init
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xiamuceer
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"""AI服务封装 - 统一的OpenAI和Claude接口"""
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from typing import Optional, AsyncGenerator, List, Dict, Any
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from openai import AsyncOpenAI
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from anthropic import AsyncAnthropic
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from app.config import settings
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from app.logger import get_logger
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import httpx
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logger = get_logger(__name__)
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class AIService:
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"""AI服务统一接口"""
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def __init__(self):
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"""初始化AI客户端（优化并发性能）"""
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# 初始化OpenAI客户端
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if settings.openai_api_key:
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# 创建自定义的httpx客户端来避免proxies参数问题
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try:
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# 配置连接池限制，支持高并发
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# max_keepalive_connections: 保持活跃的连接数（提高复用率）
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# max_connections: 最大并发连接数（防止资源耗尽）
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limits = httpx.Limits(
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max_keepalive_connections=50, # 保持50个活跃连接
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max_connections=100, # 最多100个并发连接
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keepalive_expiry=30.0 # 30秒后过期未使用的连接
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)
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# 使用httpx.AsyncClient并设置超时和连接池
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# connect: 连接超时10秒
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# read: 读取超时180秒（3分钟，适合长文本生成）
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# write: 写入超时10秒
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# pool: 连接池超时10秒
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http_client = httpx.AsyncClient(
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timeout=httpx.Timeout(
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connect=10.0,
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read=180.0,
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write=10.0,
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pool=10.0
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),
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limits=limits
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)
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client_kwargs = {
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"api_key": settings.openai_api_key,
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"http_client": http_client
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}
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if settings.openai_base_url:
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client_kwargs["base_url"] = settings.openai_base_url
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self.openai_client = AsyncOpenAI(**client_kwargs)
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logger.info("✅ OpenAI客户端初始化成功")
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logger.info(" - 超时设置：连接10s，读取180s")
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logger.info(" - 连接池：50个保活连接，最大100个并发")
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except Exception as e:
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logger.error(f"OpenAI客户端初始化失败: {e}")
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self.openai_client = None
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else:
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self.openai_client = None
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logger.warning("OpenAI API key未配置")
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# 初始化Anthropic客户端
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if settings.anthropic_api_key:
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try:
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# 为Anthropic设置相同的超时和连接池配置
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limits = httpx.Limits(
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max_keepalive_connections=50,
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max_connections=100,
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keepalive_expiry=30.0
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)
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http_client = httpx.AsyncClient(
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timeout=httpx.Timeout(
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connect=10.0,
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read=180.0,
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write=10.0,
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pool=10.0
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),
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limits=limits
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)
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client_kwargs = {
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"api_key": settings.anthropic_api_key,
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"http_client": http_client
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}
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if settings.anthropic_base_url:
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client_kwargs["base_url"] = settings.anthropic_base_url
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self.anthropic_client = AsyncAnthropic(**client_kwargs)
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logger.info("✅ Anthropic客户端初始化成功")
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logger.info(" - 超时设置：连接10s，读取180s")
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logger.info(" - 连接池：50个保活连接，最大100个并发")
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except Exception as e:
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logger.error(f"Anthropic客户端初始化失败: {e}")
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self.anthropic_client = None
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else:
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self.anthropic_client = None
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logger.warning("Anthropic API key未配置")
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async def generate_text(
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self,
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prompt: str,
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provider: Optional[str] = None,
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model: Optional[str] = None,
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temperature: Optional[float] = None,
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max_tokens: Optional[int] = None,
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system_prompt: Optional[str] = None
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) -> str:
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"""
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生成文本
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Args:
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prompt: 用户提示词
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provider: AI提供商 (openai/anthropic)
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model: 模型名称
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temperature: 温度参数
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max_tokens: 最大token数
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system_prompt: 系统提示词
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Returns:
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生成的文本
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"""
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provider = provider or settings.default_ai_provider
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model = model or settings.default_model
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temperature = temperature or settings.default_temperature
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max_tokens = max_tokens or settings.default_max_tokens
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if provider == "openai":
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return await self._generate_openai(
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prompt, model, temperature, max_tokens, system_prompt
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)
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elif provider == "anthropic":
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return await self._generate_anthropic(
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prompt, model, temperature, max_tokens, system_prompt
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)
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else:
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raise ValueError(f"不支持的AI提供商: {provider}")
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async def generate_text_stream(
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self,
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prompt: str,
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provider: Optional[str] = None,
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model: Optional[str] = None,
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temperature: Optional[float] = None,
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max_tokens: Optional[int] = None,
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system_prompt: Optional[str] = None
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) -> AsyncGenerator[str, None]:
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"""
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流式生成文本
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Args:
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prompt: 用户提示词
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provider: AI提供商
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model: 模型名称
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temperature: 温度参数
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max_tokens: 最大token数
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system_prompt: 系统提示词
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Yields:
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生成的文本片段
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"""
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provider = provider or settings.default_ai_provider
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model = model or settings.default_model
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temperature = temperature or settings.default_temperature
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max_tokens = max_tokens or settings.default_max_tokens
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if provider == "openai":
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async for chunk in self._generate_openai_stream(
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prompt, model, temperature, max_tokens, system_prompt
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):
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yield chunk
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elif provider == "anthropic":
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async for chunk in self._generate_anthropic_stream(
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prompt, model, temperature, max_tokens, system_prompt
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):
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yield chunk
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else:
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raise ValueError(f"不支持的AI提供商: {provider}")
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async def _generate_openai(
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self,
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prompt: str,
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model: str,
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temperature: float,
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max_tokens: int,
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system_prompt: Optional[str]
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) -> str:
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"""使用OpenAI生成文本"""
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if not self.openai_client:
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raise ValueError("OpenAI客户端未初始化，请检查API key配置")
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messages = []
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if system_prompt:
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messages.append({"role": "system", "content": system_prompt})
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messages.append({"role": "user", "content": prompt})
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try:
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logger.info(f"🔵 开始调用OpenAI API")
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logger.info(f" - 模型: {model}")
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logger.info(f" - 温度: {temperature}")
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logger.info(f" - 最大tokens: {max_tokens}")
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logger.info(f" - Prompt长度: {len(prompt)} 字符")
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logger.info(f" - 消息数量: {len(messages)}")
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response = await self.openai_client.chat.completions.create(
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model=model,
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messages=messages,
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temperature=temperature,
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max_tokens=max_tokens
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)
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logger.info(f"✅ OpenAI API调用成功")
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logger.info(f" - 响应ID: {response.id if hasattr(response, 'id') else 'N/A'}")
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logger.info(f" - 选项数量: {len(response.choices)}")
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if not response.choices:
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logger.error("❌ OpenAI返回的choices为空")
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return ""
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content = response.choices[0].message.content
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logger.info(f" - 返回内容长度: {len(content) if content else 0} 字符")
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if content:
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logger.info(f" - 返回内容预览（前200字符）: {content[:200]}")
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return content
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else:
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logger.error("❌ OpenAI返回了空内容")
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logger.error(f" - 完整响应: {response}")
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raise ValueError("AI返回了空内容，请检查API配置或稍后重试")
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except Exception as e:
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logger.error(f"❌ OpenAI API调用失败")
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logger.error(f" - 错误类型: {type(e).__name__}")
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logger.error(f" - 错误信息: {str(e)}")
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logger.error(f" - 模型: {model}")
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raise
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async def _generate_openai_stream(
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self,
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prompt: str,
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model: str,
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temperature: float,
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max_tokens: int,
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system_prompt: Optional[str]
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) -> AsyncGenerator[str, None]:
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"""使用OpenAI流式生成文本"""
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if not self.openai_client:
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raise ValueError("OpenAI客户端未初始化，请检查API key配置")
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messages = []
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if system_prompt:
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messages.append({"role": "system", "content": system_prompt})
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messages.append({"role": "user", "content": prompt})
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try:
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logger.info(f"🔵 开始调用OpenAI流式API")
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logger.info(f" - 模型: {model}")
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logger.info(f" - Prompt长度: {len(prompt)} 字符")
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logger.info(f" - 最大tokens: {max_tokens}")
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stream = await self.openai_client.chat.completions.create(
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model=model,
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messages=messages,
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temperature=temperature,
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max_tokens=max_tokens,
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stream=True
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)
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logger.info(f"✅ OpenAI流式API连接成功，开始接收数据...")
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chunk_count = 0
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async for chunk in stream:
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if chunk.choices and len(chunk.choices) > 0:
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if chunk.choices[0].delta.content:
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chunk_count += 1
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yield chunk.choices[0].delta.content
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logger.info(f"✅ OpenAI流式生成完成，共接收 {chunk_count} 个chunk")
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except httpx.TimeoutException as e:
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logger.error(f"❌ OpenAI流式API超时")
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logger.error(f" - 错误: {str(e)}")
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logger.error(f" - 提示: 请检查网络连接或考虑缩短prompt长度")
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raise TimeoutError(f"AI服务超时（180秒），请稍后重试或减少上下文长度") from e
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except Exception as e:
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logger.error(f"❌ OpenAI流式API调用失败: {str(e)}")
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logger.error(f" - 错误类型: {type(e).__name__}")
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raise
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async def _generate_anthropic(
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self,
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prompt: str,
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model: str,
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temperature: float,
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max_tokens: int,
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system_prompt: Optional[str]
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) -> str:
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"""使用Anthropic生成文本"""
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if not self.anthropic_client:
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raise ValueError("Anthropic客户端未初始化，请检查API key配置")
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try:
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response = await self.anthropic_client.messages.create(
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model=model,
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max_tokens=max_tokens,
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temperature=temperature,
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system=system_prompt or "",
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messages=[{"role": "user", "content": prompt}]
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)
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return response.content[0].text
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except Exception as e:
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logger.error(f"Anthropic API调用失败: {str(e)}")
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raise
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async def _generate_anthropic_stream(
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self,
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prompt: str,
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model: str,
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temperature: float,
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max_tokens: int,
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system_prompt: Optional[str]
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) -> AsyncGenerator[str, None]:
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"""使用Anthropic流式生成文本"""
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if not self.anthropic_client:
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raise ValueError("Anthropic客户端未初始化，请检查API key配置")
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try:
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logger.info(f"🔵 开始调用Anthropic流式API")
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logger.info(f" - 模型: {model}")
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logger.info(f" - Prompt长度: {len(prompt)} 字符")
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logger.info(f" - 最大tokens: {max_tokens}")
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async with self.anthropic_client.messages.stream(
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model=model,
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max_tokens=max_tokens,
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temperature=temperature,
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system=system_prompt or "",
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messages=[{"role": "user", "content": prompt}]
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) as stream:
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logger.info(f"✅ Anthropic流式API连接成功，开始接收数据...")
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chunk_count = 0
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async for text in stream.text_stream:
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chunk_count += 1
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yield text
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logger.info(f"✅ Anthropic流式生成完成，共接收 {chunk_count} 个chunk")
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except httpx.TimeoutException as e:
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logger.error(f"❌ Anthropic流式API超时")
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logger.error(f" - 错误: {str(e)}")
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raise TimeoutError(f"AI服务超时（180秒），请稍后重试或减少上下文长度") from e
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except Exception as e:
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logger.error(f"❌ Anthropic流式API调用失败: {str(e)}")
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logger.error(f" - 错误类型: {type(e).__name__}")
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raise
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# 创建全局AI服务实例
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ai_service = AIService()
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