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[Model] Add Qwen3CoderToolParser (#21396)
Signed-off-by: simon-mo <xmo@berkeley.edu> Co-authored-by: simon-mo <xmo@berkeley.edu>
This commit is contained in:
Yiheng Xu
GitHub
parent
ae268b6326
commit
4594fc3b28
618
tests/tool_use/test_qwen3coder_tool_parser.py
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618
tests/tool_use/test_qwen3coder_tool_parser.py
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# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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import json
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from collections.abc import Generator
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from typing import Optional
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import pytest
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from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
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ChatCompletionToolsParam,
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DeltaMessage, FunctionCall,
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ToolCall)
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from vllm.entrypoints.openai.tool_parsers.qwen3coder_tool_parser import (
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Qwen3CoderToolParser)
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from vllm.transformers_utils.detokenizer import detokenize_incrementally
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from vllm.transformers_utils.tokenizer import AnyTokenizer, get_tokenizer
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MODEL = "Qwen/Qwen3-Coder-480B-A35B-Instruct-FP8"
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@pytest.fixture(scope="module")
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def qwen3_tokenizer():
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return get_tokenizer(tokenizer_name=MODEL)
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@pytest.fixture
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def qwen3_tool_parser(qwen3_tokenizer):
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return Qwen3CoderToolParser(qwen3_tokenizer)
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@pytest.fixture
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def sample_tools():
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return [
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ChatCompletionToolsParam(type="function",
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function={
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"name": "get_current_weather",
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"description": "Get the current weather",
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"parameters": {
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"type": "object",
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"properties": {
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"city": {
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"type": "string",
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"description": "The city name"
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},
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"state": {
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"type": "string",
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"description":
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"The state code"
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},
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"unit": {
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"type": "string",
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"enum":
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["fahrenheit", "celsius"]
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}
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},
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"required": ["city", "state"]
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}
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}),
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ChatCompletionToolsParam(type="function",
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function={
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"name": "calculate_area",
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"description":
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"Calculate area of a shape",
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"parameters": {
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"type": "object",
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"properties": {
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"shape": {
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"type": "string"
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},
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"dimensions": {
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"type": "object"
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},
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"precision": {
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"type": "integer"
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}
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}
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}
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})
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]
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def assert_tool_calls(actual_tool_calls: list[ToolCall],
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expected_tool_calls: list[ToolCall]):
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assert len(actual_tool_calls) == len(expected_tool_calls)
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for actual_tool_call, expected_tool_call in zip(actual_tool_calls,
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expected_tool_calls):
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# Qwen3 parser doesn't generate IDs during extraction
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assert actual_tool_call.type == "function"
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assert (
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actual_tool_call.function.name == expected_tool_call.function.name)
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assert (json.loads(actual_tool_call.function.arguments) == json.loads(
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expected_tool_call.function.arguments))
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def stream_delta_message_generator(
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qwen3_tool_parser: Qwen3CoderToolParser,
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qwen3_tokenizer: AnyTokenizer,
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model_output: str,
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request: Optional[ChatCompletionRequest] = None
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) -> Generator[DeltaMessage, None, None]:
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all_token_ids = qwen3_tokenizer.encode(model_output,
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add_special_tokens=False)
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previous_text = ""
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previous_tokens = None
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prefix_offset = 0
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read_offset = 0
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for i, delta_token in enumerate(all_token_ids):
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delta_token_ids = [delta_token]
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previous_token_ids = all_token_ids[:i]
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current_token_ids = all_token_ids[:i + 1]
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(new_tokens, delta_text, new_prefix_offset,
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new_read_offset) = detokenize_incrementally(
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tokenizer=qwen3_tokenizer,
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all_input_ids=current_token_ids,
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prev_tokens=previous_tokens,
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prefix_offset=prefix_offset,
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read_offset=read_offset,
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skip_special_tokens=False,
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spaces_between_special_tokens=True,
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)
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current_text = previous_text + delta_text
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delta_message = qwen3_tool_parser.extract_tool_calls_streaming(
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previous_text,
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current_text,
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delta_text,
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previous_token_ids,
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current_token_ids,
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delta_token_ids,
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request=request,
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)
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if delta_message:
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yield delta_message
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previous_text = current_text
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previous_tokens = (previous_tokens +
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new_tokens if previous_tokens else new_tokens)
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prefix_offset = new_prefix_offset
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read_offset = new_read_offset
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def test_extract_tool_calls_no_tools(qwen3_tool_parser):
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model_output = "This is a test response without any tool calls"
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extracted_tool_calls = qwen3_tool_parser.extract_tool_calls(
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model_output, request=None) # type: ignore[arg-type]
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assert not extracted_tool_calls.tools_called
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assert extracted_tool_calls.tool_calls == []
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assert extracted_tool_calls.content == model_output
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@pytest.mark.parametrize(
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ids=[
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"single_tool",
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"single_tool_with_content",
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"single_tool_multiline_param",
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"parallel_tools",
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"tool_with_typed_params",
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],
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argnames=["model_output", "expected_tool_calls", "expected_content"],
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argvalues=[
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('''<tool_call>
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<function=get_current_weather>
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<parameter=city>
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Dallas
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</parameter>
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<parameter=state>
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TX
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</parameter>
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<parameter=unit>
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fahrenheit
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</parameter>
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</function>
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</tool_call>''', [
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ToolCall(
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function=FunctionCall(name="get_current_weather",
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arguments=json.dumps({
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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})))
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], None),
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('''Sure! Let me check the weather for you.<tool_call>
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<function=get_current_weather>
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<parameter=city>
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Dallas
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</parameter>
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<parameter=state>
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TX
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</parameter>
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<parameter=unit>
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fahrenheit
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</parameter>
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</function>
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</tool_call>''', [
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ToolCall(
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function=FunctionCall(name="get_current_weather",
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arguments=json.dumps({
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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})))
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], "Sure! Let me check the weather for you."),
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('''<tool_call>
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<function=calculate_area>
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<parameter=shape>
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rectangle
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</parameter>
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<parameter=dimensions>
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{"width": 10,
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"height": 20}
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</parameter>
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<parameter=precision>
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2
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</parameter>
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</function>
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</tool_call>''', [
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ToolCall(function=FunctionCall(name="calculate_area",
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arguments=json.dumps({
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"shape": "rectangle",
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"dimensions": {
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"width": 10,
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"height": 20
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},
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"precision": 2
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})))
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], None),
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('''<tool_call>
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<function=get_current_weather>
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<parameter=city>
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Dallas
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</parameter>
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<parameter=state>
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TX
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</parameter>
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<parameter=unit>
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fahrenheit
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</parameter>
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</function>
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</tool_call>
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<tool_call>
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<function=get_current_weather>
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<parameter=city>
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Orlando
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</parameter>
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<parameter=state>
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FL
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</parameter>
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<parameter=unit>
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fahrenheit
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</parameter>
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</function>
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</tool_call>''', [
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ToolCall(
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function=FunctionCall(name="get_current_weather",
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arguments=json.dumps({
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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}))),
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ToolCall(
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function=FunctionCall(name="get_current_weather",
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arguments=json.dumps({
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"city": "Orlando",
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"state": "FL",
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"unit": "fahrenheit"
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})))
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], None),
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('''Let me calculate that area for you.<tool_call>
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<function=calculate_area>
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<parameter=shape>
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circle
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</parameter>
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<parameter=dimensions>
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{"radius": 15.5}
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</parameter>
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<parameter=precision>
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3
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</parameter>
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</function>
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</tool_call>''', [
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ToolCall(function=FunctionCall(name="calculate_area",
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arguments=json.dumps({
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"shape": "circle",
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"dimensions": {
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"radius": 15.5
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},
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"precision": 3
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})))
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], "Let me calculate that area for you."),
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],
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)
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def test_extract_tool_calls(qwen3_tool_parser, sample_tools, model_output,
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expected_tool_calls, expected_content):
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request = ChatCompletionRequest(model=MODEL,
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messages=[],
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tools=sample_tools)
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extracted_tool_calls = qwen3_tool_parser.extract_tool_calls(
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model_output, request=request)
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assert extracted_tool_calls.tools_called
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assert_tool_calls(extracted_tool_calls.tool_calls, expected_tool_calls)
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assert extracted_tool_calls.content == expected_content
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def test_extract_tool_calls_fallback_no_tags(qwen3_tool_parser, sample_tools):
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"""Test fallback parsing when XML tags are missing"""
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model_output = '''<function=get_current_weather>
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<parameter=city>
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Dallas
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</parameter>
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<parameter=state>
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TX
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</parameter>
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</function>'''
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request = ChatCompletionRequest(model=MODEL,
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messages=[],
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tools=sample_tools)
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extracted_tool_calls = qwen3_tool_parser.extract_tool_calls(
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model_output, request=request)
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assert extracted_tool_calls.tools_called
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assert len(extracted_tool_calls.tool_calls) == 1
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assert (extracted_tool_calls.tool_calls[0].function.name ==
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"get_current_weather")
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def test_extract_tool_calls_type_conversion(qwen3_tool_parser):
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"""Test parameter type conversion based on tool schema"""
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tools = [
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ChatCompletionToolsParam(type="function",
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function={
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"name": "test_types",
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"parameters": {
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"type": "object",
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"properties": {
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"int_param": {
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"type": "integer"
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},
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"float_param": {
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"type": "float"
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},
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"bool_param": {
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"type": "boolean"
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},
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"str_param": {
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"type": "string"
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},
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"obj_param": {
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"type": "object"
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}
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}
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}
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})
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]
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model_output = '''<tool_call>
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<function=test_types>
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<parameter=int_param>
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42
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</parameter>
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<parameter=float_param>
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3.14
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</parameter>
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<parameter=bool_param>
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true
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</parameter>
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<parameter=str_param>
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hello world
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</parameter>
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<parameter=obj_param>
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{"key": "value"}
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</parameter>
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</function>
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</tool_call>'''
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request = ChatCompletionRequest(model=MODEL, messages=[], tools=tools)
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extracted_tool_calls = qwen3_tool_parser.extract_tool_calls(
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model_output, request=request)
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args = json.loads(extracted_tool_calls.tool_calls[0].function.arguments)
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assert args["int_param"] == 42
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assert args["float_param"] == 3.14
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assert args["bool_param"] is True
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assert args["str_param"] == "hello world"
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assert args["obj_param"] == {"key": "value"}
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@pytest.mark.parametrize(
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ids=[
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"no_tools",
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"single_tool",
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"single_tool_with_content",
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"parallel_tools",
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],
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argnames=["model_output", "expected_tool_calls", "expected_content"],
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argvalues=[
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("This is a test without tools", [], "This is a test without tools"),
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('''<tool_call>
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<function=get_current_weather>
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<parameter=city>
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Dallas
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</parameter>
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<parameter=state>
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TX
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</parameter>
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<parameter=unit>
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fahrenheit
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</parameter>
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</function>
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</tool_call>''', [
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ToolCall(
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function=FunctionCall(name="get_current_weather",
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arguments=json.dumps({
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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})))
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], ""),
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('''Sure! Let me check the weather for you.<tool_call>
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<function=get_current_weather>
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<parameter=city>
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Dallas
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</parameter>
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<parameter=state>
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TX
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</parameter>
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<parameter=unit>
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fahrenheit
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</parameter>
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</function>
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</tool_call>''', [
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ToolCall(
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function=FunctionCall(name="get_current_weather",
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arguments=json.dumps({
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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})))
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], "Sure! Let me check the weather for you."),
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('''<tool_call>
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<function=get_current_weather>
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<parameter=city>
|
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Dallas
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</parameter>
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<parameter=state>
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TX
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</parameter>
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<parameter=unit>
|
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fahrenheit
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</parameter>
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</function>
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</tool_call>
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<tool_call>
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<function=get_current_weather>
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<parameter=city>
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Orlando
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</parameter>
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<parameter=state>
|
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FL
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</parameter>
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<parameter=unit>
|
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celsius
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</parameter>
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</function>
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</tool_call>''', [
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ToolCall(
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function=FunctionCall(name="get_current_weather",
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arguments=json.dumps({
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"city": "Dallas",
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"state": "TX",
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"unit": "fahrenheit"
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}))),
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ToolCall(
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function=FunctionCall(name="get_current_weather",
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arguments=json.dumps({
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"city": "Orlando",
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"state": "FL",
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"unit": "celsius"
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})))
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], ""),
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],
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)
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def test_extract_tool_calls_streaming(qwen3_tool_parser, qwen3_tokenizer,
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sample_tools, model_output,
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expected_tool_calls, expected_content):
|
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"""Test incremental streaming behavior"""
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request = ChatCompletionRequest(model=MODEL,
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messages=[],
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tools=sample_tools)
|
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other_content = ''
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tool_states = {} # Track state per tool index
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for delta_message in stream_delta_message_generator(
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qwen3_tool_parser, qwen3_tokenizer, model_output, request):
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# role should never be streamed from tool parser
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assert not delta_message.role
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if delta_message.content:
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other_content += delta_message.content
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if delta_message.tool_calls:
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for tool_call in delta_message.tool_calls:
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idx = tool_call.index
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# Initialize state for new tool
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if idx not in tool_states:
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tool_states[idx] = {
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"id": None,
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"name": None,
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"arguments": "",
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"type": None
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}
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# First chunk should have id, name, and type
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if tool_call.id:
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tool_states[idx]["id"] = tool_call.id
|
||||
|
||||
if tool_call.type:
|
||||
assert tool_call.type == "function"
|
||||
tool_states[idx]["type"] = tool_call.type
|
||||
|
||||
if tool_call.function:
|
||||
if tool_call.function.name:
|
||||
# Should only be set once
|
||||
assert tool_states[idx]["name"] is None
|
||||
tool_states[idx]["name"] = tool_call.function.name
|
||||
|
||||
if tool_call.function.arguments is not None:
|
||||
# Accumulate arguments incrementally
|
||||
tool_states[idx][
|
||||
"arguments"] += tool_call.function.arguments
|
||||
|
||||
# Verify final content
|
||||
assert other_content == expected_content
|
||||
|
||||
# Verify we got all expected tool calls
|
||||
assert len(tool_states) == len(expected_tool_calls)
|
||||
|
||||
# Verify each tool call
|
||||
for idx, expected_tool in enumerate(expected_tool_calls):
|
||||
state = tool_states[idx]
|
||||
assert state["id"] is not None
|
||||
assert state["type"] == "function"
|
||||
assert state["name"] == expected_tool.function.name
|
||||
|
||||
# Parse accumulated arguments
|
||||
arguments_str = state["arguments"]
|
||||
assert arguments_str is not None
|
||||
actual_args = json.loads(arguments_str)
|
||||
expected_args = json.loads(expected_tool.function.arguments)
|
||||
assert actual_args == expected_args
|
||||
|
||||
|
||||
def test_extract_tool_calls_streaming_incremental(qwen3_tool_parser,
|
||||
qwen3_tokenizer,
|
||||
sample_tools):
|
||||
"""Test that streaming is truly incremental"""
|
||||
model_output = '''I'll check the weather.<tool_call>
|
||||
<function=get_current_weather>
|
||||
<parameter=city>
|
||||
Dallas
|
||||
</parameter>
|
||||
<parameter=state>
|
||||
TX
|
||||
</parameter>
|
||||
</function>
|
||||
</tool_call>'''
|
||||
|
||||
request = ChatCompletionRequest(model=MODEL,
|
||||
messages=[],
|
||||
tools=sample_tools)
|
||||
|
||||
chunks = []
|
||||
for delta_message in stream_delta_message_generator(
|
||||
qwen3_tool_parser, qwen3_tokenizer, model_output, request):
|
||||
chunks.append(delta_message)
|
||||
|
||||
# Should have multiple chunks
|
||||
assert len(chunks) > 3
|
||||
|
||||
# First chunk(s) should be content
|
||||
assert chunks[0].content is not None
|
||||
assert chunks[0].tool_calls is None or chunks[0].tool_calls == []
|
||||
|
||||
# Should have a chunk with tool header (id, name, type)
|
||||
header_found = False
|
||||
for chunk in chunks:
|
||||
if chunk.tool_calls and chunk.tool_calls[0].id:
|
||||
header_found = True
|
||||
assert (chunk.tool_calls[0].function.name == "get_current_weather")
|
||||
assert chunk.tool_calls[0].type == "function"
|
||||
# Empty initially
|
||||
assert chunk.tool_calls[0].function.arguments == ""
|
||||
break
|
||||
assert header_found
|
||||
|
||||
# Should have chunks with incremental arguments
|
||||
arg_chunks = []
|
||||
for chunk in chunks:
|
||||
if chunk.tool_calls and chunk.tool_calls[0].function.arguments:
|
||||
arg_chunks.append(chunk.tool_calls[0].function.arguments)
|
||||
|
||||
# Arguments should be streamed incrementally
|
||||
assert len(arg_chunks) > 1
|
||||
|
||||
# Concatenated arguments should form valid JSON
|
||||
full_args = "".join(arg_chunks)
|
||||
parsed_args = json.loads(full_args)
|
||||
assert parsed_args["city"] == "Dallas"
|
||||
assert parsed_args["state"] == "TX"
|
||||
@ -17,6 +17,7 @@ from .minimax_tool_parser import MinimaxToolParser
|
||||
from .mistral_tool_parser import MistralToolParser
|
||||
from .phi4mini_tool_parser import Phi4MiniJsonToolParser
|
||||
from .pythonic_tool_parser import PythonicToolParser
|
||||
from .qwen3coder_tool_parser import Qwen3CoderToolParser
|
||||
from .xlam_tool_parser import xLAMToolParser
|
||||
|
||||
__all__ = [
|
||||
@ -38,4 +39,5 @@ __all__ = [
|
||||
"KimiK2ToolParser",
|
||||
"HunyuanA13BToolParser",
|
||||
"Glm4MoeModelToolParser",
|
||||
"Qwen3CoderToolParser",
|
||||
]
|
||||
|
||||
669
vllm/entrypoints/openai/tool_parsers/qwen3coder_tool_parser.py
Normal file
669
vllm/entrypoints/openai/tool_parsers/qwen3coder_tool_parser.py
Normal file
@ -0,0 +1,669 @@
|
||||
# SPDX-License-Identifier: Apache-2.0
|
||||
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
|
||||
|
||||
import json
|
||||
import uuid
|
||||
from collections.abc import Sequence
|
||||
from typing import Any, Optional, Union
|
||||
|
||||
import regex as re
|
||||
|
||||
from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
|
||||
ChatCompletionToolsParam,
|
||||
DeltaFunctionCall, DeltaMessage,
|
||||
DeltaToolCall,
|
||||
ExtractedToolCallInformation,
|
||||
FunctionCall, ToolCall)
|
||||
from vllm.entrypoints.openai.tool_parsers.abstract_tool_parser import (
|
||||
ToolParser, ToolParserManager)
|
||||
from vllm.logger import init_logger
|
||||
from vllm.transformers_utils.tokenizer import AnyTokenizer
|
||||
|
||||
logger = init_logger(__name__)
|
||||
|
||||
|
||||
@ToolParserManager.register_module(["qwen3_coder"])
|
||||
class Qwen3CoderToolParser(ToolParser):
|
||||
|
||||
def __init__(self, tokenizer: AnyTokenizer):
|
||||
super().__init__(tokenizer)
|
||||
|
||||
self.current_tool_name_sent: bool = False
|
||||
self.prev_tool_call_arr: list[dict] = []
|
||||
self.streamed_args_for_tool: list[str] = []
|
||||
|
||||
# Sentinel tokens for streaming mode
|
||||
self.tool_call_start_token: str = "<tool_call>"
|
||||
self.tool_call_end_token: str = "</tool_call>"
|
||||
self.tool_call_prefix: str = "<function="
|
||||
self.function_end_token: str = "</function>"
|
||||
self.parameter_prefix: str = "<parameter="
|
||||
self.parameter_end_token: str = "</parameter>"
|
||||
self.is_tool_call_started: bool = False
|
||||
self.failed_count: int = 0
|
||||
|
||||
# Streaming state variables
|
||||
self.current_tool_index: int = 0
|
||||
self.header_sent: bool = False
|
||||
self.current_tool_string_id: Optional[str] = None
|
||||
self.current_function_name: Optional[str] = None
|
||||
self.current_param_name: Optional[str] = None
|
||||
self.current_param_value: str = ""
|
||||
self.param_count: int = 0
|
||||
self.in_param: bool = False
|
||||
self.in_function: bool = False
|
||||
self.accumulated_text: str = ""
|
||||
self.json_started: bool = False
|
||||
self.json_closed: bool = False
|
||||
|
||||
# Enhanced streaming state - reset for each new message
|
||||
self._reset_streaming_state()
|
||||
|
||||
# Regex patterns
|
||||
self.tool_call_complete_regex = re.compile(
|
||||
r"<tool_call>(.*?)</tool_call>", re.DOTALL)
|
||||
self.tool_call_regex = re.compile(
|
||||
r"<tool_call>(.*?)</tool_call>|<tool_call>(.*?)$", re.DOTALL)
|
||||
self.tool_call_function_regex = re.compile(
|
||||
r"<function=(.*?)</function>|<function=(.*)$", re.DOTALL)
|
||||
self.tool_call_parameter_regex = re.compile(
|
||||
r"<parameter=(.*?)</parameter>|<parameter=(.*?)$", re.DOTALL)
|
||||
|
||||
if not self.model_tokenizer:
|
||||
raise ValueError(
|
||||
"The model tokenizer must be passed to the ToolParser "
|
||||
"constructor during construction.")
|
||||
|
||||
self.tool_call_start_token_id = self.vocab.get(
|
||||
self.tool_call_start_token)
|
||||
self.tool_call_end_token_id = self.vocab.get(self.tool_call_end_token)
|
||||
|
||||
if (self.tool_call_start_token_id is None
|
||||
or self.tool_call_end_token_id is None):
|
||||
raise RuntimeError(
|
||||
"Qwen3 XML Tool parser could not locate tool call start/end "
|
||||
"tokens in the tokenizer!")
|
||||
|
||||
logger.debug("vLLM Successfully import tool parser %s !",
|
||||
self.__class__.__name__)
|
||||
|
||||
def _generate_tool_call_id(self) -> str:
|
||||
"""Generate a unique tool call ID."""
|
||||
return f"call_{uuid.uuid4().hex[:24]}"
|
||||
|
||||
def _reset_streaming_state(self):
|
||||
"""Reset all streaming state."""
|
||||
self.current_tool_index = 0
|
||||
self.is_tool_call_started = False
|
||||
self.header_sent = False
|
||||
self.current_tool_string_id = None
|
||||
self.current_function_name = None
|
||||
self.current_param_name = None
|
||||
self.current_param_value = ""
|
||||
self.param_count = 0
|
||||
self.in_param = False
|
||||
self.in_function = False
|
||||
self.accumulated_text = ""
|
||||
self.json_started = False
|
||||
self.json_closed = False
|
||||
|
||||
def _parse_xml_function_call(
|
||||
self, function_call_str: str,
|
||||
tools: Optional[list[ChatCompletionToolsParam]]
|
||||
) -> Optional[ToolCall]:
|
||||
|
||||
def get_arguments_config(func_name: str) -> dict:
|
||||
if tools is None:
|
||||
return {}
|
||||
for config in tools:
|
||||
if not hasattr(config, "type") or not (
|
||||
hasattr(config, "function")
|
||||
and hasattr(config.function, "name")):
|
||||
continue
|
||||
if (config.type == "function"
|
||||
and config.function.name == func_name):
|
||||
if not hasattr(config.function, "parameters"):
|
||||
return {}
|
||||
params = config.function.parameters
|
||||
if isinstance(params, dict) and "properties" in params:
|
||||
return params["properties"]
|
||||
elif isinstance(params, dict):
|
||||
return params
|
||||
else:
|
||||
return {}
|
||||
logger.warning("Tool '%s' is not defined in the tools list.",
|
||||
func_name)
|
||||
return {}
|
||||
|
||||
def convert_param_value(param_value: str, param_name: str,
|
||||
param_config: dict, func_name: str) -> Any:
|
||||
# Handle null value for any type
|
||||
if param_value.lower() == "null":
|
||||
return None
|
||||
|
||||
converted_value: Any
|
||||
|
||||
if param_name not in param_config:
|
||||
if param_config != {}:
|
||||
logger.warning(
|
||||
"Parsed parameter '%s' is not defined in the tool "
|
||||
"parameters for tool '%s', directly returning the "
|
||||
"string value.", param_name, func_name)
|
||||
return param_value
|
||||
|
||||
if (isinstance(param_config[param_name], dict)
|
||||
and "type" in param_config[param_name]):
|
||||
param_type = str(
|
||||
param_config[param_name]["type"]).strip().lower()
|
||||
else:
|
||||
param_type = "string"
|
||||
if param_type in [
|
||||
"string", "str", "text", "varchar", "char", "enum"
|
||||
]:
|
||||
return param_value
|
||||
elif (param_type.startswith("int") or param_type.startswith("uint")
|
||||
or param_type.startswith("long")
|
||||
or param_type.startswith("short")
|
||||
or param_type.startswith("unsigned")):
|
||||
try:
|
||||
converted_value = int(param_value)
|
||||
return converted_value
|
||||
except ValueError:
|
||||
logger.warning(
|
||||
"Parsed value '%s' of parameter '%s' is not an "
|
||||
"integer in tool '%s', degenerating to string.",
|
||||
param_value, param_name, func_name)
|
||||
return param_value
|
||||
elif (param_type.startswith("num")
|
||||
or param_type.startswith("float")):
|
||||
try:
|
||||
float_param_value = float(param_value)
|
||||
converted_value = (float_param_value if float_param_value -
|
||||
int(float_param_value) != 0 else
|
||||
int(float_param_value))
|
||||
return converted_value
|
||||
except ValueError:
|
||||
logger.warning(
|
||||
"Parsed value '%s' of parameter '%s' is not a float "
|
||||
"in tool '%s', degenerating to string.", param_value,
|
||||
param_name, func_name)
|
||||
return param_value
|
||||
elif param_type in ["boolean", "bool", "binary"]:
|
||||
param_value = param_value.lower()
|
||||
if param_value not in ["true", "false"]:
|
||||
logger.warning(
|
||||
"Parsed value '%s' of parameter '%s' is not a "
|
||||
"boolean (`true` of `false`) in tool '%s', "
|
||||
"degenerating to false.", param_value, param_name,
|
||||
func_name)
|
||||
return param_value == "true"
|
||||
else:
|
||||
if param_type == "object" or param_type.startswith("dict"):
|
||||
try:
|
||||
converted_value = json.loads(param_value)
|
||||
return converted_value
|
||||
except json.JSONDecodeError:
|
||||
logger.warning(
|
||||
"Parsed value '%s' of parameter '%s' is not a "
|
||||
"valid JSON object in tool '%s', will try other "
|
||||
"methods to parse it.", param_value, param_name,
|
||||
func_name)
|
||||
try:
|
||||
converted_value = eval(param_value)
|
||||
return converted_value
|
||||
except Exception:
|
||||
logger.warning(
|
||||
"Parsed value '%s' of parameter '%s' cannot be "
|
||||
"converted via Python `eval()` in tool '%s', "
|
||||
"degenerating to string.", param_value, param_name,
|
||||
func_name)
|
||||
return param_value
|
||||
|
||||
# Extract function name
|
||||
end_index = function_call_str.index(">")
|
||||
function_name = function_call_str[:end_index]
|
||||
param_config = get_arguments_config(function_name)
|
||||
parameters = function_call_str[end_index + 1:]
|
||||
param_dict = {}
|
||||
for match in self.tool_call_parameter_regex.findall(parameters):
|
||||
match_text = match[0] if match[0] else match[1]
|
||||
idx = match_text.index(">")
|
||||
param_name = match_text[:idx]
|
||||
param_value = str(match_text[idx + 1:])
|
||||
# Remove prefix and trailing \n
|
||||
if param_value.startswith("\n"):
|
||||
param_value = param_value[1:]
|
||||
if param_value.endswith("\n"):
|
||||
param_value = param_value[:-1]
|
||||
|
||||
param_dict[param_name] = convert_param_value(
|
||||
param_value, param_name, param_config, function_name)
|
||||
return ToolCall(
|
||||
type="function",
|
||||
function=FunctionCall(name=function_name,
|
||||
arguments=json.dumps(param_dict,
|
||||
ensure_ascii=False)),
|
||||
)
|
||||
|
||||
def _get_function_calls(self, model_output: str) -> list[str]:
|
||||
# Find all tool calls
|
||||
matched_ranges = self.tool_call_regex.findall(model_output)
|
||||
raw_tool_calls = [
|
||||
match[0] if match[0] else match[1] for match in matched_ranges
|
||||
]
|
||||
|
||||
# Back-off strategy if no tool_call tags found
|
||||
if len(raw_tool_calls) == 0:
|
||||
raw_tool_calls = [model_output]
|
||||
|
||||
raw_function_calls = []
|
||||
for tool_call in raw_tool_calls:
|
||||
raw_function_calls.extend(
|
||||
self.tool_call_function_regex.findall(tool_call))
|
||||
|
||||
function_calls = [
|
||||
match[0] if match[0] else match[1] for match in raw_function_calls
|
||||
]
|
||||
return function_calls
|
||||
|
||||
def extract_tool_calls(
|
||||
self,
|
||||
model_output: str,
|
||||
request: ChatCompletionRequest,
|
||||
) -> ExtractedToolCallInformation:
|
||||
# Quick check to avoid unnecessary processing
|
||||
if self.tool_call_prefix not in model_output:
|
||||
return ExtractedToolCallInformation(tools_called=False,
|
||||
tool_calls=[],
|
||||
content=model_output)
|
||||
|
||||
try:
|
||||
function_calls = self._get_function_calls(model_output)
|
||||
if len(function_calls) == 0:
|
||||
return ExtractedToolCallInformation(tools_called=False,
|
||||
tool_calls=[],
|
||||
content=model_output)
|
||||
|
||||
tool_calls = [
|
||||
self._parse_xml_function_call(function_call_str, request.tools)
|
||||
for function_call_str in function_calls
|
||||
]
|
||||
|
||||
# Populate prev_tool_call_arr for serving layer to set
|
||||
# finish_reason
|
||||
self.prev_tool_call_arr.clear() # Clear previous calls
|
||||
for tool_call in tool_calls:
|
||||
if tool_call:
|
||||
self.prev_tool_call_arr.append({
|
||||
"name":
|
||||
tool_call.function.name,
|
||||
"arguments":
|
||||
tool_call.function.arguments,
|
||||
})
|
||||
|
||||
# Extract content before tool calls
|
||||
content_index = model_output.find(self.tool_call_start_token)
|
||||
content_index = (content_index if content_index >= 0 else
|
||||
model_output.find(self.tool_call_prefix))
|
||||
content = model_output[:content_index] # .rstrip()
|
||||
|
||||
return ExtractedToolCallInformation(
|
||||
tools_called=(len(tool_calls) > 0),
|
||||
tool_calls=tool_calls,
|
||||
content=content if content else None,
|
||||
)
|
||||
|
||||
except Exception:
|
||||
logger.exception("Error in extracting tool call from response.")
|
||||
return ExtractedToolCallInformation(tools_called=False,
|
||||
tool_calls=[],
|
||||
content=model_output)
|
||||
|
||||
def extract_tool_calls_streaming(
|
||||
self,
|
||||
previous_text: str,
|
||||
current_text: str,
|
||||
delta_text: str,
|
||||
previous_token_ids: Sequence[int],
|
||||
current_token_ids: Sequence[int],
|
||||
delta_token_ids: Sequence[int],
|
||||
request: ChatCompletionRequest,
|
||||
) -> Union[DeltaMessage, None]:
|
||||
# If no delta text, return None unless it's an EOS token after tool
|
||||
# calls
|
||||
if not delta_text:
|
||||
# Check if this is an EOS token after all tool calls are complete
|
||||
# We check for tool calls in the text even if is_tool_call_started
|
||||
# is False because it might have been reset after processing all
|
||||
# tools
|
||||
if (delta_token_ids
|
||||
and self.tool_call_end_token_id not in delta_token_ids):
|
||||
# Count complete tool calls
|
||||
complete_calls = len(
|
||||
self.tool_call_complete_regex.findall(current_text))
|
||||
|
||||
# If we have completed tool calls and populated
|
||||
# prev_tool_call_arr
|
||||
if (complete_calls > 0 and len(self.prev_tool_call_arr) > 0):
|
||||
# Check if all tool calls are closed
|
||||
open_calls = (
|
||||
current_text.count(self.tool_call_start_token) -
|
||||
current_text.count(self.tool_call_end_token))
|
||||
if open_calls == 0:
|
||||
# Return empty delta message to allow finish_reason
|
||||
# processing
|
||||
return DeltaMessage(content="")
|
||||
elif not self.is_tool_call_started and current_text:
|
||||
# This is a regular content response that's now complete
|
||||
return DeltaMessage(content="")
|
||||
return None
|
||||
|
||||
# Check if this is the first call (reset state if needed)
|
||||
if not previous_text:
|
||||
self._reset_streaming_state()
|
||||
|
||||
# Update accumulated text
|
||||
self.accumulated_text = current_text
|
||||
|
||||
# Check if we need to advance to next tool
|
||||
if self.json_closed and not self.in_function:
|
||||
# Check if this tool call has ended
|
||||
tool_ends = current_text.count(self.tool_call_end_token)
|
||||
if tool_ends > self.current_tool_index:
|
||||
# This tool has ended, advance to next
|
||||
self.current_tool_index += 1
|
||||
self.header_sent = False
|
||||
self.param_count = 0
|
||||
self.json_started = False
|
||||
self.json_closed = False
|
||||
|
||||
# Check if there are more tool calls
|
||||
tool_starts_count = current_text.count(
|
||||
self.tool_call_start_token)
|
||||
if self.current_tool_index >= tool_starts_count:
|
||||
# No more tool calls
|
||||
self.is_tool_call_started = False
|
||||
# Continue processing next tool
|
||||
return None
|
||||
|
||||
# Handle normal content before tool calls
|
||||
if not self.is_tool_call_started:
|
||||
# Check if tool call is starting
|
||||
if (self.tool_call_start_token_id in delta_token_ids
|
||||
or self.tool_call_start_token in delta_text):
|
||||
self.is_tool_call_started = True
|
||||
# Return any content before the tool call
|
||||
if self.tool_call_start_token in delta_text:
|
||||
content_before = delta_text[:delta_text.index(
|
||||
self.tool_call_start_token)]
|
||||
if content_before:
|
||||
return DeltaMessage(content=content_before)
|
||||
return None
|
||||
else:
|
||||
# Check if we're between tool calls - skip whitespace
|
||||
if (current_text.rstrip().endswith(self.tool_call_end_token)
|
||||
and delta_text.strip() == ""):
|
||||
# We just ended a tool call, skip whitespace
|
||||
return None
|
||||
# Normal content, no tool call
|
||||
return DeltaMessage(content=delta_text)
|
||||
|
||||
# Check if we're between tool calls (waiting for next one)
|
||||
# Count tool calls we've seen vs processed
|
||||
tool_starts_count = current_text.count(self.tool_call_start_token)
|
||||
if self.current_tool_index >= tool_starts_count:
|
||||
# We're past all tool calls, shouldn't be here
|
||||
return None
|
||||
|
||||
# We're in a tool call, find the current tool call portion
|
||||
# Need to find the correct tool call based on current_tool_index
|
||||
tool_starts: list[int] = []
|
||||
idx = 0
|
||||
while True:
|
||||
idx = current_text.find(self.tool_call_start_token, idx)
|
||||
if idx == -1:
|
||||
break
|
||||
tool_starts.append(idx)
|
||||
idx += len(self.tool_call_start_token)
|
||||
|
||||
if self.current_tool_index >= len(tool_starts):
|
||||
# No more tool calls to process yet
|
||||
return None
|
||||
|
||||
tool_start_idx = tool_starts[self.current_tool_index]
|
||||
# Find where this tool call ends (or current position if not ended yet)
|
||||
tool_end_idx = current_text.find(self.tool_call_end_token,
|
||||
tool_start_idx)
|
||||
if tool_end_idx == -1:
|
||||
tool_text = current_text[tool_start_idx:]
|
||||
else:
|
||||
tool_text = current_text[tool_start_idx:tool_end_idx +
|
||||
len(self.tool_call_end_token)]
|
||||
|
||||
# Looking for function header
|
||||
if not self.header_sent:
|
||||
if self.tool_call_prefix in tool_text:
|
||||
func_start = (tool_text.find(self.tool_call_prefix) +
|
||||
len(self.tool_call_prefix))
|
||||
func_end = tool_text.find(">", func_start)
|
||||
|
||||
if func_end != -1:
|
||||
# Found complete function name
|
||||
self.current_function_name = tool_text[func_start:func_end]
|
||||
self.current_tool_string_id = self._generate_tool_call_id()
|
||||
self.header_sent = True
|
||||
self.in_function = True
|
||||
|
||||
# IMPORTANT: Add to prev_tool_call_arr immediately when we
|
||||
# detect a tool call. This ensures
|
||||
# finish_reason="tool_calls" even if parsing isn't complete
|
||||
already_added = any(
|
||||
tool.get("name") == self.current_function_name
|
||||
for tool in self.prev_tool_call_arr)
|
||||
if not already_added:
|
||||
self.prev_tool_call_arr.append({
|
||||
"name": self.current_function_name,
|
||||
"arguments":
|
||||
"{}", # Placeholder, will be updated later
|
||||
})
|
||||
|
||||
# Send header with function info
|
||||
return DeltaMessage(tool_calls=[
|
||||
DeltaToolCall(
|
||||
index=self.current_tool_index,
|
||||
id=self.current_tool_string_id,
|
||||
function=DeltaFunctionCall(
|
||||
name=self.current_function_name, arguments=""),
|
||||
type="function",
|
||||
)
|
||||
])
|
||||
return None
|
||||
|
||||
# We've sent header, now handle function body
|
||||
if self.in_function:
|
||||
# Send opening brace if not sent yet
|
||||
if (not self.json_started
|
||||
and self.parameter_prefix not in delta_text):
|
||||
self.json_started = True
|
||||
return DeltaMessage(tool_calls=[
|
||||
DeltaToolCall(
|
||||
index=self.current_tool_index,
|
||||
function=DeltaFunctionCall(arguments="{"),
|
||||
)
|
||||
])
|
||||
|
||||
# Make sure json_started is set if we're processing parameters
|
||||
if not self.json_started:
|
||||
self.json_started = True
|
||||
|
||||
# Check for function end in accumulated text
|
||||
if not self.json_closed and self.function_end_token in tool_text:
|
||||
# Close JSON
|
||||
self.json_closed = True
|
||||
|
||||
# Extract the complete tool call to update prev_tool_call_arr
|
||||
# with final arguments. Find the function content
|
||||
func_start = (tool_text.find(self.tool_call_prefix) +
|
||||
len(self.tool_call_prefix))
|
||||
func_content_end = tool_text.find(self.function_end_token,
|
||||
func_start)
|
||||
if func_content_end != -1:
|
||||
func_content = tool_text[func_start:func_content_end]
|
||||
# Parse to get the complete arguments
|
||||
try:
|
||||
parsed_tool = self._parse_xml_function_call(
|
||||
func_content, request.tools if request else None)
|
||||
if parsed_tool:
|
||||
# Update existing entry in prev_tool_call_arr with
|
||||
# complete arguments
|
||||
for i, tool in enumerate(self.prev_tool_call_arr):
|
||||
if (tool.get("name") ==
|
||||
parsed_tool.function.name):
|
||||
self.prev_tool_call_arr[i]["arguments"] = (
|
||||
parsed_tool.function.arguments)
|
||||
break
|
||||
except Exception:
|
||||
pass # Ignore parsing errors during streaming
|
||||
|
||||
result = DeltaMessage(tool_calls=[
|
||||
DeltaToolCall(
|
||||
index=self.current_tool_index,
|
||||
function=DeltaFunctionCall(arguments="}"),
|
||||
)
|
||||
])
|
||||
|
||||
# Reset state for next tool
|
||||
self.in_function = False
|
||||
self.json_closed = True
|
||||
|
||||
return result
|
||||
|
||||
# Look for parameters
|
||||
# Count how many complete parameters we have processed
|
||||
complete_params = tool_text.count(self.parameter_end_token)
|
||||
|
||||
# Check if we should start a new parameter
|
||||
if not self.in_param and self.param_count < complete_params:
|
||||
# Find the unprocessed parameter
|
||||
# Count parameter starts
|
||||
param_starts = []
|
||||
idx = 0
|
||||
while True:
|
||||
idx = tool_text.find(self.parameter_prefix, idx)
|
||||
if idx == -1:
|
||||
break
|
||||
param_starts.append(idx)
|
||||
idx += len(self.parameter_prefix)
|
||||
|
||||
if len(param_starts) > self.param_count:
|
||||
# Process the next parameter
|
||||
param_idx = param_starts[self.param_count]
|
||||
param_start = param_idx + len(self.parameter_prefix)
|
||||
remaining = tool_text[param_start:]
|
||||
|
||||
if ">" in remaining:
|
||||
# We have the complete parameter name
|
||||
name_end = remaining.find(">")
|
||||
self.current_param_name = remaining[:name_end]
|
||||
|
||||
# Find the parameter value
|
||||
value_start = param_start + name_end + 1
|
||||
value_text = tool_text[value_start:]
|
||||
if value_text.startswith("\n"):
|
||||
value_text = value_text[1:]
|
||||
|
||||
# Find where this parameter ends
|
||||
param_end_idx = value_text.find(
|
||||
self.parameter_end_token)
|
||||
if param_end_idx != -1:
|
||||
# Complete parameter found
|
||||
param_value = value_text[:param_end_idx]
|
||||
if param_value.endswith("\n"):
|
||||
param_value = param_value[:-1]
|
||||
|
||||
# Build complete JSON fragment for this parameter
|
||||
if self.param_count == 0:
|
||||
json_fragment = (
|
||||
'"' + self.current_param_name + '": "' +
|
||||
json.dumps(param_value)[1:-1] + '"')
|
||||
else:
|
||||
json_fragment = (
|
||||
', "' + self.current_param_name + '": "' +
|
||||
json.dumps(param_value)[1:-1] + '"')
|
||||
|
||||
self.param_count += 1
|
||||
|
||||
return DeltaMessage(tool_calls=[
|
||||
DeltaToolCall(
|
||||
index=self.current_tool_index,
|
||||
function=DeltaFunctionCall(
|
||||
arguments=json_fragment),
|
||||
)
|
||||
])
|
||||
|
||||
# Continue parameter value
|
||||
if self.in_param:
|
||||
if self.parameter_end_token in delta_text:
|
||||
# End of parameter
|
||||
end_idx = delta_text.find(self.parameter_end_token)
|
||||
value_chunk = delta_text[:end_idx]
|
||||
|
||||
# Skip past > if at start
|
||||
if not self.current_param_value and ">" in value_chunk:
|
||||
gt_idx = value_chunk.find(">")
|
||||
value_chunk = value_chunk[gt_idx + 1:]
|
||||
|
||||
if (not self.current_param_value
|
||||
and value_chunk.startswith("\n")):
|
||||
value_chunk = value_chunk[1:]
|
||||
|
||||
# Calculate incremental JSON
|
||||
full_value = self.current_param_value + value_chunk
|
||||
prev_escaped = (json.dumps(self.current_param_value)[1:-1]
|
||||
if self.current_param_value else "")
|
||||
full_escaped = json.dumps(full_value)[1:-1]
|
||||
delta_escaped = full_escaped[len(prev_escaped):]
|
||||
|
||||
self.in_param = False
|
||||
self.current_param_value = ""
|
||||
|
||||
return DeltaMessage(tool_calls=[
|
||||
DeltaToolCall(
|
||||
index=self.current_tool_index,
|
||||
function=DeltaFunctionCall(
|
||||
arguments=delta_escaped + '"'),
|
||||
)
|
||||
])
|
||||
else:
|
||||
# Continue accumulating value
|
||||
value_chunk = delta_text
|
||||
|
||||
# Handle first chunk after param name
|
||||
if not self.current_param_value and ">" in value_chunk:
|
||||
gt_idx = value_chunk.find(">")
|
||||
value_chunk = value_chunk[gt_idx + 1:]
|
||||
|
||||
if (not self.current_param_value
|
||||
and value_chunk.startswith("\n")):
|
||||
value_chunk = value_chunk[1:]
|
||||
|
||||
if value_chunk:
|
||||
# Stream the escaped delta
|
||||
prev_escaped = (json.dumps(
|
||||
self.current_param_value)[1:-1]
|
||||
if self.current_param_value else "")
|
||||
self.current_param_value += value_chunk
|
||||
full_escaped = json.dumps(
|
||||
self.current_param_value)[1:-1]
|
||||
delta_escaped = full_escaped[len(prev_escaped):]
|
||||
|
||||
if delta_escaped:
|
||||
return DeltaMessage(tool_calls=[
|
||||
DeltaToolCall(
|
||||
index=self.current_tool_index,
|
||||
function=DeltaFunctionCall(
|
||||
arguments=delta_escaped),
|
||||
)
|
||||
])
|
||||
|
||||
return None
|
||||
Loading…
x
Reference in New Issue
Block a user