#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
提示词API路由
"""

import logging
from typing import Dict, Any, Optional
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel, Field

from api.services.prompt_service import PromptService
from api.services.prompt_builder import PromptBuilderService
from api.dependencies import get_config, get_tweet_service

logger = logging.getLogger(__name__)

# 创建路由
router = APIRouter(
    tags=["prompt"],
    responses={404: {"description": "Not found"}},
)

# 依赖注入函数
def get_prompt_service():
    """获取提示词服务"""
    from core.config import get_config_manager
    return PromptService(get_config_manager())

def get_prompt_builder():
    """获取提示词构建器服务"""
    from core.config import get_config_manager
    config_manager = get_config_manager()
    prompt_service = PromptService(config_manager)
    return PromptBuilderService(config_manager, prompt_service)


# 请求和响应模型
class PromptRequest(BaseModel):
    """提示词请求模型"""
    style: str = Field(..., description="内容风格")
    audience: str = Field(..., description="目标受众")
    
    class Config:
        schema_extra = {
            "example": {
                "style": "攻略风",
                "audience": "亲子向"
            }
        }


class PromptResponse(BaseModel):
    """提示词响应模型"""
    style_content: str = Field(..., description="风格提示词")
    audience_content: str = Field(..., description="受众提示词")
    
    class Config:
        schema_extra = {
            "example": {
                "style_content": "以实用信息为主，包含详细的游玩路线...",
                "audience_content": "家庭出游，有小孩同行，关注安全性..."
            }
        }


class PromptBuilderRequest(BaseModel):
    """提示词构建器请求模型"""
    topic: Dict[str, Any] = Field(..., description="选题信息")
    step: Optional[str] = Field(None, description="步骤，如topic、content、judge等")
    
    class Config:
        schema_extra = {
            "example": {
                "topic": {
                    "index": "1",
                    "date": "2023-07-15",
                    "object": "北京故宫",
                    "product": "故宫门票",
                    "style": "攻略风",
                    "targetAudience": "亲子向",
                    "logic": "暑期旅游热门景点推荐"
                },
                "step": "content"
            }
        }


class PromptBuilderResponse(BaseModel):
    """提示词构建器响应模型"""
    system_prompt: str = Field(..., description="系统提示词")
    user_prompt: str = Field(..., description="用户提示词")
    
    class Config:
        schema_extra = {
            "example": {
                "system_prompt": "你是一位专业的旅游内容创作者...",
                "user_prompt": "请为北京故宫创作一篇旅游攻略..."
            }
        }


class GenerateContentResponse(BaseModel):
    """生成内容响应模型"""
    request_id: str = Field(..., description="请求ID")
    topic_index: str = Field(..., description="选题索引")
    content: Dict[str, Any] = Field(..., description="生成的内容")
    
    class Config:
        schema_extra = {
            "example": {
                "request_id": "content-20240715-123456-a1b2c3d4",
                "topic_index": "1",
                "content": {
                    "title": "【北京故宫】避开人潮的秘密路线，90%的人都不知道！",
                    "content": "故宫，作为中国最著名的文化遗产之一...",
                    "tag": ["北京旅游", "故宫", "旅游攻略", "避暑胜地"]
                }
            }
        }


@router.post("/get-style-audience", response_model=PromptResponse)
async def get_style_audience(
    request: PromptRequest,
    prompt_service: PromptService = Depends(get_prompt_service)
):
    """获取风格和受众提示词"""
    try:
        style_content = prompt_service.get_style_content(request.style)
        audience_content = prompt_service.get_audience_content(request.audience)
        
        return PromptResponse(
            style_content=style_content,
            audience_content=audience_content
        )
    except Exception as e:
        logger.error(f"获取提示词失败: {e}")
        raise HTTPException(status_code=500, detail=f"获取提示词失败: {str(e)}")


@router.post("/build-prompt", response_model=PromptBuilderResponse)
async def build_prompt(
    request: PromptBuilderRequest,
    prompt_builder: PromptBuilderService = Depends(get_prompt_builder)
):
    """构建完整提示词"""
    try:
        # 根据请求中的step确定构建哪种类型的提示词
        step = request.step or "content"
        
        if step == "topic":
            # 构建选题提示词
            # 从topic中提取必要的参数
            numTopics = request.topic.get("numTopics", 5)
            month = request.topic.get("month", "7")
            system_prompt, user_prompt = prompt_builder.build_topic_prompt(
                dates=month,
                numTopics=numTopics
            )
        elif step == "judge":
            # 构建审核提示词
            # 需要提供生成的内容
            content = request.topic.get("content", {})
            system_prompt, user_prompt = prompt_builder.build_judge_prompt(request.topic, content)
        else:
            # 默认构建内容生成提示词
            system_prompt, user_prompt = prompt_builder.build_content_prompt(request.topic, step)
        
        return PromptBuilderResponse(
            system_prompt=system_prompt,
            user_prompt=user_prompt
        )
    except Exception as e:
        logger.error(f"构建提示词失败: {e}")
        raise HTTPException(status_code=500, detail=f"构建提示词失败: {str(e)}")


@router.post("/generate-content", response_model=GenerateContentResponse)
async def generate_content(
    request: PromptBuilderRequest,
    prompt_builder: PromptBuilderService = Depends(get_prompt_builder),
    tweet_service = Depends(get_tweet_service)
):
    """使用构建的提示词生成内容"""
    try:
        # 构建提示词
        step = request.step or "content"
        system_prompt, user_prompt = prompt_builder.build_content_prompt(request.topic, step)
        
        # 使用提示词生成内容
        request_id, topic_index, content = await tweet_service.generate_content_with_prompt(
            topic=request.topic,
            system_prompt=system_prompt,
            user_prompt=user_prompt
        )
        
        return GenerateContentResponse(
            request_id=request_id,
            topic_index=topic_index,
            content=content
        )
    except Exception as e:
        logger.error(f"生成内容失败: {e}")
        raise HTTPException(status_code=500, detail=f"生成内容失败: {str(e)}")