确认了根据获得的提示词进行内容生成的功能
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@ -6,6 +6,7 @@ API依赖注入模块
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"""
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from typing import Optional
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from fastapi import Depends
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from core.config import get_config_manager, ConfigManager
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from core.ai import AIAgent
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from utils.file_io import OutputManager
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@ -50,3 +51,8 @@ def get_output_manager() -> OutputManager:
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if output_manager is None:
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raise RuntimeError("输出管理器未初始化")
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return output_manager
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def get_tweet_service():
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"""获取文字内容服务"""
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from api.services.tweet import TweetService
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return TweetService(get_ai_agent(), get_config(), get_output_manager())
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@ -6,171 +6,138 @@
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"""
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import logging
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from typing import Dict, Any, Optional
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from fastapi import APIRouter, Depends, HTTPException
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from typing import List, Dict, Any
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from pydantic import BaseModel, Field
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from core.config import ConfigManager
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from api.services.prompt_service import PromptService
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from api.services.prompt_builder import PromptBuilderService
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from api.models.prompt import (
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StyleRequest, StyleResponse, StyleListResponse,
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AudienceRequest, AudienceResponse, AudienceListResponse,
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ScenicSpotRequest, ScenicSpotResponse, ScenicSpotListResponse,
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PromptBuilderRequest, PromptBuilderResponse
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)
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# 从依赖注入模块导入依赖
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from api.dependencies import get_config
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from api.dependencies import get_config, get_tweet_service
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logger = logging.getLogger(__name__)
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# 创建路由
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router = APIRouter()
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router = APIRouter(
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tags=["prompt"],
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responses={404: {"description": "Not found"}},
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)
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# 依赖注入函数
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def get_prompt_service(
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config_manager: ConfigManager = Depends(get_config)
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) -> PromptService:
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def get_prompt_service():
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"""获取提示词服务"""
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return PromptService(config_manager)
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from core.config import get_config_manager
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return PromptService(get_config_manager())
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def get_prompt_builder(
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config_manager: ConfigManager = Depends(get_config),
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prompt_service: PromptService = Depends(get_prompt_service)
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) -> PromptBuilderService:
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"""获取提示词构建服务"""
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def get_prompt_builder():
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"""获取提示词构建器服务"""
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from core.config import get_config_manager
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config_manager = get_config_manager()
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prompt_service = PromptService(config_manager)
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return PromptBuilderService(config_manager, prompt_service)
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@router.get("/styles", response_model=StyleListResponse)
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async def get_all_styles(
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# 请求和响应模型
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class PromptRequest(BaseModel):
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"""提示词请求模型"""
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style: str = Field(..., description="内容风格")
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audience: str = Field(..., description="目标受众")
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class Config:
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schema_extra = {
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"example": {
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"style": "攻略风",
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"audience": "亲子向"
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}
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}
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class PromptResponse(BaseModel):
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"""提示词响应模型"""
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style_content: str = Field(..., description="风格提示词")
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audience_content: str = Field(..., description="受众提示词")
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class Config:
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schema_extra = {
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"example": {
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"style_content": "以实用信息为主，包含详细的游玩路线...",
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"audience_content": "家庭出游，有小孩同行，关注安全性..."
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}
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}
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class PromptBuilderRequest(BaseModel):
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"""提示词构建器请求模型"""
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topic: Dict[str, Any] = Field(..., description="选题信息")
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step: Optional[str] = Field(None, description="步骤，如topic、content、judge等")
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class Config:
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schema_extra = {
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"example": {
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"topic": {
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"index": "1",
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"date": "2023-07-15",
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"object": "北京故宫",
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"product": "故宫门票",
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"style": "攻略风",
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"target_audience": "亲子向",
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"logic": "暑期旅游热门景点推荐"
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},
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"step": "content"
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}
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}
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class PromptBuilderResponse(BaseModel):
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"""提示词构建器响应模型"""
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system_prompt: str = Field(..., description="系统提示词")
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user_prompt: str = Field(..., description="用户提示词")
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class Config:
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schema_extra = {
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"example": {
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"system_prompt": "你是一位专业的旅游内容创作者...",
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"user_prompt": "请为北京故宫创作一篇旅游攻略..."
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}
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}
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class GenerateContentResponse(BaseModel):
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"""生成内容响应模型"""
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request_id: str = Field(..., description="请求ID")
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topic_index: str = Field(..., description="选题索引")
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content: Dict[str, Any] = Field(..., description="生成的内容")
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class Config:
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schema_extra = {
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"example": {
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"request_id": "content_20230715_123456",
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"topic_index": "1",
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"content": {
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"title": "【北京故宫】避开人潮的秘密路线，90%的人都不知道！",
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"content": "故宫，作为中国最著名的文化遗产之一...",
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"tag": ["北京旅游", "故宫", "旅游攻略", "避暑胜地"]
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}
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}
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}
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@router.post("/get-style-audience", response_model=PromptResponse)
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async def get_style_audience(
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request: PromptRequest,
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prompt_service: PromptService = Depends(get_prompt_service)
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):
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"""获取所有内容风格"""
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"""获取风格和受众提示词"""
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try:
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styles_dict = prompt_service.get_all_styles()
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# 将字典列表转换为StyleResponse对象列表
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styles = [StyleResponse(name=style["name"], description=style["description"]) for style in styles_dict]
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return StyleListResponse(styles=styles)
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style_content = prompt_service.get_style_content(request.style)
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audience_content = prompt_service.get_audience_content(request.audience)
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return PromptResponse(
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style_content=style_content,
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audience_content=audience_content
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)
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except Exception as e:
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logger.error(f"获取所有风格失败: {e}")
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raise HTTPException(status_code=500, detail=f"获取风格列表失败: {str(e)}")
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@router.get("/styles/{style_name}", response_model=StyleResponse)
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async def get_style(
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style_name: str,
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prompt_service: PromptService = Depends(get_prompt_service)
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):
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"""获取指定内容风格"""
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try:
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content = prompt_service.get_style_content(style_name)
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return StyleResponse(name=style_name, description=content)
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except Exception as e:
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logger.error(f"获取风格 '{style_name}' 失败: {e}")
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raise HTTPException(status_code=404, detail=f"未找到风格: {style_name}")
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@router.post("/styles", response_model=StyleResponse)
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async def create_or_update_style(
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style: StyleRequest,
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prompt_service: PromptService = Depends(get_prompt_service)
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):
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"""创建或更新内容风格"""
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try:
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if not style.description:
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# 如果没有提供描述，则获取现有的
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content = prompt_service.get_style_content(style.name)
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return StyleResponse(name=style.name, description=content)
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success = prompt_service.save_style(style.name, style.description)
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if not success:
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raise HTTPException(status_code=500, detail=f"保存风格 '{style.name}' 失败")
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return StyleResponse(name=style.name, description=style.description)
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except Exception as e:
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logger.error(f"保存风格 '{style.name}' 失败: {e}")
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raise HTTPException(status_code=500, detail=f"操作失败: {str(e)}")
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@router.get("/audiences", response_model=AudienceListResponse)
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async def get_all_audiences(
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prompt_service: PromptService = Depends(get_prompt_service)
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):
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"""获取所有目标受众"""
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try:
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audiences_dict = prompt_service.get_all_audiences()
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# 将字典列表转换为AudienceResponse对象列表
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audiences = [AudienceResponse(name=audience["name"], description=audience["description"]) for audience in audiences_dict]
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return AudienceListResponse(audiences=audiences)
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except Exception as e:
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logger.error(f"获取所有受众失败: {e}")
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raise HTTPException(status_code=500, detail=f"获取受众列表失败: {str(e)}")
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@router.get("/audiences/{audience_name}", response_model=AudienceResponse)
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async def get_audience(
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audience_name: str,
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prompt_service: PromptService = Depends(get_prompt_service)
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):
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"""获取指定目标受众"""
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try:
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content = prompt_service.get_audience_content(audience_name)
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return AudienceResponse(name=audience_name, description=content)
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except Exception as e:
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logger.error(f"获取受众 '{audience_name}' 失败: {e}")
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raise HTTPException(status_code=404, detail=f"未找到受众: {audience_name}")
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@router.post("/audiences", response_model=AudienceResponse)
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async def create_or_update_audience(
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audience: AudienceRequest,
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prompt_service: PromptService = Depends(get_prompt_service)
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):
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"""创建或更新目标受众"""
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try:
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if not audience.description:
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# 如果没有提供描述，则获取现有的
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content = prompt_service.get_audience_content(audience.name)
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return AudienceResponse(name=audience.name, description=content)
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success = prompt_service.save_audience(audience.name, audience.description)
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if not success:
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raise HTTPException(status_code=500, detail=f"保存受众 '{audience.name}' 失败")
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return AudienceResponse(name=audience.name, description=audience.description)
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except Exception as e:
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logger.error(f"保存受众 '{audience.name}' 失败: {e}")
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raise HTTPException(status_code=500, detail=f"操作失败: {str(e)}")
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@router.get("/scenic-spots", response_model=ScenicSpotListResponse)
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async def get_all_scenic_spots(
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prompt_service: PromptService = Depends(get_prompt_service)
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):
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"""获取所有景区"""
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try:
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spots_dict = prompt_service.get_all_scenic_spots()
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# 将字典列表转换为ScenicSpotResponse对象列表
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spots = [ScenicSpotResponse(name=spot["name"], description=spot["description"]) for spot in spots_dict]
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return ScenicSpotListResponse(spots=spots)
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except Exception as e:
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logger.error(f"获取所有景区失败: {e}")
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raise HTTPException(status_code=500, detail=f"获取景区列表失败: {str(e)}")
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@router.get("/scenic-spots/{spot_name}", response_model=ScenicSpotResponse)
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async def get_scenic_spot(
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spot_name: str,
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prompt_service: PromptService = Depends(get_prompt_service)
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):
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"""获取指定景区信息"""
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try:
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content = prompt_service.get_scenic_spot_info(spot_name)
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return ScenicSpotResponse(name=spot_name, description=content)
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except Exception as e:
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logger.error(f"获取景区 '{spot_name}' 失败: {e}")
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raise HTTPException(status_code=404, detail=f"未找到景区: {spot_name}")
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logger.error(f"获取提示词失败: {e}")
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raise HTTPException(status_code=500, detail=f"获取提示词失败: {str(e)}")
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@router.post("/build-prompt", response_model=PromptBuilderResponse)
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@ -205,3 +172,32 @@ async def build_prompt(
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except Exception as e:
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logger.error(f"构建提示词失败: {e}")
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raise HTTPException(status_code=500, detail=f"构建提示词失败: {str(e)}")
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@router.post("/generate-content", response_model=GenerateContentResponse)
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async def generate_content(
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request: PromptBuilderRequest,
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prompt_builder: PromptBuilderService = Depends(get_prompt_builder),
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tweet_service = Depends(get_tweet_service)
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):
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"""使用构建的提示词生成内容"""
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try:
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# 构建提示词
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step = request.step or "content"
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system_prompt, user_prompt = prompt_builder.build_content_prompt(request.topic, step)
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# 使用提示词生成内容
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request_id, topic_index, content = await tweet_service.generate_content_with_prompt(
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topic=request.topic,
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system_prompt=system_prompt,
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user_prompt=user_prompt
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)
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return GenerateContentResponse(
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request_id=request_id,
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topic_index=topic_index,
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content=content
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)
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except Exception as e:
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logger.error(f"生成内容失败: {e}")
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raise HTTPException(status_code=500, detail=f"生成内容失败: {str(e)}")
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@ -6,36 +6,51 @@
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"""
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import logging
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from typing import List, Dict, Any, Optional
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from fastapi import APIRouter, Depends, HTTPException
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from typing import List, Dict, Any
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from core.config import ConfigManager
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from core.ai import AIAgent
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from utils.file_io import OutputManager
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from api.services.tweet import TweetService
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from api.models.tweet import (
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TopicRequest, TopicResponse,
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ContentRequest, ContentResponse,
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JudgeRequest, JudgeResponse,
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PipelineRequest, PipelineResponse
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)
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from api.services.tweet import TweetService
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from api.dependencies import get_tweet_service
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# 从依赖注入模块导入依赖
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from api.dependencies import get_config, get_ai_agent, get_output_manager
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# 创建一个新的模型用于接收预构建提示词的请求
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from pydantic import BaseModel, Field
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class ContentWithPromptRequest(BaseModel):
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"""带有预构建提示词的内容生成请求模型"""
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topic: Dict[str, Any] = Field(..., description="选题信息")
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system_prompt: str = Field(..., description="系统提示词")
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user_prompt: str = Field(..., description="用户提示词")
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class Config:
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schema_extra = {
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"example": {
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"topic": {
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"index": "1",
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"date": "2023-07-15",
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"object": "北京故宫",
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"product": "故宫门票",
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"style": "旅游攻略",
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"target_audience": "年轻人",
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"logic": "暑期旅游热门景点推荐"
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},
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"system_prompt": "你是一位专业的旅游内容创作者...",
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"user_prompt": "请为以下景点创作一篇旅游文章..."
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}
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}
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logger = logging.getLogger(__name__)
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# 创建路由
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router = APIRouter()
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# 依赖注入函数
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def get_tweet_service(
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config_manager: ConfigManager = Depends(get_config),
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ai_agent: AIAgent = Depends(get_ai_agent),
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output_manager: OutputManager = Depends(get_output_manager)
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) -> TweetService:
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"""获取文字内容服务"""
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return TweetService(ai_agent, config_manager, output_manager)
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router = APIRouter(
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prefix="/tweet",
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tags=["tweet"],
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responses={404: {"description": "Not found"}},
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)
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@router.post("/topics", response_model=TopicResponse, summary="生成选题")
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@ -93,6 +108,35 @@ async def generate_content(
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raise HTTPException(status_code=500, detail=f"生成内容失败: {str(e)}")
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@router.post("/content-with-prompt", response_model=ContentResponse, summary="使用预构建提示词生成内容")
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async def generate_content_with_prompt(
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request: ContentWithPromptRequest,
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tweet_service: TweetService = Depends(get_tweet_service)
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):
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"""
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使用预构建的提示词为选题生成内容
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- **topic**: 选题信息
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- **system_prompt**: 系统提示词
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- **user_prompt**: 用户提示词
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"""
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try:
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request_id, topic_index, content = await tweet_service.generate_content_with_prompt(
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topic=request.topic,
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system_prompt=request.system_prompt,
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user_prompt=request.user_prompt
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)
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return ContentResponse(
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request_id=request_id,
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topic_index=topic_index,
|
||||
content=content
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"使用预构建提示词生成内容失败: {e}", exc_info=True)
|
||||
raise HTTPException(status_code=500, detail=f"使用预构建提示词生成内容失败: {str(e)}")
|
||||
|
||||
|
||||
@router.post("/judge", response_model=JudgeResponse, summary="审核内容")
|
||||
async def judge_content(
|
||||
request: JudgeRequest,
|
||||
|
||||
Binary file not shown.
@ -98,6 +98,30 @@ class TweetService:
|
||||
logger.info(f"内容生成完成，请求ID: {request_id}, 选题索引: {topic_index}")
|
||||
return request_id, topic_index, content
|
||||
|
||||
async def generate_content_with_prompt(self, topic: Dict[str, Any], system_prompt: str, user_prompt: str) -> Tuple[str, str, Dict[str, Any]]:
|
||||
"""
|
||||
使用预构建的提示词为选题生成内容
|
||||
|
||||
Args:
|
||||
topic: 选题信息
|
||||
system_prompt: 系统提示词
|
||||
user_prompt: 用户提示词
|
||||
|
||||
Returns:
|
||||
请求ID、选题索引和生成的内容
|
||||
"""
|
||||
topic_index = topic.get('index', 'unknown')
|
||||
logger.info(f"开始使用预构建提示词为选题 {topic_index} 生成内容")
|
||||
|
||||
# 使用预构建的提示词生成内容
|
||||
content = await self.content_generator.generate_content_with_prompt(topic, system_prompt, user_prompt)
|
||||
|
||||
# 生成请求ID
|
||||
request_id = f"content_{datetime.now().strftime('%Y%m%d_%H%M%S')}_{str(uuid.uuid4())[:8]}"
|
||||
|
||||
logger.info(f"内容生成完成，请求ID: {request_id}, 选题索引: {topic_index}")
|
||||
return request_id, topic_index, content
|
||||
|
||||
async def judge_content(self, topic: Dict[str, Any], content: Dict[str, Any]) -> Tuple[str, str, Dict[str, Any], bool]:
|
||||
"""
|
||||
审核内容
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user