添加产品规格文档并优化项目结构

Made-with: Cursor

modules/llm_factory.py

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+"""
+LLM 工厂模块
+提供统一的 LLM 客户端构建接口
+"""
+
+from typing import Optional
+from contextlib import contextmanager
+import os
+
+
+@contextmanager
+def temp_env_vars(vars_dict):
+    """临时设置环境变量的上下文管理器"""
+    old_values = {}
+    for key, value in vars_dict.items():
+        old_values[key] = os.environ.get(key)
+        os.environ[key] = value
+    try:
+        yield
+    finally:
+        for key, old_value in old_values.items():
+            if old_value is None:
+                os.environ.pop(key, None)
+            else:
+                os.environ[key] = old_value
+
+
+def build_deepseek(api_key: str, model: str, temperature: float):
+    """构建 DeepSeek LLM"""
+    from langchain_deepseek import ChatDeepSeek
+    return ChatDeepSeek(api_key=api_key, model=model, temperature=temperature)
+
+
+def build_openai(api_key: str, model: str, temperature: float):
+    """构建 OpenAI LLM"""
+    from langchain_openai import ChatOpenAI
+    return ChatOpenAI(api_key=api_key, model=model, temperature=temperature)
+
+
+def build_tongyi(api_key: str, model: str, temperature: float):
+    """构建通义千问 LLM"""
+    try:
+        from langchain_community.chat_models import ChatTongyi
+        return ChatTongyi(api_key=api_key, model=model, model_kwargs={"temperature": temperature})
+    except Exception:
+        from langchain_aliyun import ChatTongyi  # type: ignore
+        return ChatTongyi(api_key=api_key, model=model, temperature=temperature)
+
+
+def build_groq(api_key: str, model: str, temperature: float):
+    """构建 Groq LLM"""
+    from langchain_groq import ChatGroq
+    return ChatGroq(api_key=api_key, model=model, temperature=temperature)
+
+
+def build_moonshot(api_key: str, model: str, temperature: float):
+    """构建 Moonshot (Kimi) LLM"""
+    try:
+        from langchain_moonshot import ChatMoonshot  # type: ignore
+        return ChatMoonshot(api_key=api_key, model=model, temperature=temperature)
+    except Exception:
+        from langchain_community.chat_models import MoonshotChat  # type: ignore
+        return MoonshotChat(api_key=api_key, model=model, temperature=temperature)
+
+
+def build_doubao(api_key: str, temperature: float):
+    """构建豆包 LLM"""
+    try:
+        from modules.chat_doubao import create_chat_doubao
+        return create_chat_doubao(api_key=api_key, temperature=temperature)
+    except ImportError as e:
+        raise ValueError(f"豆包初始化失败：缺少依赖库。请运行：pip install 'volcengine-python-sdk[ark]'。错误：{e}")
+    except Exception as e:
+        raise ValueError(f"豆包初始化失败：{e}。请确保 API Key 格式为：access_key:secret_key:endpoint_id")
+
+
+def build_wenxin(api_key: str, model: str, temperature: float):
+    """构建文心一言 LLM"""
+    parts = api_key.split(":")
+    if len(parts) != 2:
+        raise ValueError("文心一言 API Key 格式错误，应为：app_key:app_secret（用冒号分隔）")
+    
+    app_key, app_secret = parts
+    
+    # 优先使用 langchain-community 的千帆接口（已包含在依赖中）
+    try:
+        from langchain_community.chat_models import QianfanChatEndpoint
+        
+        with temp_env_vars({"QIANFAN_AK": app_key, "QIANFAN_SK": app_secret}):
+            return QianfanChatEndpoint(
+                model=model if model else "ernie-bot-turbo",
+                temperature=temperature,
+            )
+    except ImportError:
+        # 备选方案：尝试 langchain-wenxin
+        try:
+            from langchain_wenxin import ChatWenxin
+            return ChatWenxin(
+                baidu_api_key=app_key,
+                baidu_secret_key=app_secret,
+                model=model if model else "ernie-bot-turbo",
+                temperature=temperature,
+            )
+        except ImportError as e:
+            raise ValueError(f"文心一言初始化失败：缺少依赖库。请运行：pip install qianfan（或使用已安装的 langchain-community）。错误：{e}")
+    except Exception as e:
+        raise ValueError(f"文心一言初始化失败：{e}")
+
+
+# Provider 映射表
+PROVIDER_BUILDERS = {
+    "DeepSeek": lambda api_key, model, temp: build_deepseek(api_key, model, temp),
+    "OpenAI (GPT)": lambda api_key, model, temp: build_openai(api_key, model, temp),
+    "Tongyi (通义千问)": lambda api_key, model, temp: build_tongyi(api_key, model, temp),
+    "Groq": lambda api_key, model, temp: build_groq(api_key, model, temp),
+    "Moonshot (Kimi)": lambda api_key, model, temp: build_moonshot(api_key, model, temp),
+    "豆包（字节跳动）": lambda api_key, model, temp: build_doubao(api_key, temp),
+    "文心一言（百度）": lambda api_key, model, temp: build_wenxin(api_key, model, temp),
+}
+
+
+def build_llm(provider: str, api_key: str, model: str, temperature: float):
+    """
+    统一的 LLM 构建接口
+    
+    Args:
+        provider: 提供商名称
+        api_key: API Key
+        model: 模型名称
+        temperature: 温度参数
+        
+    Returns:
+        LLM 实例
+        
+    Raises:
+        ValueError: 不支持的提供商或初始化失败
+    """
+    builder = PROVIDER_BUILDERS.get(provider)
+    if builder is None:
+        raise ValueError(f"不支持的 LLM 提供商: {provider}")
+    
+    return builder(api_key, model, temperature)
+
+
+def get_supported_providers():
+    """获取支持的提供商列表"""
+    return list(PROVIDER_BUILDERS.keys())
+
+
+def get_default_model(provider: str) -> str:
+    """获取提供商的默认模型"""
+    defaults = {
+        "DeepSeek": "deepseek-chat",
+        "OpenAI (GPT)": "gpt-4o-mini",
+        "Tongyi (通义千问)": "qwen-max",
+        "Groq": "llama3-70b-8192",
+        "Moonshot (Kimi)": "moonshot-v1-128k",
+        "豆包（字节跳动）": "",
+        "文心一言（百度）": "ernie-bot-turbo",
+    }
+    return defaults.get(provider, "")