init

AlgoriAgent/projects/algoriAgent/agent_manager.py

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+import sys  
+import os  
+current_directory = os.path.dirname(os.path.abspath(__file__))    
+sys.path.append(current_directory)  
+
+import agentscope
+from agentscope.message import Msg
+import os
+import asyncio
+import threading
+import json
+
+from agent.flex_service_toolkit import *
+from AlgoriAgent.projects.algoriAgent.agent.algori_agent import *
+
+from agentscope.service import (
+    ServiceToolkit,
+    ServiceResponse,
+    ServiceExecStatus,
+)
+import configparser
+
+config = configparser.ConfigParser()
+config.read('config.ini')
+openai_api_key = config['Global']['api_key']
+
+
+
+OPENAI_CFG_DICT = {
+    "config_name": "openai_cfg",    # 此配置的名称，必须保证唯一
+    "model_type": "openai_chat",         # 模型类型
+    "model_name": "gpt-4o-mini",  # 模型名称
+    #"model_name": "gpt-4",  # 模型名称
+    #"model_name": "llama3",
+    
+    "api_key": openai_api_key,      # OpenAI API key. 如果没有设置，将使用环境变量中的 OPENAI_API_KEY
+
+    "client_args": {
+        "base_url": config['Global']['base_chat_url']
+    },
+
+}
+
+import uuid
+from AlgoriAgent.projects.algoriAgent.tools.judge_tools import judge
+EMPTY_CHAPTER_CHAIN = [ Chapter(1, CHAPTER_FOCUS, "本章是未打开某个具体章节时的默认章节。", "处于本章节时不会有任何章节跳转。请作为一名经验丰富的算法教师，回答用户的问题。") ]
+
+def tool_name_to_tool(tool_name_list):
+    tools = []
+    for tool_name in tool_name_list:
+        if tool_name == "":
+            continue
+        if tool_name == "judge":
+            tools.append(judge)
+            
+    return tools
+
+class AgentManager:
+    def __init__(self):
+
+        agentscope.init(model_configs=[OPENAI_CFG_DICT])#, studio_url="http://0.0.0.0:5000")
+        self.agents = {}
+
+    def new_agent(self, markdown:str, markdown_prompt:str, score_prompt:str, id = None):
+        '''
+        markdown: 教案的markdown文件内容
+        markdown_prompt: 教案的prompt的markdown文件内容
+        score_prompt: 评分的prompt的markdown文件内容
+        根据3个教案的prompt，生成一个agent，返回agent的id与agent
+        '''
+        markdown_list = markdown.split("\n")
+        markdown_prompt_list = markdown_prompt.split("\n")
+        score_prompt_list = score_prompt.split("\n")
+        # 获取 H1 标题
+        title = ""
+        for line in markdown_list:
+            if line.startswith("# "):
+                title = line[2:]
+                break
+        
+        # 对于 H3 标题 构造每一个 Chapter
+        # 首先找到所有的 H3 标题 
+        chapter_dict = {}
+        chapter_sequence = []
+        for line in markdown_list:
+            if line.startswith("### "):
+                chapter_name = line[4:]
+                chapter_dict[chapter_name] = {}
+                chapter_sequence.append(chapter_name)
+        # 将 H3 标题 和 其对应的内容 构造成一个 Chapter
+
+        h3_name = ""
+        content = ""
+        for i in range(len(markdown_list)):
+            if markdown_list[i].startswith("### "): 
+                if(h3_name != ""):
+                    chapter_dict[h3_name]["markdown"] = content
+                h3_name = markdown_list[i][4:]
+                content = ""
+                continue
+            if h3_name != "":
+                content += markdown_list[i]+"\n"
+        if(h3_name != ""):
+            chapter_dict[h3_name]["markdown"] = content
+        
+
+        h3_name = ""
+        content = ""
+        require_tools = []
+        for i in range(len(markdown_prompt_list)):
+            if markdown_prompt_list[i].startswith("### "): 
+                if(h3_name != ""):
+                    chapter_dict[h3_name]["markdown_prompt"] = content
+                    chapter_dict[h3_name]["require_tools"] = tool_name_to_tool(require_tools)
+                h3_name = markdown_prompt_list[i][4:]
+                content = ""
+                continue
+
+            if h3_name != "":
+                if markdown_prompt_list[i].startswith("_require_tools"):
+                    require_tools.append(markdown_prompt_list[i].split("=")[1].strip())
+                    continue
+                content += markdown_prompt_list[i]+"\n"
+        if(h3_name != ""):
+            chapter_dict[h3_name]["markdown_prompt"] = content
+            chapter_dict[h3_name]["require_tools"] = tool_name_to_tool(require_tools)
+            
+        
+        h3_name = ""
+        content = ""
+        for i in range(len(score_prompt_list)):
+            if score_prompt_list[i].startswith("### "): 
+                if(h3_name != ""):
+                    chapter_dict[h3_name]["score_prompt"] = content
+                h3_name = score_prompt_list[i][4:]
+                content = ""
+                continue
+
+            if h3_name != "":
+                content += score_prompt_list[i]+"\n"
+        if(h3_name != ""):
+            chapter_dict[h3_name]["score_prompt"] = content
+
+
+        chapter_chain = []
+        No = 1
+        print (chapter_dict)
+        for chapter_name in chapter_sequence:
+            chapter_chain.append(Chapter(No, CHAPTER_LATTER, title, chapter_dict[chapter_name]["markdown"], chapter_dict[chapter_name]["markdown_prompt"], chapter_dict[chapter_name]["score_prompt"],chapter_dict[chapter_name]["require_tools"]))
+            No+=1
+        chapter_chain[0].Focus()
+
+
+        # Prepare the tools for the agent
+        service_toolkit = FlexServiceToolkit()
+        # for tool_function in unity_function_list:
+        #     service_toolkit.add(tool_function)
+        agent = ChapterChainAgent(
+                    name="assistant",
+                    model_config_name="openai_cfg",
+                    verbose=True,
+                    service_toolkit=service_toolkit,
+                    max_iters=5,
+                    chapter_chain=chapter_chain
+                )
+        self.agents[id] = agent
+        return id, agent
+        
+
+
+    def new_agent_with_chain(self, chapter_chain = None, id = None):
+        '''
+
+        '''
+        if chapter_chain is None:
+            chapter_chain = EMPTY_CHAPTER_CHAIN
+        
+        # Prepare the tools for the agent
+        service_toolkit = FlexServiceToolkit()
+        # for tool_function in unity_function_list:
+        #     service_toolkit.add(tool_function)
+        agent = ChapterChainAgent(
+                    name="assistant",
+                    model_config_name="openai_cfg",
+                    verbose=True,
+                    service_toolkit=service_toolkit,
+                    max_iters=5,
+                    chapter_chain=EMPTY_CHAPTER_CHAIN
+                )
+        if id is None: id = uuid.uuid4()
+        self.agents[id] = agent
+        return id, agent
+
+
+    def get_agent(self, id=None):
+        '''
+            如果在get agent之前没有new agent，并用id进行访问，就返回一个章节链为空的agent
+        '''
+        if id:
+            if  id in self.agents:
+                return self.agents[id]
+            self.agents[id] = self.new_agent(id)[1]
+        else:
+            id = str(uuid.uuid4())
+            self.agents[id] = self.new_agent()[1]
+        return id, self.agents[id]
+        
+
+    def invoke(self,id, query, user_backboard):
+        msg = Msg("user", query, role="user")
+        return self.agents[id](msg, user_backboard = user_backboard)
+    
+    
+import time
+if __name__ == '__main__':
+    # tool_demo = ToolDemo("Lava")
+    # response = tool_demo.invoke("I want such a Gurouce, when use it, it will be thrown and fly towards the mouse position for a short time, and stop. And will damage Enemy who step on it. I call it Lava Gurouce.")
+    # print(response)
+    # Start the WebSocket server in a separate thread
+    manager = AgentManager()
+    id, agent = manager.new_agent()
+
+    # Main thread logic
+    try:
+        # Your code that might be interrupted
+        while True:
+            input_data = input("用户：")
+            print(manager.invoke(id, input_data))
+            
+    except KeyboardInterrupt:
+        print("Process interrupted by user.")
+        # You can add any cleanup code here if needed
+    finally:
+        print("Exiting program.")
+        # Code to run before the program exits