refactor: AI对话基本完成

pkg/openai/requester/apis/chatcmpl.py

@@ -2,8 +2,10 @@ from __future__ import annotations
 
 import asyncio
 import typing
+import json
 
 import openai
+import openai.types.chat.chat_completion as chat_completion
 
 from .. import api
 from ....core import entities as core_entities
@@ -12,21 +14,127 @@ from ...session import entities as session_entities
 
 
 class OpenAIChatCompletion(api.LLMAPIRequester):
-
-    client: openai.Client
+    client: openai.AsyncClient
 
     async def initialize(self):
-        self.client = openai.Client(
-            base_url=self.ap.cfg_mgr.data['openai_config']['reverse_proxy'],
-            timeout=self.ap.cfg_mgr.data['process_message_timeout']
+        self.client = openai.AsyncClient(
+            api_key="",
+            base_url=self.ap.cfg_mgr.data["openai_config"]["reverse_proxy"],
+            timeout=self.ap.cfg_mgr.data["process_message_timeout"],
         )
 
-    async def request(self, query: core_entities.Query, conversation: session_entities.Conversation) -> typing.AsyncGenerator[llm_entities.Message, None]:
-        """请求
-        """
-        await asyncio.sleep(10)
+    async def _req(
+        self,
+        args: dict,
+    ) -> chat_completion.ChatCompletion:
+        self.ap.logger.debug(f"req chat_completion with args {args}")
+        return await self.client.chat.completions.create(**args)
 
-        yield llm_entities.Message(
-            role=llm_entities.MessageRole.ASSISTANT,
-            content="hello"
-        )
+    async def _make_msg(
+        self,
+        chat_completion: chat_completion.ChatCompletion,
+    ) -> llm_entities.Message:
+        chatcmpl_message = chat_completion.choices[0].message.dict()
+
+        message = llm_entities.Message(**chatcmpl_message)
+
+        return message
+
+    async def _closure(
+        self,
+        req_messages: list[dict],
+        conversation: session_entities.Conversation,
+        user_text: str = None,
+        function_ret: str = None,
+    ) -> llm_entities.Message:
+        self.client.api_key = conversation.use_model.token_mgr.get_token()
+
+        args = self.ap.cfg_mgr.data["completion_api_params"].copy()
+        args["model"] = conversation.use_model.name
+
+        tools = await self.ap.tool_mgr.generate_tools_for_openai(conversation)
+        # tools = [
+        #     {
+        #         "type": "function",
+        #         "function": {
+        #             "name": "get_current_weather",
+        #             "description": "Get the current weather in a given location",
+        #             "parameters": {
+        #                 "type": "object",
+        #                 "properties": {
+        #                     "location": {
+        #                         "type": "string",
+        #                         "description": "The city and state, e.g. San Francisco, CA",
+        #                     },
+        #                     "unit": {
+        #                         "type": "string",
+        #                         "enum": ["celsius", "fahrenheit"],
+        #                     },
+        #                 },
+        #                 "required": ["location"],
+        #             },
+        #         },
+        #     }
+        # ]
+        if tools:
+            args["tools"] = tools
+
+        # 设置此次请求中的messages
+        messages = req_messages
+        args["messages"] = messages
+
+        # 发送请求
+        resp = await self._req(args)
+
+        # 处理请求结果
+        message = await self._make_msg(resp)
+
+        return message
+
+    async def request(
+        self, query: core_entities.Query, conversation: session_entities.Conversation
+    ) -> typing.AsyncGenerator[llm_entities.Message, None]:
+        """请求"""
+
+        pending_tool_calls = []
+
+        req_messages = [
+            m.dict(exclude_none=True) for m in conversation.prompt.messages
+        ] + [m.dict(exclude_none=True) for m in conversation.messages]
+
+        req_messages.append({"role": "user", "content": str(query.message_chain)})
+
+        msg = await self._closure(req_messages, conversation)
+
+        yield msg
+
+        pending_tool_calls = msg.tool_calls
+
+        req_messages.append(msg.dict(exclude_none=True))
+
+        while pending_tool_calls:
+            for tool_call in pending_tool_calls:
+                func = tool_call.function
+
+                parameters = json.loads(func.arguments)
+
+                func_ret = await self.ap.tool_mgr.execute_func_call(
+                    query, func.name, parameters
+                )
+
+                msg = llm_entities.Message(
+                    role="tool", content=json.dumps(func_ret, ensure_ascii=False), tool_call_id=tool_call.id
+                )
+
+                yield msg
+
+                req_messages.append(msg.dict(exclude_none=True))
+
+            # 处理完所有调用，继续请求
+            msg = await self._closure(req_messages, conversation)
+
+            yield msg
+
+            pending_tool_calls = msg.tool_calls
+
+            req_messages.append(msg.dict(exclude_none=True))

pkg/openai/requester/modelmgr.py

@@ -19,7 +19,8 @@ class ModelManager:
 
     async def initialize(self):
         openai_chat_completion = chatcmpl.OpenAIChatCompletion(self.ap)
-        openai_token_mgr = token.TokenManager(self.ap, self.ap.cfg_mgr.data['openai_config']['api_key'].values())
+        await openai_chat_completion.initialize()
+        openai_token_mgr = token.TokenManager(self.ap, list(self.ap.cfg_mgr.data['openai_config']['api_key'].values()))
 
         self.model_list.append(
             entities.LLMModelInfo(