Merge branch 'rc/new-plugin' into refactor/new-plugin-system

pkg/provider/modelmgr/requester.py

@@ -20,22 +20,45 @@ class RuntimeLLMModel:
     token_mgr: token.TokenManager
     """api key管理器"""
 
-    requester: LLMAPIRequester
+    requester: ProviderAPIRequester
     """请求器实例"""
 
     def __init__(
         self,
         model_entity: persistence_model.LLMModel,
         token_mgr: token.TokenManager,
-        requester: LLMAPIRequester,
+        requester: ProviderAPIRequester,
     ):
         self.model_entity = model_entity
         self.token_mgr = token_mgr
         self.requester = requester
 
 
-class LLMAPIRequester(metaclass=abc.ABCMeta):
-    """LLM API请求器"""
+class RuntimeEmbeddingModel:
+    """运行时 Embedding 模型"""
+
+    model_entity: persistence_model.EmbeddingModel
+    """模型数据"""
+
+    token_mgr: token.TokenManager
+    """api key管理器"""
+
+    requester: ProviderAPIRequester
+    """请求器实例"""
+
+    def __init__(
+        self,
+        model_entity: persistence_model.EmbeddingModel,
+        token_mgr: token.TokenManager,
+        requester: ProviderAPIRequester,
+    ):
+        self.model_entity = model_entity
+        self.token_mgr = token_mgr
+        self.requester = requester
+
+
+class ProviderAPIRequester(metaclass=abc.ABCMeta):
+    """Provider API请求器"""
 
     name: str = None
 
@@ -61,6 +84,7 @@ class LLMAPIRequester(metaclass=abc.ABCMeta):
         messages: typing.List[provider_message.Message],
         funcs: typing.List[resource_tool.LLMTool] = None,
         extra_args: dict[str, typing.Any] = {},
+        remove_think: bool = False,
     ) -> provider_message.Message:
         """调用API
 
@@ -69,8 +93,50 @@ class LLMAPIRequester(metaclass=abc.ABCMeta):
             messages (typing.List[llm_entities.Message]): 消息对象列表
             funcs (typing.List[tools_entities.LLMFunction], optional): 使用的工具函数列表. Defaults to None.
             extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}.
+            remove_think (bool, optional): 是否移思考中的消息. Defaults to False.
 
         Returns:
             llm_entities.Message: 返回消息对象
         """
         pass
+
+    async def invoke_llm_stream(
+        self,
+        query: pipeline_query.Query,
+        model: RuntimeLLMModel,
+        messages: typing.List[provider_message.Message],
+        funcs: typing.List[resource_tool.LLMTool] = None,
+        extra_args: dict[str, typing.Any] = {},
+        remove_think: bool = False,
+    ) -> provider_message.MessageChunk:
+        """调用API
+
+        Args:
+            model (RuntimeLLMModel): 使用的模型信息
+            messages (typing.List[provider_message.Message]): 消息对象列表
+            funcs (typing.List[resource_tool.LLMTool], optional): 使用的工具函数列表. Defaults to None.
+            extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}.
+            remove_think (bool, optional): 是否移除思考中的消息. Defaults to False.
+
+        Returns:
+            typing.AsyncGenerator[provider_message.MessageChunk]: 返回消息对象
+        """
+        pass
+
+    async def invoke_embedding(
+        self,
+        model: RuntimeEmbeddingModel,
+        input_text: typing.List[str],
+        extra_args: dict[str, typing.Any] = {},
+    ) -> typing.List[typing.List[float]]:
+        """调用 Embedding API
+
+        Args:
+            model (RuntimeEmbeddingModel): 使用的模型信息
+            input_text (typing.List[str]): 输入文本
+            extra_args (dict[str, typing.Any], optional): 额外的参数. Defaults to {}.
+
+        Returns:
+            typing.List[typing.List[float]]: 返回的 embedding 向量
+        """
+        pass