init
This commit is contained in:
xiamuceer
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"""服务层模块"""
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@@ -0,0 +1,363 @@
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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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@@ -0,0 +1,149 @@
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"""
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LinuxDO OAuth2 服务
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"""
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import httpx
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import secrets
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from typing import Optional, Dict, Any
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from app.config import settings
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class LinuxDOOAuthService:
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"""LinuxDO OAuth2 服务类"""
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# LinuxDO OAuth2 端点
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AUTHORIZE_URL = "https://connect.linux.do/oauth2/authorize"
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TOKEN_URL = "https://connect.linux.do/oauth2/token"
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USERINFO_URL = "https://connect.linux.do/api/user" # 修复：使用正确的用户信息端点
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def __init__(self):
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self.client_id = settings.LINUXDO_CLIENT_ID
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self.client_secret = settings.LINUXDO_CLIENT_SECRET
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self.redirect_uri = settings.LINUXDO_REDIRECT_URI
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# 验证redirect_uri配置
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if not self.redirect_uri:
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raise ValueError(
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"LINUXDO_REDIRECT_URI 未配置！\n"
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"请在 .env 文件中设置正确的回调地址：\n"
|
||||
"本地开发: LINUXDO_REDIRECT_URI=http://localhost:8000/api/auth/callback\n"
|
||||
"Docker部署: LINUXDO_REDIRECT_URI=https://your-domain.com/api/auth/callback"
|
||||
)
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||||
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||||
# 警告：检查是否使用了localhost（在非开发环境）
|
||||
if not settings.debug and "localhost" in self.redirect_uri.lower():
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||||
import logging
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||||
logger = logging.getLogger(__name__)
|
||||
logger.warning(
|
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f"⚠️ 生产环境检测到使用 localhost 作为回调地址: {self.redirect_uri}\n"
|
||||
"这可能导致OAuth回调失败！请使用实际的域名或服务器IP。"
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||||
)
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||||
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||||
def generate_state(self) -> str:
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||||
"""生成随机 state 参数"""
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return secrets.token_urlsafe(32)
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||||
|
||||
def get_authorization_url(self, state: str) -> str:
|
||||
"""
|
||||
获取授权 URL
|
||||
|
||||
Args:
|
||||
state: 随机 state 参数
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||||
|
||||
Returns:
|
||||
授权 URL
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||||
"""
|
||||
params = {
|
||||
"client_id": self.client_id,
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||||
"redirect_uri": self.redirect_uri,
|
||||
"response_type": "code",
|
||||
"scope": "read",
|
||||
"state": state
|
||||
}
|
||||
|
||||
query_string = "&".join([f"{k}={v}" for k, v in params.items()])
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||||
return f"{self.AUTHORIZE_URL}?{query_string}"
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||||
|
||||
async def get_access_token(self, code: str) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
使用授权码获取访问令牌
|
||||
|
||||
Args:
|
||||
code: 授权码
|
||||
|
||||
Returns:
|
||||
包含 access_token 的字典,失败返回 None
|
||||
"""
|
||||
data = {
|
||||
"client_id": self.client_id,
|
||||
"client_secret": self.client_secret,
|
||||
"code": code,
|
||||
"grant_type": "authorization_code",
|
||||
"redirect_uri": self.redirect_uri
|
||||
}
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient() as client:
|
||||
response = await client.post(
|
||||
self.TOKEN_URL,
|
||||
data=data,
|
||||
headers={"Content-Type": "application/x-www-form-urlencoded"}
|
||||
)
|
||||
|
||||
if response.status_code == 200:
|
||||
return response.json()
|
||||
else:
|
||||
print(f"获取访问令牌失败: {response.status_code} {response.text}")
|
||||
return None
|
||||
|
||||
except Exception as e:
|
||||
print(f"获取访问令牌异常: {e}")
|
||||
return None
|
||||
|
||||
async def get_user_info(self, access_token: str) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
使用访问令牌获取用户信息
|
||||
|
||||
Args:
|
||||
access_token: 访问令牌
|
||||
|
||||
Returns:
|
||||
用户信息字典,失败返回 None
|
||||
"""
|
||||
try:
|
||||
# 添加真实浏览器请求头，避免被 Cloudflare 拦截
|
||||
headers = {
|
||||
"Authorization": f"Bearer {access_token}",
|
||||
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36",
|
||||
"Accept": "application/json",
|
||||
"Accept-Language": "zh-CN,zh;q=0.9,en;q=0.8",
|
||||
}
|
||||
|
||||
# 不自动处理编码，让 httpx 自动解压
|
||||
async with httpx.AsyncClient(follow_redirects=True, timeout=30.0) as client:
|
||||
response = await client.get(
|
||||
self.USERINFO_URL,
|
||||
headers=headers
|
||||
)
|
||||
|
||||
print(f"获取用户信息响应状态: {response.status_code}")
|
||||
print(f"响应头: {response.headers}")
|
||||
|
||||
if response.status_code == 200:
|
||||
try:
|
||||
user_data = response.json()
|
||||
print(f"用户信息: {user_data}")
|
||||
return user_data
|
||||
except Exception as json_error:
|
||||
print(f"解析 JSON 失败: {json_error}")
|
||||
print(f"响应内容前100字符: {response.text[:100]}")
|
||||
return None
|
||||
else:
|
||||
print(f"获取用户信息失败: {response.status_code}")
|
||||
print(f"响应内容: {response.text[:200]}")
|
||||
return None
|
||||
|
||||
except Exception as e:
|
||||
print(f"获取用户信息异常: {type(e).__name__}: {str(e)}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
return None
|
||||
@@ -0,0 +1,730 @@
|
||||
"""提示词管理服务"""
|
||||
from typing import Dict, Any
|
||||
import json
|
||||
|
||||
|
||||
class PromptService:
|
||||
"""提示词模板管理"""
|
||||
|
||||
# 世界构建提示词
|
||||
WORLD_BUILDING = """你是一位资深的世界观设计师。请根据以下信息构建一个完整的小说世界观：
|
||||
|
||||
书名：{title}
|
||||
主题：{theme}
|
||||
类型：{genre}
|
||||
|
||||
请生成包含以下内容的世界构建框架：
|
||||
|
||||
1. **时间背景**：具体的时代设定、时间流逝特点、重要历史事件
|
||||
2. **地理位置**：主要地点描述、地理环境特征、空间布局
|
||||
3. **氛围基调**：整体氛围感觉、情感色彩、视觉风格
|
||||
4. **世界规则**：基本运行法则、特殊设定、社会规则和禁忌、权力结构
|
||||
|
||||
要求：
|
||||
- 与主题高度契合
|
||||
- 设定要合理自洽
|
||||
- 为故事发展提供支撑
|
||||
- 具有独特性和吸引力
|
||||
|
||||
**重要：你必须只返回纯JSON格式，不要包含任何markdown标记、代码块标记或其他说明文字。**
|
||||
|
||||
请严格按照以下JSON格式返回（每个字段为200-300字的文本描述）：
|
||||
{{
|
||||
"time_period": "时间背景的详细描述，包括时代设定、时间特点、历史事件",
|
||||
"location": "地理位置的详细描述，包括主要地点、环境特征、空间布局",
|
||||
"atmosphere": "氛围基调的详细描述，包括整体氛围、情感色彩、视觉风格",
|
||||
"rules": "世界规则的详细描述，包括运行法则、特殊设定、社会规则、权力结构"
|
||||
}}
|
||||
|
||||
再次强调：只返回纯JSON对象，不要有```json```这样的标记，不要有任何额外的文字说明。"""
|
||||
|
||||
# 批量角色生成提示词
|
||||
CHARACTERS_BATCH_GENERATION = """你是一位专业的角色设定师。请根据以下世界观和要求，生成{count}个立体丰满的角色和组织：
|
||||
|
||||
世界观信息：
|
||||
- 时间背景：{time_period}
|
||||
- 地理位置：{location}
|
||||
- 氛围基调：{atmosphere}
|
||||
- 世界规则：{rules}
|
||||
|
||||
主题：{theme}
|
||||
类型：{genre}
|
||||
特殊要求：{requirements}
|
||||
|
||||
【数量要求 - 必须严格遵守】
|
||||
请精确生成{count}个实体，不多不少。数组中必须包含且仅包含{count}个对象。
|
||||
|
||||
实体类型分配：
|
||||
- 至少1个主角（protagonist）
|
||||
- 多个配角（supporting）
|
||||
- 可以包含反派（antagonist）
|
||||
- 可以包含1-2个重要组织
|
||||
|
||||
要求：
|
||||
- 角色要符合世界观设定
|
||||
- 性格和背景要有深度
|
||||
- 角色之间要有关系网络
|
||||
- 组织要有存在的合理性
|
||||
- 所有实体要为故事服务
|
||||
|
||||
**重要：你必须只返回纯JSON数组格式，不要包含任何markdown标记、代码块标记或其他说明文字。**
|
||||
|
||||
请严格按照以下JSON数组格式返回（每个角色为数组中的一个对象）：
|
||||
[
|
||||
{{
|
||||
"name": "角色姓名",
|
||||
"age": 25,
|
||||
"gender": "男/女/其他",
|
||||
"is_organization": false,
|
||||
"role_type": "protagonist/supporting/antagonist",
|
||||
"personality": "性格特点的详细描述（100-200字），包括核心性格、优缺点、特殊习惯",
|
||||
"background": "背景故事的详细描述（100-200字），包括家庭背景、成长经历、重要转折",
|
||||
"appearance": "外貌描述（50-100字），包括身高、体型、面容、着装风格",
|
||||
"traits": ["特长1", "特长2", "特长3"],
|
||||
"relationships_array": [
|
||||
{{
|
||||
"target_character_name": "已生成的角色名称",
|
||||
"relationship_type": "关系类型（师父/朋友/敌人/父亲/母亲等）",
|
||||
"intimacy_level": 75,
|
||||
"description": "关系描述"
|
||||
}}
|
||||
],
|
||||
"organization_memberships": [
|
||||
{{
|
||||
"organization_name": "已生成的组织名称",
|
||||
"position": "职位",
|
||||
"rank": 5,
|
||||
"loyalty": 80
|
||||
}}
|
||||
]
|
||||
}},
|
||||
{{
|
||||
"name": "组织名称",
|
||||
"is_organization": true,
|
||||
"role_type": "supporting",
|
||||
"personality": "组织特性描述（100-200字），包括运作方式、核心理念、行事风格",
|
||||
"background": "组织背景（100-200字），包括建立历史、发展历程、重要事件",
|
||||
"appearance": "组织外在表现（50-100字），如总部位置、标志性建筑等",
|
||||
"organization_type": "组织类型",
|
||||
"organization_purpose": "组织目的",
|
||||
"organization_members": ["成员1", "成员2"],
|
||||
"traits": []
|
||||
}}
|
||||
]
|
||||
|
||||
**关系类型参考（从中选择或自定义）：**
|
||||
- 家族：父亲、母亲、兄弟、姐妹、子女、配偶、恋人
|
||||
- 社交：师父、徒弟、朋友、同学、同事、邻居、知己
|
||||
- 职业：上司、下属、合作伙伴
|
||||
- 敌对：敌人、仇人、竞争对手、宿敌
|
||||
|
||||
**重要说明：**
|
||||
1. **数量控制**：数组中必须精确包含{count}个对象，不能多也不能少
|
||||
2. **关系约束**：relationships_array只能引用本批次中已经出现的角色名称
|
||||
3. **组织约束**：organization_memberships只能引用本批次中is_organization=true的实体名称
|
||||
4. **禁止幻觉**：不要引用任何不存在的角色或组织，如果没有可引用的就留空数组[]
|
||||
5. intimacy_level和loyalty都是0-100的整数
|
||||
6. 角色之间要形成合理的关系网络
|
||||
|
||||
**示例说明**：
|
||||
- 如果生成了角色A、组织B、角色C，则角色A的organization_memberships只能是[组织B]，不能是其他组织
|
||||
- 如果角色A在数组第一位，它的relationships_array必须为空[]，因为还没有其他角色
|
||||
- 如果角色C在数组第三位，它的relationships_array可以引用角色A，但不能引用不存在的角色D
|
||||
|
||||
再次强调：
|
||||
1. 只返回纯JSON数组，不要有```json```这样的标记
|
||||
2. 数组中必须精确包含{count}个对象
|
||||
3. 不要引用任何本批次中不存在的角色或组织名称"""
|
||||
|
||||
# 完整大纲生成提示词
|
||||
COMPLETE_OUTLINE_GENERATION = """你是一位经验丰富的小说作家和编剧。请根据以下信息生成完整的{chapter_count}章小说大纲：
|
||||
|
||||
基本信息：
|
||||
- 书名：{title}
|
||||
- 主题：{theme}
|
||||
- 类型：{genre}
|
||||
- 章节数：{chapter_count}
|
||||
- 叙事视角：{narrative_perspective}
|
||||
- 目标字数：{target_words}
|
||||
|
||||
世界观：
|
||||
- 时间背景：{time_period}
|
||||
- 地理位置：{location}
|
||||
- 氛围基调：{atmosphere}
|
||||
- 世界规则：{rules}
|
||||
|
||||
角色信息：
|
||||
{characters_info}
|
||||
|
||||
其他要求：{requirements}
|
||||
|
||||
整体要求：
|
||||
- 结构完整：起承转合清晰
|
||||
- 情节连贯：章节之间紧密衔接
|
||||
- 冲突递进：矛盾逐步升级
|
||||
- 人物成长：角色有明确的变化弧线
|
||||
- 节奏把控：有张有弛
|
||||
- 视角统一：采用{narrative_perspective}视角叙事
|
||||
|
||||
**重要：你必须只返回纯JSON数组格式，不要包含任何markdown标记、代码块标记或其他说明文字。**
|
||||
|
||||
请严格按照以下JSON数组格式返回（共{chapter_count}个章节对象）：
|
||||
[
|
||||
{{
|
||||
"chapter_number": 1,
|
||||
"title": "第一章标题",
|
||||
"summary": "章节概要的详细描述（100-200字），包含主要情节、冲突、转折等",
|
||||
"scenes": ["场景1描述", "场景2描述", "场景3描述"],
|
||||
"characters": ["角色1", "角色2"],
|
||||
"key_points": ["情节要点1", "情节要点2"],
|
||||
"emotion": "本章情感基调",
|
||||
"goal": "本章叙事目标"
|
||||
}},
|
||||
{{
|
||||
"chapter_number": 2,
|
||||
"title": "第二章标题",
|
||||
"summary": "章节概要...",
|
||||
"scenes": ["场景1", "场景2"],
|
||||
"characters": ["角色1", "角色2"],
|
||||
"key_points": ["要点1", "要点2"],
|
||||
"emotion": "情感基调",
|
||||
"goal": "叙事目标"
|
||||
}}
|
||||
]
|
||||
|
||||
再次强调：只返回纯JSON数组，不要有```json```这样的标记，不要有任何额外的文字说明。数组中要包含{chapter_count}个章节对象。"""
|
||||
|
||||
# 大纲续写提示词
|
||||
OUTLINE_CONTINUE_GENERATION = """你是一位经验丰富的小说作家和编剧。请基于以下信息续写小说大纲：
|
||||
|
||||
【项目信息】
|
||||
- 书名：{title}
|
||||
- 主题：{theme}
|
||||
- 类型：{genre}
|
||||
- 叙事视角：{narrative_perspective}
|
||||
- 续写章节数：{chapter_count}章
|
||||
|
||||
【世界观】
|
||||
- 时间背景：{time_period}
|
||||
- 地理位置：{location}
|
||||
- 氛围基调：{atmosphere}
|
||||
- 世界规则：{rules}
|
||||
|
||||
【角色信息】
|
||||
{characters_info}
|
||||
|
||||
【已有章节概览】（共{current_chapter_count}章）
|
||||
{all_chapters_brief}
|
||||
|
||||
【最近剧情】
|
||||
{recent_plot}
|
||||
|
||||
【续写指导】
|
||||
- 当前情节阶段：{plot_stage_instruction}
|
||||
- 起始章节编号：第{start_chapter}章
|
||||
- 故事发展方向：{story_direction}
|
||||
- 其他要求：{requirements}
|
||||
|
||||
请生成第{start_chapter}章到第{end_chapter}章的大纲。
|
||||
要求：
|
||||
- 与前文自然衔接，保持故事连贯性
|
||||
- 遵循情节阶段的发展要求
|
||||
- 保持与已有章节相同的风格和详细程度
|
||||
- 推进角色成长和情节发展
|
||||
|
||||
**重要：你必须只返回纯JSON数组格式，不要包含任何markdown标记、代码块标记或其他说明文字。**
|
||||
|
||||
请严格按照以下JSON数组格式返回（共{chapter_count}个章节对象）：
|
||||
[
|
||||
{{
|
||||
"chapter_number": {start_chapter},
|
||||
"title": "章节标题",
|
||||
"summary": "章节概要的详细描述（100-200字），包含主要情节、角色互动、关键事件、冲突与转折",
|
||||
"scenes": ["场景1描述", "场景2描述", "场景3描述"],
|
||||
"characters": ["涉及角色1", "涉及角色2"],
|
||||
"key_points": ["情节要点1", "情节要点2"],
|
||||
"emotion": "本章情感基调",
|
||||
"goal": "本章叙事目标"
|
||||
}},
|
||||
{{
|
||||
"chapter_number": {start_chapter} + 1,
|
||||
"title": "章节标题",
|
||||
"summary": "章节概要...",
|
||||
"scenes": ["场景1", "场景2"],
|
||||
"characters": ["角色1", "角色2"],
|
||||
"key_points": ["要点1", "要点2"],
|
||||
"emotion": "情感基调",
|
||||
"goal": "叙事目标"
|
||||
}}
|
||||
]
|
||||
|
||||
再次强调：
|
||||
1. 只返回纯JSON数组，不要有```json```这样的标记
|
||||
2. 数组中要包含{chapter_count}个章节对象
|
||||
3. 每个summary必须是100-200字的详细描述
|
||||
4. 确保字段结构与已有章节完全一致"""
|
||||
|
||||
# AI去味提示词（核心特色功能）
|
||||
AI_DENOISING = """你是一位追求自然写作风格的编辑。你的任务是将AI生成的文本改写得更像人类作家的手笔。
|
||||
|
||||
原文：
|
||||
{original_text}
|
||||
|
||||
修改要求：
|
||||
1. 去除AI痕迹：
|
||||
- 删除过于工整的排比句
|
||||
- 减少重复的修辞手法
|
||||
- 去掉刻意的对称结构
|
||||
- 避免机械式的总结陈词
|
||||
|
||||
2. 增加人性化：
|
||||
- 使用更口语化的表达
|
||||
- 添加不完美的细节
|
||||
- 保留适度的随意性
|
||||
- 增加真实的情感波动
|
||||
|
||||
3. 优化叙事：
|
||||
- 让节奏更自然不做作
|
||||
- 用简单词汇替换华丽辞藻
|
||||
- 保持叙述的松弛感
|
||||
- 让对话更生活化
|
||||
|
||||
4. 保持原意：
|
||||
- 不改变核心情节
|
||||
- 保留关键信息点
|
||||
- 维持角色性格
|
||||
- 确保逻辑连贯
|
||||
|
||||
修改风格：
|
||||
- 像是一个喜欢讲故事的普通人写的
|
||||
- 有点粗糙但很真诚
|
||||
- 自然流畅不刻意
|
||||
- 让人读起来很舒服
|
||||
|
||||
请直接输出修改后的文本，无需解释。"""
|
||||
|
||||
# 章节完整创作提示词
|
||||
CHAPTER_GENERATION = """你是一位专业的小说作家。请根据以下信息创作本章内容：
|
||||
|
||||
项目信息：
|
||||
- 书名：{title}
|
||||
- 主题：{theme}
|
||||
- 类型：{genre}
|
||||
- 叙事视角：{narrative_perspective}
|
||||
|
||||
世界观：
|
||||
- 时间背景：{time_period}
|
||||
- 地理位置：{location}
|
||||
- 氛围基调：{atmosphere}
|
||||
- 世界规则：{rules}
|
||||
|
||||
角色信息：
|
||||
{characters_info}
|
||||
|
||||
全书大纲：
|
||||
{outlines_context}
|
||||
|
||||
本章信息：
|
||||
- 章节序号：第{chapter_number}章
|
||||
- 章节标题：{chapter_title}
|
||||
- 章节大纲：{chapter_outline}
|
||||
|
||||
创作要求：
|
||||
1. 严格按照大纲内容展开情节
|
||||
2. 保持与前后章节的连贯性
|
||||
3. 符合角色性格设定
|
||||
4. 体现世界观特色
|
||||
5. 使用{narrative_perspective}视角
|
||||
6. 字数不得低于3000字
|
||||
7. 语言自然流畅，避免AI痕迹
|
||||
|
||||
**写作风格要求（重要）：**
|
||||
- 让故事自然流淌，写到哪算哪
|
||||
- 结尾处直接结束情节，不要加总结性段落
|
||||
- 不要在章节末尾写"这一天/这一夜就这样过去了"之类的总结句
|
||||
- 不要用"他/她陷入了沉思"作为结尾
|
||||
- 避免刻意的情感升华或哲理感悟收尾
|
||||
- 章节结尾可以戛然而止，可以是对话，可以是动作，可以是悬念
|
||||
- 就像在讲一个故事，讲完了就停，不需要画龙点睛
|
||||
|
||||
请直接输出章节正文内容，不要包含章节标题和其他说明文字。"""
|
||||
|
||||
# 章节完整创作提示词（带前置章节上下文）
|
||||
CHAPTER_GENERATION_WITH_CONTEXT = """你是一位专业的小说作家。请根据以下信息创作本章内容：
|
||||
|
||||
项目信息：
|
||||
- 书名：{title}
|
||||
- 主题：{theme}
|
||||
- 类型：{genre}
|
||||
- 叙事视角：{narrative_perspective}
|
||||
|
||||
世界观：
|
||||
- 时间背景：{time_period}
|
||||
- 地理位置：{location}
|
||||
- 氛围基调：{atmosphere}
|
||||
- 世界规则：{rules}
|
||||
|
||||
角色信息：
|
||||
{characters_info}
|
||||
|
||||
全书大纲：
|
||||
{outlines_context}
|
||||
|
||||
【已完成的前置章节内容】
|
||||
{previous_content}
|
||||
|
||||
本章信息：
|
||||
- 章节序号：第{chapter_number}章
|
||||
- 章节标题：{chapter_title}
|
||||
- 章节大纲：{chapter_outline}
|
||||
|
||||
创作要求：
|
||||
1. **剧情连贯性（最重要）**：
|
||||
- 必须承接前面章节的剧情发展
|
||||
- 注意角色状态、情节进展、时间线的连续性
|
||||
- 不能出现与前文矛盾的内容
|
||||
- 自然过渡，避免突兀的跳跃
|
||||
|
||||
2. **情节推进**：
|
||||
- 严格按照本章大纲展开情节
|
||||
- 推动故事向前发展
|
||||
- 保持与全书大纲的一致性
|
||||
|
||||
3. **角色一致性**：
|
||||
- 符合角色性格设定
|
||||
- 延续角色在前文中的成长和变化
|
||||
- 保持角色关系的连贯性
|
||||
|
||||
4. **写作风格**：
|
||||
- 使用{narrative_perspective}视角
|
||||
- 字数不得低于3000字
|
||||
- 语言自然流畅，避免AI痕迹
|
||||
- 体现世界观特色
|
||||
|
||||
5. **承上启下**：
|
||||
- 开头自然衔接上一章结尾
|
||||
- 结尾为下一章做好铺垫
|
||||
|
||||
**写作风格要求（重要）：**
|
||||
- 让故事自然流淌，写到哪算哪
|
||||
- 结尾处直接结束情节，不要加总结性段落
|
||||
- 不要在章节末尾写"这一天/这一夜就这样过去了"之类的总结句
|
||||
- 不要用"他/她陷入了沉思"作为结尾
|
||||
- 避免刻意的情感升华或哲理感悟收尾
|
||||
- 章节结尾可以戛然而止，可以是对话，可以是动作，可以是悬念
|
||||
- 就像在讲一个故事，讲完了就停，不需要画龙点睛
|
||||
|
||||
请直接输出章节正文内容，不要包含章节标题和其他说明文字。"""
|
||||
|
||||
# 大纲生成提示词
|
||||
OUTLINE_GENERATION = """你是一位经验丰富的小说作家和编剧。请根据以下信息生成小说大纲：
|
||||
|
||||
类型：{genre}
|
||||
主题：{theme}
|
||||
目标字数：{target_words}
|
||||
其他要求：{requirements}
|
||||
|
||||
请生成一个完整的章节大纲框架，包含：
|
||||
1. 合理的章节数量（根据字数）
|
||||
2. 每章的标题和内容概要
|
||||
3. 清晰的故事结构（起承转合）
|
||||
4. 情节的递进和冲突升级
|
||||
5. 角色的成长弧线
|
||||
|
||||
**重要：你必须只返回纯JSON格式，不要包含任何markdown标记、代码块标记或其他说明文字。**
|
||||
|
||||
请严格按照以下JSON格式返回：
|
||||
{{
|
||||
"chapters": [
|
||||
{{
|
||||
"order": 1,
|
||||
"title": "章节标题",
|
||||
"content": "章节内容概要（150-200字）"
|
||||
}}
|
||||
]
|
||||
}}
|
||||
|
||||
再次强调：只返回纯JSON对象，不要有```json```这样的标记，不要有任何额外的文字说明。"""
|
||||
|
||||
# 单个角色生成提示词
|
||||
SINGLE_CHARACTER_GENERATION = """你是一位专业的角色设定师。请根据以下信息创建一个立体饱满的小说角色。
|
||||
|
||||
{project_context}
|
||||
|
||||
{user_input}
|
||||
|
||||
请生成一个完整的角色卡片，包含以下所有信息：
|
||||
|
||||
1. **基本信息**：
|
||||
- 姓名：如果用户未提供，请生成一个符合世界观的名字
|
||||
- 年龄：具体数字或年龄段
|
||||
- 性别：男/女/其他
|
||||
|
||||
2. **外貌特征**（100-150字）：
|
||||
- 身高体型、面容特征、着装风格
|
||||
- 要符合角色定位和世界观设定
|
||||
|
||||
3. **性格特点**（150-200字）：
|
||||
- 核心性格特质（至少3个）
|
||||
- 优点和缺点
|
||||
- 特殊习惯或癖好
|
||||
- 性格要有复杂性和矛盾性
|
||||
|
||||
4. **背景故事**（200-300字）：
|
||||
- 家庭背景
|
||||
- 成长经历
|
||||
- 重要转折事件
|
||||
- 如何与项目主题关联
|
||||
- 融入用户提供的背景设定
|
||||
|
||||
5. **人际关系**：
|
||||
- 与现有角色的关系（如果有）
|
||||
- 重要的人际纽带
|
||||
- 社会地位和人脉
|
||||
|
||||
6. **特殊能力/特长**：
|
||||
- 擅长的领域
|
||||
- 特殊技能或知识
|
||||
- 符合世界观设定
|
||||
|
||||
**你必须只返回纯JSON格式，不要包含任何markdown标记、代码块标记或其他说明文字。**
|
||||
|
||||
请严格按照以下JSON格式返回：
|
||||
{{
|
||||
"name": "角色姓名",
|
||||
"age": "年龄",
|
||||
"gender": "性别",
|
||||
"appearance": "外貌描述（100-150字）",
|
||||
"personality": "性格特点（150-200字）",
|
||||
"background": "背景故事（200-300字）",
|
||||
"traits": ["特长1", "特长2", "特长3"],
|
||||
|
||||
"relationships_text": "人际关系的文字描述（用于显示）",
|
||||
|
||||
"relationships": [
|
||||
{{
|
||||
"target_character_name": "已存在的角色名称",
|
||||
"relationship_type": "关系类型（如：师父、朋友、敌人、父亲、母亲等）",
|
||||
"intimacy_level": 75,
|
||||
"description": "这段关系的详细描述",
|
||||
"started_at": "关系开始的故事时间点（可选）"
|
||||
}}
|
||||
],
|
||||
|
||||
"organization_memberships": [
|
||||
{{
|
||||
"organization_name": "已存在的组织名称",
|
||||
"position": "职位名称",
|
||||
"rank": 8,
|
||||
"loyalty": 80,
|
||||
"joined_at": "加入时间（可选）",
|
||||
"status": "active"
|
||||
}}
|
||||
]
|
||||
}}
|
||||
|
||||
**关系类型参考（请从中选择或自定义）：**
|
||||
- 家族关系：父亲、母亲、兄弟、姐妹、子女、配偶、恋人
|
||||
- 社交关系：师父、徒弟、朋友、同学、同事、邻居、知己
|
||||
- 职业关系：上司、下属、合作伙伴
|
||||
- 敌对关系：敌人、仇人、竞争对手、宿敌
|
||||
|
||||
**重要说明：**
|
||||
1. relationships数组：只包含与上面列出的已存在角色的关系，通过target_character_name匹配
|
||||
2. organization_memberships数组：只包含与上面列出的已存在组织的关系
|
||||
3. intimacy_level和loyalty都是0-100的整数
|
||||
4. 如果没有关系或组织，对应数组为空[]
|
||||
5. relationships_text是自然语言描述，用于展示给用户看
|
||||
|
||||
**角色设定要求：**
|
||||
- 角色要符合项目的世界观和主题
|
||||
- 如果是主角，要有明确的成长空间和目标动机
|
||||
- 如果是反派，要有合理的动机，不能脸谱化
|
||||
- 配角要有独特性，不能是工具人
|
||||
- 所有设定要为故事服务
|
||||
|
||||
再次强调：只返回纯JSON对象，不要有```json```这样的标记，不要有任何额外的文字说明。"""
|
||||
|
||||
@staticmethod
|
||||
def format_prompt(template: str, **kwargs) -> str:
|
||||
"""
|
||||
格式化提示词模板
|
||||
|
||||
Args:
|
||||
template: 提示词模板
|
||||
**kwargs: 模板参数
|
||||
|
||||
Returns:
|
||||
格式化后的提示词
|
||||
"""
|
||||
try:
|
||||
return template.format(**kwargs)
|
||||
except KeyError as e:
|
||||
raise ValueError(f"缺少必需的参数: {e}")
|
||||
|
||||
@classmethod
|
||||
def get_denoising_prompt(cls, original_text: str) -> str:
|
||||
"""获取AI去味提示词"""
|
||||
return cls.format_prompt(
|
||||
cls.AI_DENOISING,
|
||||
original_text=original_text
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def get_world_building_prompt(cls, title: str, theme: str, genre: str = "") -> str:
|
||||
"""获取世界构建提示词"""
|
||||
return cls.format_prompt(
|
||||
cls.WORLD_BUILDING,
|
||||
title=title,
|
||||
theme=theme,
|
||||
genre=genre or "通用类型"
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def get_characters_batch_prompt(cls, count: int, time_period: str, location: str,
|
||||
atmosphere: str, rules: str, theme: str,
|
||||
genre: str = "", requirements: str = "") -> str:
|
||||
"""获取批量角色生成提示词"""
|
||||
return cls.format_prompt(
|
||||
cls.CHARACTERS_BATCH_GENERATION,
|
||||
count=count,
|
||||
time_period=time_period,
|
||||
location=location,
|
||||
atmosphere=atmosphere,
|
||||
rules=rules,
|
||||
theme=theme,
|
||||
genre=genre or "通用类型",
|
||||
requirements=requirements or "无特殊要求"
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def get_complete_outline_prompt(cls, title: str, theme: str, genre: str,
|
||||
chapter_count: int, narrative_perspective: str,
|
||||
target_words: int, time_period: str, location: str,
|
||||
atmosphere: str, rules: str, characters_info: str,
|
||||
requirements: str = "") -> str:
|
||||
"""获取完整大纲生成提示词"""
|
||||
return cls.format_prompt(
|
||||
cls.COMPLETE_OUTLINE_GENERATION,
|
||||
title=title,
|
||||
theme=theme,
|
||||
genre=genre,
|
||||
chapter_count=chapter_count,
|
||||
narrative_perspective=narrative_perspective,
|
||||
target_words=target_words,
|
||||
time_period=time_period,
|
||||
location=location,
|
||||
atmosphere=atmosphere,
|
||||
rules=rules,
|
||||
characters_info=characters_info,
|
||||
requirements=requirements or "无特殊要求"
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def get_chapter_generation_prompt(cls, title: str, theme: str, genre: str,
|
||||
narrative_perspective: str, time_period: str,
|
||||
location: str, atmosphere: str, rules: str,
|
||||
characters_info: str, outlines_context: str,
|
||||
chapter_number: int, chapter_title: str,
|
||||
chapter_outline: str) -> str:
|
||||
"""获取章节完整创作提示词"""
|
||||
return cls.format_prompt(
|
||||
cls.CHAPTER_GENERATION,
|
||||
title=title,
|
||||
theme=theme,
|
||||
genre=genre,
|
||||
narrative_perspective=narrative_perspective,
|
||||
time_period=time_period,
|
||||
location=location,
|
||||
atmosphere=atmosphere,
|
||||
rules=rules,
|
||||
characters_info=characters_info,
|
||||
outlines_context=outlines_context,
|
||||
chapter_number=chapter_number,
|
||||
chapter_title=chapter_title,
|
||||
chapter_outline=chapter_outline
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def get_chapter_generation_with_context_prompt(cls, title: str, theme: str, genre: str,
|
||||
narrative_perspective: str, time_period: str,
|
||||
location: str, atmosphere: str, rules: str,
|
||||
characters_info: str, outlines_context: str,
|
||||
previous_content: str, chapter_number: int,
|
||||
chapter_title: str, chapter_outline: str) -> str:
|
||||
"""获取章节完整创作提示词（带前置章节上下文）"""
|
||||
return cls.format_prompt(
|
||||
cls.CHAPTER_GENERATION_WITH_CONTEXT,
|
||||
title=title,
|
||||
theme=theme,
|
||||
genre=genre,
|
||||
narrative_perspective=narrative_perspective,
|
||||
time_period=time_period,
|
||||
location=location,
|
||||
atmosphere=atmosphere,
|
||||
rules=rules,
|
||||
characters_info=characters_info,
|
||||
outlines_context=outlines_context,
|
||||
previous_content=previous_content,
|
||||
chapter_number=chapter_number,
|
||||
chapter_title=chapter_title,
|
||||
chapter_outline=chapter_outline
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def get_outline_prompt(cls, genre: str, theme: str, target_words: int,
|
||||
requirements: str = "") -> str:
|
||||
"""获取大纲生成提示词"""
|
||||
return cls.format_prompt(
|
||||
cls.OUTLINE_GENERATION,
|
||||
genre=genre,
|
||||
theme=theme,
|
||||
target_words=target_words,
|
||||
requirements=requirements or "无特殊要求"
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def get_outline_continue_prompt(cls, title: str, theme: str, genre: str,
|
||||
narrative_perspective: str, chapter_count: int,
|
||||
time_period: str, location: str, atmosphere: str,
|
||||
rules: str, characters_info: str,
|
||||
current_chapter_count: int, all_chapters_brief: str,
|
||||
recent_plot: str, plot_stage_instruction: str,
|
||||
start_chapter: int, story_direction: str,
|
||||
requirements: str = "") -> str:
|
||||
"""获取大纲续写提示词"""
|
||||
end_chapter = start_chapter + chapter_count - 1
|
||||
return cls.format_prompt(
|
||||
cls.OUTLINE_CONTINUE_GENERATION,
|
||||
title=title,
|
||||
theme=theme,
|
||||
genre=genre,
|
||||
narrative_perspective=narrative_perspective,
|
||||
chapter_count=chapter_count,
|
||||
time_period=time_period,
|
||||
location=location,
|
||||
atmosphere=atmosphere,
|
||||
rules=rules,
|
||||
characters_info=characters_info,
|
||||
current_chapter_count=current_chapter_count,
|
||||
all_chapters_brief=all_chapters_brief,
|
||||
recent_plot=recent_plot,
|
||||
plot_stage_instruction=plot_stage_instruction,
|
||||
start_chapter=start_chapter,
|
||||
end_chapter=end_chapter,
|
||||
story_direction=story_direction,
|
||||
requirements=requirements or "无特殊要求"
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def get_single_character_prompt(cls, project_context: str, user_input: str) -> str:
|
||||
"""获取单个角色生成提示词"""
|
||||
return cls.format_prompt(
|
||||
cls.SINGLE_CHARACTER_GENERATION,
|
||||
project_context=project_context,
|
||||
user_input=user_input
|
||||
)
|
||||
|
||||
|
||||
# 创建全局提示词服务实例
|
||||
prompt_service = PromptService()
|
||||
Reference in New Issue
Block a user