import io
import json
from unittest.mock import Mock, patch

import pytest
from PIL import Image

from services.chat_model_config import ChatModelConfig
from services.vision_service import (
    ImageValidationError,
    build_attachment_warning,
    call_vision_model,
    parse_vision_analysis,
    prepare_image,
)


def _image_bytes(fmt="PNG", size=(120, 80)):
    output = io.BytesIO()
    Image.new("RGB", size, "#f97316").save(output, format=fmt)
    return output.getvalue()


def _config():
    return ChatModelConfig(
        api_base_url="https://model.test/v1",
        api_key="secret-key",
        model="chat-model",
        max_tokens=1024,
        timeout_seconds=30,
        vision_model="vision-model",
        ocr_model="ocr-model",
        vision_max_tokens=2048,
        vision_timeout_seconds=90,
        source="test",
    )


def test_prepare_image_validates_and_reencodes_without_metadata():
    prepared = prepare_image(_image_bytes())

    assert prepared.mime_type == "image/jpeg"
    assert prepared.width == 120
    assert prepared.height == 80
    with Image.open(io.BytesIO(prepared.data)) as image:
        assert image.format == "JPEG"
        assert not image.getexif()


def test_prepare_image_rejects_non_image_content():
    with pytest.raises(ImageValidationError, match="格式无效"):
        prepare_image(b"not-an-image")


def test_vision_request_uses_openai_compatible_image_content():
    response = Mock()
    response.raise_for_status.return_value = None
    response.json.return_value = {
        "choices": [{"message": {"content": '{"category":"general_image"}'}}],
        "usage": {"total_tokens": 88},
    }
    prepared = prepare_image(_image_bytes())

    with patch("services.vision_service.httpx.post", return_value=response) as request:
        result = call_vision_model(
            prepared,
            _config(),
            model="vision-model",
            prompt="describe",
            json_output=True,
        )

    payload = request.call_args.kwargs["json"]
    content = payload["messages"][0]["content"]
    assert payload["model"] == "vision-model"
    assert payload["response_format"] == {"type": "json_object"}
    assert content[0]["type"] == "image_url"
    assert content[0]["image_url"]["url"].startswith("data:image/jpeg;base64,")
    assert content[1] == {"type": "text", "text": "describe"}
    assert result["usage"]["total_tokens"] == 88


def test_parse_medical_analysis_and_build_warning():
    analysis = parse_vision_analysis(json.dumps({
        "category": "medical_document",
        "summary": "血常规报告",
        "visible_text": "白细胞 11.2",
        "key_facts": ["白细胞偏高"],
        "uncertainties": ["日期模糊"],
        "medical": {"document_type": "检验报告"},
    }, ensure_ascii=False))

    assert analysis["category"] == "medical_document"
    assert analysis["medical"]["document_type"] == "检验报告"
    warning = build_attachment_warning(analysis, ocr_failed=True)
    assert "日期模糊" in warning
    assert "人工核对" in warning
    assert "不能替代医生诊断" in warning