add function call parser for DeepSeek V3 (#5224)
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@@ -163,6 +163,35 @@ When using FlashInfer MLA wrapper (`--attention-backend flashinfer`) with specul
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See [Separate Reasoning](https://docs.sglang.ai/backend/separate_reasoning.html).
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### Function calling for DeepSeek Models
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Add arguments `--tool-call-parser deepseekv3` to enable this feature. For example (running on 1 * H20 node):
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```
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python3 -m sglang.launch_server --model deepseek-ai/DeepSeek-V3-0324 --tp 8 --port 30000 --host 0.0.0.0 --mem-fraction-static 0.9 --disable-cuda-graph --tool-call-parser deepseekv3
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```
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Sample Request:
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```
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curl "http://127.0.0.1:30000/v1/chat/completions" \
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-H "Content-Type: application/json" \
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-d '{"temperature": 0, "max_tokens": 100, "model": "deepseek-ai/DeepSeek-V3-0324", "tools": [{"type": "function", "function": {"name": "query_weather", "description": "Get weather of an city, the user should supply a city first", "parameters": {"type": "object", "properties": {"city": {"type": "string", "description": "The city, e.g. Beijing"}}, "required": ["city"]}}}], "messages": [{"role": "user", "content": "Hows the weather like in Qingdao today"}]}'
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```
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Expected Response
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```
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{"id": "62af80528930423a82c806651ec66e7c", "object": "chat.completion", "created": 1744431333, "model": "deepseek-ai/DeepSeek-V3-0324", "choices": [{"index": 0, "message": {"role": "assistant", "content": null, "reasoning_content": null, "tool_calls": [{"id": "0", "type": "function", "function": {"name": "query_weather", "arguments": "{\\"city\\": \\"Guangzhou\\"}"}}]}, "logprobs": null, "finish_reason": "tool_calls", "matched_stop": null}], "usage": {"prompt_tokens": 118, "total_tokens": 140, "completion_tokens": 22, "prompt_tokens_details": null}}
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```
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Important Notes:
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1. Use a lower `"temperature"` value for better results.
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2. Currently, the function calling implementation for deepseek is incompatible with streaming requests.
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## FAQ
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1. **Question**: What should I do if model loading takes too long and NCCL timeout occurs?
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@@ -25,6 +25,7 @@ TOOLS_TAG_LIST = [
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"<tool_call>",
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"<|python_tag|>",
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"[TOOL_CALLS]",
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"<|tool▁calls▁begin|>",
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]
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@@ -477,6 +478,64 @@ class Llama32Detector(BaseFormatDetector):
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)
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class DeepSeekV3Detector(BaseFormatDetector):
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"""
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Detector for DeepSeek models.
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Assumes function call format:
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'<|tool▁calls▁begin|><|tool▁call▁begin|>function<|tool▁sep|>get_current_weather\n```json\n{"location": "Tokyo"}\n```<|tool▁call▁end|>\n<|tool▁call▁begin|>function<|tool▁sep|>get_current_weather\n```json\n{"location": "Paris"}\n```<|tool▁call▁end|><|tool▁calls▁end|><|end▁of▁sentence|>
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"""
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def __init__(self):
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super().__init__()
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self.bot_token = "<|tool▁calls▁begin|>"
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self.eot_token = "<|tool▁calls▁end|>"
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self.func_call_regex = r"<|tool▁call▁begin|>.*?<|tool▁call▁end|>"
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self.func_detail_regex = r"<|tool▁call▁begin|>(.*)<|tool▁sep|>(.*)\n```json\n(.*)\n```<|tool▁call▁end|>"
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def has_tool_call(self, text: str) -> bool:
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"""Check if the text contains a deepseek format tool call."""
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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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"""
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One-time parsing: Detects and parses tool calls in the provided text.
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:param text: The complete text to parse.
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:param tools: List of available tools.
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:return: ParseResult indicating success or failure, consumed text, leftover text, and parsed calls.
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"""
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idx = text.find(self.bot_token)
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normal_text = text[:idx].strip() if idx != -1 else text
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if self.bot_token not in text:
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return StreamingParseResult(normal_text=normal_text, calls=[])
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match_result_list = re.findall(self.func_call_regex, text, re.DOTALL)
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calls = []
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try:
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for match_result in match_result_list:
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# Get function name
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func_detail = re.search(self.func_detail_regex, match_result, re.DOTALL)
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func_name = func_detail.group(2)
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func_args = func_detail.group(3)
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func_args = json.loads(func_args)
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# construct match_result for parse_base_json
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match_result = {"name": func_name, "parameters": func_args}
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calls.extend(self.parse_base_json(match_result, tools))
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return StreamingParseResult(normal_text=normal_text, calls=calls)
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except Exception as e:
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logger.error(f"Error in detect_and_parse: {e}")
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# return the normal text if parsing fails
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return StreamingParseResult(normal_text=text)
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def structure_info(self) -> _GetInfoFunc:
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return lambda name: StructureInfo(
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begin="<|tool▁calls▁begin|><|tool▁call▁begin|>function<|tool▁sep|>"
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+ name
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+ "\n```json\n",
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end="\n```<|tool▁call▁end|><|tool▁calls▁end|>",
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trigger="<|tool▁calls▁begin|>",
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)
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class MultiFormatParser:
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def __init__(self, detectors: List[BaseFormatDetector]):
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"""
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@@ -543,6 +602,7 @@ class FunctionCallParser:
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"llama3": Llama32Detector,
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"qwen25": Qwen25Detector,
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"mistral": MistralDetector,
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"deepseekv3": DeepSeekV3Detector,
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}
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def __init__(self, tools: List[Tool], tool_call_parser: str):
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@@ -938,6 +938,35 @@ def v1_chat_generate_request(
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if chat_template_name is None:
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openai_compatible_messages = []
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if (
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tools
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and tokenizer_manager.server_args.tool_call_parser == "deepseekv3"
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):
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# add function call prompt to deepseekv3
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openai_compatible_messages.append(
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{
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"role": "system",
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"content": """You are a helpful Assistant.
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## Tools
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### Function
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You have the following functions available:
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"""
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+ "".join(
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[
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f"""
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- `{tool['name']}`:
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```json
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{json.dumps(tool)}
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```
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"""
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for tool in tools
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]
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),
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}
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)
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# TODO fix the compatible issues with xgrammar
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strict_tag = None
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for message in request.messages:
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if isinstance(message.content, str):
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openai_compatible_messages.append(
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@@ -1087,7 +1087,7 @@ class ServerArgs:
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parser.add_argument(
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"--tool-call-parser",
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type=str,
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choices=["qwen25", "mistral", "llama3"],
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choices=["qwen25", "mistral", "llama3", "deepseekv3"],
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default=ServerArgs.tool_call_parser,
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help="Specify the parser for handling tool-call interactions. Options include: 'qwen25', 'mistral', and 'llama3'.",
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)
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