Files
sglang/python/sglang/srt/function_call/gpt_oss_detector.py
2025-09-02 18:25:04 -07:00

220 lines
8.1 KiB
Python

import json
import logging
import re
from typing import List, Optional
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,
)
from sglang.srt.parser.harmony_parser import HarmonyParser
logger = logging.getLogger(__name__)
class GptOssDetector(BaseFormatDetector):
"""
Detector for T4-style function calls using HarmonyParser.
Handles tool calls in the format:
<|channel|>commentary to={namespace.function}<|constrain|>json<|message|>{args}<|call|>
"""
def __init__(self):
super().__init__()
self.harmony_parser = HarmonyParser()
self.bot_token = "<|start|>assistant<|channel|>commentary"
self.eot_token = "<|call|>"
# Pattern to extract function name and JSON from tool_call event content
self.tool_extract_pattern = re.compile(
r"to=([a-zA-Z_][a-zA-Z0-9_.]*)\s*<\|constrain\|>json<\|message\|>(.*?)(?:<\|call\|>|$)",
re.DOTALL,
)
def has_tool_call(self, text: str) -> bool:
"""Check if text contains TypeScript-style function call markers."""
return self.bot_token in text
def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
"""Parse TypeScript-style function calls from complete text."""
if not self.has_tool_call(text):
return StreamingParseResult(normal_text=text, calls=[])
# Parse with HarmonyParser
events = self.harmony_parser.parse(text)
# Flush buffer for complete parsing
events += self.harmony_parser.parse("")
tool_indices = self._get_tool_indices(tools)
calls = []
normal_parts = []
tool_index = 0
for event in events:
if event.event_type == "tool_call":
# Extract tool call from event content
tool_call = self._extract_tool_call_from_event(
event.raw_text if event.raw_text else event.content,
tool_indices,
tool_index,
)
if tool_call:
calls.append(tool_call)
tool_index += 1
elif event.event_type == "normal":
normal_parts.append(event.content)
# Ignore reasoning events in function call context
normal_text = " ".join(normal_parts).strip()
return StreamingParseResult(normal_text=normal_text, calls=calls)
def parse_streaming_increment(
self, new_text: str, tools: List[Tool]
) -> StreamingParseResult:
"""Parse incremental streaming text for TypeScript-style function calls."""
self._buffer += new_text
# Always use HarmonyParser for parsing to ensure proper filtering
events = self.harmony_parser.parse(new_text)
# Quick check if we might have tool calls
if (
"<|channel|>commentary to=" not in self._buffer
and not self.current_tool_name_sent
):
# No tool calls detected, check for final content
if (
"<|channel|>final" in self._buffer
or "assistantfinal" in self._buffer.lower()
):
# Extract normal text from events
normal_text = "".join(
[e.content for e in events if e.event_type == "normal"]
)
if normal_text:
self._buffer = ""
return StreamingParseResult(normal_text=normal_text, calls=[])
# For other content, extract normal text from events (with filtering applied)
normal_text = "".join(
[e.content for e in events if e.event_type == "normal"]
)
if normal_text or events:
self._buffer = ""
return StreamingParseResult(normal_text=normal_text, calls=[])
else:
# No events processed, continue buffering
return StreamingParseResult(normal_text="", calls=[])
if not events:
# No complete events yet
return StreamingParseResult(normal_text="", calls=[])
# Initialize state if needed
if not hasattr(self, "_tool_indices"):
self._tool_indices = self._get_tool_indices(tools)
calls = []
normal_text = ""
for event in events:
if event.event_type == "tool_call":
# We got a complete tool call from HarmonyParser
tool_call_info = self._extract_tool_call_from_event(
event.raw_text if event.raw_text else event.content,
self._tool_indices,
self.current_tool_id if self.current_tool_id >= 0 else 0,
)
if tool_call_info:
# Initialize state if first tool
if self.current_tool_id == -1:
self.current_tool_id = 0
self.prev_tool_call_arr = []
self.streamed_args_for_tool = [""]
# Ensure arrays are large enough
while len(self.prev_tool_call_arr) <= self.current_tool_id:
self.prev_tool_call_arr.append({})
while len(self.streamed_args_for_tool) <= self.current_tool_id:
self.streamed_args_for_tool.append("")
# Store tool call info
self.prev_tool_call_arr[self.current_tool_id] = {
"name": tool_call_info.name,
"arguments": json.loads(tool_call_info.parameters),
}
# Emit the complete tool call at once
# (Could be modified to emit name first, then args, if needed)
calls.append(tool_call_info)
# Mark as streamed
self.streamed_args_for_tool[self.current_tool_id] = (
tool_call_info.parameters
)
# Move to next tool
self.current_tool_id += 1
self.current_tool_name_sent = False
elif event.event_type == "normal":
normal_text += event.content
# Clear buffer since HarmonyParser handles buffering
self._buffer = ""
return StreamingParseResult(normal_text=normal_text, calls=calls)
def _extract_tool_call_from_event(
self, content: str, tool_indices: dict, tool_index: int
) -> Optional[ToolCallItem]:
"""
Extract tool call information from HarmonyParser event content.
Content format: "commentary to=functions.get_weather<|constrain|>json<|message|>{...}"
"""
match = self.tool_extract_pattern.search(content)
if not match:
logger.debug(f"Could not extract tool call from: {content[:100]}")
return None
full_function_name = match.group(1)
json_content = match.group(2)
# Extract function name (last part after .)
function_name = (
full_function_name.split(".")[-1]
if "." in full_function_name
else full_function_name
)
# Check if tool exists
if function_name not in tool_indices:
logger.debug(f"Function {function_name} not in available tools")
return None
# Parse JSON arguments
try:
arguments = json.loads(json_content) if json_content.strip() else {}
except json.JSONDecodeError as e:
logger.debug(f"Failed to parse JSON arguments: {e}")
return None
return ToolCallItem(
tool_index=tool_index,
name=function_name,
parameters=json.dumps(arguments, ensure_ascii=False),
)
def structure_info(self) -> _GetInfoFunc:
raise NotImplementedError("structure_info not used with HarmonyParser")
def build_ebnf(self, tools: List[Tool]) -> str:
raise NotImplementedError("build_ebnf not used with HarmonyParser")