# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project

import json
from collections.abc import Generator

import pytest
from openai.types.responses.function_tool import FunctionTool
from xgrammar import StructuralTag

from vllm.entrypoints.openai.chat_completion.protocol import (
    ChatCompletionNamedFunction,
    ChatCompletionNamedToolChoiceParam,
    ChatCompletionRequest,
    ChatCompletionToolsParam,
)
from vllm.entrypoints.openai.engine.protocol import (
    DeltaMessage,
    FunctionCall,
    ToolCall,
)
from vllm.tokenizers import TokenizerLike, get_tokenizer
from vllm.tokenizers.detokenizer_utils import detokenize_incrementally
from vllm.tool_parsers.qwen3coder_tool_parser import (
    Qwen3CoderToolParser,
)
from vllm.tool_parsers.qwen3xml_tool_parser import Qwen3XMLToolParser

MODEL = "Qwen/Qwen3-Coder-30B-A3B-Instruct-FP8"


@pytest.fixture(scope="module")
def qwen3_tokenizer():
    return get_tokenizer(tokenizer_name=MODEL)


@pytest.fixture
def qwen3_tool_parser(qwen3_tokenizer, sample_tools):
    return Qwen3CoderToolParser(qwen3_tokenizer, tools=sample_tools)


@pytest.fixture
def qwen3_xml_tool_parser(qwen3_tokenizer, sample_tools):
    return Qwen3XMLToolParser(qwen3_tokenizer, tools=sample_tools)


@pytest.fixture(params=["xml"])
def qwen3_tool_parser_parametrized(qwen3_tool_parser, qwen3_xml_tool_parser, request):
    """Parameterized fixture that provides both parser types for testing"""
    if request.param == "original":
        return qwen3_tool_parser
    else:
        return qwen3_xml_tool_parser


WEATHER_PARAMS = {
    "type": "object",
    "properties": {
        "city": {"type": "string", "description": "The city name"},
        "state": {"type": "string", "description": "The state code"},
        "unit": {"type": "string", "enum": ["fahrenheit", "celsius"]},
    },
    "required": ["city", "state"],
}

AREA_PARAMS = {
    "type": "object",
    "properties": {
        "shape": {"type": "string"},
        "dimensions": {"type": "object"},
        "precision": {"type": "integer"},
    },
}


@pytest.fixture(params=["chat_completion", "responses_api"])
def sample_tools(request):
    if request.param == "chat_completion":
        return [
            ChatCompletionToolsParam(
                type="function",
                function={
                    "name": "get_current_weather",
                    "description": "Get the current weather",
                    "parameters": WEATHER_PARAMS,
                },
            ),
            ChatCompletionToolsParam(
                type="function",
                function={
                    "name": "calculate_area",
                    "description": "Calculate area of a shape",
                    "parameters": AREA_PARAMS,
                },
            ),
        ]
    else:
        return [
            FunctionTool(
                type="function",
                name="get_current_weather",
                description="Get the current weather",
                parameters=WEATHER_PARAMS,
            ),
            FunctionTool(
                type="function",
                name="calculate_area",
                description="Calculate area of a shape",
                parameters=AREA_PARAMS,
            ),
        ]


def _as_chat_completion_tools(
    tools: list[ChatCompletionToolsParam | FunctionTool],
) -> list[ChatCompletionToolsParam]:
    normalized: list[ChatCompletionToolsParam] = []
    for tool in tools:
        if isinstance(tool, ChatCompletionToolsParam):
            normalized.append(tool)
        else:
            normalized.append(
                ChatCompletionToolsParam(
                    type="function",
                    function={
                        "name": tool.name,
                        "description": tool.description,
                        "parameters": tool.parameters,
                    },
                )
            )
    return normalized


def assert_tool_calls(
    actual_tool_calls: list[ToolCall], expected_tool_calls: list[ToolCall]
):
    assert len(actual_tool_calls) == len(expected_tool_calls)

    for actual_tool_call, expected_tool_call in zip(
        actual_tool_calls, expected_tool_calls
    ):
        # Qwen3 parser doesn't generate IDs during extraction
        assert actual_tool_call.type == "function"
        assert actual_tool_call.function.name == expected_tool_call.function.name
        assert json.loads(actual_tool_call.function.arguments) == json.loads(
            expected_tool_call.function.arguments
        )


def stream_delta_message_generator(
    qwen3_tool_parser,
    qwen3_tokenizer: TokenizerLike,
    model_output: str,
    request: ChatCompletionRequest | None = None,
) -> Generator[DeltaMessage, None, None]:
    all_token_ids = qwen3_tokenizer.encode(model_output, add_special_tokens=False)

    previous_text = ""
    previous_tokens = None
    prefix_offset = 0
    read_offset = 0
    for i, delta_token in enumerate(all_token_ids):
        delta_token_ids = [delta_token]
        previous_token_ids = all_token_ids[:i]
        current_token_ids = all_token_ids[: i + 1]

        (new_tokens, delta_text, new_prefix_offset, new_read_offset) = (
            detokenize_incrementally(
                tokenizer=qwen3_tokenizer,
                all_input_ids=current_token_ids,
                prev_tokens=previous_tokens,
                prefix_offset=prefix_offset,
                read_offset=read_offset,
                skip_special_tokens=False,
                spaces_between_special_tokens=True,
            )
        )

        current_text = previous_text + delta_text

        delta_message = qwen3_tool_parser.extract_tool_calls_streaming(
            previous_text,
            current_text,
            delta_text,
            previous_token_ids,
            current_token_ids,
            delta_token_ids,
            request=request,
        )
        if delta_message:
            yield delta_message

        previous_text = current_text
        previous_tokens = (
            previous_tokens + new_tokens if previous_tokens else new_tokens
        )
        prefix_offset = new_prefix_offset
        read_offset = new_read_offset


def test_extract_tool_calls_no_tools(qwen3_tool_parser_parametrized):
    model_output = "This is a test response without any tool calls"
    extracted_tool_calls = qwen3_tool_parser_parametrized.extract_tool_calls(
        model_output, request=None
    )  # type: ignore[arg-type]
    assert not extracted_tool_calls.tools_called
    assert extracted_tool_calls.tool_calls == []
    assert extracted_tool_calls.content == model_output


@pytest.mark.parametrize(
    ids=[
        "single_tool",
        "single_tool_with_content",
        "single_tool_multiline_param",
        "parallel_tools",
        "tool_with_typed_params",
    ],
    argnames=["model_output", "expected_tool_calls", "expected_content"],
    argvalues=[
        (
            """<tool_call>
<function=get_current_weather>
<parameter=city>
Dallas
</parameter>
<parameter=state>
TX
</parameter>
<parameter=unit>
fahrenheit
</parameter>
</function>
</tool_call>""",
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}
                        ),
                    )
                )
            ],
            None,
        ),
        (
            """Sure! Let me check the weather for you.<tool_call>
<function=get_current_weather>
<parameter=city>
Dallas
</parameter>
<parameter=state>
TX
</parameter>
<parameter=unit>
fahrenheit
</parameter>
</function>
</tool_call>""",
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}
                        ),
                    )
                )
            ],
            "Sure! Let me check the weather for you.",
        ),
        (
            """<tool_call>
<function=calculate_area>
<parameter=shape>
rectangle
</parameter>
<parameter=dimensions>
{"width": 10, 
 "height": 20}
</parameter>
<parameter=precision>
2
</parameter>
</function>
</tool_call>""",
            [
                ToolCall(
                    function=FunctionCall(
                        name="calculate_area",
                        arguments=json.dumps(
                            {
                                "shape": "rectangle",
                                "dimensions": {"width": 10, "height": 20},
                                "precision": 2,
                            }
                        ),
                    )
                )
            ],
            None,
        ),
        (
            """<tool_call>
<function=get_current_weather>
<parameter=city>
Dallas
</parameter>
<parameter=state>
TX
</parameter>
<parameter=unit>
fahrenheit
</parameter>
</function>
</tool_call>
<tool_call>
<function=get_current_weather>
<parameter=city>
Orlando
</parameter>
<parameter=state>
FL
</parameter>
<parameter=unit>
fahrenheit
</parameter>
</function>
</tool_call>""",
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}
                        ),
                    )
                ),
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "Orlando", "state": "FL", "unit": "fahrenheit"}
                        ),
                    )
                ),
            ],
            None,
        ),
        (
            """Let me calculate that area for you.<tool_call>
<function=calculate_area>
<parameter=shape>
circle
</parameter>
<parameter=dimensions>
{"radius": 15.5}
</parameter>
<parameter=precision>
3
</parameter>
</function>
</tool_call>""",
            [
                ToolCall(
                    function=FunctionCall(
                        name="calculate_area",
                        arguments=json.dumps(
                            {
                                "shape": "circle",
                                "dimensions": {"radius": 15.5},
                                "precision": 3,
                            }
                        ),
                    )
                )
            ],
            "Let me calculate that area for you.",
        ),
    ],
)
def test_extract_tool_calls(
    qwen3_tool_parser_parametrized,
    model_output,
    expected_tool_calls,
    expected_content,
):
    request = ChatCompletionRequest(model=MODEL, messages=[])
    extracted_tool_calls = qwen3_tool_parser_parametrized.extract_tool_calls(
        model_output, request=request
    )
    assert extracted_tool_calls.tools_called

    assert_tool_calls(extracted_tool_calls.tool_calls, expected_tool_calls)

    assert extracted_tool_calls.content == expected_content


def test_extract_tool_calls_fallback_no_tags(
    qwen3_tool_parser_parametrized,
):
    """Test fallback parsing when XML tags are missing"""
    model_output = """<function=get_current_weather>
<parameter=city>
Dallas
</parameter>
<parameter=state>
TX
</parameter>
</function>"""

    request = ChatCompletionRequest(model=MODEL, messages=[])
    extracted_tool_calls = qwen3_tool_parser_parametrized.extract_tool_calls(
        model_output, request=request
    )

    assert extracted_tool_calls.tools_called
    assert len(extracted_tool_calls.tool_calls) == 1
    assert extracted_tool_calls.tool_calls[0].function.name == "get_current_weather"


def test_extract_tool_calls_type_conversion(qwen3_tokenizer):
    """Test parameter type conversion based on tool schema"""
    tools = [
        ChatCompletionToolsParam(
            type="function",
            function={
                "name": "test_types",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "int_param": {"type": "integer"},
                        "float_param": {"type": "float"},
                        "bool_param": {"type": "boolean"},
                        "str_param": {"type": "string"},
                        "obj_param": {"type": "object"},
                    },
                },
            },
        )
    ]

    model_output = """<tool_call>
<function=test_types>
<parameter=int_param>
42
</parameter>
<parameter=float_param>
3.14
</parameter>
<parameter=bool_param>
true
</parameter>
<parameter=str_param>
hello world
</parameter>
<parameter=obj_param>
{"key": "value"}
</parameter>
</function>
</tool_call>"""

    parser = Qwen3XMLToolParser(qwen3_tokenizer, tools=tools)
    request = ChatCompletionRequest(model=MODEL, messages=[], tools=tools)
    extracted_tool_calls = parser.extract_tool_calls(model_output, request=request)

    args = json.loads(extracted_tool_calls.tool_calls[0].function.arguments)
    assert args["int_param"] == 42
    assert args["float_param"] == 3.14
    assert args["bool_param"] is True
    assert args["str_param"] == "hello world"
    assert args["obj_param"] == {"key": "value"}


@pytest.mark.parametrize(
    ids=[
        "no_tools",
        "single_tool",
        "single_tool_with_content",
        "single_tool_multiline_param",
        "parallel_tools",
        "tool_with_typed_params",  # Added this test case
    ],
    argnames=["model_output", "expected_tool_calls", "expected_content"],
    argvalues=[
        ("This is a test without tools", [], "This is a test without tools"),
        (
            """<tool_call>
<function=get_current_weather>
<parameter=city>
Dallas
</parameter>
<parameter=state>
TX
</parameter>
<parameter=unit>
fahrenheit
</parameter>
</function>
</tool_call>""",
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}
                        ),
                    )
                )
            ],
            None,
        ),
        (
            """Sure! Let me check the weather for you.<tool_call>
<function=get_current_weather>
<parameter=city>
Dallas
</parameter>
<parameter=state>
TX
</parameter>
<parameter=unit>
fahrenheit
</parameter>
</function>
</tool_call>""",
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}
                        ),
                    )
                )
            ],
            "Sure! Let me check the weather for you.",
        ),
        (
            """<tool_call>
<function=calculate_area>
<parameter=shape>
rectangle
</parameter>
<parameter=dimensions>
{"width": 10, 
 "height": 20}
</parameter>
<parameter=precision>
2
</parameter>
</function>
</tool_call>""",
            [
                ToolCall(
                    function=FunctionCall(
                        name="calculate_area",
                        arguments=json.dumps(
                            {
                                "shape": "rectangle",
                                "dimensions": {"width": 10, "height": 20},
                                "precision": 2,
                            }
                        ),
                    )
                )
            ],
            None,
        ),
        (
            """<tool_call>
<function=get_current_weather>
<parameter=city>
Dallas
</parameter>
<parameter=state>
TX
</parameter>
<parameter=unit>
fahrenheit
</parameter>
</function>
</tool_call>
<tool_call>
<function=get_current_weather>
<parameter=city>
Orlando
</parameter>
<parameter=state>
FL
</parameter>
<parameter=unit>
celsius
</parameter>
</function>
</tool_call>""",
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "Dallas", "state": "TX", "unit": "fahrenheit"}
                        ),
                    )
                ),
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "Orlando", "state": "FL", "unit": "celsius"}
                        ),
                    )
                ),
            ],
            None,
        ),
        # Added tool_with_typed_params test case
        (
            """Let me calculate that area for you.<tool_call>
<function=calculate_area>
<parameter=shape>
circle
</parameter>
<parameter=dimensions>
{"radius": 15.5}
</parameter>
<parameter=precision>
3
</parameter>
</function>
</tool_call>""",
            [
                ToolCall(
                    function=FunctionCall(
                        name="calculate_area",
                        arguments=json.dumps(
                            {
                                "shape": "circle",
                                "dimensions": {"radius": 15.5},
                                "precision": 3,
                            }
                        ),
                    )
                )
            ],
            "Let me calculate that area for you.",
        ),
    ],
)
def test_extract_tool_calls_streaming(
    qwen3_tool_parser_parametrized,
    qwen3_tokenizer,
    model_output,
    expected_tool_calls,
    expected_content,
):
    """Test incremental streaming behavior including typed parameters"""
    request = ChatCompletionRequest(model=MODEL, messages=[])

    other_content = ""
    tool_states = {}  # Track state per tool index

    for delta_message in stream_delta_message_generator(
        qwen3_tool_parser_parametrized, qwen3_tokenizer, model_output, request
    ):
        # role should never be streamed from tool parser
        assert not delta_message.role

        if delta_message.content:
            other_content += delta_message.content

        if delta_message.tool_calls:
            for tool_call in delta_message.tool_calls:
                idx = tool_call.index

                # Initialize state for new tool
                if idx not in tool_states:
                    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 or "")  # Handle None case

    # Verify we got all expected tool calls
    assert len(tool_states) == len(expected_tool_calls)
    assert len(qwen3_tool_parser_parametrized.prev_tool_call_arr) == 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_missing_closing_parameter_tag(
    qwen3_tool_parser_parametrized,
):
    """Test handling of missing closing </parameter> tag"""
    # Using get_current_weather from sample_tools but with malformed XML
    model_output = """Let me check the weather for you:
<tool_call>
<function=get_current_weather>
<parameter=city>
Dallas
<parameter=state>
TX
</parameter>
<parameter=unit>
fahrenheit
</parameter>
</function>
</tool_call>"""

    request = ChatCompletionRequest(model=MODEL, messages=[])
    extracted_tool_calls = qwen3_tool_parser_parametrized.extract_tool_calls(
        model_output, request=request
    )

    # The parser should handle the malformed XML gracefully
    assert extracted_tool_calls.tools_called
    assert len(extracted_tool_calls.tool_calls) == 1

    # Verify the function name is correct
    assert extracted_tool_calls.tool_calls[0].function.name == "get_current_weather"

    # Verify the arguments are parsed despite the missing closing tag
    args = json.loads(extracted_tool_calls.tool_calls[0].function.arguments)
    assert "city" in args
    assert args["city"] == "Dallas"
    assert args["state"] == "TX"
    assert args["unit"] == "fahrenheit"

    # Check that content before the tool call is preserved
    assert "Let me check the weather for you:" in extracted_tool_calls.content


def test_extract_tool_calls_streaming_missing_closing_tag(
    qwen3_tool_parser_parametrized, qwen3_tokenizer
):
    """Test streaming with missing closing </parameter> tag"""
    # Using get_current_weather from sample_tools but with malformed XML
    model_output = """Let me check the weather for you:
<tool_call>
<function=get_current_weather>
<parameter=city>
Dallas
<parameter=state>
TX
</parameter>
<parameter=unit>
fahrenheit
</parameter>
</function>
</tool_call>"""

    request = ChatCompletionRequest(model=MODEL, messages=[])

    other_content = ""
    tool_states = {}

    for delta_message in stream_delta_message_generator(
        qwen3_tool_parser_parametrized, qwen3_tokenizer, model_output, request
    ):
        if delta_message.content:
            other_content += delta_message.content

        if delta_message.tool_calls:
            for tool_call in delta_message.tool_calls:
                idx = tool_call.index

                if idx not in tool_states:
                    tool_states[idx] = {
                        "id": None,
                        "name": None,
                        "arguments": "",
                        "type": None,
                    }

                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:
                        tool_states[idx]["name"] = tool_call.function.name

                    if tool_call.function.arguments is not None:
                        tool_states[idx]["arguments"] += tool_call.function.arguments

    # Verify content was streamed
    assert "Let me check the weather for you:" in other_content
    # Verify we got the tool call
    assert len(tool_states) == 1
    assert len(qwen3_tool_parser_parametrized.prev_tool_call_arr) == 1

    state = tool_states[0]
    assert state["id"] is not None
    assert state["type"] == "function"
    assert state["name"] == "get_current_weather"

    # Verify arguments were parsed correctly despite missing closing tag
    assert state["arguments"] is not None
    args = json.loads(state["arguments"])
    assert args["city"] == "Dallas"
    assert args["state"] == "TX"
    assert args["unit"] == "fahrenheit"


def test_extract_tool_calls_streaming_incremental(
    qwen3_tool_parser_parametrized, qwen3_tokenizer
):
    """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=[])

    chunks = []
    for delta_message in stream_delta_message_generator(
        qwen3_tool_parser_parametrized, 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"


def test_extract_tool_calls_complex_type_with_single_quote(
    qwen3_tokenizer,
):
    """Test parameter type conversion based on tool schema"""
    tools = [
        ChatCompletionToolsParam(
            type="function",
            function={
                "name": "test_types",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "int_param": {"type": "integer"},
                        "float_param": {"type": "float"},
                        "bool_param": {"type": "boolean"},
                        "str_param": {"type": "string"},
                        "obj_param": {"type": "object"},
                    },
                },
            },
        )
    ]

    model_output = """<tool_call>
<function=test_types>
<parameter=obj_param>
{'key': 'value'}
</parameter>
</function>
</tool_call>"""

    parser = Qwen3XMLToolParser(qwen3_tokenizer, tools=tools)
    request = ChatCompletionRequest(model=MODEL, messages=[], tools=tools)
    extracted_tool_calls = parser.extract_tool_calls(model_output, request=request)

    args = json.loads(extracted_tool_calls.tool_calls[0].function.arguments)
    assert args["obj_param"] == {"key": "value"}


def test_extract_tool_calls_streaming_missing_opening_tag(
    qwen3_tool_parser_parametrized, qwen3_tokenizer
):
    """Test streaming with missing opening <tool_call> tag

    This tests that the streaming parser correctly handles
    tool calls that start directly with <function=...>
    """
    model_output = """I'll check the weather for you.

<function=get_current_weather>
<parameter=city>
Dallas
</parameter>
<parameter=state>
TX
</parameter>
<parameter=unit>
fahrenheit
</parameter>
</function>
</tool_call>"""

    request = ChatCompletionRequest(model=MODEL, messages=[])

    other_content = ""
    tool_states = {}

    for delta_message in stream_delta_message_generator(
        qwen3_tool_parser_parametrized, qwen3_tokenizer, model_output, request
    ):
        if delta_message.content:
            other_content += delta_message.content

        if delta_message.tool_calls:
            for tool_call in delta_message.tool_calls:
                idx = tool_call.index

                if idx not in tool_states:
                    tool_states[idx] = {
                        "id": None,
                        "name": None,
                        "arguments": "",
                        "type": None,
                    }

                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:
                        tool_states[idx]["name"] = tool_call.function.name

                    if tool_call.function.arguments is not None:
                        tool_states[idx]["arguments"] += tool_call.function.arguments

    # Verify content was streamed
    assert "I'll check the weather for you." in other_content

    # Verify we got the tool call
    assert len(tool_states) == 1
    assert len(qwen3_tool_parser_parametrized.prev_tool_call_arr) == 1

    state = tool_states[0]
    assert state["id"] is not None
    assert state["type"] == "function"
    assert state["name"] == "get_current_weather"

    # Verify arguments were parsed correctly despite missing opening tag
    assert state["arguments"] is not None
    args = json.loads(state["arguments"])
    assert args["city"] == "Dallas"
    assert args["state"] == "TX"
    assert args["unit"] == "fahrenheit"


def test_malformed_xml_no_gt_delimiter(qwen3_tool_parser):
    """Regression: malformed XML without '>' must not crash (PR #36774)."""
    model_output = (
        "<tool_call>\n"
        "<function=get_current_weather\n"
        "<parameter=city>Dallas</parameter>\n"
        "</function>\n"
        "</tool_call>"
    )

    request = ChatCompletionRequest(model=MODEL, messages=[])
    result = qwen3_tool_parser.extract_tool_calls(model_output, request=request)
    assert result is not None
    assert isinstance(result.tool_calls, list)
    assert all(tc is not None for tc in result.tool_calls)


def test_none_tool_calls_filtered(qwen3_tool_parser):
    """Regression: None tool calls filtered from output (PR #36774)."""
    model_output = (
        "<tool_call>\n"
        "<function=bad_func_no_gt\n"
        "</function>\n"
        "</tool_call>\n"
        "<tool_call>\n"
        "<function=get_current_weather>\n"
        "<parameter=city>Dallas</parameter>\n"
        "<parameter=state>TX</parameter>\n"
        "</function>\n"
        "</tool_call>"
    )

    request = ChatCompletionRequest(model=MODEL, messages=[])
    result = qwen3_tool_parser.extract_tool_calls(model_output, request=request)
    assert all(tc is not None for tc in result.tool_calls)
    assert result.tools_called
    assert len(result.tool_calls) == 1
    assert result.tool_calls[0].function.name == "get_current_weather"
    args = json.loads(result.tool_calls[0].function.arguments)
    assert args["city"] == "Dallas"
    assert args["state"] == "TX"


def test_anyof_parameter_not_double_encoded(qwen3_tokenizer):
    """Regression: anyOf parameters must not be double-encoded (PR #36032)."""
    tools = [
        ChatCompletionToolsParam(
            type="function",
            function={
                "name": "update_record",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "data": {
                            "anyOf": [{"type": "object"}, {"type": "null"}],
                        },
                    },
                },
            },
        )
    ]

    parser = Qwen3CoderToolParser(qwen3_tokenizer, tools=tools)

    model_output = (
        "<tool_call>\n"
        "<function=update_record>\n"
        '<parameter=data>{"key": "value", "count": 42}</parameter>\n'
        "</function>\n"
        "</tool_call>"
    )

    request = ChatCompletionRequest(model=MODEL, messages=[], tools=tools)
    result = parser.extract_tool_calls(model_output, request=request)

    assert result.tools_called
    assert len(result.tool_calls) == 1
    args = json.loads(result.tool_calls[0].function.arguments)
    assert isinstance(args["data"], dict)
    assert args["data"] == {"key": "value", "count": 42}


def test_streaming_multi_param_single_chunk(qwen3_tool_parser, qwen3_tokenizer):
    """Regression: speculative decode delivering multiple params at once (PR #35615)."""
    request = ChatCompletionRequest(model=MODEL, messages=[])

    deltas = [
        "<tool_call>",
        "\n<function=get_current_weather>",
        "\n",  # triggers json_started -> sends "{"
        # This single delta delivers all three parameters at once
        "<parameter=city>\nDallas\n</parameter>"
        "\n<parameter=state>\nTX\n</parameter>"
        "\n<parameter=unit>\nfahrenheit\n</parameter>",
        "\n</function>",
        "\n</tool_call>",
    ]

    from tests.tool_parsers.utils import (
        run_tool_extraction_streaming,
    )

    reconstructor = run_tool_extraction_streaming(
        qwen3_tool_parser,
        deltas,
        request,
        assert_one_tool_per_delta=False,
    )

    assert len(reconstructor.tool_calls) == 1
    args = json.loads(reconstructor.tool_calls[0].function.arguments)
    assert args["city"] == "Dallas"
    assert args["state"] == "TX"
    assert args["unit"] == "fahrenheit"


def test_no_double_serialization_string_args(qwen3_tool_parser):
    """Regression: string arguments must not be double-serialized (PR #35615)."""
    tools = [
        ChatCompletionToolsParam(
            type="function",
            function={
                "name": "greet",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "message": {"type": "string"},
                    },
                },
            },
        )
    ]

    model_output = (
        "<tool_call>\n"
        "<function=greet>\n"
        "<parameter=message>hello world</parameter>\n"
        "</function>\n"
        "</tool_call>"
    )

    request = ChatCompletionRequest(model=MODEL, messages=[], tools=tools)
    result = qwen3_tool_parser.extract_tool_calls(model_output, request=request)

    assert result.tools_called
    assert len(result.tool_calls) == 1
    raw_arguments = result.tool_calls[0].function.arguments
    args = json.loads(raw_arguments)
    assert args["message"] == "hello world"
    assert '\\"hello world\\"' not in raw_arguments


def test_get_vllm_registry_structural_tag_returns_structural_tag(
    qwen3_tool_parser: Qwen3CoderToolParser,
    sample_tools: list[ChatCompletionToolsParam],
) -> None:
    request_tools = _as_chat_completion_tools(sample_tools)
    req = ChatCompletionRequest(
        messages=[],
        model="m",
        tools=request_tools,
        tool_choice="auto",
    )
    tag = qwen3_tool_parser.get_structural_tag(req)
    assert isinstance(tag, StructuralTag)

    req = ChatCompletionRequest(
        messages=[],
        model="m",
        tools=request_tools,
        tool_choice="required",
    )
    tag = qwen3_tool_parser.get_structural_tag(req)
    assert isinstance(tag, StructuralTag)

    if request_tools:
        tool = request_tools[0]
        req = ChatCompletionRequest(
            messages=[],
            model="m",
            tools=request_tools,
        )
        req.tool_choice = ChatCompletionNamedToolChoiceParam(
            function=ChatCompletionNamedFunction(name=tool.function.name)
        )
        tag = qwen3_tool_parser.get_structural_tag(req)
        assert isinstance(tag, StructuralTag)


@pytest.mark.parametrize("include_reasoning", [True, False])
def test_adjust_request_auto_uses_vllm_registry_structural_tag(
    monkeypatch: pytest.MonkeyPatch,
    qwen3_tool_parser: Qwen3CoderToolParser,
    sample_tools: list[ChatCompletionToolsParam],
    include_reasoning: bool,
) -> None:
    monkeypatch.setattr(
        "vllm.tool_parsers.abstract_tool_parser.VLLM_ENFORCE_STRICT_TOOL_CALLING",
        True,
    )
    request_tools = _as_chat_completion_tools(sample_tools)
    req = ChatCompletionRequest(
        messages=[],
        model="m",
        tools=request_tools,
        tool_choice="auto",
        include_reasoning=include_reasoning,
    )
    out = qwen3_tool_parser.adjust_request(req)
    assert out.structured_outputs is not None
    assert out.structured_outputs.structural_tag is not None
    assert isinstance(out.structured_outputs.structural_tag, str)
    loaded = json.loads(out.structured_outputs.structural_tag)
    assert isinstance(loaded, dict)


def test_adjust_request_required_prefers_structural_tag(
    monkeypatch: pytest.MonkeyPatch,
    qwen3_tool_parser: Qwen3CoderToolParser,
    sample_tools: list[ChatCompletionToolsParam],
) -> None:
    monkeypatch.setattr(
        "vllm.tool_parsers.abstract_tool_parser.VLLM_ENFORCE_STRICT_TOOL_CALLING",
        True,
    )
    request_tools = _as_chat_completion_tools(sample_tools)
    req = ChatCompletionRequest(
        messages=[],
        model="m",
        tools=request_tools,
        tool_choice="required",
    )
    out = qwen3_tool_parser.adjust_request(req)
    assert out.structured_outputs is not None
    assert out.structured_outputs.structural_tag is not None
