"""共享测试 fixtures 和配置"""

from typing import Optional
from unittest.mock import Mock

import pytest


class MockAIClient:
    """模拟 AI 客户端"""

    def __init__(self, response: str = "Mock AI response"):
        self.response = response

    def generate(
        self,
        prompt: str,
        max_tokens: int = 16000,
        disable_reasoning: Optional[bool] = None
    ) -> str:
        """生成模拟响应"""
        return self.response


@pytest.fixture
def mock_ai_client():
    """提供模拟 AI 客户端"""
    return MockAIClient()


@pytest.fixture
def sample_segments():
    """提供示例字幕分段数据"""
    return [
        {"index": 1, "start": "00:00:00,000", "end": "00:00:05,000", "text": "大家好，欢迎来到我的频道"},
        {"index": 2, "start": "00:00:05,000", "end": "00:00:10,000", "text": "今天我们要讲的是机器学习的基础知识"},
        {"index": 3, "start": "00:00:10,000", "end": "00:00:15,000", "text": "首先，什么是机器学习"},
        {"index": 4, "start": "00:00:15,000", "end": "00:00:20,000", "text": "机器学习是人工智能的一个分支"},
        {"index": 5, "start": "00:00:20,000", "end": "00:00:25,000", "text": "它让计算机能够从数据中学习"},
    ]


@pytest.fixture
def sample_metadata():
    """提供示例视频元数据"""
    return {
        "title": "机器学习入门教程",
        "category": "教育",
        "tags": ["编程", "AI", "教程"],
        "description": "从零开始学习机器学习"
    }


@pytest.fixture
def sample_metadata_movie():
    """提供电影类型示例元数据"""
    return {
        "title": "星际穿越",
        "category": "影视",
        "tags": ["科幻", "电影"],
        "description": "一部关于太空探索的科幻电影"
    }