"""Test Azure OpenAI provider (Responses API via OpenAI SDK)."""

from unittest.mock import AsyncMock, MagicMock

import pytest

from nanobot.providers.azure_openai_provider import AzureOpenAIProvider
from nanobot.providers.base import LLMResponse


# ---------------------------------------------------------------------------
# Init & validation
# ---------------------------------------------------------------------------


def test_init_creates_sdk_client():
    """Provider creates an AsyncOpenAI client with correct base_url."""
    provider = AzureOpenAIProvider(
        api_key="test-key",
        api_base="https://test-resource.openai.azure.com",
        default_model="gpt-4o-deployment",
    )
    assert provider.api_key == "test-key"
    assert provider.api_base == "https://test-resource.openai.azure.com/"
    assert provider.default_model == "gpt-4o-deployment"
    # SDK client base_url ends with /openai/v1/
    assert str(provider._client.base_url).rstrip("/").endswith("/openai/v1")


def test_init_base_url_no_trailing_slash():
    """Trailing slashes are normalised before building base_url."""
    provider = AzureOpenAIProvider(
        api_key="k", api_base="https://res.openai.azure.com",
    )
    assert str(provider._client.base_url).rstrip("/").endswith("/openai/v1")


def test_init_base_url_with_trailing_slash():
    provider = AzureOpenAIProvider(
        api_key="k", api_base="https://res.openai.azure.com/",
    )
    assert str(provider._client.base_url).rstrip("/").endswith("/openai/v1")


def test_init_validation_missing_key():
    with pytest.raises(ValueError, match="Azure OpenAI api_key is required"):
        AzureOpenAIProvider(api_key="", api_base="https://test.com")


def test_init_validation_missing_base():
    with pytest.raises(ValueError, match="Azure OpenAI api_base is required"):
        AzureOpenAIProvider(api_key="test", api_base="")


def test_no_api_version_in_base_url():
    """The /openai/v1/ path should NOT contain an api-version query param."""
    provider = AzureOpenAIProvider(api_key="k", api_base="https://res.openai.azure.com")
    base = str(provider._client.base_url)
    assert "api-version" not in base


# ---------------------------------------------------------------------------
# _supports_temperature
# ---------------------------------------------------------------------------


def test_supports_temperature_standard_model():
    assert AzureOpenAIProvider._supports_temperature("gpt-4o") is True


def test_supports_temperature_reasoning_model():
    assert AzureOpenAIProvider._supports_temperature("o3-mini") is False
    assert AzureOpenAIProvider._supports_temperature("gpt-5-chat") is False
    assert AzureOpenAIProvider._supports_temperature("o4-mini") is False


def test_supports_temperature_with_reasoning_effort():
    assert AzureOpenAIProvider._supports_temperature("gpt-4o", reasoning_effort="medium") is False


# ---------------------------------------------------------------------------
# _build_body — Responses API body construction
# ---------------------------------------------------------------------------


def test_build_body_basic():
    provider = AzureOpenAIProvider(
        api_key="k", api_base="https://res.openai.azure.com", default_model="gpt-4o",
    )
    messages = [{"role": "system", "content": "You are helpful."}, {"role": "user", "content": "Hi"}]
    body = provider._build_body(messages, None, None, 4096, 0.7, None, None)

    assert body["model"] == "gpt-4o"
    assert body["instructions"] == "You are helpful."
    assert body["temperature"] == 0.7
    assert body["max_output_tokens"] == 4096
    assert body["store"] is False
    assert "reasoning" not in body
    # input should contain the converted user message only (system extracted)
    assert any(
        item.get("role") == "user"
        for item in body["input"]
    )


def test_build_body_max_tokens_minimum():
    """max_output_tokens should never be less than 1."""
    provider = AzureOpenAIProvider(api_key="k", api_base="https://r.com", default_model="gpt-4o")
    body = provider._build_body([{"role": "user", "content": "x"}], None, None, 0, 0.7, None, None)
    assert body["max_output_tokens"] == 1


def test_build_body_with_tools():
    provider = AzureOpenAIProvider(api_key="k", api_base="https://r.com", default_model="gpt-4o")
    tools = [{"type": "function", "function": {"name": "get_weather", "parameters": {}}}]
    body = provider._build_body(
        [{"role": "user", "content": "weather?"}], tools, None, 4096, 0.7, None, None,
    )
    assert body["tools"] == [{"type": "function", "name": "get_weather", "description": "", "parameters": {}}]
    assert body["tool_choice"] == "auto"


def test_build_body_with_reasoning():
    provider = AzureOpenAIProvider(api_key="k", api_base="https://r.com", default_model="gpt-5-chat")
    body = provider._build_body(
        [{"role": "user", "content": "think"}], None, "gpt-5-chat", 4096, 0.7, "medium", None,
    )
    assert body["reasoning"] == {"effort": "medium"}
    assert "reasoning.encrypted_content" in body.get("include", [])
    # temperature omitted for reasoning models
    assert "temperature" not in body


def test_build_body_image_conversion():
    """image_url content blocks should be converted to input_image."""
    provider = AzureOpenAIProvider(api_key="k", api_base="https://r.com", default_model="gpt-4o")
    messages = [{
        "role": "user",
        "content": [
            {"type": "text", "text": "What's in this image?"},
            {"type": "image_url", "image_url": {"url": "https://example.com/img.png"}},
        ],
    }]
    body = provider._build_body(messages, None, None, 4096, 0.7, None, None)
    user_item = body["input"][0]
    content_types = [b["type"] for b in user_item["content"]]
    assert "input_text" in content_types
    assert "input_image" in content_types
    image_block = next(b for b in user_item["content"] if b["type"] == "input_image")
    assert image_block["image_url"] == "https://example.com/img.png"


def test_build_body_sanitizes_single_dict_content_block():
    """Single content dicts should be preserved via shared message sanitization."""
    provider = AzureOpenAIProvider(api_key="k", api_base="https://r.com", default_model="gpt-4o")
    messages = [{
        "role": "user",
        "content": {"type": "text", "text": "Hi from dict content"},
    }]

    body = provider._build_body(messages, None, None, 4096, 0.7, None, None)

    assert body["input"][0]["content"] == [{"type": "input_text", "text": "Hi from dict content"}]


# ---------------------------------------------------------------------------
# chat() — non-streaming
# ---------------------------------------------------------------------------


def _make_sdk_response(
    content="Hello!", tool_calls=None, status="completed",
    usage=None,
):
    """Build a mock that quacks like an openai Response object."""
    resp = MagicMock()
    resp.model_dump = MagicMock(return_value={
        "output": [
            {"type": "message", "role": "assistant", "content": [{"type": "output_text", "text": content}]},
            *([{
                "type": "function_call",
                "call_id": tc["call_id"], "id": tc["id"],
                "name": tc["name"], "arguments": tc["arguments"],
            } for tc in (tool_calls or [])]),
        ],
        "status": status,
        "usage": {
            "input_tokens": (usage or {}).get("input_tokens", 10),
            "output_tokens": (usage or {}).get("output_tokens", 5),
            "total_tokens": (usage or {}).get("total_tokens", 15),
        },
    })
    return resp


@pytest.mark.asyncio
async def test_chat_success():
    provider = AzureOpenAIProvider(
        api_key="test-key", api_base="https://test.openai.azure.com", default_model="gpt-4o",
    )
    mock_resp = _make_sdk_response(content="Hello!")
    provider._client.responses = MagicMock()
    provider._client.responses.create = AsyncMock(return_value=mock_resp)

    result = await provider.chat([{"role": "user", "content": "Hi"}])

    assert isinstance(result, LLMResponse)
    assert result.content == "Hello!"
    assert result.finish_reason == "stop"
    assert result.usage["prompt_tokens"] == 10


@pytest.mark.asyncio
async def test_chat_uses_default_model():
    provider = AzureOpenAIProvider(
        api_key="k", api_base="https://test.openai.azure.com", default_model="my-deployment",
    )
    mock_resp = _make_sdk_response(content="ok")
    provider._client.responses = MagicMock()
    provider._client.responses.create = AsyncMock(return_value=mock_resp)

    await provider.chat([{"role": "user", "content": "test"}])

    call_kwargs = provider._client.responses.create.call_args[1]
    assert call_kwargs["model"] == "my-deployment"


@pytest.mark.asyncio
async def test_chat_custom_model():
    provider = AzureOpenAIProvider(
        api_key="k", api_base="https://test.openai.azure.com", default_model="gpt-4o",
    )
    mock_resp = _make_sdk_response(content="ok")
    provider._client.responses = MagicMock()
    provider._client.responses.create = AsyncMock(return_value=mock_resp)

    await provider.chat([{"role": "user", "content": "test"}], model="custom-deploy")

    call_kwargs = provider._client.responses.create.call_args[1]
    assert call_kwargs["model"] == "custom-deploy"


@pytest.mark.asyncio
async def test_chat_with_tool_calls():
    provider = AzureOpenAIProvider(
        api_key="k", api_base="https://test.openai.azure.com", default_model="gpt-4o",
    )
    mock_resp = _make_sdk_response(
        content=None,
        tool_calls=[{
            "call_id": "call_123", "id": "fc_1",
            "name": "get_weather", "arguments": '{"location": "SF"}',
        }],
    )
    provider._client.responses = MagicMock()
    provider._client.responses.create = AsyncMock(return_value=mock_resp)

    result = await provider.chat(
        [{"role": "user", "content": "Weather?"}],
        tools=[{"type": "function", "function": {"name": "get_weather", "parameters": {}}}],
    )

    assert len(result.tool_calls) == 1
    assert result.tool_calls[0].name == "get_weather"
    assert result.tool_calls[0].arguments == {"location": "SF"}


@pytest.mark.asyncio
async def test_chat_error_handling():
    provider = AzureOpenAIProvider(
        api_key="k", api_base="https://test.openai.azure.com", default_model="gpt-4o",
    )
    provider._client.responses = MagicMock()
    provider._client.responses.create = AsyncMock(side_effect=Exception("Connection failed"))

    result = await provider.chat([{"role": "user", "content": "Hi"}])

    assert isinstance(result, LLMResponse)
    assert "Connection failed" in result.content
    assert result.finish_reason == "error"


@pytest.mark.asyncio
async def test_chat_reasoning_param_format():
    """reasoning_effort should be sent as reasoning={effort: ...} not a flat string."""
    provider = AzureOpenAIProvider(
        api_key="k", api_base="https://test.openai.azure.com", default_model="gpt-5-chat",
    )
    mock_resp = _make_sdk_response(content="thought")
    provider._client.responses = MagicMock()
    provider._client.responses.create = AsyncMock(return_value=mock_resp)

    await provider.chat(
        [{"role": "user", "content": "think"}], reasoning_effort="medium",
    )

    call_kwargs = provider._client.responses.create.call_args[1]
    assert call_kwargs["reasoning"] == {"effort": "medium"}
    assert "reasoning_effort" not in call_kwargs


# ---------------------------------------------------------------------------
# chat_stream()
# ---------------------------------------------------------------------------


@pytest.mark.asyncio
async def test_chat_stream_success():
    """Streaming should call on_content_delta and return combined response."""
    provider = AzureOpenAIProvider(
        api_key="test-key", api_base="https://test.openai.azure.com", default_model="gpt-4o",
    )

    # Build mock SDK stream events
    events = []
    ev1 = MagicMock(type="response.output_text.delta", delta="Hello")
    ev2 = MagicMock(type="response.output_text.delta", delta=" world")
    resp_obj = MagicMock(status="completed")
    ev3 = MagicMock(type="response.completed", response=resp_obj)
    events = [ev1, ev2, ev3]

    async def mock_stream():
        for e in events:
            yield e

    provider._client.responses = MagicMock()
    provider._client.responses.create = AsyncMock(return_value=mock_stream())

    deltas: list[str] = []

    async def on_delta(text: str) -> None:
        deltas.append(text)

    result = await provider.chat_stream(
        [{"role": "user", "content": "Hi"}], on_content_delta=on_delta,
    )

    assert result.content == "Hello world"
    assert result.finish_reason == "stop"
    assert deltas == ["Hello", " world"]


@pytest.mark.asyncio
async def test_chat_stream_with_tool_calls():
    """Streaming tool calls should be accumulated correctly."""
    provider = AzureOpenAIProvider(
        api_key="k", api_base="https://test.openai.azure.com", default_model="gpt-4o",
    )

    item_added = MagicMock(type="function_call", call_id="call_1", id="fc_1", arguments="")
    item_added.name = "get_weather"
    ev_added = MagicMock(type="response.output_item.added", item=item_added)
    ev_args_delta = MagicMock(type="response.function_call_arguments.delta", call_id="call_1", delta='{"loc')
    ev_args_done = MagicMock(
        type="response.function_call_arguments.done",
        call_id="call_1", arguments='{"location":"SF"}',
    )
    item_done = MagicMock(
        type="function_call", call_id="call_1", id="fc_1",
        arguments='{"location":"SF"}',
    )
    item_done.name = "get_weather"
    ev_item_done = MagicMock(type="response.output_item.done", item=item_done)
    resp_obj = MagicMock(status="completed")
    ev_completed = MagicMock(type="response.completed", response=resp_obj)

    async def mock_stream():
        for e in [ev_added, ev_args_delta, ev_args_done, ev_item_done, ev_completed]:
            yield e

    provider._client.responses = MagicMock()
    provider._client.responses.create = AsyncMock(return_value=mock_stream())

    result = await provider.chat_stream(
        [{"role": "user", "content": "weather?"}],
        tools=[{"type": "function", "function": {"name": "get_weather", "parameters": {}}}],
    )

    assert len(result.tool_calls) == 1
    assert result.tool_calls[0].name == "get_weather"
    assert result.tool_calls[0].arguments == {"location": "SF"}


@pytest.mark.asyncio
async def test_chat_stream_error():
    """Streaming should return error when SDK raises."""
    provider = AzureOpenAIProvider(
        api_key="k", api_base="https://test.openai.azure.com", default_model="gpt-4o",
    )
    provider._client.responses = MagicMock()
    provider._client.responses.create = AsyncMock(side_effect=Exception("Connection failed"))

    result = await provider.chat_stream([{"role": "user", "content": "Hi"}])

    assert "Connection failed" in result.content
    assert result.finish_reason == "error"


# ---------------------------------------------------------------------------
# get_default_model
# ---------------------------------------------------------------------------


def test_get_default_model():
    provider = AzureOpenAIProvider(
        api_key="k", api_base="https://r.com", default_model="my-deploy",
    )
    assert provider.get_default_model() == "my-deploy"