vLLM/tests/parser/mistral/test_tool_calls.py

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

import json
from collections.abc import Generator
from unittest.mock import MagicMock, patch

import partial_json_parser
import pytest
import regex as re
from mistral_common.protocol.instruct.messages import AssistantMessage
from mistral_common.protocol.instruct.request import InstructRequest
from mistral_common.protocol.instruct.tool_calls import (
    FunctionCall,
    ToolCall,
)
from mistral_common.protocol.instruct.tool_calls import (
    NamedToolChoice as MistralNamedToolChoice,
)
from mistral_common.protocol.instruct.tool_calls import (
    ToolChoice as MistralToolChoice,
)
from mistral_common.protocol.instruct.tool_calls import (
    ToolChoiceEnum as MistralToolChoiceEnum,
)
from partial_json_parser.core.options import Allow

from vllm.entrypoints.generate.base.protocol import (
    DeltaFunctionCall,
    DeltaMessage,
    DeltaToolCall,
    ExtractedToolCallInformation,
    StructuralTagResponseFormat,
)
from vllm.entrypoints.openai.chat_completion.protocol import (
    ChatCompletionRequest,
)
from vllm.parser.engine.events import EventType
from vllm.parser.engine.streaming_parser_engine import StreamingParserEngine
from vllm.parser.mistral import _DEFAULT_JSON_SCHEMA, MistralParser, mistral_config
from vllm.parser.parser_manager import ParserManager
from vllm.sampling_params import StructuredOutputsParams
from vllm.tokenizers import TokenizerLike, get_tokenizer
from vllm.tokenizers.detokenizer_utils import detokenize_incrementally
from vllm.tokenizers.mistral import MistralTokenizer
from vllm.tool_parsers.mistral_tool_parser import MistralToolParser

_DUMMY_REQUEST = ChatCompletionRequest(messages=[], model="test")
# Minimal request for the engine driver: tool_choice=None falls through to
# auto extraction without triggering "tools must be set" validation.
_ENGINE_REQUEST = ChatCompletionRequest(messages=[], model="test", tool_choice=None)


@pytest.fixture(scope="module")
def mistral_pre_v11_tokenizer():
    MODEL = "mistralai/Mistral-7B-Instruct-v0.3"
    return get_tokenizer(tokenizer_name=MODEL)


@pytest.fixture(scope="module")
def mistral_tokenizer():
    MODEL = "mistralai/Mistral-Small-3.2-24B-Instruct-2506"
    return get_tokenizer(tokenizer_name=MODEL, tokenizer_mode="mistral")


@pytest.fixture
def mistral_pre_v11_tool_parser(mistral_pre_v11_tokenizer):
    return MistralToolParser(mistral_pre_v11_tokenizer)


@pytest.fixture
def mistral_tool_parser(mistral_tokenizer):
    return MistralToolParser(mistral_tokenizer)


@pytest.fixture
def non_mistral_parser() -> MistralToolParser:
    mock_tokenizer = MagicMock()
    mock_tokenizer.get_vocab.return_value = {"[TOOL_CALLS]": 1}
    # Ensure the legacy (non-grammar) path is taken by MistralParser.
    mock_tokenizer.supports_grammar = False
    return MistralToolParser(mock_tokenizer)


def assert_tool_calls(
    actual_tool_calls: list[ToolCall] | list[DeltaToolCall],
    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
    ):
        assert isinstance(actual_tool_call.id, str)
        assert len(actual_tool_call.id) == 9

        if isinstance(actual_tool_call, ToolCall):
            assert actual_tool_call.type == "function"
        elif isinstance(actual_tool_call, DeltaToolCall):
            assert actual_tool_call.function is not None
            assert actual_tool_call.function.name is not None
            assert actual_tool_call.function.arguments is not None
        assert actual_tool_call.function is not None
        assert actual_tool_call.function.name == expected_tool_call.function.name, (
            f"got wrong function name:${actual_tool_call.function.name}"
        )
        actual_args = actual_tool_call.function.arguments
        # Streaming deltas (DeltaToolCall) may have partial JSON because the
        # engine holds back the final closing brace until finish() is called.
        # Apply partial_json_parser so the comparison works for both the
        # legacy (complete JSON) and engine (potentially partial) paths.
        if isinstance(actual_tool_call, DeltaToolCall) and actual_args is not None:
            actual_args = partial_json_parser.ensure_json(
                actual_args, Allow.OBJ | Allow.STR
            )
        assert actual_args == expected_tool_call.function.arguments, (
            f"got wrong function argument:${actual_tool_call.function.arguments}"
        )


def fix_tool_call_tokenization(
    tokens: list[int],
    mistral_tool_parser: MistralToolParser,
    mistral_tokenizer: TokenizerLike,
):
    """Replace textual token sequences for the control markers ([TOOL_CALLS]
    and [ARGS]) with their single special token IDs.

    Real generation emits these as control tokens; encoding the marker *string*
    can instead yield literal text tokens. The engine detects markers by id, so
    the test stream must carry the special ids.
    """
    vocab = mistral_tokenizer.get_vocab()
    markers: list[tuple[str, int]] = [
        (
            mistral_tool_parser._parser_engine.bot_token,
            mistral_tool_parser._parser_engine.bot_token_id,
        )
    ]
    args_id = vocab.get("[ARGS]")
    if args_id is not None:
        markers.append(("[ARGS]", args_id))

    # (textual token sequence, special id) pairs to replace.
    replacements: list[tuple[list[int], int]] = []
    for text, special_id in markers:
        if special_id is None:
            continue
        textual = mistral_tokenizer.encode(text=text, add_special_tokens=False)
        if textual:
            replacements.append((textual, special_id))

    result_tokens: list[int] = []
    i = 0
    while i < len(tokens):
        for textual, special_id in replacements:
            if tokens[i : i + len(textual)] == textual:
                result_tokens.append(special_id)
                i += len(textual)
                break
        else:
            result_tokens.append(tokens[i])
            i += 1

    return result_tokens


def encode_mistral_output(tokenizer: MistralTokenizer, text: str) -> list[int]:
    """Encode generated output with control markers as their special-token ids.

    Real generation emits ``[TOOL_CALLS]``/``[ARGS]`` as single control tokens.
    Encoding the marker *strings* can instead glue them to neighbours (e.g.
    ``}[``) and yield literal text tokens, which the id-based engine never sees.
    Split on the markers and insert their special ids so the token stream
    matches real generation.
    """
    vocab = tokenizer.get_vocab()
    marker_ids = {
        "[TOOL_CALLS]": vocab.get("[TOOL_CALLS]"),
        "[ARGS]": vocab.get("[ARGS]"),
    }
    ids: list[int] = []
    for part in re.split(r"(\[TOOL_CALLS\]|\[ARGS\])", text):
        if part in marker_ids:
            # Fall back to text encoding here and the id-based engine path
            # silently stops being exercised while the tests still pass.
            assert marker_ids[part] is not None, f"{part} missing from vocab"
            ids.append(marker_ids[part])
        elif part:
            ids.extend(tokenizer.encode(part, add_special_tokens=False))
    return ids


def stream_delta_message_generator(
    mistral_tool_parser: MistralToolParser,
    mistral_tokenizer: TokenizerLike,
    model_output: str | None,
    tools: list[tuple[str, str]] | None,
    chunk_size: int = 1,
    driver: str = "legacy",
    reasoning_parser: str | None = None,
) -> Generator[DeltaMessage, None, None]:
    if (
        isinstance(mistral_tokenizer, MistralTokenizer)
        and mistral_tokenizer.version >= 11
    ):
        # With the newer versions of the tokenizer,
        # we cannot tokenize free text
        # so we need to create a list of messages to get tokenized
        assert tools is not None
        assistant_msg = AssistantMessage(
            tool_calls=[
                ToolCall(
                    function=FunctionCall(
                        name=name,
                        arguments=arg,
                    )
                )
                for (name, arg) in tools
            ],
        )
        request = InstructRequest(
            messages=[assistant_msg],
        )
        all_token_ids = mistral_tokenizer.instruct.encode_instruct(request).tokens
    else:
        # Older versions of the tokenizer are
        # able to encode directly the model's output (free text) into tokens
        assert model_output is not None
        all_token_ids = mistral_tokenizer.encode(model_output, add_special_tokens=False)

    all_token_ids = fix_tool_call_tokenization(
        all_token_ids, mistral_tool_parser, mistral_tokenizer
    )

    if isinstance(mistral_tokenizer, MistralTokenizer):
        # Real serving streams only generated tokens; encode_instruct adds
        # framing (BOS/EOS) the parser never receives. Strip them so the
        # id-based engine detection sees a realistic stream.
        if all_token_ids and all_token_ids[0] == mistral_tokenizer.bos_token_id:
            all_token_ids = all_token_ids[1:]
        if all_token_ids and all_token_ids[-1] == mistral_tokenizer.eos_token_id:
            all_token_ids = all_token_ids[:-1]

    if driver == "engine":
        _parser_cls = ParserManager.get_parser(
            tool_parser_name="mistral",
            reasoning_parser_name=reasoning_parser,
            enable_auto_tools=True,
        )
        _engine_parser = _parser_cls(mistral_tokenizer, None)
        if reasoning_parser is not None:
            _req_with_tools = ChatCompletionRequest(
                messages=[],
                model="test",
                tools=SAMPLE_TOOLS_DICTS,
                tool_choice="auto",
            )
            _engine_req = _engine_parser.adjust_request(_req_with_tools)
        else:
            _engine_req = _ENGINE_REQUEST

    previous_text = ""
    previous_tokens = None
    prefix_offset = 0
    read_offset = 0
    pending_text = ""
    pending_token_ids: list[int] = []
    for i, delta_token in enumerate(all_token_ids):
        (new_tokens, delta_text, new_prefix_offset, new_read_offset) = (
            detokenize_incrementally(
                tokenizer=mistral_tokenizer,
                all_input_ids=all_token_ids[: i + 1],
                prev_tokens=previous_tokens,
                prefix_offset=prefix_offset,
                read_offset=read_offset,
                skip_special_tokens=isinstance(mistral_tokenizer, MistralTokenizer),
                spaces_between_special_tokens=True,
            )
        )
        previous_tokens = (
            previous_tokens + new_tokens if previous_tokens else new_tokens
        )
        prefix_offset = new_prefix_offset
        read_offset = new_read_offset

        # Buffer tokens so each streamed delta can carry ``chunk_size`` tokens,
        # reproducing the multi-token deltas produced by async scheduling /
        # stream_interval > 1.
        pending_text += delta_text
        pending_token_ids.append(delta_token)
        if len(pending_token_ids) < chunk_size and i != len(all_token_ids) - 1:
            continue

        previous_token_ids = all_token_ids[: i + 1 - len(pending_token_ids)]
        current_token_ids = all_token_ids[: i + 1]
        current_text = previous_text + pending_text

        if driver == "legacy":
            delta_message = mistral_tool_parser.extract_tool_calls_streaming(
                previous_text,
                current_text,
                pending_text,
                previous_token_ids,
                current_token_ids,
                pending_token_ids,
                request=_DUMMY_REQUEST,
            )
        else:  # engine: per-delta windows, mirroring parse_delta behaviour
            delta_message = _engine_parser.parse_delta(
                delta_text=pending_text,
                delta_token_ids=list(pending_token_ids),
                request=_engine_req,
                prompt_token_ids=[1],
                finished=(i == len(all_token_ids) - 1),
            )
        if delta_message:
            yield delta_message

        previous_text = current_text
        pending_text = ""
        pending_token_ids = []

    # For the legacy driver the engine holds back the final closing brace
    # in _args_buffer until finish_streaming() is called, mirroring how
    # the real serving layer flushes at end of stream.
    if driver == "legacy":
        flush_delta = mistral_tool_parser.finish_streaming()
        if flush_delta:
            yield flush_delta


@pytest.mark.parametrize(
    "parser_fixture",
    ["mistral_pre_v11_tool_parser", "mistral_tool_parser"],
    ids=["pre_v11", "v11"],
)
def test_extract_tool_calls_no_tools(parser_fixture, request):
    parser = request.getfixturevalue(parser_fixture)
    model_output = "This is a test"
    result = parser.extract_tool_calls(model_output, request=_DUMMY_REQUEST)
    assert result == ExtractedToolCallInformation(
        tools_called=False, tool_calls=[], content=model_output
    )


@pytest.mark.parametrize(
    ids=[
        "single_tool_add",
        "single_tool_weather",
        "argument_before_name",
        "argument_before_name_and_name_in_argument",
        "multiple_tools",
        "content_before_tool",
        "trailing_data_after_json",
    ],
    argnames=["model_output", "expected_tool_calls", "expected_content"],
    argvalues=[
        (
            """[TOOL_CALLS][{"name": "add", "arguments":{"a": 3.5, "b": 4}}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3.5, "b": 4})
                    )
                )
            ],
            None,
        ),
        (
            """[TOOL_CALLS] [{"name": "get_current_weather", "arguments":{"city": "San Francisco", "state": "CA", "unit": "celsius"}}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                )
            ],
            None,
        ),
        (
            """[TOOL_CALLS] [{"arguments":{"city": "San Francisco", "state": "CA", "unit": "celsius"}, "name": "get_current_weather"}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                )
            ],
            None,
        ),
        (
            """[TOOL_CALLS] [{"arguments":{"name": "John Doe"}, "name": "get_age"}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_age",
                        arguments=json.dumps(
                            {
                                "name": "John Doe",
                            }
                        ),
                    )
                )
            ],
            None,
        ),
        (
            """[TOOL_CALLS] [{"name": "add", "arguments": {"a": 3.5, "b": 4}}, {"name": "get_current_weather", "arguments":{"city": "San Francisco", "state": "CA", "unit": "celsius"}}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3.5, "b": 4})
                    )
                ),
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                ),
            ],
            None,
        ),
        (
            """Hello[TOOL_CALLS] [{"name": "add", "arguments":{"a": 1, "b": 2}}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 1, "b": 2})
                    )
                )
            ],
            "Hello",
        ),
        (
            """[TOOL_CALLS] [{"name": "get_current_weather", "arguments":{"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}]\nextra trailing data""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {
                                "city": "Dallas",
                                "state": "TX",
                                "unit": "fahrenheit",
                            }
                        ),
                    )
                )
            ],
            None,
        ),
    ],
)
def test_extract_tool_calls_pre_v11_tokenizer(
    mistral_pre_v11_tool_parser, model_output, expected_tool_calls, expected_content
):
    extracted_tool_calls = mistral_pre_v11_tool_parser.extract_tool_calls(
        model_output, request=_DUMMY_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_pre_v11_multiple_bot_tokens_raises(
    mistral_pre_v11_tool_parser,
):
    model_output = (
        '[TOOL_CALLS] [{"name": "add", "arguments":{"a": 1}}]'
        '[TOOL_CALLS] [{"name": "sub", "arguments":{"b": 2}}]'
    )
    with pytest.raises(ValueError, match="Only one BOT token"):
        mistral_pre_v11_tool_parser.extract_tool_calls(
            model_output, request=_DUMMY_REQUEST
        )


def test_extract_tool_calls_pre_v11_regex_fallback(
    mistral_pre_v11_tool_parser,
):
    """The regex fallback path finds valid JSON via regex when the primary
    raw_decode fails on leading junk. It should re-serialize arguments
    and return a valid tool call."""
    model_output = (
        '[TOOL_CALLS]  junk [{"name": "add", "arguments":{"a": 1, "b": 2}}] trail'
    )
    result = mistral_pre_v11_tool_parser.extract_tool_calls(
        model_output, request=_DUMMY_REQUEST
    )
    assert result.tools_called
    assert len(result.tool_calls) == 1
    assert result.tool_calls[0].function.name == "add"
    assert result.tool_calls[0].function.arguments == json.dumps({"a": 1, "b": 2})


def test_extract_tool_calls_pre_v11_regex_fallback_fails(
    mistral_pre_v11_tool_parser,
):
    model_output = "[TOOL_CALLS] not json at all"
    result = mistral_pre_v11_tool_parser.extract_tool_calls(
        model_output, request=_DUMMY_REQUEST
    )
    assert result == ExtractedToolCallInformation(
        tools_called=False, tool_calls=[], content="not json at all"
    )


@pytest.mark.parametrize(
    ids=[
        "single_tool_add",
        "single_tool_weather",
        "multiple_tool_calls",
        "single_tool_add_args",
        "single_tool_weather_args",
        "multiple_tool_calls_args",
        "content_before_tool_args",
        "complex",
        "wrong_json",
        "trailing_text_after_json",
        "trailing_text_after_args_json",
    ],
    argnames=["model_output", "expected_tool_calls", "expected_content"],
    argvalues=[
        (
            """[TOOL_CALLS]add_this_and_that{"a": 3.5, "b": 4}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add_this_and_that",
                        arguments=json.dumps({"a": 3.5, "b": 4}),
                    )
                )
            ],
            None,
        ),
        (
            """[TOOL_CALLS]get_current_weather{"city": "San Francisco", "state": "CA", "unit": "celsius"}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                )
            ],
            None,
        ),
        (
            """[TOOL_CALLS]add{"a": 3.5, "b": 4}[TOOL_CALLS]multiply{"a": 3, "b": 6}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3.5, "b": 4})
                    )
                ),
                ToolCall(
                    function=FunctionCall(
                        name="multiply", arguments=json.dumps({"a": 3, "b": 6})
                    )
                ),
            ],
            None,
        ),
        (
            # v11+ emits an explicit [ARGS] separator between name and args.
            """[TOOL_CALLS]add_this_and_that[ARGS]{"a": 3.5, "b": 4}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add_this_and_that",
                        arguments=json.dumps({"a": 3.5, "b": 4}),
                    )
                )
            ],
            None,
        ),
        (
            """[TOOL_CALLS]get_current_weather[ARGS]{"city": "San Francisco", "state": "CA", "unit": "celsius"}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                )
            ],
            None,
        ),
        (
            """[TOOL_CALLS]add[ARGS]{"a": 3.5, "b": 4}[TOOL_CALLS]multiply[ARGS]{"a": 3, "b": 6}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3.5, "b": 4})
                    )
                ),
                ToolCall(
                    function=FunctionCall(
                        name="multiply", arguments=json.dumps({"a": 3, "b": 6})
                    )
                ),
            ],
            None,
        ),
        (
            """hi[TOOL_CALLS]add[ARGS]{"a": 1, "b": 2}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 1, "b": 2})
                    )
                )
            ],
            "hi",
        ),
        (
            # Complex
            """hi{hi[TOOL_CALLS]bash{"command": "print(\\"hello world!\\")\\nre.compile(r\'{}\')""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="bash",
                        arguments=json.dumps(
                            {"command": "print(\"hello world!\")\nre.compile(r'{}')"}
                        )[:-2],
                    )
                )
            ],
            "hi{hi",
        ),
        (
            # Wrong json
            """hi{hi[TOOL_CALLS]bash{"command": "print(\\"hello world!\\")\\nre.compile(r\'{}\')"}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="bash",
                        arguments=json.dumps(
                            {"command": "print(\"hello world!\")\nre.compile(r'{}')"}
                        ),
                    )
                )
            ],
            "hi{hi",
        ),
        (
            # gh#48975: trailing text after the JSON object must not leak into
            # arguments (v11+ name{args} format has no terminator).
            """[TOOL_CALLS]get_current_weather{"city": "San Francisco"}Estimating the weather...""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps({"city": "San Francisco"}),
                    )
                )
            ],
            None,
        ),
        (
            # gh#48975 with the explicit [ARGS] separator.
            """[TOOL_CALLS]get_current_weather[ARGS]{"city": "San Francisco"}Estimating the weather...""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps({"city": "San Francisco"}),
                    )
                )
            ],
            None,
        ),
    ],
)
def test_extract_tool_calls(
    mistral_tool_parser, model_output, expected_tool_calls, expected_content
):
    extracted_tool_calls = mistral_tool_parser.extract_tool_calls(
        model_output, request=_DUMMY_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_v11_without_args_skipped(mistral_tool_parser):
    # Before Stage 2: the legacy path skipped tool calls with no arg separator,
    # returning tools_called=True with an empty list.  After Stage 2 the engine
    # path is used for v11; it recognises the name and emits a tool call with
    # empty arguments ("{}").  The semantic result is equivalent — a valid zero-
    # argument call — and is strictly more correct than silently dropping it.
    model_output = "[TOOL_CALLS]toolname_no_args"
    result = mistral_tool_parser.extract_tool_calls(
        model_output, request=_DUMMY_REQUEST
    )
    assert result.tools_called
    assert len(result.tool_calls) == 1
    assert result.tool_calls[0].function.name == "toolname_no_args"
    assert result.tool_calls[0].function.arguments == "{}"
    assert result.content is None


def test_extract_tool_calls_malformed_name_before_marker_emits_empty_name(
    mistral_tool_parser,
):
    model_output = 'bash[TOOL_CALLS]{"command": "cat file.py"}'
    result = mistral_tool_parser.extract_tool_calls(
        model_output, request=_DUMMY_REQUEST
    )
    assert result.tools_called
    assert len(result.tool_calls) == 1
    assert result.tool_calls[0].function.name == ""
    assert result.tool_calls[0].function.arguments == json.dumps(
        {"command": "cat file.py"}
    )
    assert result.content == "bash"


def test_extract_tool_calls_well_formed_name_unaffected(mistral_tool_parser):
    model_output = '[TOOL_CALLS]bash[ARGS]{"command": "ls -la"}'
    result = mistral_tool_parser.extract_tool_calls(
        model_output, request=_DUMMY_REQUEST
    )
    assert result.tools_called
    assert len(result.tool_calls) == 1
    assert result.tool_calls[0].function.name == "bash"
    assert result.tool_calls[0].function.arguments == json.dumps({"command": "ls -la"})
    assert result.content is None


def test_extract_tool_calls_empty_name_unparsable_args_no_crash(
    mistral_tool_parser,
):
    # Empty name AND args that never form valid JSON: still emitted (raw
    # text as arguments) instead of raising.
    model_output = "bash[TOOL_CALLS]{not valid json at all"
    result = mistral_tool_parser.extract_tool_calls(
        model_output, request=_DUMMY_REQUEST
    )
    assert result.tools_called
    assert len(result.tool_calls) == 1
    assert result.tool_calls[0].function.name == ""
    assert result.tool_calls[0].function.arguments == "{not valid json at all"
    assert result.content == "bash"


def test_extract_tool_calls_streaming_malformed_name_before_marker(
    mistral_tool_parser,
):
    # Streaming counterpart: once the args start the slot can never go back to
    # naming, so the (empty) name is already final and streams immediately
    # alongside the args.
    model_output = 'bash[TOOL_CALLS]{"command": "cat file.py"}'
    mid_delta = mistral_tool_parser.extract_tool_calls_streaming(
        previous_text="",
        current_text=model_output,
        delta_text=model_output,
        previous_token_ids=[],
        current_token_ids=[],
        delta_token_ids=[],
        request=_DUMMY_REQUEST,
    )
    assert mid_delta is not None
    assert mid_delta.content == "bash"
    assert len(mid_delta.tool_calls) == 1
    assert mid_delta.tool_calls[0].function.name == ""
    assert mid_delta.tool_calls[0].function.arguments == '{"command": "cat file.py"'

    final_delta = mistral_tool_parser.finish_streaming()
    assert final_delta is not None
    assert len(final_delta.tool_calls) == 1
    assert final_delta.tool_calls[0].function.name is None
    assert final_delta.tool_calls[0].function.arguments == "}"


def test_extract_tool_calls_parallel_malformed_then_well_formed(
    mistral_tool_parser,
):
    # A malformed empty-name call followed by a well-formed one must not
    # regress into brace-splitting: nested braces in the second call's
    # arguments must stay intact, and both calls must be correctly separated.
    model_output = (
        'bash[TOOL_CALLS]{"command": "ls"}'
        '[TOOL_CALLS]submit[ARGS]{"answer": {"nested": 1}}'
    )
    result = mistral_tool_parser.extract_tool_calls(
        model_output, request=_DUMMY_REQUEST
    )
    assert result.tools_called
    assert len(result.tool_calls) == 2
    assert result.tool_calls[0].function.name == ""
    assert result.tool_calls[0].function.arguments == json.dumps({"command": "ls"})
    assert result.tool_calls[1].function.name == "submit"
    assert result.tool_calls[1].function.arguments == json.dumps(
        {"answer": {"nested": 1}}
    )
    assert result.content == "bash"


def _test_extract_tool_calls_streaming(
    tool_parser,
    tokenizer,
    model_output,
    tools,
    expected_tool_calls,
    expected_content,
    driver: str = "legacy",
    reasoning_parser: str | None = None,
):
    other_content: str = ""
    function_names: list[str] = []
    function_args_strs: list[str] = []
    tool_call_idx: int = -1
    tool_call_ids: list[str | None] = []

    for delta_message in stream_delta_message_generator(
        tool_parser,
        tokenizer,
        model_output,
        tools,
        driver=driver,
        reasoning_parser=reasoning_parser,
    ):
        # role should never be streamed from tool parser
        assert not delta_message.role

        if delta_message.content:
            other_content += delta_message.content

        streamed_tool_calls = delta_message.tool_calls

        if streamed_tool_calls and len(streamed_tool_calls) > 0:
            # On the final finished=True delta the engine's _flush_engine_parsers
            # may append the flushed '}' as a separate DeltaToolCall for the
            # same index without coalescing.  Merge entries sharing an index so
            # the "one diff per delta" invariant can be checked after merging.
            if len(streamed_tool_calls) > 1:
                assert len({tc.index for tc in streamed_tool_calls}) == 1, (
                    "only within-chunk finish/flush of one tool is allowed; "
                    "distinct indices in one delta indicate a regression: "
                    f"{[tc.index for tc in streamed_tool_calls]}"
                )
                by_index: dict[int, DeltaToolCall] = {}
                for tc in streamed_tool_calls:
                    existing = by_index.get(tc.index)
                    if existing is None:
                        by_index[tc.index] = tc
                    else:
                        if tc.id and not existing.id:
                            existing.id = tc.id
                        if tc.type and not existing.type:
                            existing.type = tc.type
                        if tc.function and existing.function and tc.function.arguments:
                            existing.function.arguments = (
                                existing.function.arguments or ""
                            ) + tc.function.arguments
                streamed_tool_calls = list(by_index.values())

            # make sure only one diff is present - correct even for parallel
            assert len(streamed_tool_calls) == 1
            tool_call = streamed_tool_calls[0]

            # if a new tool is being called, set up empty arguments
            if tool_call.index != tool_call_idx:
                tool_call_idx = tool_call.index
                function_args_strs.append("")
                tool_call_ids.append(None)

            # if a tool call ID is streamed, make sure one hasn't been already
            if tool_call.id and not tool_call_ids[tool_call.index]:
                tool_call_ids[tool_call.index] = tool_call.id

            # if parts of the function start being streamed
            if tool_call.function:
                # if the function name is defined, set it. it should be streamed
                # IN ENTIRETY, exactly one time.
                if tool_call.function.name:
                    assert isinstance(tool_call.function.name, str)
                    function_names.append(tool_call.function.name)

                if tool_call.function.arguments:
                    # make sure they're a string and then add them to the list
                    assert isinstance(tool_call.function.arguments, str)

                    function_args_strs[tool_call.index] += tool_call.function.arguments

    assert other_content == expected_content

    actual_tool_calls = [
        ToolCall(
            id=tool_call_id,
            function=FunctionCall(
                name=function_name,
                arguments=partial_json_parser.ensure_json(
                    function_args_str, Allow.OBJ | Allow.STR
                ),
            ),
        )
        for tool_call_id, function_name, function_args_str in zip(
            tool_call_ids, function_names, function_args_strs
        )
    ]
    assert_tool_calls(actual_tool_calls, expected_tool_calls)


@pytest.mark.parametrize("driver", ["legacy", "engine"])
@pytest.mark.parametrize(
    ids=[
        "no_tools",
        "single_tool_add",
        "single_tool_add_strings",
        "single_tool_weather",
        "argument_before_name",
        "argument_before_name_and_name_in_argument",
        "multiple_tools",
        "trailing_data_after_json",
    ],
    argnames=["model_output", "expected_tool_calls", "expected_content"],
    argvalues=[
        ("""This is a test""", [], """This is a test"""),
        (
            """[TOOL_CALLS]  [ {"name":"add" , "arguments" : {"a": 3, "b": 4} } ]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3, "b": 4})
                    )
                )
            ],
            "",
        ),
        (
            """[TOOL_CALLS] [{"name": "add", "arguments":{"a": "3", "b": "4"}}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": "3", "b": "4"})
                    )
                )
            ],
            "",
        ),
        (
            """[TOOL_CALLS] [{"name": "get_current_weather", "arguments": {"city": "San Francisco", "state": "CA", "unit": "celsius"}}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                )
            ],
            "",
        ),
        (
            """[TOOL_CALLS] [{"arguments": {"city": "San Francisco", "state": "CA", "unit": "celsius"}, "name": "get_current_weather"}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                )
            ],
            "",
        ),
        (
            """[TOOL_CALLS] [{"arguments": {"name": "John Doe"}, "name": "get_age"}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_age",
                        arguments=json.dumps(
                            {
                                "name": "John Doe",
                            }
                        ),
                    )
                )
            ],
            "",
        ),
        (
            """[TOOL_CALLS] [{"name": "add", "arguments": {"a": 3.5, "b": 4}}, {"name": "get_current_weather", "arguments":{"city": "San Francisco", "state": "CA", "unit": "celsius"}}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3.5, "b": 4})
                    )
                ),
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                ),
            ],
            "",
        ),
        (
            """[TOOL_CALLS] [{"name": "get_current_weather", "arguments":{"city": "Dallas", "state": "TX", "unit": "fahrenheit"}}]\nextra trailing data""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {
                                "city": "Dallas",
                                "state": "TX",
                                "unit": "fahrenheit",
                            }
                        ),
                    )
                )
            ],
            "\nextra trailing data",
        ),
    ],
)
def test_extract_tool_calls_streaming_pre_v11_tokenizer(
    mistral_pre_v11_tool_parser,
    mistral_pre_v11_tokenizer,
    model_output,
    expected_tool_calls,
    expected_content,
    driver,
):
    _test_extract_tool_calls_streaming(
        mistral_pre_v11_tool_parser,
        mistral_pre_v11_tokenizer,
        model_output,
        None,
        expected_tool_calls,
        expected_content,
        driver=driver,
    )


@pytest.mark.parametrize(
    "driver,reasoning_parser",
    [("legacy", None), ("engine", None), ("engine", "mistral")],
    ids=["legacy", "engine_no_reasoning", "engine_with_reasoning"],
)
@pytest.mark.parametrize(
    ids=[
        "single_tool_add",
        "single_tool_add_strings",
        "multiple_tools",
    ],
    argnames=["tools", "expected_tool_calls", "expected_content"],
    argvalues=[
        (
            [("add", '{"a": 3, "b": 4}')],
            # [TOOL_CALLS]add{"a": 3, "b": 4}
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3, "b": 4})
                    )
                )
            ],
            "",
        ),
        (
            [("add_two_strings", '{"a": "3", "b": "4"}')],
            # [TOOL_CALLS]add_two_strings{"a": "3", "b": "4"}
            [
                ToolCall(
                    function=FunctionCall(
                        name="add_two_strings",
                        arguments=json.dumps({"a": "3", "b": "4"}),
                    )
                )
            ],
            "",
        ),
        (
            [
                ("add", '{"a": 3.5, "b": 4}'),
                (
                    "get_current_weather",
                    '{"city": "San Francisco", "state": "CA", "unit": "celsius"}',  # noqa: E501
                ),
            ],
            # [TOOL_CALLS]add{"a": 3.5, "b": 4}[TOOL_CALLS]get_current_weather{"city": "San Francisco", "state": "CA", "unit": "celsius"}  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3.5, "b": 4})
                    )
                ),
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                ),
            ],
            "",
        ),
    ],
)
def test_extract_tool_calls_streaming(
    mistral_tool_parser,
    mistral_tokenizer,
    tools,
    expected_tool_calls,
    expected_content,
    driver,
    reasoning_parser,
):
    _test_extract_tool_calls_streaming(
        mistral_tool_parser,
        mistral_tokenizer,
        None,
        tools,
        expected_tool_calls,
        expected_content,
        driver=driver,
        reasoning_parser=reasoning_parser,
    )


# Drives extract_tool_calls_streaming directly (bespoke detokenization loop),
# not via stream_delta_message_generator — driver parametrization not needed.
def test_extract_tool_calls_streaming_v11_no_tools(
    mistral_tool_parser, mistral_tokenizer
):
    model_output = "This is a test"
    # add_special_tokens=False: real serving streams only generated tokens.
    all_token_ids = mistral_tokenizer.encode(model_output, add_special_tokens=False)
    skip_special = isinstance(mistral_tokenizer, MistralTokenizer)
    collected_content = ""
    previous_text = ""
    previous_tokens = None
    prefix_offset = 0
    read_offset = 0
    for i in range(len(all_token_ids)):
        current_token_ids = all_token_ids[: i + 1]
        previous_token_ids = all_token_ids[:i]
        delta_token_ids = [all_token_ids[i]]

        new_tokens, delta_text, prefix_offset, read_offset = detokenize_incrementally(
            tokenizer=mistral_tokenizer,
            all_input_ids=current_token_ids,
            prev_tokens=previous_tokens,
            prefix_offset=prefix_offset,
            read_offset=read_offset,
            skip_special_tokens=skip_special,
            spaces_between_special_tokens=True,
        )
        current_text = previous_text + delta_text
        previous_tokens = (
            previous_tokens + new_tokens if previous_tokens else new_tokens
        )

        delta_message = mistral_tool_parser.extract_tool_calls_streaming(
            previous_text=previous_text,
            current_text=current_text,
            delta_text=delta_text,
            previous_token_ids=previous_token_ids,
            current_token_ids=current_token_ids,
            delta_token_ids=delta_token_ids,
            request=_DUMMY_REQUEST,
        )
        if delta_message and delta_message.content:
            collected_content += delta_message.content
        if delta_message:
            assert not delta_message.tool_calls

        previous_text = current_text

    assert collected_content == model_output


def test_mistral_parser_drops_eos_from_output(mistral_tokenizer):
    """EOS token must never surface as content/reasoning; literal EOS string
    must be preserved when the EOS token id is absent.

    The engine drops special tokens by id, so:
    Case A: the real EOS token id causes the text to be dropped.
    Case B: the same EOS string with a non-EOS token id is preserved.
    """
    if not isinstance(mistral_tokenizer, MistralTokenizer):
        pytest.skip("Requires MistralTokenizer")

    eos_id: int = mistral_tokenizer.eos_token_id
    eos_text: str = mistral_tokenizer.decode([eos_id])
    assert eos_text

    # Case A: real EOS token — text must be dropped.
    parser_a = MistralParser(mistral_tokenizer)
    parser_a.initialize_streaming()
    events_a = parser_a._feed(eos_text, [eos_id])
    events_a.extend(parser_a._engine.finish())
    delta_a = parser_a._events_to_delta(events_a, finished=True)
    content_a = (delta_a.content if delta_a else None) or ""
    reasoning_a = (delta_a.reasoning if delta_a else None) or ""
    assert eos_text not in content_a
    assert eos_text not in reasoning_a

    # Case B: EOS text with a non-EOS token id — text must be preserved.
    # This proves content equal to the EOS string is not silently dropped
    # when it did not come from the real EOS token.
    non_eos_ids = mistral_tokenizer.encode(text="hello", add_special_tokens=False)
    non_eos_id = next(tid for tid in non_eos_ids if tid != eos_id)
    parser_b = MistralParser(mistral_tokenizer)
    parser_b.initialize_streaming()
    events_b = parser_b._feed(eos_text, [non_eos_id])
    events_b.extend(parser_b._engine.finish())
    delta_b = parser_b._events_to_delta(events_b, finished=True)
    content_b = (delta_b.content if delta_b else None) or ""
    reasoning_b = (delta_b.reasoning if delta_b else None) or ""
    assert eos_text in content_b or eos_text in reasoning_b


@pytest.mark.parametrize(
    "parser_fixture, tokenizer_fixture, model_output,"
    " expected_tool_calls, expected_content",
    [
        pytest.param(
            "mistral_tool_parser",
            "mistral_tokenizer",
            """[TOOL_CALLS]add_this_and_that{"a": 3.5, "b": 4}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add_this_and_that",
                        arguments=json.dumps({"a": 3.5, "b": 4}),
                    )
                )
            ],
            "",
            id="v11-single_tool_add",
        ),
        pytest.param(
            "mistral_tool_parser",
            "mistral_tokenizer",
            """[TOOL_CALLS]get_current_weather{"city": "San Francisco", "state": "CA", "unit": "celsius"}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                )
            ],
            "",
            id="v11-single_tool_weather",
        ),
        pytest.param(
            "mistral_tool_parser",
            "mistral_tokenizer",
            """[TOOL_CALLS]add{"a": 3.5, "b": 4}[TOOL_CALLS]multiply{"a": 3, "b": 6}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3.5, "b": 4})
                    )
                ),
                ToolCall(
                    function=FunctionCall(
                        name="multiply", arguments=json.dumps({"a": 3, "b": 6})
                    )
                ),
            ],
            "",
            id="v11-multiple_tool_calls",
        ),
        pytest.param(
            "mistral_tool_parser",
            "mistral_tokenizer",
            """bla[TOOL_CALLS]add_this_and_that{"a": 3.5, "b": 4}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add_this_and_that",
                        arguments=json.dumps({"a": 3.5, "b": 4}),
                    )
                )
            ],
            "bla",
            id="v11-content_before_tool",
        ),
        pytest.param(
            "mistral_tool_parser",
            "mistral_tokenizer",
            """[TOOL_CALLS]add_this_and_that[ARGS]{"a": 3.5, "b": 4}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add_this_and_that",
                        arguments=json.dumps({"a": 3.5, "b": 4}),
                    )
                )
            ],
            "",
            id="v11-single_tool_add_args",
        ),
        pytest.param(
            "mistral_tool_parser",
            "mistral_tokenizer",
            """[TOOL_CALLS]add[ARGS]{"a": 3.5, "b": 4}[TOOL_CALLS]multiply[ARGS]{"a": 3, "b": 6}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3.5, "b": 4})
                    )
                ),
                ToolCall(
                    function=FunctionCall(
                        name="multiply", arguments=json.dumps({"a": 3, "b": 6})
                    )
                ),
            ],
            "",
            id="v11-multiple_tool_calls_args",
        ),
        pytest.param(
            "mistral_tool_parser",
            "mistral_tokenizer",
            """bla[TOOL_CALLS]add_this_and_that[ARGS]{"a": 3.5, "b": 4}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add_this_and_that",
                        arguments=json.dumps({"a": 3.5, "b": 4}),
                    )
                )
            ],
            "bla",
            id="v11-content_before_tool_args",
        ),
        pytest.param(
            "mistral_tool_parser",
            "mistral_tokenizer",
            """hi{hi[TOOL_CALLS]bash{"command": "print(\\"hello world!\\")\\nre.compile(r\'{}\')"}""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="bash",
                        arguments=json.dumps(
                            {"command": "print(\"hello world!\")\nre.compile(r'{}')"}
                        ),
                    )
                )
            ],
            "hi{hi",
            id="v11-complex",
        ),
        pytest.param(
            "mistral_pre_v11_tool_parser",
            "mistral_pre_v11_tokenizer",
            """This is a test""",
            [],
            """This is a test""",
            id="pre_v11-no_tools",
        ),
        pytest.param(
            "mistral_pre_v11_tool_parser",
            "mistral_pre_v11_tokenizer",
            """[TOOL_CALLS]  [ {"name":"add" , "arguments" : {"a": 3, "b": 4} } ]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3, "b": 4})
                    )
                )
            ],
            "",
            id="pre_v11-single_tool_add",
        ),
        pytest.param(
            "mistral_pre_v11_tool_parser",
            "mistral_pre_v11_tokenizer",
            """[TOOL_CALLS] [{"name": "add", "arguments":{"a": "3", "b": "4"}}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": "3", "b": "4"})
                    )
                )
            ],
            "",
            id="pre_v11-single_tool_add_strings",
        ),
        pytest.param(
            "mistral_pre_v11_tool_parser",
            "mistral_pre_v11_tokenizer",
            """[TOOL_CALLS] [{"name": "get_current_weather", "arguments": {"city": "San Francisco", "state": "CA", "unit": "celsius"}}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                )
            ],
            "",
            id="pre_v11-single_tool_weather",
        ),
        pytest.param(
            "mistral_pre_v11_tool_parser",
            "mistral_pre_v11_tokenizer",
            """[TOOL_CALLS] [{"arguments": {"city": "San Francisco", "state": "CA", "unit": "celsius"}, "name": "get_current_weather"}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                )
            ],
            "",
            id="pre_v11-argument_before_name",
        ),
        pytest.param(
            "mistral_pre_v11_tool_parser",
            "mistral_pre_v11_tokenizer",
            """[TOOL_CALLS] [{"arguments": {"name": "John Doe"}, "name": "get_age"}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="get_age",
                        arguments=json.dumps(
                            {
                                "name": "John Doe",
                            }
                        ),
                    )
                )
            ],
            "",
            id="pre_v11-argument_before_name_and_name_in_argument",
        ),
        pytest.param(
            "mistral_pre_v11_tool_parser",
            "mistral_pre_v11_tokenizer",
            """[TOOL_CALLS] [{"arguments": {"a": 3.5, "b": 4}, "name": "add"}, {"arguments":{"city": "San Francisco", "state": "CA", "unit": "celsius"}, "name": "get_current_weather"}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3.5, "b": 4})
                    )
                ),
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {"city": "San Francisco", "state": "CA", "unit": "celsius"}
                        ),
                    )
                ),
            ],
            "",
            id="pre_v11-multiple_tools",
        ),
        pytest.param(
            "mistral_pre_v11_tool_parser",
            "mistral_pre_v11_tokenizer",
            """Some text[TOOL_CALLS] [{"name": "add", "arguments":{"a": 1, "b": 2}}]""",  # noqa: E501
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 1, "b": 2})
                    )
                )
            ],
            "Some text",
            id="pre_v11-content_before_tool",
        ),
    ],
)
def test_extract_tool_calls_streaming_one_chunk(
    parser_fixture,
    tokenizer_fixture,
    model_output,
    expected_tool_calls,
    expected_content,
    request,
):
    tool_parser = request.getfixturevalue(parser_fixture)
    tokenizer = request.getfixturevalue(tokenizer_fixture)

    # Real serving streams only generated tokens (no BOS/EOS framing) with the
    # control markers as special ids.
    if isinstance(tokenizer, MistralTokenizer) and tokenizer.version >= 11:
        all_token_ids = encode_mistral_output(tokenizer, model_output)
    else:
        all_token_ids = tokenizer.encode(model_output, add_special_tokens=False)
        all_token_ids = fix_tool_call_tokenization(
            all_token_ids, tool_parser, tokenizer
        )

    delta_message = tool_parser.extract_tool_calls_streaming(
        previous_text="",
        current_text=model_output,
        delta_text=model_output,
        previous_token_ids=[],
        current_token_ids=all_token_ids,
        delta_token_ids=all_token_ids,
        request=_DUMMY_REQUEST,
    )
    # The engine buffers the final closing brace ('}') in _args_buffer until
    # finish_streaming() is called, mirroring real serving.  Flush it and
    # merge the result so the asserted arguments are complete.
    flush_delta = tool_parser.finish_streaming()
    if flush_delta is not None and flush_delta.tool_calls:
        if delta_message is not None and delta_message.tool_calls:
            for flush_tc in flush_delta.tool_calls:
                for existing_tc in delta_message.tool_calls:
                    if existing_tc.index == flush_tc.index and flush_tc.function:
                        existing_tc.function = (
                            existing_tc.function or DeltaFunctionCall()
                        )
                        existing_tc.function.arguments = (
                            existing_tc.function.arguments or ""
                        ) + (flush_tc.function.arguments or "")
        elif delta_message is not None:
            delta_message.tool_calls = flush_delta.tool_calls
        else:
            delta_message = flush_delta

    assert isinstance(delta_message, DeltaMessage)
    assert len(delta_message.tool_calls) == len(expected_tool_calls)

    assert_tool_calls(delta_message.tool_calls, expected_tool_calls)

    if delta_message.content is None:
        assert expected_content == ""
    else:
        assert delta_message.content == expected_content


@pytest.mark.parametrize(
    "parser_fixture, model_output, fake_count, two_phase",
    [
        pytest.param(
            "mistral_pre_v11_tool_parser",
            '[TOOL_CALLS] [{"name": "add", "arguments":{"a": 1, "b": 2}}]',
            30,
            False,
            id="pre_v11",
        ),
    ],
)
def test_fast_detokenization_text_detection(
    parser_fixture, model_output, fake_count, two_phase, request
):
    """Regression: bot_token in text but not token_ids (PR #37209).

    Only the pre-v11 legacy path detects the marker from text; v11+ routes
    through the engine and detects the marker by token id.
    """
    parser = request.getfixturevalue(parser_fixture)
    # Token IDs that do NOT contain bot_token_id.
    fake_token_ids = list(range(99, 99 + fake_count))

    if two_phase:
        # First delta: pure content, no bot token yet
        delta_message_before = parser.extract_tool_calls_streaming(
            previous_text="",
            current_text="Hello",
            delta_text="Hello",
            previous_token_ids=[],
            current_token_ids=[99],
            delta_token_ids=[99],
            request=_DUMMY_REQUEST,
        )
        assert delta_message_before is not None
        assert delta_message_before.content == "Hello"
        assert not delta_message_before.tool_calls

        previous_text = "Hello"
        current_text = "Hello" + model_output
        previous_token_ids = [99]
        delta_token_ids = fake_token_ids[1:]
    else:
        previous_text = ""
        current_text = model_output
        previous_token_ids = []
        delta_token_ids = fake_token_ids

    delta_message = parser.extract_tool_calls_streaming(
        previous_text=previous_text,
        current_text=current_text,
        delta_text=model_output,
        previous_token_ids=previous_token_ids,
        current_token_ids=fake_token_ids,
        delta_token_ids=delta_token_ids,
        request=_DUMMY_REQUEST,
    )
    assert delta_message is not None
    assert delta_message.tool_calls is not None
    assert len(delta_message.tool_calls) == 1
    assert delta_message.tool_calls[0].function is not None
    assert delta_message.tool_calls[0].function.name == "add"


def test_extract_tool_calls_streaming_exception_returns_none(
    mistral_pre_v11_tool_parser,
):
    # v11 routes through the ParserEngine and does not swallow exceptions;
    # only the pre-v11 legacy state-machine path has explicit exception handling.
    parser = mistral_pre_v11_tool_parser
    patched_method = "_extract_tool_calls_streaming_pre_v11_tokenizer"
    current_text = '[TOOL_CALLS] [{"name":"a","arguments":{}}]'
    with patch.object(
        parser._parser_engine, patched_method, side_effect=RuntimeError("boom")
    ):
        result = parser.extract_tool_calls_streaming(
            previous_text="",
            current_text=current_text,
            delta_text=current_text,
            previous_token_ids=[],
            current_token_ids=[parser._parser_engine.bot_token_id],
            delta_token_ids=[parser._parser_engine.bot_token_id],
            request=_DUMMY_REQUEST,
        )
    assert result is None


SAMPLE_TOOLS_DICTS = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get the weather",
            "parameters": {
                "type": "object",
                "properties": {"city": {"type": "string"}},
                "required": ["city"],
            },
        },
    },
    {
        "type": "function",
        "function": {
            "name": "add",
            "description": "Add two numbers",
            "parameters": {
                "type": "object",
                "properties": {
                    "a": {"type": "number"},
                    "b": {"type": "number"},
                },
                "required": ["a", "b"],
            },
        },
    },
]


def _make_request(**kwargs) -> ChatCompletionRequest:
    defaults: dict = {
        "messages": [],
        "model": "mistralai/Mistral-Small-3.2-24B-Instruct-2506",
        "tools": SAMPLE_TOOLS_DICTS,
        "tool_choice": "auto",
    }
    defaults.update(kwargs)
    return ChatCompletionRequest(**defaults)


@pytest.mark.parametrize(
    "request_kwargs,expected_mode,expected_parallel",
    [
        ({"tool_choice": "auto"}, MistralToolChoiceEnum.auto, True),
        ({"tool_choice": "none"}, MistralToolChoiceEnum.none, True),
        ({"tool_choice": "required"}, MistralToolChoiceEnum.required, True),
        ({"tool_choice": None, "tools": None}, MistralToolChoiceEnum.auto, True),
        (
            {
                "tool_choice": {
                    "type": "function",
                    "function": {"name": "get_weather"},
                }
            },
            MistralNamedToolChoice.model_validate(
                {"type": "function", "function": {"name": "get_weather"}}
            ),
            True,
        ),
        (
            {"tool_choice": "auto", "parallel_tool_calls": False},
            MistralToolChoiceEnum.auto,
            False,
        ),
        (
            {"tool_choice": "auto", "response_format": {"type": "text"}},
            MistralToolChoiceEnum.auto,
            True,
        ),
    ],
    ids=[
        "auto",
        "none",
        "required",
        "null_tool_choice",
        "named_tool_choice",
        "parallel_false",
        "response_format_text",
    ],
)
def test_adjust_request_grammar_factory(
    mistral_tool_parser: MistralToolParser,
    request_kwargs: dict,
    expected_mode: MistralToolChoice,
    expected_parallel: bool,
) -> None:
    request = _make_request(**request_kwargs)
    factory = mistral_tool_parser.model_tokenizer.grammar_factory

    with patch.object(
        factory,
        "get_lark_from_jinja",
        wraps=factory.get_lark_from_jinja,
    ) as mock_get_lark:
        result = mistral_tool_parser.adjust_request(request)

        mock_get_lark.assert_called_once()
        call_kwargs = mock_get_lark.call_args

        assert call_kwargs.kwargs["mode"] == expected_mode
        assert call_kwargs.kwargs["json_schema"] is None
        assert call_kwargs.kwargs["parallel_tool_calls"] == expected_parallel

    assert result.structured_outputs is not None
    assert isinstance(result.structured_outputs.grammar, str)
    assert len(result.structured_outputs.grammar) > 0


def test_adjust_request_unsupported_grammar_for_tokenizer(mistral_tokenizer) -> None:
    with patch.object(
        type(mistral_tokenizer),
        "supports_grammar",
        new_callable=lambda: property(lambda self: False),
    ):
        parser = MistralToolParser(mistral_tokenizer)
        request = _make_request()
        result = parser.adjust_request(request)

        assert result.structured_outputs is None


@pytest.mark.parametrize(
    "tool_choice,expected_skip",
    [("auto", False), ("none", False)],
    ids=["auto_skip_false", "none_skip_false"],
)
def test_adjust_request_non_mistral_tokenizer(
    non_mistral_parser: MistralToolParser,
    tool_choice: str,
    expected_skip: bool,
) -> None:
    # MistralParser (ParserEngine) always sets skip_special_tokens=False so
    # that special tokens like [TOOL_CALLS] are visible to the parser even
    # when tool_choice="none".
    request = _make_request(tool_choice=tool_choice)
    result = non_mistral_parser.adjust_request(request)

    assert result.skip_special_tokens is expected_skip


@pytest.mark.parametrize(
    "so_kwargs",
    [
        {"regex": r"\d+"},
        {"choice": ["a", "b"]},
        {
            "structural_tag": json.dumps(
                {
                    "structures": [
                        {
                            "begin": "<tool>",
                            "schema": {"type": "object"},
                            "end": "</tool>",
                        }
                    ],
                    "triggers": ["<tool>"],
                }
            )
        },
        {"grammar": "start: 'hello'"},
    ],
    ids=["regex", "choice", "structural_tag", "grammar"],
)
def test_adjust_request_unsupported_structured_outputs(
    mistral_tool_parser: MistralToolParser,
    so_kwargs: dict,
) -> None:
    request = _make_request(
        structured_outputs=StructuredOutputsParams(**so_kwargs),
    )
    result = mistral_tool_parser.adjust_request(request)

    assert result.structured_outputs == request.structured_outputs


def test_adjust_request_unsupported_response_format(
    mistral_tool_parser: MistralToolParser,
) -> None:
    request = _make_request(
        response_format=StructuralTagResponseFormat(
            type="structural_tag",
            format={
                "type": "triggered_tags",
                "tags": [
                    {
                        "begin": "<tool>",
                        "content": {"type": "any_text"},
                        "end": "</tool>",
                    }
                ],
                "triggers": ["<tool>"],
            },
        ),
    )
    result = mistral_tool_parser.adjust_request(request)
    assert result.structured_outputs is None
    assert result.response_format == request.response_format


@pytest.mark.parametrize(
    "so_kwargs,expected_json_schema",
    [
        ({"json_object": True}, _DEFAULT_JSON_SCHEMA),
        ({"json": '{"type": "object"}'}, {"type": "object"}),
        (
            {"json": {"type": "object", "properties": {"x": {"type": "integer"}}}},
            {"type": "object", "properties": {"x": {"type": "integer"}}},
        ),
    ],
    ids=["json_object", "json_str", "json_dict"],
)
def test_adjust_request_structured_outputs_generates_grammar(
    mistral_tool_parser: MistralToolParser,
    so_kwargs: dict,
    expected_json_schema: str,
) -> None:
    request = _make_request(
        structured_outputs=StructuredOutputsParams(**so_kwargs),
    )
    factory = mistral_tool_parser.model_tokenizer.grammar_factory

    with patch.object(
        factory,
        "get_lark_from_jinja",
        wraps=factory.get_lark_from_jinja,
    ) as mock_get_lark:
        result = mistral_tool_parser.adjust_request(request)

        mock_get_lark.assert_called_once()
        assert mock_get_lark.call_args.kwargs["json_schema"] == expected_json_schema

    assert result.structured_outputs is not None
    assert isinstance(result.structured_outputs.grammar, str)
    assert len(result.structured_outputs.grammar) > 0


@pytest.mark.parametrize(
    "response_format_kwargs,expected_json_schema",
    [
        ({"type": "json_object"}, _DEFAULT_JSON_SCHEMA),
        (
            {
                "type": "json_schema",
                "json_schema": {
                    "name": "my_schema",
                    "schema": {
                        "type": "object",
                        "properties": {"x": {"type": "integer"}},
                    },
                },
            },
            {"type": "object", "properties": {"x": {"type": "integer"}}},
        ),
    ],
    ids=["json_object", "json_schema_with_schema"],
)
def test_adjust_request_response_format_generates_grammar(
    mistral_tool_parser: MistralToolParser,
    response_format_kwargs: dict,
    expected_json_schema: str,
) -> None:
    request = _make_request(response_format=response_format_kwargs)
    factory = mistral_tool_parser.model_tokenizer.grammar_factory

    with patch.object(
        factory,
        "get_lark_from_jinja",
        wraps=factory.get_lark_from_jinja,
    ) as mock_get_lark:
        result = mistral_tool_parser.adjust_request(request)

        mock_get_lark.assert_called_once()
        assert mock_get_lark.call_args.kwargs["json_schema"] == expected_json_schema

    assert result.structured_outputs is not None
    assert isinstance(result.structured_outputs.grammar, str)
    assert len(result.structured_outputs.grammar) > 0


@pytest.mark.parametrize(
    "tool_choice, expected_method, not_called_method",
    [
        ("none", "get_lark_for_json_schema", None),
        ("auto", "get_lark_from_jinja", "get_lark_for_json_schema"),
    ],
    ids=["none_uses_json_schema_factory", "auto_uses_jinja_factory"],
)
def test_adjust_request_tool_choice_with_json_schema_factory_routing(
    mistral_tool_parser: MistralToolParser,
    tool_choice: str,
    expected_method: str,
    not_called_method: str | None,
) -> None:
    request = _make_request(
        tool_choice=tool_choice,
        structured_outputs=StructuredOutputsParams(json='{"type": "object"}'),
    )
    factory = mistral_tool_parser.model_tokenizer.grammar_factory

    patches = {
        expected_method: patch.object(
            factory,
            expected_method,
            wraps=getattr(factory, expected_method),
        ),
    }
    if not_called_method:
        patches[not_called_method] = patch.object(
            factory,
            not_called_method,
            wraps=getattr(factory, not_called_method),
        )

    with patches[expected_method] as mock_expected:
        ctx = patches[not_called_method] if not_called_method else None
        if ctx:
            with ctx as mock_not_called:
                result = mistral_tool_parser.adjust_request(request)
                mock_not_called.assert_not_called()
        else:
            result = mistral_tool_parser.adjust_request(request)

        mock_expected.assert_called_once()
        assert mock_expected.call_args.kwargs["json_schema"] == {"type": "object"}

    assert result.structured_outputs is not None
    assert isinstance(result.structured_outputs.grammar, str)
    assert len(result.structured_outputs.grammar) > 0


def test_grammar_from_parser_default_false() -> None:
    request = _make_request()
    assert request._grammar_from_parser is False


def test_grammar_from_parser_set_by_adjust_request(
    mistral_tool_parser: MistralToolParser,
) -> None:
    request = _make_request()
    result = mistral_tool_parser.adjust_request(request)
    assert result._grammar_from_parser is True


@pytest.mark.parametrize("driver", ["legacy", "engine"])
@pytest.mark.parametrize("chunk_size", [2, 3, 4, 5])
def test_streaming_pre_v11_parallel_calls_batched_deltas(
    mistral_pre_v11_tool_parser, mistral_pre_v11_tokenizer, chunk_size, driver
):
    """A batched delta spanning the boundary between two parallel calls must
    keep them on distinct indices (the bug collapsed both onto index 0)."""
    model_output = (
        '[TOOL_CALLS] [{"name": "add", "arguments": {"a": 3.5, "b": 4}}, '
        '{"name": "get_current_weather", "arguments": '
        '{"city": "San Francisco", "state": "CA", "unit": "celsius"}}]'
    )
    names: list[str] = []
    args: list[str] = []
    idx = -1
    for delta_message in stream_delta_message_generator(
        mistral_pre_v11_tool_parser,
        mistral_pre_v11_tokenizer,
        model_output,
        tools=None,
        chunk_size=chunk_size,
        driver=driver,
    ):
        for tool_call in delta_message.tool_calls or []:
            if tool_call.index != idx:
                idx = tool_call.index
                args.append("")
            if tool_call.function and tool_call.function.name:
                names.append(tool_call.function.name)
            if tool_call.function and tool_call.function.arguments:
                args[tool_call.index] += tool_call.function.arguments

    assert names == ["add", "get_current_weather"]
    assert len(args) == 2
    # trailing args of the final call are flushed by the serving layer
    assert json.loads(args[0]) == {"a": 3.5, "b": 4}


@pytest.mark.parametrize(
    "reasoning_encoding",
    ["text", "special_token"],
    ids=["text_encoding", "special_token_encoding"],
)
def test_content_tool_calls_transition_emits_reasoning_end(
    mistral_tokenizer,
    reasoning_encoding,
):
    """(CONTENT, TOOL_CALLS) must emit REASONING_END when reasoning is enabled."""

    cfg = mistral_config(reasoning_encoding=reasoning_encoding)
    engine = StreamingParserEngine(
        config=cfg, tokenizer=mistral_tokenizer, vocab=mistral_tokenizer.get_vocab()
    )
    engine.skip_tool_parsing = True

    bot_token_id = mistral_tokenizer.get_vocab().get("[TOOL_CALLS]")
    assert bot_token_id is not None

    events = engine.feed(delta_text="[TOOL_CALLS]", delta_token_ids=[bot_token_id])
    event_types = [e.type for e in events]

    assert EventType.REASONING_END in event_types, (
        f"REASONING_END missing for reasoning_encoding={reasoning_encoding!r}; "
        f"got events: {event_types}"
    )
    # Tool call start must NOT appear in skip_tool_parsing mode
    assert EventType.TOOL_CALL_START not in event_types


@pytest.mark.parametrize("chunk_size", [1, 3])
@pytest.mark.parametrize(
    "tools,expected_tool_calls,expected_content",
    [
        (
            [("add", '{"a": 3, "b": 4}')],
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3, "b": 4})
                    )
                )
            ],
            "",
        ),
        (
            [
                ("add", '{"a": 3.5, "b": 4}'),
                (
                    "get_current_weather",
                    '{"city": "San Francisco", "state": "CA", "unit": "celsius"}',
                ),
            ],
            [
                ToolCall(
                    function=FunctionCall(
                        name="add", arguments=json.dumps({"a": 3.5, "b": 4})
                    )
                ),
                ToolCall(
                    function=FunctionCall(
                        name="get_current_weather",
                        arguments=json.dumps(
                            {
                                "city": "San Francisco",
                                "state": "CA",
                                "unit": "celsius",
                            }
                        ),
                    )
                ),
            ],
            "",
        ),
    ],
    ids=["single_tool_add", "parallel_tools"],
)
def test_reasoning_active_no_think_block_no_leak(
    mistral_tool_parser,
    mistral_tokenizer,
    tools,
    expected_tool_calls,
    expected_content,
    chunk_size,
):
    """Tool call without a preceding think block must not leak as content
    when the reasoning parser is active."""
    accumulated_content = ""
    function_names: list[str] = []
    function_args_strs: list[str] = []
    tool_call_idx = -1
    tool_call_ids: list[str | None] = []

    for delta_message in stream_delta_message_generator(
        mistral_tool_parser,
        mistral_tokenizer,
        model_output=None,
        tools=tools,
        chunk_size=chunk_size,
        driver="engine",
        reasoning_parser="mistral",
    ):
        if delta_message.content:
            accumulated_content += delta_message.content

        for tool_call in delta_message.tool_calls or []:
            if tool_call.index != tool_call_idx:
                tool_call_idx = tool_call.index
                function_args_strs.append("")
                tool_call_ids.append(None)
            if tool_call.id and not tool_call_ids[tool_call.index]:
                tool_call_ids[tool_call.index] = tool_call.id
            if tool_call.function:
                if tool_call.function.name:
                    function_names.append(tool_call.function.name)
                if tool_call.function.arguments:
                    function_args_strs[tool_call.index] += tool_call.function.arguments

    assert "[TOOL_CALLS]" not in accumulated_content
    assert "[ARGS]" not in accumulated_content
    assert accumulated_content == expected_content

    actual_tool_calls = [
        ToolCall(
            id=tc_id,
            function=FunctionCall(
                name=name,
                arguments=partial_json_parser.ensure_json(args, Allow.OBJ | Allow.STR),
            ),
        )
        for tc_id, name, args in zip(tool_call_ids, function_names, function_args_strs)
    ]
    assert_tool_calls(actual_tool_calls, expected_tool_calls)


# ---------------------------------------------------------------------------
# Pre-v11 guided schema injection and bare-array extraction tests
# ---------------------------------------------------------------------------


@pytest.mark.parametrize(
    "tool_choice,expected_items_count",
    [
        ("required", 2),  # all tools
        (
            {"type": "function", "function": {"name": "get_weather"}},
            1,
        ),  # named: single tool
    ],
    ids=["required", "named"],
)
def test_adjust_request_pre_v11_guided_schema_injected(
    mistral_pre_v11_tool_parser: MistralToolParser,
    tool_choice: object,
    expected_items_count: int,
) -> None:
    request = _make_request(tool_choice=tool_choice)
    result = mistral_pre_v11_tool_parser.adjust_request(request)

    assert result.structured_outputs is not None
    schema = result.structured_outputs.json
    if isinstance(schema, str):
        schema = json.loads(schema)
    assert schema["type"] == "array"
    assert schema["minItems"] == 1
    items = schema["items"]
    assert "anyOf" in items
    assert len(items["anyOf"]) == expected_items_count
    for entry in items["anyOf"]:
        props = entry["properties"]
        assert "name" in props
        assert "arguments" in props


@pytest.mark.parametrize(
    "response_format",
    [{"type": "json_object"}, {"type": "json_schema", "json_schema": {"name": "s"}}],
    ids=["json_object", "json_schema"],
)
def test_adjust_request_pre_v11_required_clears_response_format(
    mistral_pre_v11_tool_parser: MistralToolParser,
    response_format: dict,
) -> None:
    """required + response_format must inject the tool schema and clear
    response_format so the tool schema is the sole structured-output
    constraint, matching the base ToolParser (otherwise the request either
    hits the "multiple constraints" engine error or, with no constraint,
    rambles to finish_reason='length')."""
    request = _make_request(tool_choice="required", response_format=response_format)
    result = mistral_pre_v11_tool_parser.adjust_request(request)

    assert result.response_format is None
    assert result.structured_outputs is not None
    schema = result.structured_outputs.json
    if isinstance(schema, str):
        schema = json.loads(schema)
    assert schema["type"] == "array"


def test_adjust_request_non_mistral_tokenizer_required_injects_schema(
    non_mistral_parser: MistralToolParser,
) -> None:
    """The guided-schema injection must also fire for non-Mistral (e.g. HF-mode)
    tokenizers driving the Mistral tool parser, mirroring the base ToolParser so
    required + response_format does not fall back to an unconstrained ramble."""
    request = _make_request(
        tool_choice="required", response_format={"type": "json_object"}
    )
    result = non_mistral_parser.adjust_request(request)

    assert result.response_format is None
    assert result.structured_outputs is not None
    assert result.structured_outputs.json is not None


@pytest.mark.parametrize(
    "tool_choice",
    ["auto", "none"],
    ids=["auto", "none"],
)
def test_adjust_request_pre_v11_no_injection_for_auto_none(
    mistral_pre_v11_tool_parser: MistralToolParser,
    tool_choice: str,
) -> None:
    request = _make_request(tool_choice=tool_choice)
    result = mistral_pre_v11_tool_parser.adjust_request(request)

    assert result.structured_outputs is None


def test_legacy_extract_tool_calls_guided_bare_array_required(
    mistral_pre_v11_tool_parser: MistralToolParser,
) -> None:
    model_output = '[{"name": "get_current_weather", "arguments": {"city": "Dallas"}}]'
    request = _make_request(tool_choice="required")

    result = mistral_pre_v11_tool_parser.extract_tool_calls(
        model_output, request=request
    )

    assert result.tools_called
    assert len(result.tool_calls) == 1
    tc = result.tool_calls[0]
    assert tc.function.name == "get_current_weather"
    assert json.loads(tc.function.arguments) == {"city": "Dallas"}
    assert isinstance(tc.id, str)
    assert len(tc.id) == 9
    assert result.content is None


def test_legacy_extract_tool_calls_none_with_tools(
    mistral_pre_v11_tool_parser: MistralToolParser,
) -> None:
    model_output = (
        '[TOOL_CALLS] [{"name": "get_current_weather",'
        ' "arguments": {"city": "Dallas"}}]'
    )
    request = _make_request(tool_choice="none")

    result = mistral_pre_v11_tool_parser.extract_tool_calls(
        model_output, request=request
    )

    assert not result.tools_called
    assert result.tool_calls == []
    assert result.content == model_output


def test_guided_streaming_required_pre_v11(
    mistral_pre_v11_tool_parser: MistralToolParser,
    mistral_pre_v11_tokenizer,
) -> None:
    model_output = '[{"name": "get_current_weather", "arguments": {"city": "Dallas"}}]'
    request = _make_request(tool_choice="required")
    all_token_ids = mistral_pre_v11_tokenizer.encode(
        model_output, add_special_tokens=False
    )

    function_name: str | None = None
    function_args = ""
    tool_call_id: str | None = None
    previous_text = ""
    previous_tokens = None
    prefix_offset = 0
    read_offset = 0

    for i, token_id in enumerate(all_token_ids):
        (new_tokens, delta_text, prefix_offset, read_offset) = detokenize_incrementally(
            tokenizer=mistral_pre_v11_tokenizer,
            all_input_ids=all_token_ids[: i + 1],
            prev_tokens=previous_tokens,
            prefix_offset=prefix_offset,
            read_offset=read_offset,
            skip_special_tokens=False,
            spaces_between_special_tokens=True,
        )
        previous_tokens = (
            (previous_tokens + new_tokens) if previous_tokens else new_tokens
        )
        current_text = previous_text + delta_text

        delta_message = mistral_pre_v11_tool_parser.extract_tool_calls_streaming(
            previous_text=previous_text,
            current_text=current_text,
            delta_text=delta_text,
            previous_token_ids=all_token_ids[:i],
            current_token_ids=all_token_ids[: i + 1],
            delta_token_ids=[token_id],
            request=request,
        )
        previous_text = current_text

        if delta_message and delta_message.tool_calls:
            for tc in delta_message.tool_calls:
                if tc.id and not tool_call_id:
                    tool_call_id = tc.id
                if tc.function:
                    if tc.function.name:
                        function_name = tc.function.name
                    if tc.function.arguments:
                        function_args += tc.function.arguments

    assert function_name == "get_current_weather"
    assert tool_call_id is not None
    assert len(tool_call_id) == 9
    assert json.loads(function_args) == {"city": "Dallas"}


# ---------------------------------------------------------------------------
# Malformed-name-before-marker matrix: {malformed, well-formed, mixed
# parallel} x {streaming, non-streaming}.
#
# These tests drive a real MistralParser built from the module's
# `mistral_tokenizer` fixture (grammar-capable v11+ tokenizer, so the
# declarative ParserEngine path is exercised, not the pre-v11 legacy state
# machine) with actual bash/search_replace/submit tools, mirroring the tools
# present in the real captured traces this bug was found in.
# ---------------------------------------------------------------------------

_BASH_SEARCH_SUBMIT_TOOLS_DICTS = [
    {
        "type": "function",
        "function": {
            "name": "bash",
            "description": "Run a bash command",
            "parameters": {
                "type": "object",
                "properties": {"command": {"type": "string"}},
                "required": ["command"],
            },
        },
    },
    {
        "type": "function",
        "function": {
            "name": "search_replace",
            "description": "Search and replace text in a file",
            "parameters": {
                "type": "object",
                "properties": {
                    "path": {"type": "string"},
                    "search": {"type": "string"},
                    "replace": {"type": "string"},
                },
                "required": ["path", "search", "replace"],
            },
        },
    },
    {
        "type": "function",
        "function": {
            "name": "submit",
            "description": "Submit the final answer",
            "parameters": {
                "type": "object",
                "properties": {"answer": {"type": "object"}},
                "required": ["answer"],
            },
        },
    },
]


def _malformed_matrix_request() -> ChatCompletionRequest:
    return ChatCompletionRequest(
        messages=[],
        model="test",
        tools=_BASH_SEARCH_SUBMIT_TOOLS_DICTS,
        tool_choice="auto",
    )


def _stream_via_parse_delta(
    parser: MistralParser,
    tokenizer: MistralTokenizer,
    model_output: str,
    request: ChatCompletionRequest,
) -> tuple[str, list[str | None], list[str]]:
    """Feed `model_output` through `parser.parse_delta` token-by-token.

    This is the exact API production serving drives on every generated
    token (see `ParserEngine.parse_delta`), unlike
    `extract_tool_calls_streaming` which some legacy call sites drive with
    pre-computed previous/current text windows.
    """
    parser.initialize_streaming()
    all_token_ids = encode_mistral_output(tokenizer, model_output)

    content = ""
    tool_call_idx = -1
    names: list[str | None] = []
    args: list[str] = []

    previous_tokens = None
    prefix_offset = 0
    read_offset = 0
    for i, token_id in enumerate(all_token_ids):
        new_tokens, delta_text, prefix_offset, read_offset = detokenize_incrementally(
            tokenizer=tokenizer,
            all_input_ids=all_token_ids[: i + 1],
            prev_tokens=previous_tokens,
            prefix_offset=prefix_offset,
            read_offset=read_offset,
            skip_special_tokens=False,
            spaces_between_special_tokens=True,
        )
        previous_tokens = (
            previous_tokens + new_tokens if previous_tokens else new_tokens
        )
        finished = i == len(all_token_ids) - 1

        delta_message = parser.parse_delta(
            delta_text=delta_text,
            delta_token_ids=[token_id],
            request=request,
            prompt_token_ids=[1],
            finished=finished,
        )
        if delta_message is None:
            continue
        if delta_message.content:
            content += delta_message.content
        for tool_call in delta_message.tool_calls or []:
            if tool_call.index != tool_call_idx:
                tool_call_idx = tool_call.index
                names.append(None)
                args.append("")
            if tool_call.function:
                if tool_call.function.name is not None:
                    names[tool_call.index] = tool_call.function.name
                if tool_call.function.arguments:
                    args[tool_call.index] += tool_call.function.arguments

    return content, names, args


_MALFORMED_MATRIX_CASES = [
    pytest.param(
        # 2x2 corner: name present, `[ARGS]` token present.
        '[TOOL_CALLS]bash[ARGS]{"command": "ls -la"}',
        ["bash"],
        [json.dumps({"command": "ls -la"})],
        None,
        id="wellformed_single",
    ),
    pytest.param(
        # 2x2 corner: name present, no `[ARGS]` token.
        '[TOOL_CALLS]bash{"command": "ls -la"}',
        ["bash"],
        [json.dumps({"command": "ls -la"})],
        None,
        id="wellformed_single_no_args_token",
    ),
    pytest.param(
        # 2x2 corner: name skipped, no `[ARGS]` token. "bash" lands in
        # content before the marker, then generation jumps straight to
        # args (no NAME slot, no [ARGS]).
        'bash[TOOL_CALLS]{"command": "cat file.py"}',
        [""],
        [json.dumps({"command": "cat file.py"})],
        "bash",
        id="malformed_single",
    ),
    pytest.param(
        # 2x2 corner: name skipped, `[ARGS]` token present.
        'bash[TOOL_CALLS][ARGS]{"command": "cat file.py"}',
        [""],
        [json.dumps({"command": "cat file.py"})],
        "bash",
        id="malformed_single_args_token",
    ),
    pytest.param(
        # parallel well-formed x2; the second call's nested braces in its
        # arguments must not confuse call splitting.
        '[TOOL_CALLS]bash[ARGS]{"command": "ls"}'
        '[TOOL_CALLS]submit[ARGS]{"answer": {"nested": 1}}',
        ["bash", "submit"],
        [json.dumps({"command": "ls"}), json.dumps({"answer": {"nested": 1}})],
        None,
        id="parallel_wellformed",
    ),
    pytest.param(
        # parallel malformed x2: both calls skip the NAME slot entirely
        # (marker immediately followed by `{`), each ending with an empty
        # name and correctly separated (nested-brace) arguments.
        'bash[TOOL_CALLS]{"command": "ls"}[TOOL_CALLS]{"answer": {"nested": 1}}',
        ["", ""],
        [json.dumps({"command": "ls"}), json.dumps({"answer": {"nested": 1}})],
        "bash",
        id="parallel_malformed",
    ),
    pytest.param(
        # parallel malformed x2, `[ARGS]` token variant: both calls skip
        # the NAME slot but enter TOOL_ARGS via `[ARGS]` instead of `{`.
        'bash[TOOL_CALLS][ARGS]{"command": "ls"}'
        '[TOOL_CALLS][ARGS]{"answer": {"nested": 1}}',
        ["", ""],
        [json.dumps({"command": "ls"}), json.dumps({"answer": {"nested": 1}})],
        "bash",
        id="parallel_malformed_args_token",
    ),
    pytest.param(
        # mixed: malformed first call, well-formed second call. The
        # important case: proves calls are split on the `[TOOL_CALLS]`
        # marker, not on braces — the first call's simple args and the
        # second call's nested-brace args must not bleed into each other.
        'bash[TOOL_CALLS]{"command": "ls"}'
        '[TOOL_CALLS]submit[ARGS]{"answer": {"nested": 1}}',
        ["", "submit"],
        [json.dumps({"command": "ls"}), json.dumps({"answer": {"nested": 1}})],
        "bash",
        id="mixed_malformed_then_wellformed",
    ),
    pytest.param(
        # mixed, `[ARGS]` token variant: malformed first call enters
        # TOOL_ARGS via `[ARGS]` instead of `{`, second call well-formed.
        'bash[TOOL_CALLS][ARGS]{"command": "ls"}'
        '[TOOL_CALLS]submit[ARGS]{"answer": {"nested": 1}}',
        ["", "submit"],
        [json.dumps({"command": "ls"}), json.dumps({"answer": {"nested": 1}})],
        "bash",
        id="mixed_malformed_args_token_then_wellformed",
    ),
    pytest.param(
        # mixed: well-formed first call, malformed second call (NAME slot
        # skipped entirely for the second call).
        '[TOOL_CALLS]bash[ARGS]{"command": "ls"}[TOOL_CALLS]{"answer": {"nested": 1}}',
        ["bash", ""],
        [json.dumps({"command": "ls"}), json.dumps({"answer": {"nested": 1}})],
        None,
        id="mixed_wellformed_then_malformed",
    ),
]


@pytest.mark.parametrize(
    "model_output,expected_names,expected_args,expected_content",
    _MALFORMED_MATRIX_CASES,
)
def test_malformed_tool_call_matrix_non_streaming(
    mistral_tokenizer,
    model_output,
    expected_names,
    expected_args,
    expected_content,
):
    parser = MistralParser(mistral_tokenizer)
    request = _malformed_matrix_request()

    result = parser.extract_tool_calls_from_content(model_output, request)

    assert result.tools_called
    assert [tc.function.name for tc in result.tool_calls] == expected_names
    assert [tc.function.arguments for tc in result.tool_calls] == expected_args
    assert result.content == expected_content


@pytest.mark.parametrize(
    "model_output,expected_names,expected_args,expected_content",
    _MALFORMED_MATRIX_CASES,
)
def test_malformed_tool_call_matrix_streaming(
    mistral_tokenizer,
    model_output,
    expected_names,
    expected_args,
    expected_content,
):
    parser = MistralParser(mistral_tokenizer)
    request = _malformed_matrix_request()

    content, names, args = _stream_via_parse_delta(
        parser, mistral_tokenizer, model_output, request
    )

    assert content == (expected_content or "")
    assert names == expected_names
    assert args == expected_args


# Real payload captured from a production SWE-bench-agent.
_REAL_LEAK_CONTENT = 'bash[TOOL_CALLS]{"command": "cd /testbed && git diff xarray/core/weighted.py"}ometracediff --git a/xarray/core/weighted.py b/xarray/core/weighted.py\\nindex 5f2d138e..9c38b0b7 100644\\n--- a/xarray/core/weighted.py\\n+++ b/xarray/core/weighted.py\\n@@ -1,4 +1,6 @@\\n from typing import TYPE_CHECKING, Hashable, Iterable, Optional, Union, overload\\n+\\n+import numpy as np\\n \\n from .computation import dot\\n from .options import _get_keep_attrs\\n@@ -105,6 +107,10 @@ class Weighted:\\n         )\\n \\n         self.obj = obj\\n-        self.weights = weights\\n+        # Ensure weights are numeric (float64) to avoid boolean arithmetic issues\\n+        # in dot products and weighted operations\\n+        if not np.issubdtype(weights.dtype, np.number):\\n+            weights = weights.astype(np.float64)\\n+        self.weights = weights\\n "}现在 hareview the changes we made:bash[ARGS]{"command": "cat /testbed/xarray/core/weighted.py | head -120 | tail -20"}'  # noqa: E501


def test_extract_tool_calls_real_captured_malformed_output(mistral_tokenizer):
    parser = MistralParser(mistral_tokenizer)
    request = _malformed_matrix_request()

    result = parser.extract_tool_calls_from_content(_REAL_LEAK_CONTENT, request)

    assert result.tools_called
    assert len(result.tool_calls) == 1
    assert result.tool_calls[0].function.name == ""
    assert result.tool_calls[0].function.arguments == json.dumps(
        {"command": "cd /testbed && git diff xarray/core/weighted.py"}
    )
    assert result.content == "bash"