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chore: import upstream snapshot with attribution
2026-07-13 12:38:16 +08:00

203 lines
7.0 KiB
Python

import json
import logging
import re
from typing import List
from sglang.srt.entrypoints.openai.protocol import Tool
from sglang.srt.function_call.base_format_detector import BaseFormatDetector
from sglang.srt.function_call.core_types import (
StreamingParseResult,
ToolCallItem,
_GetInfoFunc,
)
logger = logging.getLogger(__name__)
REGEX_FUNCTION_CALL = re.compile(
r"(?:function call<\|role_sep\|>\n|<\|function_call\|>)(.*)",
re.DOTALL,
)
REGEX_CONTENT_PATTERN = re.compile(
r"^(.*?)(?:<\|message_sep\|>|<\|function_call\|>)",
re.DOTALL,
)
NAME_REGEX = re.compile(
r'"name"\s*:\s*"([^"]*)"',
re.DOTALL,
)
ARGS_REGEX = re.compile(
r'"arguments"\s*:\s*(.*)',
re.DOTALL,
)
class GigaChat3Detector(BaseFormatDetector):
def __init__(self) -> None:
super().__init__()
self.tool_started: bool = False
self.tool_name_sent: bool = False
self.end_content: bool = False
self._buffer: str = ""
self.prev_tool_call_arr: list[dict] = []
def has_tool_call(self, text: str) -> bool:
"""Check if text contains a tool call marker"""
return "function call<|role_sep|>\n" in text or "<|function_call|>" in text
def detect_and_parse(
self,
text: str,
tools: List[Tool],
) -> StreamingParseResult:
"""
Non-streaming parsing of complete model output.
Extracts tool calls and content from the full text.
"""
logger.debug(f"[GigaChat3] detect_and_parse: {text}")
model_output = text
function_call = None
content = None
if model_output.rstrip().endswith("</s>"):
model_output = model_output[: model_output.rfind("</s>")]
m_func = REGEX_FUNCTION_CALL.search(model_output)
if m_func:
try:
function_call = json.loads(m_func.group(1), strict=False)
if not (
isinstance(function_call, dict)
and "name" in function_call
and "arguments" in function_call
):
function_call = None
elif not isinstance(function_call["arguments"], dict):
function_call = None
except json.JSONDecodeError as e:
logger.warning(f"[GigaChat3] JSON decode error: {e}")
return StreamingParseResult(
normal_text=model_output,
calls=[],
)
m_content = REGEX_CONTENT_PATTERN.search(model_output)
if m_content:
content = m_content.group(1)
else:
content = model_output
if not function_call:
return StreamingParseResult(normal_text=content, calls=[])
name = function_call["name"]
args = function_call["arguments"]
match_result = {"name": name, "arguments": args}
calls = self.parse_base_json(match_result, tools)
return StreamingParseResult(normal_text=content, calls=calls)
def parse_streaming_increment(
self,
new_text: str,
tools: List[Tool],
) -> StreamingParseResult:
"""
Streaming parser for incremental text chunks.
Maintains state across calls to build complete tool calls.
"""
if not new_text:
return StreamingParseResult()
logger.debug(f"[GigaChat3] parse_streaming_increment: '{new_text}'")
self._buffer += new_text
current_text = self._buffer
delta_text = new_text
content = None
func_name = None
cur_args = None
m_func = REGEX_FUNCTION_CALL.search(current_text)
if not self.tool_started:
m_content = REGEX_CONTENT_PATTERN.search(delta_text)
if m_content:
content = m_content.group(1)
self.end_content = True
else:
if not self.end_content:
content = delta_text
if m_func:
self.tool_started = True
logger.debug("[GigaChat3] Tool call started")
if content:
return StreamingParseResult(normal_text=content)
if not m_func:
return StreamingParseResult()
json_tail = m_func.group(1).strip()
name_match = NAME_REGEX.search(json_tail)
if name_match:
func_name = name_match.group(1)
args_match = ARGS_REGEX.search(json_tail)
if args_match:
cur_args = args_match.group(1).strip()
if cur_args.endswith("</s>"):
cur_args = cur_args[: -len("</s>")]
if cur_args.endswith("}"):
try:
candidate = cur_args[:-1].strip()
json.loads(candidate, strict=False)
cur_args = candidate
except json.JSONDecodeError:
pass
calls: List[ToolCallItem] = []
if not self.prev_tool_call_arr:
self.prev_tool_call_arr.append({})
if not self.tool_name_sent:
if not func_name:
return StreamingParseResult()
self.tool_name_sent = True
self.prev_tool_call_arr[0]["name"] = func_name
logger.debug(f"[GigaChat3] Sending tool name: {func_name}")
calls.append(
ToolCallItem(
tool_index=0,
name=func_name,
parameters="",
)
)
return StreamingParseResult(calls=calls)
if cur_args is None:
return StreamingParseResult()
prev_args = self.prev_tool_call_arr[0].get("arguments_str", "")
if not prev_args:
delta_args = cur_args
elif cur_args.startswith(prev_args):
delta_args = cur_args[len(prev_args) :]
else:
logger.warning(
f"[GigaChat3] Arguments overlap mismatch. "
f"prev='{prev_args[:50]}...' cur='{cur_args[:50]}...'"
)
return StreamingParseResult()
if not delta_args:
return StreamingParseResult()
self.prev_tool_call_arr[0]["arguments_str"] = cur_args
try:
args_dict = json.loads(cur_args, strict=False)
self.prev_tool_call_arr[0]["arguments"] = args_dict
except json.JSONDecodeError:
self.prev_tool_call_arr[0]["arguments"] = {}
logger.debug(f"[GigaChat3] Sending args delta: '{delta_args[:100]}...'")
calls.append(
ToolCallItem(
tool_index=0,
name=None,
parameters=delta_args,
)
)
return StreamingParseResult(calls=calls)
def supports_structural_tag(self) -> bool:
"""GigaChat3 does not use structural tags"""
return False
def structure_info(self) -> _GetInfoFunc:
"""Not applicable for GigaChat3"""
raise NotImplementedError(
"GigaChat3Detector does not support structural_tag format."
)