"""即梦AI工具 - FastAPI接口"""
import os
from typing import Optional, Literal
from contextlib import asynccontextmanager
from fastapi import FastAPI, HTTPException
from pydantic import BaseModel, Field
from dotenv import load_dotenv
from jimeng_client import JimengClient

# 加载环境变量
load_dotenv()

# 全局客户端实例
client: Optional[JimengClient] = None


@asynccontextmanager
async def lifespan(app: FastAPI):
    """应用生命周期管理"""
    global client
    
    api_key = os.getenv("JIMENG_API_KEY")
    cookie = os.getenv("JIMENG_COOKIE")
    base_url = os.getenv("JIMENG_BASE_URL", "https://api.jimeng.ai")
    
    client = JimengClient(api_key=api_key, cookie=cookie, base_url=base_url)
    
    yield
    
    if client:
        await client.close()


app = FastAPI(
    title="即梦AI工具",
    description="支持文生图(Seendance 2.0)和图生视频(Seedream Lite 5.0)",
    version="1.0.0",
    lifespan=lifespan
)


class GenerateRequest(BaseModel):
    """生成请求模型"""
    action: Literal["text2image", "image2video", "query_status"] = Field(
        ...,
        description="操作类型"
    )
    
    # 通用参数
    prompt: Optional[str] = Field(None, description="正向提示词")
    negative_prompt: Optional[str] = Field("", description="负向提示词")
    seed: Optional[int] = Field(-1, description="随机种子")
    
    # 文生图参数
    model: Optional[str] = Field("seendance_2.0", description="模型选择")
    aspect_ratio: Optional[str] = Field("1:1", description="图片长宽比")
    image_count: Optional[int] = Field(1, ge=1, le=4, description="生成图片数量")
    cfg_scale: Optional[float] = Field(7.0, ge=1.0, le=20.0, description="创意强度")
    steps: Optional[int] = Field(20, ge=10, le=50, description="生成步数")
    
    # 图生视频参数
    image_url: Optional[str] = Field(None, description="参考图片URL")
    image_base64: Optional[str] = Field(None, description="参考图片Base64")
    video_duration: Optional[int] = Field(5, description="视频时长(秒)")
    motion_strength: Optional[float] = Field(0.5, ge=0.0, le=1.0, description="运动强度")
    start_frame: Optional[str] = Field(None, description="首帧图片")
    end_frame: Optional[str] = Field(None, description="尾帧图片")
    
    # 查询参数
    task_id: Optional[str] = Field(None, description="任务ID")
    
    # 认证参数
    cookie: Optional[str] = Field(None, description="认证Cookie")
    api_key: Optional[str] = Field(None, description="API密钥")


class GenerateResponse(BaseModel):
    """生成响应模型"""
    task_id: str
    status: Literal["pending", "processing", "completed", "failed"]
    progress: Optional[float] = None
    result: Optional[dict] = None
    error: Optional[str] = None
    estimated_time: Optional[int] = None


@app.get("/health")
async def health_check():
    """健康检查"""
    return {
        "status": "healthy",
        "service": "jimeng_ai",
        "version": "1.0.0"
    }


@app.post("/generate", response_model=GenerateResponse)
async def generate(request: GenerateRequest):
    """创建生成任务"""
    if not client:
        raise HTTPException(status_code=500, detail="Client not initialized")
    
    # 使用请求中的认证信息（如果提供）
    active_client = client
    if request.api_key or request.cookie:
        active_client = JimengClient(
            api_key=request.api_key or client.api_key,
            cookie=request.cookie or client.cookie,
            base_url=client.base_url
        )
    
    try:
        if request.action == "text2image":
            if not request.prompt:
                raise HTTPException(status_code=400, detail="prompt is required for text2image")
            
            result = await active_client.text2image(
                prompt=request.prompt,
                negative_prompt=request.negative_prompt or "",
                aspect_ratio=request.aspect_ratio or "1:1",
                image_count=request.image_count or 1,
                cfg_scale=request.cfg_scale or 7.0,
                steps=request.steps or 20,
                seed=request.seed or -1
            )
            
        elif request.action == "image2video":
            if not request.image_url and not request.image_base64:
                raise HTTPException(
                    status_code=400,
                    detail="Either image_url or image_base64 is required for image2video"
                )
            
            result = await active_client.image2video(
                image_url=request.image_url,
                image_base64=request.image_base64,
                prompt=request.prompt or "",
                video_duration=request.video_duration or 5,
                motion_strength=request.motion_strength or 0.5,
                start_frame=request.start_frame,
                end_frame=request.end_frame,
                seed=request.seed or -1
            )
            
        elif request.action == "query_status":
            if not request.task_id:
                raise HTTPException(status_code=400, detail="task_id is required for query_status")
            
            result = await active_client.query_status(request.task_id)
            
        else:
            raise HTTPException(status_code=400, detail=f"Unknown action: {request.action}")
        
        return GenerateResponse(**result)
        
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
    finally:
        if active_client != client:
            await active_client.close()


@app.get("/status/{task_id}", response_model=GenerateResponse)
async def get_status(task_id: str):
    """查询任务状态"""
    if not client:
        raise HTTPException(status_code=500, detail="Client not initialized")
    
    try:
        result = await client.query_status(task_id)
        return GenerateResponse(**result)
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))


@app.post("/cleanup")
async def cleanup_cache():
    """清理过期缓存"""
    if not client:
        raise HTTPException(status_code=500, detail="Client not initialized")
    
    client.cleanup_cache()
    return {"status": "success", "message": "Cache cleaned up"}


if __name__ == "__main__":
    import uvicorn
    import argparse
    
    parser = argparse.ArgumentParser(description="即梦AI工具服务")
    parser.add_argument("--port", type=int, default=8000, help="服务端口")
    parser.add_argument("--host", type=str, default="0.0.0.0", help="服务地址")
    args = parser.parse_args()
    
    uvicorn.run(app, host=args.host, port=args.port)