
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self.prev_tool_call_arr.append({})
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while len(self.streamed_args_for_tool) <= self.current_tool_id:
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self.streamed_args_for_tool.append("")
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# Store tool call info
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self.prev_tool_call_arr[self.current_tool_id] = {
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"name": function_name,
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"arguments": {},
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}
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# Send tool name with empty parameters
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calls.append(
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ToolCallItem(
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tool_index=self.current_tool_id,
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name=function_name,
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parameters="",
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)
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)
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# Remove the processed function declaration
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self._buf = self._buf[function_match.end() :]
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continue
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else:
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# Invalid function name, reset state
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logger.warning(f"Invalid function name: {function_name}")
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self._reset_streaming_state()
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normal += self._buf
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self._buf = ""
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break
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else:
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# Function name not complete yet, wait for more text
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break
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# Parse parameters incrementally
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if self._function_name_sent:
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# Process parameters and get any calls to emit
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parameter_calls = self._parse_and_stream_parameters(self._buf)
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calls.extend(parameter_calls)
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# Check if tool call is complete
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if self.tool_call_function_end_token in self._buf:
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end_pos = self._buf.find(self.tool_call_function_end_token)
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# Add closing brace to complete the JSON object
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current_streamed = self.streamed_args_for_tool[self.current_tool_id]
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if current_streamed:
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# Count opening and closing braces to check if JSON is complete
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open_braces = current_streamed.count("{")
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close_braces = current_streamed.count("}")
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if open_braces > close_braces:
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calls.append(
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ToolCallItem(
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tool_index=self.current_tool_id,
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name=None,
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parameters="}",
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)
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)
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self.streamed_args_for_tool[self.current_tool_id] = (
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current_streamed + "}"
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)
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# Complete the tool call
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self._buf = self._buf[
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end_pos + len(self.tool_call_function_end_token) :
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]
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self._reset_streaming_state(True)
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self.current_tool_id += 1
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continue
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else:
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# Tool call not complete yet, wait for more text
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break
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return StreamingParseResult(normal_text=normal, calls=calls)
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def _parse_and_stream_parameters(self, text_to_parse: str) -> List[ToolCallItem]:
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"""
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Parse complete parameter blocks from text and return any tool call items to emit.
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This method:
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1. Finds all complete <parameter> blocks
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2. Parses them into a dictionary
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3. Compares with current parameters and generates diff if needed
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4. Updates internal state
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Args:
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text_to_parse: The text to search for parameter blocks
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Returns:
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List of ToolCallItem objects to emit (may be empty)
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"""
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calls: List[ToolCallItem] = []
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# Find all complete parameter patterns
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param_matches = list(
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re.finditer(
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r"<parameter name=\"([^>]+)\">(.*?)</parameter>",
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text_to_parse,
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re.DOTALL,
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)
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)
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# Build new parameters dictionary
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new_params = {}
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for match in param_matches:
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param_name = match.group(1).strip()
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param_value = match.group(2)
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new_params[param_name] = _safe_val(param_value)
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# Calculate parameter diff to stream with proper incremental JSON building
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if new_params != self._current_parameters:
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previous_args_json = self.streamed_args_for_tool[self.current_tool_id]
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# Build incremental JSON properly
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if not self._current_parameters:
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# First parameter(s) - start JSON object but don't close it yet
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items = []
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for key, value in new_params.items():
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items.append(
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f"{json.dumps(key, ensure_ascii=False)}: {json.dumps(value, ensure_ascii=False)}"
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)
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json_fragment = "{" + ", ".join(items)
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calls.append(
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ToolCallItem(
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tool_index=self.current_tool_id,
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name=None,
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parameters=json_fragment,
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)
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)
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self.streamed_args_for_tool[self.current_tool_id] = json_fragment
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else:
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# Additional parameters - add them incrementally
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new_keys = set(new_params.keys()) - set(self._current_parameters.keys())
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if new_keys:
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# Build the continuation part (no closing brace yet)
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continuation_parts = []
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for key in new_keys:
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value = new_params[key]
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continuation_parts.append(
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f"{json.dumps(key, ensure_ascii=False)}: {json.dumps(value, ensure_ascii=False)}"
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)
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json_fragment = ", " + ", ".join(continuation_parts)
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calls.append(
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ToolCallItem(
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tool_index=self.current_tool_id,
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name=None,
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parameters=json_fragment,
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)
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)
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self.streamed_args_for_tool[self.current_tool_id] = (
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previous_args_json + json_fragment
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)
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# Update current state
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self._current_parameters = new_params
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self.prev_tool_call_arr[self.current_tool_id]["arguments"] = new_params
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return calls
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def _reset_streaming_state(self, still_in_tool_call: bool = False):
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"""Reset streaming state for the next tool call"""
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self._in_tool_call = still_in_tool_call
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self._function_name_sent = False
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self._current_function_name = ""
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self._current_parameters = {}
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self._streamed_parameters = {}
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self.current_tool_name_sent = False
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def _extract(self, text: str, tools: List[Tool]) -> Tuple[str, List[ToolCallItem]]:
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normal_parts: List[str] = []
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calls: List[ToolCallItem] = []
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cursor = 0
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while True:
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s = text.find(self.tool_call_start_token, cursor)
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if s == -1:
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normal_parts.append(text[cursor:])
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break
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normal_parts.append(text[cursor:s])
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e = text.find(self.tool_call_end_token, s)
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if e == -1:
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normal_parts.append(text[s:])
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break
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block = text[s : e + len(self.tool_call_end_token)]
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cursor = e + len(self.tool_call_end_token)
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calls.extend(self._parse_block(block, tools))
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return "".join(normal_parts), calls
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def _parse_block(self, block: str, tools: List[Tool]) -> List[ToolCallItem]:
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res: List[ToolCallItem] = []
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for m in self.tool_call_function_regex.findall(block):
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txt = m[0] if m[0] else m[1]
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if '">' not in txt:
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continue
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idx = txt.index('">')
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fname = txt[:idx].strip()
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body = txt[idx + 2 :]
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params: Dict[str, Any] = {}
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for pm in self.tool_call_parameter_regex.findall(body):
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ptxt = pm[0] if pm[0] else pm[1]
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if '">' not in ptxt:
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continue
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pidx = ptxt.index('">')
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pname = ptxt[:pidx].strip()
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pval = ptxt[pidx + 2 :].lstrip("\n").rstrip("\n")
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params[pname] = _safe_val(pval)
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raw = {"name": fname, "arguments": params}
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try:
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# TODO: fix idx in function call, the index for a function
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# call will always be -1 in parse_base_json
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res.extend(self.parse_base_json(raw, tools))
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except Exception:
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logger.warning("invalid tool call for %s dropped", fname)
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return res
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def supports_structural_tag(self) -> bool:
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return False
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def structure_info(self) -> _GetInfoFunc:
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raise NotImplementedError
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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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individual_call_start_token=self.tool_call_start_token.replace("\n", "\\n"),
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individual_call_end_token=self.tool_call_end_token.replace("\n", "\\n"),
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tool_call_separator="\\n",
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function_format="xml",
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call_rule_fmt='"<invoke name=\\"{name}\\">\\n" {arguments_rule} "\\n</invoke>"',
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key_value_rule_fmt='"<parameter name=\\"{key}\\">\\n" {valrule} "\\n</parameter>"',
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key_value_separator='"\\n"',
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)
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