ChatAnthropic

app/ai/models.py

@@ -4,36 +4,48 @@ Usage:
     from app.ai.models import LLM
 
     llm = LLM.DOUBAO_SEED_LITE.create(temperature=0)
+    llm = LLM.CLAUDE_OPUS.create(temperature=0)
 """
 
 from enum import Enum
 
+from langchain_anthropic import ChatAnthropic
+from langchain_core.language_models import BaseChatModel
 from langchain_openai import ChatOpenAI
 
 from app.config import settings
 
-# 供应商连接配置
+# 供应商连接配置 = (api_key函数, base_url函数)
 _VOLCENGINE = (lambda: settings.volcengine_api_key, lambda: settings.volcengine_base_url)
+_ANTHROPIC = (lambda: settings.anthropic_api_key, lambda: settings.anthropic_base_url)
 
 
 class LLM(Enum):
-    """所有可用模型，每个枚举值 = (模型名, api_key函数, base_url函数)"""
+    """所有可用模型，每个枚举值 = (模型名, 封装类, api_key函数, base_url函数)"""
 
-    # 火山引擎
-    DOUBAO_PRO_32K = ("doubao-1-5-pro-32k-250115", *_VOLCENGINE)
-    DOUBAO_LITE_32K = ("doubao-1-5-lite-32k-250115", *_VOLCENGINE)
-    DOUBAO_SEED_LITE = ("doubao-seed-2-0-lite-260215", *_VOLCENGINE)
-    DOUBAO_SEED_PRO = ("doubao-seed-2-0-pro-260215", *_VOLCENGINE)
-    DEEPSEEK_V4_FLASH = ("deepseek-v4-flash-260425", *_VOLCENGINE)
+    # 火山引擎（OpenAI 兼容）
+    DOUBAO_PRO_32K = ("doubao-1-5-pro-32k-250115", ChatOpenAI, *_VOLCENGINE)
+    DOUBAO_LITE_32K = ("doubao-1-5-lite-32k-250115", ChatOpenAI, *_VOLCENGINE)
+    DOUBAO_SEED_LITE = ("doubao-seed-2-0-lite-260215", ChatOpenAI, *_VOLCENGINE)
+    DOUBAO_SEED_PRO = ("doubao-seed-2-0-pro-260215", ChatOpenAI, *_VOLCENGINE)
+    DEEPSEEK_V4_FLASH = ("deepseek-v4-flash-260425", ChatOpenAI, *_VOLCENGINE)
 
-    def __init__(self, model_name: str, api_key_fn, base_url_fn):
+    # Claude（Anthropic 风格）
+    CLAUDE_OPUS = ("claude-opus-4-6", ChatAnthropic, *_ANTHROPIC)
+
+    def __init__(self, model_name: str, cls, api_key_fn, base_url_fn):
         self.model_name = model_name
+        self._cls = cls
         self._api_key_fn = api_key_fn
         self._base_url_fn = base_url_fn
 
-    def create(self, **kwargs) -> ChatOpenAI:
-        """创建 LLM 实例，kwargs 透传给 ChatOpenAI（temperature, max_tokens 等）"""
-        return ChatOpenAI(
+    def create(self, **kwargs) -> BaseChatModel:
+        """创建 LLM 实例，kwargs 透传给底层封装（temperature, max_tokens 等）
+
+        封装类（ChatOpenAI / ChatAnthropic）均实现 langchain BaseChatModel 接口，
+        对上层调用方完全透明。
+        """
+        return self._cls(
             model=self.model_name,
             api_key=self._api_key_fn(),
             base_url=self._base_url_fn(),