Unverified Commit b9683be6 authored by Xu Wenqing's avatar Xu Wenqing Committed by GitHub
Browse files

Support DeepSeek-V3.1 tool call (#9446)


Signed-off-by: default avatar许文卿 <xwq391974@alibaba-inc.com>
Co-authored-by: default avatarXinyuan Tong <xinyuantong.cs@gmail.com>
parent a85363c1
{% if not add_generation_prompt is defined %}
{% set add_generation_prompt = false %}
{% endif %}
{% if not thinking is defined %}
{% set thinking = false %}
{% endif %}
{% set ns = namespace(is_first=false, is_tool=false, system_prompt='', is_first_sp=true, is_last_user=false) %}
{%- for message in messages %}
{%- if message['role'] == 'system' %}
{%- if ns.is_first_sp %}
{% set ns.system_prompt = ns.system_prompt + message['content'] %}
{% set ns.is_first_sp = false %}
{%- else %}
{% set ns.system_prompt = ns.system_prompt + '\n\n' + message['content'] %}
{%- endif %}
{%- endif %}
{%- endfor %}
{% if tools is defined and tools is not none %}
{% set tool_ns = namespace(text='## Tools\nYou have access to the following tools:\n') %}
{% for tool in tools %}
{% set tool_ns.text = tool_ns.text + '\n### ' + tool.function.name + '\nDescription: ' + tool.function.description + '\n\nParameters: ' + (tool.function.parameters | tojson) + '\n' %}
{% endfor %}
{% set tool_ns.text = tool_ns.text + "\nIMPORTANT: ALWAYS adhere to this exact format for tool use:\n<|tool▁calls▁begin|><|tool▁call▁begin|>tool_call_name<|tool▁sep|>tool_call_arguments<|tool▁call▁end|>{{additional_tool_calls}}<|tool▁calls▁end|>\n\nWhere:\n\n- `tool_call_name` must be an exact match to one of the available tools\n- `tool_call_arguments` must be valid JSON that strictly follows the tool's Parameters Schema\n- For multiple tool calls, chain them directly without separators or spaces\n" %}
{% set ns.system_prompt = ns.system_prompt + '\n\n' + tool_ns.text %}
{% endif %}
{{ bos_token }}{{ ns.system_prompt }}
{%- for message in messages %}
{%- if message['role'] == 'user' %}
{%- set ns.is_tool = false -%}
{%- set ns.is_first = false -%}
{%- set ns.is_last_user = true -%}
{{'<|User|>' + message['content']}}
{%- endif %}
{%- if message['role'] == 'assistant' and message['tool_calls'] is defined and message['tool_calls'] is not none %}
{%- if ns.is_last_user %}
{{'<|Assistant|></think>'}}
{%- endif %}
{%- set ns.is_last_user = false -%}
{%- set ns.is_first = false %}
{%- set ns.is_tool = false -%}
{%- for tool in message['tool_calls'] %}
{%- if not ns.is_first %}
{%- if message['content'] is none %}
{{'<|tool▁calls▁begin|><|tool▁call▁begin|>'+ tool['function']['name'] + '<|tool▁sep|>' + tool['function']['arguments'] + '<|tool▁call▁end|>'}}
{%- else %}
{{message['content'] + '<|tool▁calls▁begin|><|tool▁call▁begin|>' + tool['function']['name'] + '<|tool▁sep|>' + tool['function']['arguments'] + '<|tool▁call▁end|>'}}
{%- endif %}
{%- set ns.is_first = true -%}
{%- else %}
{{'<|tool▁call▁begin|>'+ tool['function']['name'] + '<|tool▁sep|>' + tool['function']['arguments'] + '<|tool▁call▁end|>'}}
{%- endif %}
{%- endfor %}
{{'<|tool▁calls▁end|><|end▁of▁sentence|>'}}
{%- endif %}
{%- if message['role'] == 'assistant' and (message['tool_calls'] is not defined or message['tool_calls'] is none) %}
{%- if ns.is_last_user %}
{{'<|Assistant|>'}}
{%- if message['prefix'] is defined and message['prefix'] and thinking %}
{{'<think>'}}
{%- else %}
{{'</think>'}}
{%- endif %}
{%- endif %}
{%- set ns.is_last_user = false -%}
{%- if ns.is_tool %}
{{message['content'] + '<|end▁of▁sentence|>'}}
{%- set ns.is_tool = false -%}
{%- else %}
{%- set content = message['content'] -%}
{%- if '</think>' in content %}
{%- set content = content.split('</think>', 1)[1] -%}
{%- endif %}
{{content + '<|end▁of▁sentence|>'}}
{%- endif %}
{%- endif %}
{%- if message['role'] == 'tool' %}
{%- set ns.is_last_user = false -%}
{%- set ns.is_tool = true -%}
{{'<|tool▁output▁begin|>' + message['content'] + '<|tool▁output▁end|>'}}
{%- endif %}
{%- endfor -%}
{%- if add_generation_prompt and ns.is_last_user and not ns.is_tool %}
{{'<|Assistant|>'}}
{%- if not thinking %}
{{'</think>'}}
{%- else %}
{{'<think>'}}
{%- endif %}
{% endif %}
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,
StructureInfo,
ToolCallItem,
_GetInfoFunc,
)
from sglang.srt.function_call.ebnf_composer import EBNFComposer
from sglang.srt.function_call.utils import _is_complete_json
logger = logging.getLogger(__name__)
class DeepSeekV31Detector(BaseFormatDetector):
"""
Detector for DeepSeek V3 model function call format.
The DeepSeek V3 format uses special Unicode tokens to delimit function calls
with JSON code blocks for arguments.
Format Structure:
```
<|tool▁calls▁begin|><|tool▁call▁begin|>{function_name}<|tool▁sep|>{json_arguments}<|tool▁calls▁end|><|end▁of▁sentence|>
```
Examples:
```
<|tool▁calls▁begin|><|tool▁call▁begin|>get_current_weather<|tool▁sep|>{"location": "Tokyo"}<|tool▁call▁end|><|tool▁call▁begin|>get_current_weather<|tool▁sep|>{"location": "Paris"}<|tool▁call▁end|><|tool▁calls▁end|><|end▁of▁sentence|>
```
Key Components:
- Tool Calls Section: Wrapped between `<|tool▁calls▁begin|>` and `<|tool▁calls▁end|>`
- Individual Tool Call: Wrapped between `<|tool▁call▁begin|>` and `<|tool▁call▁end|>`
- Function Declaration: `<|tool▁call▁begin|>{function_name}<|tool▁sep|>`
- Arguments: JSON code block between `<|tool▁sep|>` and `<|tool▁call▁end|>`
- Supports multiple tool calls
Reference: https://www.modelscope.cn/models/deepseek-ai/DeepSeek-V3.1
"""
def __init__(self):
super().__init__()
self.bot_token = "<|tool▁calls▁begin|>"
self.eot_token = "<|tool▁calls▁end|>"
self.func_call_regex = r"<|tool▁call▁begin|>.*?<|tool▁call▁end|>"
self.func_detail_regex = (
r"<|tool▁call▁begin|>(.*)<|tool▁sep|>(.*)<|tool▁call▁end|>"
)
self._last_arguments = ""
self.current_tool_id = -1
def has_tool_call(self, text: str) -> bool:
"""Check if the text contains a deepseek format tool call."""
return self.bot_token in text
def detect_and_parse(self, text: str, tools: List[Tool]) -> StreamingParseResult:
"""
One-time parsing: Detects and parses tool calls in the provided text.
:param text: The complete text to parse.
:param tools: List of available tools.
:return: ParseResult indicating success or failure, consumed text, leftover text, and parsed calls.
"""
idx = text.find(self.bot_token)
normal_text = text[:idx].strip() if idx != -1 else text
if self.bot_token not in text:
return StreamingParseResult(normal_text=normal_text, calls=[])
match_result_list = re.findall(self.func_call_regex, text, re.DOTALL)
calls = []
try:
for match_result in match_result_list:
# Get function name
func_detail = re.search(self.func_detail_regex, match_result, re.DOTALL)
func_name = func_detail.group(1)
func_args = func_detail.group(2)
func_args = json.loads(func_args)
# construct match_result for parse_base_json
match_result = {"name": func_name, "parameters": func_args}
calls.extend(self.parse_base_json(match_result, tools))
return StreamingParseResult(normal_text=normal_text, calls=calls)
except Exception as e:
logger.error(f"Error in detect_and_parse: {e}")
# return the normal text if parsing fails
return StreamingParseResult(normal_text=text)
def parse_streaming_increment(
self, new_text: str, tools: List[Tool]
) -> StreamingParseResult:
"""
Streaming incremental parsing tool calls for DeepSeekV3 format.
"""
self._buffer += new_text
current_text = self._buffer
# Check if we have a tool call (either the start token or individual tool call)
has_tool_call = (
self.bot_token in current_text or "<|tool▁call▁begin|>" in current_text
)
if not has_tool_call:
self._buffer = ""
for e_token in [self.eot_token, "<|tool▁call▁end|>"]:
if e_token in new_text:
new_text = new_text.replace(e_token, "")
return StreamingParseResult(normal_text=new_text)
if not hasattr(self, "_tool_indices"):
self._tool_indices = self._get_tool_indices(tools)
calls: list[ToolCallItem] = []
try:
partial_match = re.search(
pattern=r"<|tool▁call▁begin|>(.*)<|tool▁sep|>(.*)<|tool▁call▁end|>",
string=current_text,
flags=re.DOTALL,
)
if partial_match:
func_name = partial_match.group(1).strip()
func_args_raw = partial_match.group(2).strip()
# Initialize state if this is the first tool call
if self.current_tool_id == -1:
self.current_tool_id = 0
self.prev_tool_call_arr = []
self.streamed_args_for_tool = [""]
# Ensure we have enough entries in our tracking arrays
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("")
if not self.current_tool_name_sent:
calls.append(
ToolCallItem(
tool_index=self.current_tool_id,
name=func_name,
parameters="",
)
)
self.current_tool_name_sent = True
# Store the tool call info for serving layer completions endpoint
self.prev_tool_call_arr[self.current_tool_id] = {
"name": func_name,
"arguments": {},
}
else:
argument_diff = (
func_args_raw[len(self._last_arguments) :]
if func_args_raw.startswith(self._last_arguments)
else func_args_raw
)
if argument_diff:
calls.append(
ToolCallItem(
tool_index=self.current_tool_id,
name=None,
parameters=argument_diff,
)
)
self._last_arguments += argument_diff
self.streamed_args_for_tool[
self.current_tool_id
] += argument_diff
if _is_complete_json(func_args_raw):
# Update the stored arguments
try:
parsed_args = json.loads(func_args_raw)
self.prev_tool_call_arr[self.current_tool_id][
"arguments"
] = parsed_args
except json.JSONDecodeError:
pass
# Find the end of the current tool call and remove only that part from buffer
tool_call_end_pattern = (
r"<|tool▁call▁begin|>.*?<|tool▁call▁end|>"
)
match = re.search(
tool_call_end_pattern, current_text, re.DOTALL
)
if match:
# Remove the completed tool call from buffer, keep any remaining content
self._buffer = current_text[match.end() :]
else:
self._buffer = ""
result = StreamingParseResult(normal_text="", calls=calls)
self.current_tool_id += 1
self._last_arguments = ""
self.current_tool_name_sent = False
return result
return StreamingParseResult(normal_text="", calls=calls)
except Exception as e:
logger.error(f"Error in parse_streaming_increment: {e}")
return StreamingParseResult(normal_text=current_text)
def structure_info(self) -> _GetInfoFunc:
return lambda name: StructureInfo(
begin="<|tool▁call▁begin|>" + name + "<|tool▁sep|>",
end="<|tool▁call▁end|>",
trigger="<|tool▁call▁begin|>" + name + "<|tool▁sep|>",
)
def build_ebnf(self, tools: List[Tool]):
return EBNFComposer.build_ebnf(
tools,
sequence_start_token=self.bot_token,
sequence_end_token=self.eot_token,
tool_call_separator="",
call_rule_fmt='"<|tool▁call▁begin|>{name}<|tool▁sep|>{arguments_rule}<|tool▁call▁end|>"',
function_format="json",
)
...@@ -10,6 +10,7 @@ from sglang.srt.entrypoints.openai.protocol import ( ...@@ -10,6 +10,7 @@ from sglang.srt.entrypoints.openai.protocol import (
from sglang.srt.function_call.base_format_detector import BaseFormatDetector from sglang.srt.function_call.base_format_detector import BaseFormatDetector
from sglang.srt.function_call.core_types import ToolCallItem from sglang.srt.function_call.core_types import ToolCallItem
from sglang.srt.function_call.deepseekv3_detector import DeepSeekV3Detector from sglang.srt.function_call.deepseekv3_detector import DeepSeekV3Detector
from sglang.srt.function_call.deepseekv31_detector import DeepSeekV31Detector
from sglang.srt.function_call.glm4_moe_detector import Glm4MoeDetector from sglang.srt.function_call.glm4_moe_detector import Glm4MoeDetector
from sglang.srt.function_call.gpt_oss_detector import GptOssDetector from sglang.srt.function_call.gpt_oss_detector import GptOssDetector
from sglang.srt.function_call.kimik2_detector import KimiK2Detector from sglang.srt.function_call.kimik2_detector import KimiK2Detector
...@@ -37,6 +38,7 @@ class FunctionCallParser: ...@@ -37,6 +38,7 @@ class FunctionCallParser:
"qwen25": Qwen25Detector, "qwen25": Qwen25Detector,
"mistral": MistralDetector, "mistral": MistralDetector,
"deepseekv3": DeepSeekV3Detector, "deepseekv3": DeepSeekV3Detector,
"deepseekv31": DeepSeekV31Detector,
"pythonic": PythonicDetector, "pythonic": PythonicDetector,
"kimi_k2": KimiK2Detector, "kimi_k2": KimiK2Detector,
"qwen3_coder": Qwen3CoderDetector, "qwen3_coder": Qwen3CoderDetector,
......
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