""" AI 大模型对接服务 支持 OpenAI、智谱、百度文心、阿里通义等主流大模型 """ import logging from typing import Optional, Dict, Any, List from datetime import datetime import json logger = logging.getLogger(__name__) class AIService: """AI 服务类""" def __init__(self): self._client_cache: Dict[str, Any] = {} async def generate_comment( self, news_content: str, writing_style: str, persona_description: Optional[str] = None, model_config: Optional[Dict[str, Any]] = None ) -> Optional[Dict[str, Any]]: """ AI 生成评论 :param news_content: 新闻内容 :param writing_style: 写作风格 :param persona_description: 人格描述 :param model_config: 模型配置 :return: 生成结果（包含 content, tokens_used 等） """ prompt = self._build_comment_prompt( news_content, writing_style, persona_description ) return await self._call_ai_api(prompt, model_config) async def generate_reply( self, original_comment: str, news_content: str, writing_style: str, persona_description: Optional[str] = None, model_config: Optional[Dict[str, Any]] = None ) -> Optional[Dict[str, Any]]: """ AI 生成回复 :param original_comment: 原评论 :param news_content: 新闻内容 :param writing_style: 写作风格 :param persona_description: 人格描述 :param model_config: 模型配置 :return: 生成结果 """ prompt = self._build_reply_prompt( original_comment, news_content, writing_style, persona_description ) return await self._call_ai_api(prompt, model_config) def _build_comment_prompt( self, news_content: str, writing_style: str, persona_description: Optional[str] = None ) -> str: """构建评论提示词""" base_prompt = f"""你是一位虚拟用户，请根据以下要求写一条简短的评论： 写作风格：{writing_style} """ if persona_description: base_prompt += f"\n人格特征：{persona_description}\n" base_prompt += f""" 新闻内容： {news_content[:1000]} # 限制长度 请写一条 50-100 字的评论，要符合你的写作风格和人格特征。直接输出评论内容，不要有其他说明。""" return base_prompt def _build_reply_prompt( self, original_comment: str, news_content: str, writing_style: str, persona_description: Optional[str] = None ) -> str: """构建回复提示词""" base_prompt = f"""你是一位虚拟用户，请根据以下要求回复另一条评论： 写作风格：{writing_style} """ if persona_description: base_prompt += f"\n人格特征：{persona_description}\n" base_prompt += f""" 新闻内容： {news_content[:500]} 原评论： {original_comment} 请写一条 30-80 字的回复，要符合你的写作风格和人格特征。直接输出回复内容，不要有其他说明。""" return base_prompt async def _call_ai_api( self, prompt: str, model_config: Optional[Dict[str, Any]] = None ) -> Optional[Dict[str, Any]]: """ 调用 AI API（根据 model_config 中的 provider 选择对应模型） :param prompt: 提示词 :param model_config: 模型配置 :return: 生成结果 """ if not model_config: # 使用默认配置（需要从数据库加载） from app.models.ai_model import AIModelConfig from app.models.base import get_db with get_db() as db: default_model = db.query(AIModelConfig).filter( AIModelConfig.is_default == True, AIModelConfig.is_active == True ).first() if not default_model: logger.error("No default AI model configured") return None model_config = { "provider": default_model.provider, "model_name": default_model.model_name, "api_key": default_model.api_key, "api_url": default_model.api_url, "temperature": default_model.temperature, "max_tokens": default_model.max_tokens, } provider = model_config.get("provider", "").lower() try: if provider == "openai": return await self._call_openai(prompt, model_config) elif provider == "zhipu": return await self._call_zhipu(prompt, model_config) elif provider in ["baidu", "wenxin"]: return await self._call_baidu_wenxin(prompt, model_config) elif provider in ["aliyun", "dashscope"]: return await self._call_aliyun_dashscope(prompt, model_config) else: logger.error(f"Unsupported AI provider: {provider}") return None except Exception as e: logger.error(f"AI API call error: {e}") return None async def _call_openai( self, prompt: str, config: Dict[str, Any] ) -> Optional[Dict[str, Any]]: """调用 OpenAI API""" try: from openai import AsyncOpenAI client = AsyncOpenAI( api_key=config["api_key"], base_url=config.get("api_url") ) response = await client.chat.completions.create( model=config.get("model_name", "gpt-3.5-turbo"), messages=[ {"role": "user", "content": prompt} ], temperature=config.get("temperature", 0.7), max_tokens=config.get("max_tokens", 1000) ) content = response.choices[0].message.content tokens_used = response.usage.total_tokens if response.usage else 0 logger.info(f"OpenAI generated content, tokens: {tokens_used}") return { "content": content, "tokens_used": tokens_used, "provider": "openai", "model": config.get("model_name", "gpt-3.5-turbo") } except Exception as e: logger.error(f"OpenAI API error: {e}") return None async def _call_zhipu( self, prompt: str, config: Dict[str, Any] ) -> Optional[Dict[str, Any]]: """调用智谱 AI API""" try: from zhipuai import ZhipuAI client = ZhipuAI(api_key=config["api_key"]) response = client.chat.completions.create( model=config.get("model_name", "glm-4"), messages=[ {"role": "user", "content": prompt} ], temperature=config.get("temperature", 0.7), max_tokens=config.get("max_tokens", 1000) ) content = response.choices[0].message.content tokens_used = response.usage.total_tokens if response.usage else 0 logger.info(f"Zhipu AI generated content, tokens: {tokens_used}") return { "content": content, "tokens_used": tokens_used, "provider": "zhipu", "model": config.get("model_name", "glm-4") } except Exception as e: logger.error(f"Zhipu AI API error: {e}") return None async def _call_baidu_wenxin( self, prompt: str, config: Dict[str, Any] ) -> Optional[Dict[str, Any]]: """调用百度文心一言 API""" # TODO: 实现百度文心一言 API 调用 logger.warning("Baidu Wenxin API not implemented yet") return None async def _call_aliyun_dashscope( self, prompt: str, config: Dict[str, Any] ) -> Optional[Dict[str, Any]]: """调用阿里云通义千问 API""" # TODO: 实现阿里云 DashScope API 调用 logger.warning("Aliyun DashScope API not implemented yet") return None async def test_model( self, model_config: Dict[str, Any], test_prompt: str = "测试评论" ) -> Dict[str, Any]: """ 测试模型配置 :param model_config: 模型配置 :param test_prompt: 测试提示词 :return: 测试结果 """ import time start_time = time.time() result = await self._call_ai_api(test_prompt, model_config) cost_time = time.time() - start_time if result: return { "success": True, "content": result.get("content"), "tokens_used": result.get("tokens_used", 0), "cost_time": round(cost_time, 2), "error_message": None } else: return { "success": False, "content": None, "tokens_used": 0, "cost_time": round(cost_time, 2), "error_message": "Failed to generate content" } # 创建全局服务实例 ai_service = AIService()