"""Unit tests for ModelLengthFinishReasonMiddleware."""

import logging
from unittest.mock import MagicMock

from langchain_core.messages import AIMessage, HumanMessage

from deerflow.agents.middlewares.model_length_finish_reason_middleware import (
    MODEL_LENGTH_CAPPED_STOP_REASON,
    ModelLengthFinishReasonMiddleware,
)

_MW_LOGGER = "deerflow.agents.middlewares.model_length_finish_reason_middleware"


def _runtime(run_id: str = "run-1"):
    runtime = MagicMock()
    runtime.context = {"thread_id": "thread-1", "run_id": run_id}
    return runtime


def test_finish_reason_length_records_stop_reason_without_rewriting_textual_tool_call():
    mw = ModelLengthFinishReasonMiddleware()
    runtime = _runtime()
    msg = AIMessage(
        content=('<tool_call><invoke name="write_file"><path>/mnt/user-data/outputs/report.md</path><content># partial'),
        tool_calls=[],
        invalid_tool_calls=[],
        response_metadata={"finish_reason": "length"},
    )

    result = mw._apply({"messages": [msg]}, runtime)

    assert result is None
    assert runtime.context["stop_reason"] == MODEL_LENGTH_CAPPED_STOP_REASON
    assert msg.content.startswith('<tool_call><invoke name="write_file">')
    assert msg.tool_calls == []
    assert msg.invalid_tool_calls == []


def test_finish_reason_stop_with_tool_call_example_in_prose_passes_through():
    mw = ModelLengthFinishReasonMiddleware()
    runtime = _runtime()
    msg = AIMessage(
        content=('Here is an example, not a real tool call:\n\n```xml\n<tool_call><invoke name="write_file"></invoke></tool_call>\n```'),
        response_metadata={"finish_reason": "stop"},
    )

    assert mw._apply({"messages": [msg]}, runtime) is None
    assert "stop_reason" not in runtime.context


def test_additional_kwargs_finish_reason_length_records_stop_reason():
    mw = ModelLengthFinishReasonMiddleware()
    runtime = _runtime()
    msg = AIMessage(
        content="partial",
        additional_kwargs={"finish_reason": "length"},
    )

    assert mw._apply({"messages": [msg]}, runtime) is None
    assert runtime.context["stop_reason"] == MODEL_LENGTH_CAPPED_STOP_REASON


def test_gemini_max_tokens_finish_reason_records_stop_reason():
    mw = ModelLengthFinishReasonMiddleware()
    runtime = _runtime()
    msg = AIMessage(
        content="partial",
        response_metadata={"finish_reason": "MAX_TOKENS"},
    )

    assert mw._apply({"messages": [msg]}, runtime) is None
    assert runtime.context["stop_reason"] == MODEL_LENGTH_CAPPED_STOP_REASON


def test_anthropic_max_tokens_stop_reason_records_stop_reason():
    mw = ModelLengthFinishReasonMiddleware()
    runtime = _runtime()
    msg = AIMessage(
        content="partial",
        response_metadata={"stop_reason": "max_tokens"},
    )

    assert mw._apply({"messages": [msg]}, runtime) is None
    assert runtime.context["stop_reason"] == MODEL_LENGTH_CAPPED_STOP_REASON


def test_length_cap_detection_logs_observability_fields(caplog):
    mw = ModelLengthFinishReasonMiddleware()
    runtime = _runtime(run_id="run-observe")
    msg = AIMessage(
        id="msg-1",
        content="partial",
        response_metadata={"finish_reason": "length"},
    )

    with caplog.at_level(logging.INFO, logger=_MW_LOGGER):
        assert mw._apply({"messages": [msg]}, runtime) is None

    records = [record for record in caplog.records if record.message == "Provider model length cap detected"]
    assert len(records) == 1
    record = records[0]
    assert record.thread_id == "thread-1"
    assert record.run_id == "run-observe"
    assert record.message_id == "msg-1"
    assert record.detector == "openai_compatible_length"
    assert record.reason_field == "finish_reason"
    assert record.reason_value == "length"
    assert record.stamped_stop_reason is True


def test_finish_reason_length_with_tool_calls_passes_through():
    mw = ModelLengthFinishReasonMiddleware()
    runtime = _runtime()
    msg = AIMessage(
        content="",
        tool_calls=[
            {
                "id": "call_write_1",
                "name": "write_file",
                "args": {"path": "/mnt/user-data/outputs/report.md", "content": "# partial"},
            }
        ],
        response_metadata={"finish_reason": "length"},
    )

    assert mw._apply({"messages": [msg]}, runtime) is None
    assert "stop_reason" not in runtime.context


def test_empty_finish_reason_length_passes_through_for_terminal_response_recovery():
    mw = ModelLengthFinishReasonMiddleware()
    runtime = _runtime()
    msg = AIMessage(content="", response_metadata={"finish_reason": "length"})

    assert mw._apply({"messages": [msg]}, runtime) is None
    assert "stop_reason" not in runtime.context


def test_existing_stop_reason_is_not_overwritten(caplog):
    mw = ModelLengthFinishReasonMiddleware()
    runtime = _runtime()
    runtime.context["stop_reason"] = "token_capped"
    msg = AIMessage(content="partial", response_metadata={"finish_reason": "length"})

    with caplog.at_level(logging.INFO, logger=_MW_LOGGER):
        assert mw._apply({"messages": [msg]}, runtime) is None

    assert runtime.context["stop_reason"] == "token_capped"
    records = [record for record in caplog.records if record.message == "Provider model length cap detected"]
    assert len(records) == 1
    assert records[0].stamped_stop_reason is False


def test_non_ai_last_message_passes_through():
    mw = ModelLengthFinishReasonMiddleware()
    runtime = _runtime()

    assert mw._apply({"messages": [HumanMessage(content="hello")]}, runtime) is None
    assert "stop_reason" not in runtime.context