"""
异步 AI 辅助生成 API

将原有的同步 AI 生成改为异步任务模式
"""
from fastapi import APIRouter, HTTPException, Depends, BackgroundTasks
from typing import Dict, Any, Optional, List
from pydantic import BaseModel
import asyncio

from app.core.llm.glm_client import get_glm_client
from app.core.skills.skill_manager import get_skill_manager
from app.core.task_manager import get_task_manager, TaskManager
from app.models.task import TaskType, TaskStatus
from app.api.v1.ai_assistant import build_enhanced_system_prompt
from app.utils.logger import get_logger

logger = get_logger(__name__)

router = APIRouter(prefix="/ai-assistant/async", tags=["AI 异步生成"])


# ============================================================================
# 请求模型
# ============================================================================

class SkillInfo(BaseModel):
    """Skill 信息（由前端传递）"""
    id: str
    name: str
    behavior: str  # behavior_guide 内容


# ============================================================================
# 任务执行器
# ============================================================================

async def execute_generate_characters(
    task_manager: TaskManager,
    task_id: str,
    params: Dict[str, Any]
) -> Dict[str, Any]:
    """执行人物生成任务"""
    try:
        glm_client = get_glm_client()
        skill_manager = get_skill_manager()

        # 更新进度
        task_manager.update_task_progress(
            task_id, 10, 100,
            "正在构建提示词..."
        )

        # 构建系统提示词
        base_role = "你是专业的剧集创作专家，擅长创作丰富立体的人物角色。"
        skills = params.get("skills", [])
        system_prompt = await build_enhanced_system_prompt(
            base_role=base_role,
            skills=skills,
            skill_manager=skill_manager
        )

        # 构建用户提示
        extra_info = ""
        if params.get("projectName"):
            extra_info += f"\n项目名称：{params['projectName']}"
        if params.get("totalEpisodes"):
            extra_info += f"\n总集数：{params['totalEpisodes']}"
        if params.get("genre"):
            extra_info += f"\n类型：{params['genre']}"

        custom_requirements = ""
        if params.get("customPrompt"):
            custom_requirements = f"\n【用户自定义要求】\n{params['customPrompt']}\n"

        prompt = f"""请根据以下想法生成 3-5 个主要人物设定：

用户想法：{params['idea']}{extra_info}{custom_requirements}

要求：
1. 每个人物包含：姓名、身份、性格、说话风格、背景故事
2. 人物之间要有关系冲突
3. 每个人物 50-100 字
4. 格式：姓名：身份 - 性格 - 说话风格 - 背景故事
5. 严格遵守上面【应用技能指导】中的要求

请按以下格式输出：
【人物1】
姓名：xxx
身份：xxx
性格：xxx
说话风格：xxx
背景故事：xxx
【人物2】
...
"""

        task_manager.update_task_progress(
            task_id, 30, 100,
            "正在调用 AI 生成..."
        )

        response = await glm_client.chat(
            messages=[
                {"role": "system", "content": system_prompt},
                {"role": "user", "content": prompt}
            ],
            temperature=0.9
        )

        task_manager.update_task_progress(
            task_id, 90, 100,
            "正在处理结果..."
        )

        content = response["choices"][0]["message"]["content"]

        task_manager.update_task_progress(
            task_id, 100, 100,
            "生成完成！"
        )

        return {
            "success": True,
            "characters": content,
            "usage": response.get("usage")
        }

    except Exception as e:
        logger.error(f"人物生成失败: {str(e)}")
        raise


async def execute_generate_outline(
    task_manager: TaskManager,
    task_id: str,
    params: Dict[str, Any]
) -> Dict[str, Any]:
    """执行大纲生成任务"""
    try:
        glm_client = get_glm_client()
        skill_manager = get_skill_manager()

        task_manager.update_task_progress(
            task_id, 10, 100,
            "正在构建提示词..."
        )

        base_role = "你是专业的剧集创作专家，擅长构建引人入胜的剧情结构和故事节奏。"
        skills = params.get("skills", [])
        system_prompt = await build_enhanced_system_prompt(
            base_role=base_role,
            skills=skills,
            skill_manager=skill_manager
        )

        custom_requirements = ""
        if params.get("customPrompt"):
            custom_requirements = f"\n【用户自定义要求】\n{params['customPrompt']}\n"

        prompt = f"""请根据以下想法生成完整的剧集大纲：

用户想法：{params['idea']}
总集数：{params['totalEpisodes']}
类型：{params['genre']}
{f"项目名称：{params['projectName']}" if params.get('projectName') else ''}{custom_requirements}

要求：
1. 将故事分为 4-5 个阶段
2. 每个阶段包含具体的集数范围
3. 标注每个阶段的关键事件和转折点
4. 字数 200-400 字
5. 严格遵守上面【应用技能指导】中的要求

请按以下格式输出：
【阶段1】EPxx-EPxx：阶段名称
内容概要...

【阶段2】EPxx-EPxx：阶段名称
...
"""

        task_manager.update_task_progress(
            task_id, 30, 100,
            "正在调用 AI 生成..."
        )

        response = await glm_client.chat(
            messages=[
                {"role": "system", "content": system_prompt},
                {"role": "user", "content": prompt}
            ],
            temperature=0.9
        )

        task_manager.update_task_progress(
            task_id, 90, 100,
            "正在处理结果..."
        )

        content = response["choices"][0]["message"]["content"]

        task_manager.update_task_progress(
            task_id, 100, 100,
            "生成完成！"
        )

        return {
            "success": True,
            "outline": content,
            "usage": response.get("usage")
        }

    except Exception as e:
        logger.error(f"大纲生成失败: {str(e)}")
        raise


async def execute_generate_world(
    task_manager: TaskManager,
    task_id: str,
    params: Dict[str, Any]
) -> Dict[str, Any]:
    """执行世界观生成任务"""
    try:
        glm_client = get_glm_client()
        skill_manager = get_skill_manager()

        task_manager.update_task_progress(
            task_id, 10, 100,
            "正在构建提示词..."
        )

        base_role = "你是专业的世界观设定专家，擅长构建架空世界的背景设定。"
        skills = params.get("skills", [])
        system_prompt = await build_enhanced_system_prompt(
            base_role=base_role,
            skills=skills,
            skill_manager=skill_manager
        )

        custom_requirements = ""
        if params.get("customPrompt"):
            custom_requirements = f"\n【用户自定义要求】\n{params['customPrompt']}\n"

        prompt = f"""请根据以下想法生成世界观设定：

用户想法：{params['idea']}
类型：{params['genre']}
{f"项目名称：{params['projectName']}" if params.get('projectName') else ''}{custom_requirements}

要求：
1. 描述时代背景（朝代、架空世界等）
2. 描述地理环境和主要场景
3. 描述社会结构（权力体系、阶级关系）
4. 描述文化特色（习俗、服饰、语言等）
5. 字数 200-500 字
6. 严格遵守上面【应用技能指导】中的要求

请输出详细的世界观设定：
"""

        task_manager.update_task_progress(
            task_id, 30, 100,
            "正在调用 AI 生成..."
        )

        response = await glm_client.chat(
            messages=[
                {"role": "system", "content": system_prompt},
                {"role": "user", "content": prompt}
            ],
            temperature=0.9
        )

        task_manager.update_task_progress(
            task_id, 90, 100,
            "正在处理结果..."
        )

        content = response["choices"][0]["message"]["content"]

        task_manager.update_task_progress(
            task_id, 100, 100,
            "生成完成！"
        )

        return {
            "success": True,
            "worldSetting": content,
            "usage": response.get("usage")
        }

    except Exception as e:
        logger.error(f"世界观生成失败: {str(e)}")
        raise


# ============================================================================
# 异步任务创建端点
# ============================================================================

class GenerateCharactersRequest(BaseModel):
    """生成人物设定请求（异步）"""
    idea: str
    projectName: Optional[str] = None
    totalEpisodes: Optional[int] = None
    genre: Optional[str] = "古风"
    skills: Optional[List[SkillInfo]] = None
    customPrompt: Optional[str] = None
    projectId: Optional[str] = None  # 关联项目ID


class GenerateOutlineRequest(BaseModel):
    """生成大纲请求（异步）"""
    idea: str
    totalEpisodes: int = 30
    genre: str = "古风"
    projectName: Optional[str] = None
    skills: Optional[List[SkillInfo]] = None
    customPrompt: Optional[str] = None
    projectId: Optional[str] = None


class GenerateWorldRequest(BaseModel):
    """生成世界观请求（异步）"""
    idea: str
    projectName: Optional[str] = None
    genre: Optional[str] = "古风"
    skills: Optional[List[SkillInfo]] = None
    customPrompt: Optional[str] = None
    projectId: Optional[str] = None


@router.post("/generate/characters")
async def generate_characters_async(
    request: GenerateCharactersRequest,
    background_tasks: BackgroundTasks,
    task_manager: TaskManager = Depends(get_task_manager)
):
    """
    异步生成人物设定

    返回任务ID，需要通过轮询 /tasks/{task_id} 获取结果
    """
    # 创建任务
    task = task_manager.create_task(
        task_type=TaskType.GENERATE_CHARACTERS,
        params=request.dict(exclude={"projectId"}),
        project_id=request.projectId
    )

    # 在后台执行
    async def run_task():
        await task_manager.execute_task_async(
            task.id,
            lambda p: execute_generate_characters(task_manager, task.id, p)
        )

    asyncio.create_task(run_task())

    return {
        "success": True,
        "taskId": task.id,
        "message": "任务已创建，正在后台执行"
    }


@router.post("/generate/outline")
async def generate_outline_async(
    request: GenerateOutlineRequest,
    task_manager: TaskManager = Depends(get_task_manager)
):
    """
    异步生成大纲

    返回任务ID，需要通过轮询 /tasks/{task_id} 获取结果
    """
    # 创建任务
    task = task_manager.create_task(
        task_type=TaskType.GENERATE_OUTLINE,
        params=request.dict(exclude={"projectId"}),
        project_id=request.projectId
    )

    # 在后台执行
    async def run_task():
        await task_manager.execute_task_async(
            task.id,
            lambda p: execute_generate_outline(task_manager, task.id, p)
        )

    asyncio.create_task(run_task())

    return {
        "success": True,
        "taskId": task.id,
        "message": "任务已创建，正在后台执行"
    }


@router.post("/generate/world")
async def generate_world_async(
    request: GenerateWorldRequest,
    task_manager: TaskManager = Depends(get_task_manager)
):
    """
    异步生成世界观设定

    返回任务ID，需要通过轮询 /tasks/{task_id} 获取结果
    """
    # 创建任务
    task = task_manager.create_task(
        task_type=TaskType.GENERATE_WORLD,
        params=request.dict(exclude={"projectId"}),
        project_id=request.projectId
    )

    # 在后台执行
    async def run_task():
        await task_manager.execute_task_async(
            task.id,
            lambda p: execute_generate_world(task_manager, task.id, p)
        )

    asyncio.create_task(run_task())

    return {
        "success": True,
        "taskId": task.id,
        "message": "任务已创建，正在后台执行"
    }