[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
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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@@ -0,0 +1,618 @@
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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>
|
||||
<parameter=state>
|
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TX
|
||||
</parameter>
|
||||
<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>
|
||||
<parameter=state>
|
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FL
|
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</parameter>
|
||||
<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",
|
||||
"state": "TX",
|
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"unit": "fahrenheit"
|
||||
}))),
|
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ToolCall(
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function=FunctionCall(name="get_current_weather",
|
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arguments=json.dumps({
|
||||
"city": "Orlando",
|
||||
"state": "FL",
|
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"unit": "celsius"
|
||||
})))
|
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], ""),
|
||||
],
|
||||
)
|
||||
def test_extract_tool_calls_streaming(qwen3_tool_parser, qwen3_tokenizer,
|
||||
sample_tools, model_output,
|
||||
expected_tool_calls, expected_content):
|
||||
"""Test incremental streaming behavior"""
|
||||
request = ChatCompletionRequest(model=MODEL,
|
||||
messages=[],
|
||||
tools=sample_tools)
|
||||
|
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other_content = ''
|
||||
tool_states = {} # Track state per tool index
|
||||
|
||||
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
|
||||
|
||||
if delta_message.tool_calls:
|
||||
for tool_call in delta_message.tool_calls:
|
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idx = tool_call.index
|
||||
|
||||
# Initialize state for new tool
|
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if idx not in tool_states:
|
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tool_states[idx] = {
|
||||
"id": None,
|
||||
"name": None,
|
||||
"arguments": "",
|
||||
"type": None
|
||||
}
|
||||
|
||||
# First chunk should have id, name, and type
|
||||
if tool_call.id:
|
||||
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"
|
||||
Reference in New Issue
Block a user