332 lines
14 KiB
Python
332 lines
14 KiB
Python
import json
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import logging
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import re
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from typing import List
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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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logger = logging.getLogger(__name__)
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class GptOssDetector(BaseFormatDetector):
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"""
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Detector for T4-style function calls with channel format.
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Supports two formats:
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1. Direct function call: <|channel|>commentary to={namespace.function}<|constrain|>json<|message|>{args}<|call|>
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2. Commentary with action plan: <|channel|>commentary<|message|>{content}<|end|>
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For parallel function calls, each call is self-contained and starts with its own channel:
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<|channel|>commentary to=functions.get_weather<|constrain|>json<|message|>{"location":"SF"}<|call|>
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<|channel|>commentary to=functions.search<|constrain|>json<|message|>{"query":"SF attractions"}<|call|>
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Examples:
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Single: <|channel|>commentary to=functions.get_weather<|constrain|>json<|message|>{"location":"San Francisco"}<|call|>commentary
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Multiple: <|channel|>commentary to=functions.get_weather<|constrain|>json<|message|>{"location":"Paris"}<|call|>commentary<|channel|>commentary to=functions.search<|constrain|>json<|message|>{"query":"Paris tourism"}<|call|>
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With Action Plan: <|channel|>commentary<|message|>**Action plan**: 1. Do X 2. Do Y<|end|><|start|>assistant<|channel|>commentary to=functions.x<|constrain|>json<|message|>{"template": "basic_html", "path": "index.html"}<|call|>
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"""
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def __init__(self):
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super().__init__()
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self.bot_token = "<|start|>assistant<|channel|>commentary"
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self.eot_token = "<|call|>"
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# TODO: no clear indication how parallel tool call response format is
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self.tool_call_separator = ""
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# Pattern for complete function calls with to= parameter
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# Handles both <|call|> and <|call|>commentary endings
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# Also handles optional <|start|>assistant prefix and whitespace after function name
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self.function_call_pattern = re.compile(
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r"(?:<\|start\|>assistant)?<\|channel\|>commentary to=([a-zA-Z_][a-zA-Z0-9_]*(?:\.[a-zA-Z_][a-zA-Z0-9_]*)*)\s*"
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r"<\|constrain\|>json<\|message\|>(.*?)<\|call\|>(?:commentary)?",
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re.DOTALL,
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)
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# Pattern for streaming function calls (incomplete)
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# Also handles optional whitespace after function name
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self.streaming_pattern = re.compile(
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r"(?:<\|start\|>assistant)?<\|channel\|>commentary to=([a-zA-Z_][a-zA-Z0-9_]*(?:\.[a-zA-Z_][a-zA-Z0-9_]*)*)\s*"
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r"<\|constrain\|>json<\|message\|>(.*)",
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re.DOTALL,
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)
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# Pattern for commentary with action plan (no to= parameter)
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self.commentary_pattern = re.compile(
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r"<\|channel\|>commentary<\|message\|>(.*?)<\|end\|>",
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re.DOTALL,
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)
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self._last_arguments = ""
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def has_tool_call(self, text: str) -> bool:
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"""Check if text contains TypeScript-style function call markers."""
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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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"""Parse TypeScript-style function calls from complete text."""
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if not self.has_tool_call(text):
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return StreamingParseResult(normal_text=text, calls=[])
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tool_indices = self._get_tool_indices(tools)
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calls = []
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tool_index = 0
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# Process the entire text to handle mixed commentary and tool calls
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normal_text_parts = []
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# Find all commentary sections (both with and without to=)
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all_commentary_pattern = re.compile(
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r"<\|channel\|>commentary(?:\s+to=[^<]*)?<\|message\|>(.*?)(?:<\|end\|>|<\|call\|>)",
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re.DOTALL,
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)
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# Track processed positions to avoid double-processing
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processed_ranges = []
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# First, extract all tool calls
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for match in self.function_call_pattern.finditer(text):
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full_function_name = match.group(1)
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args_content = match.group(2)
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processed_ranges.append((match.start(), match.end()))
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function_name = (
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full_function_name.split(".")[-1]
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if "." in full_function_name
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else full_function_name
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)
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try:
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arguments = json.loads(args_content) if args_content.strip() else {}
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except json.JSONDecodeError:
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continue
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if function_name in tool_indices:
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calls.append(
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ToolCallItem(
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tool_index=tool_index,
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name=function_name,
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parameters=json.dumps(arguments, ensure_ascii=False),
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)
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)
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tool_index += 1
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# Then, find non-tool-call commentary sections for normal text
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for match in all_commentary_pattern.finditer(text):
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# Check if this match overlaps with any processed tool call
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match_start, match_end = match.start(), match.end()
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is_tool_call = any(
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start <= match_start < end or start < match_end <= end
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for start, end in processed_ranges
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)
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# If this commentary is not part of a tool call, include it in normal text
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if not is_tool_call:
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content = match.group(1).strip()
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if content:
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normal_text_parts.append(content)
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# Handle remaining text after all matches
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if processed_ranges:
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last_match_end = max(end for _, end in processed_ranges)
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if last_match_end < len(text):
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remaining_text = text[last_match_end:]
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# Clean up <|start|>assistant prefixes and extract final content
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# Remove standalone <|start|>assistant prefixes
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remaining_text = re.sub(r"<\|start\|>assistant(?!\w)", "", remaining_text)
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# Extract content from final channel if present
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final_pattern = re.compile(
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r"<\|channel\|>final<\|message\|>(.*?)(?:<\|return\|>|$)", re.DOTALL
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)
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final_match = final_pattern.search(remaining_text)
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if final_match:
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# Get everything before final channel + final channel content
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before_final = remaining_text[: final_match.start()].strip()
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final_content = final_match.group(1).strip()
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parts = []
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if before_final:
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parts.append(before_final)
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if final_content:
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parts.append(final_content)
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remaining_text = " ".join(parts) if parts else ""
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remaining_text = remaining_text.strip()
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if remaining_text:
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normal_text_parts.append(remaining_text)
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# Combine all normal text parts
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final_normal_text = " ".join(part for part in normal_text_parts if part).strip()
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return StreamingParseResult(normal_text=final_normal_text, 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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"""Parse incremental streaming text for TypeScript-style function calls."""
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self._buffer += new_text
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current_text = self._buffer
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# Check if we have a tool call
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has_tool_call = "<|channel|>commentary to=" in current_text
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if not has_tool_call and current_text:
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# Check for commentary without function calls
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commentary_match = self.commentary_pattern.search(current_text)
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if commentary_match:
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commentary_content = commentary_match.group(1)
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self._buffer = current_text[commentary_match.end() :]
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return StreamingParseResult(normal_text=commentary_content, calls=[])
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# Check for final channel content
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final_pattern = re.compile(
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r"<\|channel\|>final<\|message\|>(.*?)(?:<\|return\|>|$)",
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re.DOTALL,
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)
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final_match = final_pattern.search(current_text)
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if final_match:
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final_content = final_match.group(1).strip()
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self._buffer = ""
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return StreamingParseResult(normal_text=final_content, calls=[])
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self._buffer = ""
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return StreamingParseResult(normal_text=new_text, calls=[])
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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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calls = []
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try:
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# Check for streaming function call
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match = self.streaming_pattern.search(current_text)
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if match:
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full_function_name = match.group(1)
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args_content = match.group(2)
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function_name = (
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full_function_name.split(".")[-1]
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if "." in full_function_name
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else full_function_name
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)
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# Initialize state if this is the first tool call
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if self.current_tool_id == -1:
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self.current_tool_id = 0
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self.prev_tool_call_arr = []
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self.streamed_args_for_tool = [""]
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# Ensure we have enough entries in tracking arrays
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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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if not self.current_tool_name_sent:
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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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self.current_tool_name_sent = True
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# Store the 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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self.streamed_args_for_tool[self.current_tool_id] = ""
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# Check if we have a complete function call
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complete_match = self.function_call_pattern.search(current_text)
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if complete_match:
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args_content = complete_match.group(2)
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try:
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parsed_args = json.loads(args_content)
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self.prev_tool_call_arr[self.current_tool_id][
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"arguments"
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] = parsed_args
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# Send complete arguments if we haven't sent them yet
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if not self.streamed_args_for_tool[self.current_tool_id]:
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# Send the complete arguments as JSON string
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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.dumps(
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parsed_args, ensure_ascii=False
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),
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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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json.dumps(parsed_args, ensure_ascii=False)
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)
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except json.JSONDecodeError:
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pass
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# Remove the completed function call from buffer
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remaining_after_call = current_text[complete_match.end() :]
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# Clean up <|start|>assistant prefixes and extract final content
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remaining_after_call = re.sub(
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r"<\|start\|>assistant(?!\w)", "", remaining_after_call
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)
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# Extract content from final channel if present
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final_pattern = re.compile(
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r"<\|channel\|>final<\|message\|>(.*?)(?:<\|return\|>|$)",
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re.DOTALL,
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)
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final_match = final_pattern.search(remaining_after_call)
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if final_match:
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before_final = remaining_after_call[
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: final_match.start()
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].strip()
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final_content = final_match.group(1).strip()
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parts = []
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if before_final:
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parts.append(before_final)
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if final_content:
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parts.append(final_content)
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remaining_after_call = " ".join(parts) if parts else ""
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self._buffer = remaining_after_call.strip()
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# Reset state for next tool call
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self.current_tool_name_sent = False
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self.current_tool_id += 1
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# Return final content if available
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final_text = ""
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if final_match and final_content:
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final_text = final_content
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elif remaining_after_call:
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final_text = remaining_after_call
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return StreamingParseResult(normal_text=final_text, calls=calls)
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return StreamingParseResult(normal_text="", calls=calls)
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except Exception as e:
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logger.error(f"Error in parse_streaming_increment: {e}")
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return StreamingParseResult(normal_text=current_text, calls=[])
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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]) -> str:
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raise NotImplementedError()
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