feat: preliminarily implement pipeline invoking

pkg/provider/modelmgr/requesters/anthropicmsgs.py

@@ -24,16 +24,16 @@ class AnthropicMessages(requester.LLMAPIRequester):
     client: anthropic.AsyncAnthropic
 
     default_config: dict[str, typing.Any] = {
-        'base-url': 'https://api.anthropic.com/v1',
+        'base_url': 'https://api.anthropic.com/v1',
         'timeout': 120,
     }
 
     async def initialize(self):
 
         httpx_client = anthropic._base_client.AsyncHttpxClientWrapper(
-            base_url=self.ap.provider_cfg.data['requester']['anthropic-messages']['base-url'],
+            base_url=self.requester_cfg['base_url'],
             # cast to a valid type because mypy doesn't understand our type narrowing
-            timeout=typing.cast(httpx.Timeout, self.ap.provider_cfg.data['requester']['anthropic-messages']['timeout']),
+            timeout=typing.cast(httpx.Timeout, self.requester_cfg['timeout']),
             limits=anthropic._constants.DEFAULT_CONNECTION_LIMITS,
             follow_redirects=True,
             trust_env=True,
@@ -44,17 +44,18 @@ class AnthropicMessages(requester.LLMAPIRequester):
             http_client=httpx_client,
         )
 
-    async def call(
+    async def invoke_llm(
         self,
         query: core_entities.Query,
-        model: entities.LLMModelInfo,
+        model: requester.RuntimeLLMModel,
         messages: typing.List[llm_entities.Message],
         funcs: typing.List[tools_entities.LLMFunction] = None,
+        extra_args: dict[str, typing.Any] = {},
     ) -> llm_entities.Message:
         self.client.api_key = model.token_mgr.get_token()
 
-        args = self.ap.provider_cfg.data['requester']['anthropic-messages']['args'].copy()
-        args["model"] = model.name if model.model_name is None else model.model_name
+        args = extra_args.copy()
+        args["model"] = model.model_entity.name
 
         # 处理消息
 

pkg/provider/modelmgr/requesters/anthropicmsgs.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: Anthropic
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL

pkg/provider/modelmgr/requesters/bailianchatcmpl.py

@@ -14,6 +14,6 @@ class BailianChatCompletions(chatcmpl.OpenAIChatCompletions):
     client: openai.AsyncClient
 
     default_config: dict[str, typing.Any] = {
-        'base-url': 'https://dashscope.aliyuncs.com/compatible-mode/v1',
+        'base_url': 'https://dashscope.aliyuncs.com/compatible-mode/v1',
         'timeout': 120,
     }

pkg/provider/modelmgr/requesters/bailianchatcmpl.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: 阿里云百炼
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL

pkg/provider/modelmgr/requesters/chatcmpl.py

@@ -26,7 +26,7 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
     client: openai.AsyncClient
 
     default_config: dict[str, typing.Any] = {
-        "base-url": "https://api.openai.com/v1",
+        "base_url": "https://api.openai.com/v1",
         "timeout": 120,
     }
 
@@ -34,7 +34,7 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
 
         self.client = openai.AsyncClient(
             api_key="",
-            base_url=self.requester_cfg["base-url"],
+            base_url=self.requester_cfg["base_url"],
             timeout=self.requester_cfg["timeout"],
             http_client=httpx.AsyncClient(
                 trust_env=True, timeout=self.requester_cfg["timeout"]
@@ -65,16 +65,14 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
         self,
         query: core_entities.Query,
         req_messages: list[dict],
-        use_model: entities.LLMModelInfo,
+        use_model: requester.RuntimeLLMModel,
         use_funcs: list[tools_entities.LLMFunction] = None,
         extra_args: dict[str, typing.Any] = {}, # TODO: 所有的args都改为从此参数读取
     ) -> llm_entities.Message:
         self.client.api_key = use_model.token_mgr.get_token()
 
-        args = self.requester_cfg["args"].copy()
-        args["model"] = (
-            use_model.name if use_model.model_name is None else use_model.model_name
-        )
+        args = extra_args.copy()
+        args["model"] = use_model.model_entity.name
 
         if use_funcs:
             tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs)
@@ -104,10 +102,10 @@ class OpenAIChatCompletions(requester.LLMAPIRequester):
 
         return message
 
-    async def call(
+    async def invoke_llm(
         self,
         query: core_entities.Query,
-        model: entities.LLMModelInfo,
+        model: requester.RuntimeLLMModel,
         messages: typing.List[llm_entities.Message],
         funcs: typing.List[tools_entities.LLMFunction] = None,
         extra_args: dict[str, typing.Any] = {},

pkg/provider/modelmgr/requesters/chatcmpl.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: OpenAI
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL

pkg/provider/modelmgr/requesters/deepseekchatcmpl.py

@@ -13,7 +13,7 @@ class DeepseekChatCompletions(chatcmpl.OpenAIChatCompletions):
     """Deepseek ChatCompletion API 请求器"""
 
     default_config: dict[str, typing.Any] = {
-        'base-url': 'https://api.deepseek.com',
+        'base_url': 'https://api.deepseek.com',
         'timeout': 120,
     }
 
@@ -21,14 +21,14 @@ class DeepseekChatCompletions(chatcmpl.OpenAIChatCompletions):
         self,
         query: core_entities.Query,
         req_messages: list[dict],
-        use_model: entities.LLMModelInfo,
+        use_model: requester.RuntimeLLMModel,
         use_funcs: list[tools_entities.LLMFunction] = None,
         extra_args: dict[str, typing.Any] = {},
     ) -> llm_entities.Message:
         self.client.api_key = use_model.token_mgr.get_token()
 
-        args = self.requester_cfg['args'].copy()
-        args["model"] = use_model.name if use_model.model_name is None else use_model.model_name
+        args = extra_args.copy()
+        args["model"] = use_model.model_entity.name
 
         if use_funcs:
             tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs)

pkg/provider/modelmgr/requesters/deepseekchatcmpl.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: 深度求索
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL

pkg/provider/modelmgr/requesters/giteeaichatcmpl.py

@@ -18,7 +18,7 @@ class GiteeAIChatCompletions(chatcmpl.OpenAIChatCompletions):
     """Gitee AI ChatCompletions API 请求器"""
 
     default_config: dict[str, typing.Any] = {
-        'base-url': 'https://ai.gitee.com/v1',
+        'base_url': 'https://ai.gitee.com/v1',
         'timeout': 120,
     }
 
@@ -26,14 +26,14 @@ class GiteeAIChatCompletions(chatcmpl.OpenAIChatCompletions):
         self,
         query: core_entities.Query,
         req_messages: list[dict],
-        use_model: entities.LLMModelInfo,
+        use_model: requester.RuntimeLLMModel,
         use_funcs: list[tools_entities.LLMFunction] = None,
         extra_args: dict[str, typing.Any] = {},
     ) -> llm_entities.Message:
         self.client.api_key = use_model.token_mgr.get_token()
 
-        args = self.requester_cfg['args'].copy()
-        args["model"] = use_model.name if use_model.model_name is None else use_model.model_name
+        args = extra_args.copy()
+        args["model"] = use_model.model_entity.name
 
         if use_funcs:
             tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs)

pkg/provider/modelmgr/requesters/giteeaichatcmpl.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: Gitee AI
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL

pkg/provider/modelmgr/requesters/lmstudiochatcmpl.py

@@ -14,6 +14,6 @@ class LmStudioChatCompletions(chatcmpl.OpenAIChatCompletions):
     client: openai.AsyncClient
 
     default_config: dict[str, typing.Any] = {
-        'base-url': 'http://127.0.0.1:1234/v1',
+        'base_url': 'http://127.0.0.1:1234/v1',
         'timeout': 120,
     }

pkg/provider/modelmgr/requesters/lmstudiochatcmpl.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: LM Studio
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL

pkg/provider/modelmgr/requesters/moonshotchatcmpl.py

@@ -15,7 +15,7 @@ class MoonshotChatCompletions(chatcmpl.OpenAIChatCompletions):
     """Moonshot ChatCompletion API 请求器"""
 
     default_config: dict[str, typing.Any] = {
-        'base-url': 'https://api.moonshot.cn/v1',
+        'base_url': 'https://api.moonshot.cn/v1',
         'timeout': 120,
     }
 
@@ -23,14 +23,14 @@ class MoonshotChatCompletions(chatcmpl.OpenAIChatCompletions):
         self,
         query: core_entities.Query,
         req_messages: list[dict],
-        use_model: entities.LLMModelInfo,
+        use_model: requester.RuntimeLLMModel,
         use_funcs: list[tools_entities.LLMFunction] = None,
         extra_args: dict[str, typing.Any] = {},
     ) -> llm_entities.Message:
         self.client.api_key = use_model.token_mgr.get_token()
 
-        args = self.requester_cfg['args'].copy()
-        args["model"] = use_model.name if use_model.model_name is None else use_model.model_name
+        args = extra_args.copy()
+        args["model"] = use_model.model_entity.name
 
         if use_funcs:
             tools = await self.ap.tool_mgr.generate_tools_for_openai(use_funcs)

pkg/provider/modelmgr/requesters/moonshotchatcmpl.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: 月之暗面
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL

pkg/provider/modelmgr/requesters/ollamachat.py

@@ -22,35 +22,38 @@ REQUESTER_NAME: str = "ollama-chat"
 
 class OllamaChatCompletions(requester.LLMAPIRequester):
     """Ollama平台 ChatCompletion API请求器"""
+
     client: ollama.AsyncClient
 
     default_config: dict[str, typing.Any] = {
-        'base-url': 'http://127.0.0.1:11434',
-        'timeout': 120,
+        "base_url": "http://127.0.0.1:11434",
+        "timeout": 120,
     }
 
     async def initialize(self):
-        os.environ['OLLAMA_HOST'] = self.requester_cfg['base-url']
-        self.client = ollama.AsyncClient(
-            timeout=self.requester_cfg['timeout']
-        )
+        os.environ["OLLAMA_HOST"] = self.requester_cfg["base_url"]
+        self.client = ollama.AsyncClient(timeout=self.requester_cfg["timeout"])
 
-    async def _req(self,
-                   args: dict,
-                   ) -> Union[Mapping[str, Any], AsyncIterator[Mapping[str, Any]]]:
-        return await self.client.chat(
-            **args
-        )
+    async def _req(
+        self,
+        args: dict,
+    ) -> Union[Mapping[str, Any], AsyncIterator[Mapping[str, Any]]]:
+        return await self.client.chat(**args)
 
-    async def _closure(self, query: core_entities.Query, req_messages: list[dict], use_model: entities.LLMModelInfo,
-                       user_funcs: list[tools_entities.LLMFunction] = None,
-                       extra_args: dict[str, typing.Any] = {}) -> llm_entities.Message:
-        args: Any = self.requester_cfg['args'].copy()
-        args["model"] = use_model.name if use_model.model_name is None else use_model.model_name
+    async def _closure(
+        self,
+        query: core_entities.Query,
+        req_messages: list[dict],
+        use_model: requester.RuntimeLLMModel,
+        user_funcs: list[tools_entities.LLMFunction] = None,
+        extra_args: dict[str, typing.Any] = {},
+    ) -> llm_entities.Message:
+        args = extra_args.copy()
+        args["model"] = use_model.model_entity.name
 
         messages: list[dict] = req_messages.copy()
         for msg in messages:
-            if 'content' in msg and isinstance(msg["content"], list):
+            if "content" in msg and isinstance(msg["content"], list):
                 text_content: list = []
                 image_urls: list = []
                 for me in msg["content"]:
@@ -58,12 +61,16 @@ class OllamaChatCompletions(requester.LLMAPIRequester):
                         text_content.append(me["text"])
                     elif me["type"] == "image_base64":
                         image_urls.append(me["image_base64"])
-                        
+
                 msg["content"] = "\n".join(text_content)
-                msg["images"] = [url.split(',')[1] for url in image_urls]
-            if 'tool_calls' in msg:  # LangBot 内部以 str 存储 tool_calls 的参数，这里需要转换为 dict
-                for tool_call in msg['tool_calls']:
-                    tool_call['function']['arguments'] = json.loads(tool_call['function']['arguments'])
+                msg["images"] = [url.split(",")[1] for url in image_urls]
+            if (
+                "tool_calls" in msg
+            ):  # LangBot 内部以 str 存储 tool_calls 的参数，这里需要转换为 dict
+                for tool_call in msg["tool_calls"]:
+                    tool_call["function"]["arguments"] = json.loads(
+                        tool_call["function"]["arguments"]
+                    )
         args["messages"] = messages
 
         args["tools"] = []
@@ -77,8 +84,8 @@ class OllamaChatCompletions(requester.LLMAPIRequester):
         return message
 
     async def _make_msg(
-            self,
-            chat_completions: ollama.ChatResponse) -> llm_entities.Message:
+        self, chat_completions: ollama.ChatResponse
+    ) -> llm_entities.Message:
         message: ollama.Message = chat_completions.message
         if message is None:
             raise ValueError("chat_completions must contain a 'message' field")
@@ -86,43 +93,51 @@ class OllamaChatCompletions(requester.LLMAPIRequester):
         ret_msg: llm_entities.Message = None
 
         if message.content is not None:
-            ret_msg = llm_entities.Message(
-                role="assistant",
-                content=message.content
-            )
+            ret_msg = llm_entities.Message(role="assistant", content=message.content)
         if message.tool_calls is not None and len(message.tool_calls) > 0:
             tool_calls: list[llm_entities.ToolCall] = []
 
             for tool_call in message.tool_calls:
-                tool_calls.append(llm_entities.ToolCall(
-                    id=uuid.uuid4().hex,
-                    type="function",
-                    function=llm_entities.FunctionCall(
-                        name=tool_call.function.name,
-                        arguments=json.dumps(tool_call.function.arguments)
+                tool_calls.append(
+                    llm_entities.ToolCall(
+                        id=uuid.uuid4().hex,
+                        type="function",
+                        function=llm_entities.FunctionCall(
+                            name=tool_call.function.name,
+                            arguments=json.dumps(tool_call.function.arguments),
+                        ),
                     )
-                ))
+                )
             ret_msg.tool_calls = tool_calls
 
         return ret_msg
 
-    async def call(
-            self,
-            query: core_entities.Query,
-            model: entities.LLMModelInfo,
-            messages: typing.List[llm_entities.Message],
-            funcs: typing.List[tools_entities.LLMFunction] = None,
-            extra_args: dict[str, typing.Any] = {},
+    async def invoke_llm(
+        self,
+        query: core_entities.Query,
+        model: requester.RuntimeLLMModel,
+        messages: typing.List[llm_entities.Message],
+        funcs: typing.List[tools_entities.LLMFunction] = None,
+        extra_args: dict[str, typing.Any] = {},
     ) -> llm_entities.Message:
         req_messages: list = []
         for m in messages:
             msg_dict: dict = m.dict(exclude_none=True)
             content: Any = msg_dict.get("content")
             if isinstance(content, list):
-                if all(isinstance(part, dict) and part.get('type') == 'text' for part in content):
+                if all(
+                    isinstance(part, dict) and part.get("type") == "text"
+                    for part in content
+                ):
                     msg_dict["content"] = "\n".join(part["text"] for part in content)
             req_messages.append(msg_dict)
         try:
-            return await self._closure(query, req_messages, model, funcs, extra_args)
+            return await self._closure(
+                query=query,
+                req_messages=req_messages,
+                use_model=model,
+                use_funcs=funcs,
+                extra_args=extra_args,
+            )
         except asyncio.TimeoutError:
-            raise errors.RequesterError('请求超时')
+            raise errors.RequesterError("请求超时")

pkg/provider/modelmgr/requesters/ollamachat.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: Ollama
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL

pkg/provider/modelmgr/requesters/siliconflowchatcmpl.py

@@ -14,6 +14,6 @@ class SiliconFlowChatCompletions(chatcmpl.OpenAIChatCompletions):
     client: openai.AsyncClient
 
     default_config: dict[str, typing.Any] = {
-        'base-url': 'https://api.siliconflow.cn/v1',
+        'base_url': 'https://api.siliconflow.cn/v1',
         'timeout': 120,
     }

pkg/provider/modelmgr/requesters/siliconflowchatcmpl.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: 硅基流动
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL

pkg/provider/modelmgr/requesters/volcarkchatcmpl.py

@@ -14,6 +14,6 @@ class VolcArkChatCompletions(chatcmpl.OpenAIChatCompletions):
     client: openai.AsyncClient
 
     default_config: dict[str, typing.Any] = {
-        'base-url': 'https://ark.cn-beijing.volces.com/api/v3',
+        'base_url': 'https://ark.cn-beijing.volces.com/api/v3',
         'timeout': 120,
     }

pkg/provider/modelmgr/requesters/volcarkchatcmpl.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: 火山方舟
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL

pkg/provider/modelmgr/requesters/xaichatcmpl.py

@@ -14,6 +14,6 @@ class XaiChatCompletions(chatcmpl.OpenAIChatCompletions):
     client: openai.AsyncClient
 
     default_config: dict[str, typing.Any] = {
-        'base-url': 'https://api.x.ai/v1',
+        'base_url': 'https://api.x.ai/v1',
         'timeout': 120,
     }

pkg/provider/modelmgr/requesters/xaichatcmpl.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: xAI
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL

pkg/provider/modelmgr/requesters/zhipuaichatcmpl.py

@@ -14,6 +14,6 @@ class ZhipuAIChatCompletions(chatcmpl.OpenAIChatCompletions):
     client: openai.AsyncClient
 
     default_config: dict[str, typing.Any] = {
-        'base-url': 'https://open.bigmodel.cn/api/paas/v4',
+        'base_url': 'https://open.bigmodel.cn/api/paas/v4',
         'timeout': 120,
     }

pkg/provider/modelmgr/requesters/zhipuaichatcmpl.yaml

@@ -7,7 +7,7 @@ metadata:
     zh_CN: 智谱 AI
 spec:
   config:
-    - name: base-url
+    - name: base_url
       label:
         en_US: Base URL
         zh_CN: 基础 URL