refactor: AI对话基本完成

pkg/openai/tools/entities.py

@@ -0,0 +1,35 @@
+from __future__ import annotations
+
+import abc
+import typing
+import asyncio
+
+import pydantic
+
+
+class LLMFunction(pydantic.BaseModel):
+    """函数"""
+
+    name: str
+    """函数名"""
+
+    human_desc: str
+
+    description: str
+    """给LLM识别的函数描述"""
+
+    enable: typing.Optional[bool] = True
+
+    parameters: dict
+
+    func: typing.Callable
+    """供调用的python异步方法
+    
+    此异步方法第一个参数接收当前请求的query对象，可以从其中取出session等信息。
+    query参数不在parameters中，但在调用时会自动传入。
+    但在当前版本中，插件提供的内容函数都是同步的，且均为请求无关的，故在此版本的实现（以及考虑了向后兼容性的版本）中，
+    对插件的内容函数进行封装并存到这里来。
+    """
+
+    class Config:
+        arbitrary_types_allowed = True

pkg/openai/tools/toolmgr.py

@@ -0,0 +1,99 @@
+from __future__ import annotations
+
+import typing
+
+from ...core import app, entities as core_entities
+from . import entities
+from ..session import entities as session_entities
+
+
+class ToolManager:
+    """LLM工具管理器
+    """
+
+    ap: app.Application
+
+    all_functions: list[entities.LLMFunction]
+    
+    def __init__(self, ap: app.Application):
+        self.ap = ap
+        self.all_functions = []
+
+    async def initialize(self):
+        pass
+
+    def register_legacy_function(self, name: str, description: str, parameters: dict, func: callable):
+        """注册函数
+        """
+        async def wrapper(query, **kwargs):
+            return func(**kwargs)
+        function = entities.LLMFunction(
+            name=name,
+            description=description,
+            human_desc='',
+            enable=True,
+            parameters=parameters,
+            func=wrapper
+        )
+        self.all_functions.append(function)
+
+    async def register_function(self, function: entities.LLMFunction):
+        """添加函数
+        """
+        self.all_functions.append(function)
+
+    async def get_function(self, name: str) -> entities.LLMFunction:
+        """获取函数
+        """
+        for function in self.all_functions:
+            if function.name == name:
+                return function
+        return None
+    
+    async def get_all_functions(self) -> list[entities.LLMFunction]:
+        """获取所有函数
+        """
+        return self.all_functions
+    
+    async def generate_tools_for_openai(self, conversation: session_entities.Conversation) -> str:
+        """生成函数列表
+        """
+        tools = []
+
+        for function in conversation.use_funcs:
+            if function.enable:
+                function_schema = {
+                    "type": "function",
+                    "function": {
+                        "name": function.name,
+                        "description": function.description,
+                        "parameters": function.parameters
+                    }
+                }
+                tools.append(function_schema)
+
+        return tools
+
+    async def execute_func_call(
+        self,
+        query: core_entities.Query,
+        name: str,
+        parameters: dict
+    ) -> typing.Any:
+        """执行函数调用
+        """
+
+        # return "i'm not sure for the args "+str(parameters)
+
+        function = await self.get_function(name)
+        if function is None:
+            return None
+        
+        parameters = parameters.copy()
+
+        parameters = {
+            "query": query,
+            **parameters
+        }
+        
+        return await function.func(**parameters)