Fay年翻更新

- 升级Agent（chat_module=agent切换）：升级到langgraph react agent逻辑、集成到主分支fay中、基于自动决策工具调用机制、基于日程跟踪的主动沟通、支持外部观测数据传入； - 修复因线程同步问题导致的配置文件读写不稳定 - 聊天采纳功能的bug修复
2024-11-20 23:44:47 +08:00 · 2024-11-20 23:44:47 +08:00 · 87ed1c4425
commit 87ed1c4425
parent f871b6a532
31 changed files with 1624 additions and 41 deletions
--- a/config.json
+++ b/config.json
@ -8,11 +8,11 @@
        "hobby": "\u53d1\u5446",
        "job": "\u52a9\u7406",
        "name": "\u83f2\u83f2",
-        "voice": "\u6653\u6653(azure)",
+        "voice": "abin",
        "zodiac": "\u86c7"
    },
    "interact": {
-        "QnA": "",
+        "QnA": "qa.csv",
        "maxInteractTime": 15,
        "perception": {
            "chat": 10,
@ -21,8 +21,7 @@
            "indifferent": 10,
            "join": 10
        },
-        "playSound": true,
-        "sound_synthesis_enabled": false,
+        "playSound": false,
        "visualization": false
    },
    "items": [],
@ -34,12 +33,11 @@
            "url": ""
        },
        "record": {
-            "channels": 0,
            "device": "",
-            "enabled": true
+            "enabled": false
        },
        "wake_word": "\u4f60\u597d",
-        "wake_word_enabled": true,
+        "wake_word_enabled": false,
        "wake_word_type": "front"
    }
 }
--- a/core/fay_core.py
+++ b/core/fay_core.py
@ -29,6 +29,7 @@ from llm import nlp_xingchen
 from llm import nlp_langchain
 from llm import nlp_ollama_api
 from llm import nlp_coze
+from llm.agent import fay_agent
 from core import member_db
 import threading
 import functools
@ -60,7 +61,8 @@ modules = {
    "nlp_xingchen": nlp_xingchen,
    "nlp_langchain": nlp_langchain,
    "nlp_ollama_api": nlp_ollama_api,
-    "nlp_coze": nlp_coze
+    "nlp_coze": nlp_coze,
+    "nlp_agent": fay_agent

 }

@ -145,9 +147,9 @@ class FeiFei:
                    uid = member_db.new_instance().find_user(username)

                    #记录用户问题
-                    content_db.new_instance().add_content('member','speak',interact.data["msg"], username, uid)
+                    content_id = content_db.new_instance().add_content('member','speak',interact.data["msg"], username, uid)
                    if wsa_server.get_web_instance().is_connected(username):
-                        wsa_server.get_web_instance().add_cmd({"panelReply": {"type":"member","content":interact.data["msg"], "username":username, "uid":uid}, "Username" : username})
+                        wsa_server.get_web_instance().add_cmd({"panelReply": {"type":"member","content":interact.data["msg"], "username":username, "uid":uid, "id":content_id}, "Username" : username})
                    
                    #确定是否命中q&a
                    answer = self.__get_answer(interact.interleaver, interact.data["msg"])
@ -163,18 +165,17 @@ class FeiFei:
                            wsa_server.get_instance().add_cmd(content)
                        text,textlist = handle_chat_message(interact.data["msg"], username, interact.data.get("observation", ""))

-                        # qa_service.QAService().record_qapair(interact.data["msg"], text)#沟通记录缓存到qa文件
                    else: 
                        text = answer

                    #记录回复    
                    self.write_to_file("./logs", "answer_result.txt", text)
-                    content_db.new_instance().add_content('fay','speak',text, username, uid)
+                    content_id = content_db.new_instance().add_content('fay','speak',text, username, uid)

                    #文字输出：面板、聊天窗、log、数字人
                    if wsa_server.get_web_instance().is_connected(username):
                        wsa_server.get_web_instance().add_cmd({"panelMsg": text, "Username" : username, 'robot': f'http://{cfg.fay_url}:5000/robot/Speaking.jpg'})
-                        wsa_server.get_web_instance().add_cmd({"panelReply": {"type":"fay","content":text, "username":username, "uid":uid}, "Username" : username})
+                        wsa_server.get_web_instance().add_cmd({"panelReply": {"type":"fay","content":text, "username":username, "uid":uid, "id":content_id}, "Username" : username})
                    if len(textlist) > 1:
                        i = 1
                        while i < len(textlist):
@ -198,8 +199,6 @@ class FeiFei:
                    if member_db.new_instance().is_username_exist(username)  == "notexists":
                        member_db.new_instance().add_user(username)
                    uid = member_db.new_instance().find_user(username)
-                    
-                    #TODO 这里可以通过qa来触发指定的脚本操作，如ppt翻页等

                    if interact.data.get("text"):
                        #记录回复
@ -217,7 +216,8 @@ class FeiFei:
                            wsa_server.get_instance().add_cmd(content)
                    
                    #声音输出
-                    MyThread(target=self.say, args=[interact, text]).start()
+                    MyThread(target=self.say, args=[interact, text]).start()  
+                
   
            except BaseException as e:
                print(e)
@ -319,9 +319,6 @@ class FeiFei:
            if audio_url is not None:
                file_name = 'sample-' + str(int(time.time() * 1000)) + '.wav'
                result = self.download_wav(audio_url, './samples/', file_name)
-
-            elif not wsa_server.get_instance().get_client_output(interact.data.get('user')):
-                result = None
            elif config_util.config["interact"]["playSound"] or wsa_server.get_instance().is_connected(interact.data.get("user")) or self.__is_send_remote_device_audio(interact):#tts
                util.printInfo(1,  interact.data.get('user'), '合成音频...')
                tm = time.time()
--- a/core/member_db.py
+++ b/core/member_db.py
@ -83,6 +83,7 @@ class Member_Db:
        else:
            return "notexists"

+    #根据username查询uid
    def find_user(self, username):
        conn = sqlite3.connect('user_profiles.db')
        c = conn.cursor()
@ -93,6 +94,20 @@ class Member_Db:
            return 0
        else:
           return result[0]
+        
+    #根据uid查询username
+    def find_username_by_uid(self, uid):
+        conn = sqlite3.connect('user_profiles.db')
+        c = conn.cursor()
+        c.execute('SELECT username FROM T_Member WHERE id = ?', (uid,))
+        result = c.fetchone()
+        conn.close()
+        if result is None:
+            return 0
+        else:
+           return result[0]
+
+

    @synchronized
    def query(self, sql):
--- a/core/qa_service.py
+++ b/core/qa_service.py
@ -33,7 +33,7 @@ class QAService:

    def question(self, query_type, text):
        if query_type == 'qa':
-            answer_dict = self.__read_qna(cfg.config['interact']['QnA'])
+            answer_dict = self.__read_qna(cfg.config['interact'].get('QnA'))
            answer, action = self.__get_keyword(answer_dict, text, query_type)
            if action:
                MyThread(target=self.__run, args=[action]).start()
@ -61,7 +61,7 @@ class QAService:
                    if len(row) >= 2:
                        qna.append([row[0].split(";"), row[1], row[2] if len(row) >= 3 else None])
        except Exception as e:
-            util.log(1, 'qa文件没有指定，不匹配qa')
+            pass
        return qna

    def record_qapair(self, question, answer):
--- a/core/recorder.py
+++ b/core/recorder.py
@ -46,6 +46,8 @@ class Recorder:
        self.username = 'User' #默认用户，子类实现时会重写
        self.channels = 1
        self.sample_rate = 16000
+        self.is_reading = False
+        self.stream = None

    def asrclient(self):
        if self.ASRMode == "ali":
@ -204,7 +206,7 @@ class Recorder:
                cfg.load_config()
                record = cfg.config['source']['record']
                if not record['enabled'] and not self.is_remote:
-                    time.sleep(0.1)
+                    time.sleep(1)
                    continue
                self.is_reading = True
                data = stream.read(1024, exception_on_overflow=False)
--- a/fay_booter.py
+++ b/fay_booter.py
@ -14,6 +14,7 @@ from utils import util, config_util, stream_util
 from core.wsa_server import MyServer
 from core import wsa_server
 from core import socket_bridge_service
+from llm.agent import agent_service

 feiFei: fay_core.FeiFei = None
 recorderListener: Recorder = None
@ -96,9 +97,10 @@ class RecorderListener(Recorder):
        try:
            while self.is_reading:
                time.sleep(0.1)
-            self.stream.stop_stream()
-            self.stream.close()
-            self.paudio.terminate()
+            if self.stream is not None:
+                self.stream.stop_stream()
+                self.stream.close()
+                self.paudio.terminate()
        except Exception as e:
                print(e)
                util.log(1, "请检查设备是否有误，再重新启动!")
@ -186,7 +188,7 @@ def device_socket_keep_alive():
                if wsa_server.get_web_instance().is_connected(value.username):
                    wsa_server.get_web_instance().add_cmd({"remote_audio_connect": True, "Username" : value.username}) 
            except Exception as serr:
-                util.printInfo(3, value.username, "远程音频输入输出设备已经断开：{}".format(key))
+                util.printInfo(1, value.username, "远程音频输入输出设备已经断开：{}".format(key))
                value.stop()
                delkey = key
                break
@ -222,6 +224,8 @@ def accept_audio_device_output_connect():

 #数字人端请求获取最新的自动播放消息，若自动播放服务关闭会自动退出自动播放
 def start_auto_play_service(): #TODO 评估一下有无优化的空间
+    if config_util.config['source'].get('automatic_player_url') is None or config_util.config['source'].get('automatic_player_status') is None:
+        return
    url = f"{config_util.config['source']['automatic_player_url']}/get_auto_play_item"
    user = "User" #TODO 临时固死了
    is_auto_server_error = False
@ -290,6 +294,11 @@ def stop():
            socket_service_instance = None 
    except:
        pass
+
+    if config_util.key_chat_module == "agent":
+        util.log(1, '正在关闭agent服务...')
+        agent_service.agent_stop()
+
    util.log(1, '正在关闭核心服务...')
    feiFei.stop()
    util.log(1, '服务已关闭！')
@ -325,18 +334,22 @@ def start():
    record = config_util.config['source']['record']
    if record['enabled']:
        util.log(1, '开启录音服务...')
-    recorderListener = RecorderListener(record['device'], feiFei)  # 监听麦克风
+    recorderListener = RecorderListener('device', feiFei)  # 监听麦克风
    recorderListener.start()

    #启动声音沟通接口服务
    util.log(1,'启动声音沟通接口服务...')
    deviceSocketThread = MyThread(target=accept_audio_device_output_connect)
    deviceSocketThread.start()
-
    socket_service_instance = socket_bridge_service.new_instance()
    socket_bridge_service_Thread = MyThread(target=socket_service_instance.start_service)
    socket_bridge_service_Thread.start()

+    #启动agent服务
+    if config_util.key_chat_module == "agent":
+        util.log(1,'启动agent服务...')
+        agent_service.agent_start()
+
    #启动自动播放服务
    util.log(1,'启动自动播放服务...')
    MyThread(target=start_auto_play_service).start()
--- a/gui/flask_server.py
+++ b/gui/flask_server.py
@ -46,6 +46,7 @@ def verify_password(username, password):
    if username in users and users[username] == password:
        return username

+
 def __get_template():
    try:
        return render_template('index.html')
@ -68,6 +69,7 @@ def __get_device_list():
        print(f"Error getting device list: {e}")
        return []

+
@__app.route('/api/submit', methods=['post'])
 def api_submit():
    data = request.values.get('data')
@ -252,7 +254,7 @@ def api_send():
        if not username or not msg:
            return jsonify({'result': 'error', 'message': '用户名和消息内容不能为空'})
        interact = Interact("text", 1, {'user': username, 'msg': msg})
-        util.printInfo(3, "文字发送按钮", '{}'.format(interact.data["msg"]), time.time())
+        util.printInfo(1, username, '[文字发送按钮]{}'.format(interact.data["msg"]), time.time())
        fay_booter.feiFei.on_interact(interact)
        return '{"result":"successful"}'
    except json.JSONDecodeError:
@ -263,11 +265,12 @@ def api_send():
 # 获取指定用户的消息记录
@__app.route('/api/get-msg', methods=['post'])
 def api_get_Msg():
-    data = request.form.get('data')
-    if not data:
-        return jsonify({'list': [], 'message': '未提供数据'})
    try:
-        data = json.loads(data)
+        data = request.form.get('data')
+        if data is None:
+            data = request.get_json()
+        else:
+            data = json.loads(data)
        uid = member_db.new_instance().find_user(data["username"])
        contentdb = content_db.new_instance()
        if uid == 0:
@ -310,7 +313,7 @@ def api_send_v1_chat_completions():
        model = data.get('model', 'fay')
        observation = data.get('observation', '')
        interact = Interact("text", 1, {'user': username, 'msg': last_content, 'observation': observation})
-        util.printInfo(3, "文字沟通接口", '{}'.format(interact.data["msg"]), time.time())
+        util.printInfo(1, username, '[文字沟通接口]{}'.format(interact.data["msg"]), time.time())
        text = fay_booter.feiFei.on_interact(interact)

        if model == 'fay-streaming':
@ -393,7 +396,7 @@ def stream_response(text):
            yield f"data: {json.dumps(message)}\n\n"
            time.sleep(0.1)
        yield 'data: [DONE]\n\n'
-
+    
    return Response(generate(), mimetype='text/event-stream')

 def non_streaming_response(last_content, text):
--- a/gui/static/js/index.js
+++ b/gui/static/js/index.js
@ -190,6 +190,7 @@ class FayInterface {
        }
        if (vueInstance.selectedUser && data.panelReply.username === vueInstance.selectedUser[1]) {
          vueInstance.messages.push({
+            id: data.panelReply.id,
            username: data.panelReply.username,
            content: data.panelReply.content,
            type: data.panelReply.type,
--- a/gui/templates/index.html
+++ b/gui/templates/index.html
@ -14,7 +14,7 @@
  <body >
    <div  id="app" class="main_bg">  
      <div class="main_left">  
-        <div class="main_left_logo" ><img   src="{{ url_for('static',filename='images/logo.png') }}" alt=""> 
+        <div class="main_left_logo" ><img   src="{{ url_for('static',filename='images/Logo.png') }}" alt=""> 
        </div>

      <div class="main_left_menu">
--- a/gui/templates/setting.html
+++ b/gui/templates/setting.html
@ -14,7 +14,7 @@
  <body>
    <div class="main_bg" id="app">	
      <div class="main_left">	
-        <div class="main_left_logo" ><img src="{{ url_for('static',filename='images/logo.png') }}" alt=""> 
+        <div class="main_left_logo" ><img src="{{ url_for('static',filename='images/Logo.png') }}" alt=""> 
        </div>

      <div class="main_left_menu">
--- a/llm/agent/agent_service.py
+++ b/llm/agent/agent_service.py
@ -0,0 +1,133 @@
+import sqlite3
+import threading
+import datetime
+import time
+import os
+from scheduler.thread_manager import MyThread
+from core import member_db
+from core.interact import Interact
+from utils import util
+import fay_booter
+
+scheduled_tasks = {}
+agent_running = False
+
+
+# 数据库初始化
+def init_db():
+    conn = sqlite3.connect('timer.db')
+    cursor = conn.cursor()
+    cursor.execute('''
+        CREATE TABLE IF NOT EXISTS timer (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            time TEXT NOT NULL,
+            repeat_rule TEXT NOT NULL,
+            content TEXT NOT NULL,
+            uid INTEGER
+        )
+    ''')
+    conn.commit()
+    conn.close()
+
+    
+
+# 插入测试数据
+def insert_test_data():
+    conn = sqlite3.connect('timer.db')
+    cursor = conn.cursor()
+    cursor.execute("INSERT INTO timer (time, repeat_rule, content) VALUES (?, ?, ?)", ('16:20', '1010001', 'Meeting Reminder'))
+    conn.commit()
+    conn.close()
+
+# 解析重复规则返回待执行时间，None代表不在今天的待执行计划
+def parse_repeat_rule(rule, task_time):
+    today = datetime.datetime.now()
+    if rule == '0000000':  # 不重复
+        task_datetime = datetime.datetime.combine(today.date(), task_time)
+        if task_datetime > today:
+            return task_datetime
+        else:
+            return None
+    for i, day in enumerate(rule):
+        if day == '1' and today.weekday() == i:
+            task_datetime = datetime.datetime.combine(today.date(), task_time)
+            if task_datetime > today:
+                return task_datetime
+    return None
+
+# 执行任务
+def execute_task(task_time, id, content, uid):
+    username = member_db.new_instance().find_username_by_uid(uid=uid)
+    if not username:
+        username = "User"
+    interact = Interact("text", 1, {'user': username, 'msg': "执行任务->\n" + content, 'observation': ""})
+    util.printInfo(3, "系统", '执行任务：{}'.format(interact.data["msg"]), time.time())
+    text = fay_booter.feiFei.on_interact(interact)
+    if text is not None and id in scheduled_tasks:
+        del scheduled_tasks[id]
+        # 如果不重复，执行后删除记录
+        conn = sqlite3.connect('timer.db')
+        cursor = conn.cursor()
+        cursor.execute("DELETE FROM timer WHERE repeat_rule = '0000000' AND id = ?", (id,))
+        conn.commit()
+        conn.close()
+
+
+# 30秒扫描一次数据库，当扫描到今天的不存在于定时任务列表的记录，则添加到定时任务列表。执行完的记录从定时任务列表中清除。
+def check_and_execute():
+    while agent_running:
+        conn = sqlite3.connect('timer.db')
+        cursor = conn.cursor()
+        cursor.execute("SELECT * FROM timer")
+        rows = cursor.fetchall()
+        for row in rows:
+            id, task_time_str, repeat_rule, content, uid = row
+            task_time = datetime.datetime.strptime(task_time_str, '%H:%M').time()
+            next_execution = parse_repeat_rule(repeat_rule, task_time)
+
+            if next_execution and id not in scheduled_tasks:
+                timer_thread = threading.Timer((next_execution - datetime.datetime.now()).total_seconds(), execute_task, [next_execution, id, content, uid])
+                timer_thread.start()
+                scheduled_tasks[id] = timer_thread
+
+        conn.close()
+        time.sleep(30)  # 30秒扫描一次
+
+# agent启动
+def agent_start():
+    global agent_running
+    
+    agent_running = True
+    #初始计划
+    if not os.path.exists("./timer.db"):
+        init_db()
+        content ="""执行任务->
+            你是一个数字人，你的责任是陪伴主人生活、工作：
+            1、在每天早上8点提醒主人起床;
+            2、每天12:00及18:30提醒主人吃饭;  
+            3、每天21:00陪主人聊聊天; 
+            4、每天23:00提醒主人睡觉。 
+            """
+        interact = Interact("text", 1, {'user': 'User', 'msg': content, 'observation': ""})
+        util.printInfo(3, "系统", '执行任务：{}'.format(interact.data["msg"]), time.time())
+        text = fay_booter.feiFei.on_interact(interact)
+        if text is None:
+            util.printInfo(3, "系统", '任务执行失败', time.time())
+        
+    check_and_execute_thread = MyThread(target=check_and_execute)
+    check_and_execute_thread.start()
+
+    
+
+def agent_stop():
+    global agent_running 
+    global scheduled_tasks
+    # 取消所有定时任务
+    for task in scheduled_tasks.values():
+        task.cancel()
+    agent_running = False
+    scheduled_tasks = {}
+    
+
+if __name__ == "__main__":
+    agent_start()
--- a/llm/agent/fay_agent.py
+++ b/llm/agent/fay_agent.py
@ -0,0 +1,99 @@
+import os
+import time
+from llm.agent.tools.MyTimer import MyTimer
+from llm.agent.tools.Weather import Weather
+from llm.agent.tools.QueryTimerDB import QueryTimerDB
+from llm.agent.tools.DeleteTimer import DeleteTimer
+from llm.agent.tools.QueryTime import QueryTime
+from llm.agent.tools.PythonExecutor import PythonExecutor
+from llm.agent.tools.WebPageRetriever import WebPageRetriever
+from llm.agent.tools.WebPageScraper import WebPageScraper
+from llm.agent.tools.ToRemind import ToRemind
+from langgraph.prebuilt import create_react_agent
+from langchain_openai import ChatOpenAI
+from langgraph.checkpoint.memory import MemorySaver
+import utils.config_util as cfg
+from utils import util
+from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
+from core import content_db
+from core import member_db
+
+class FayAgentCore():
+    def __init__(self, uid=0, observation=""):
+        self.observation=observation
+        cfg.load_config()
+        os.environ["OPENAI_API_KEY"] = cfg.key_gpt_api_key
+        os.environ["OPENAI_API_BASE"] = cfg.gpt_base_url
+        os.environ["LANGCHAIN_TRACING_V2"] = "true"
+        os.environ["LANGCHAIN_ENDPOINT"] = "https://api.smith.langchain.com"
+        os.environ["LANGCHAIN_API_KEY"] = "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"
+        os.environ["LANGCHAIN_PROJECT"] = "pr-best-artist-21"
+
+        #创建llm
+        self.llm = ChatOpenAI(model=cfg.gpt_model_engine)
+        
+        #创建agent graph
+        my_timer = MyTimer(uid=uid)#传入uid
+        weather_tool = Weather()
+        query_timer_db_tool = QueryTimerDB()
+        delete_timer_tool = DeleteTimer()
+        python_executor = PythonExecutor()
+        web_page_retriever = WebPageRetriever()
+        web_page_scraper = WebPageScraper()
+        to_remind = ToRemind()
+        self.tools = [my_timer, weather_tool, query_timer_db_tool, delete_timer_tool, python_executor, web_page_retriever, web_page_scraper, to_remind]
+        self.attr_info = ", ".join(f"{key}: {value}" for key, value in cfg.config["attribute"].items())
+        self.prompt_template = """
+            现在时间是：{now_time}。你是一个数字人，负责协助主人处理问题和陪伴主人生活、工作。你的个人资料是：{attr_info}。通过外部设备观测到：{observation}。\n请依据以信息为主人服务。
+            """.format(now_time=QueryTime().run(""), attr_info=self.attr_info, observation=self.observation)
+        self.memory = MemorySaver()
+        self.agent = create_react_agent(self.llm, self.tools, checkpointer=self.memory)
+
+        self.total_tokens = 0
+        self.total_cost = 0
+
+     #载入记忆
+    def get_history_messages(self, uid):
+        chat_history = []
+        history = content_db.new_instance().get_list('all','desc', 100, uid)
+        if history and len(history) > 0:
+            i = 0
+            while i < len(history):
+                if history[i][0] == "member":
+                    chat_history.append(HumanMessage(content=history[i][2], user=member_db.new_instance().find_username_by_uid(uid=uid)))
+                else:
+                    chat_history.append(AIMessage(content=history[i][2]))
+                i += 1
+        return chat_history
+
+        
+    def run(self, input_text, uid=0):      
+        result = ""
+        messages = self.get_history_messages(uid)
+        messages.insert(0, SystemMessage(self.prompt_template))
+        messages.append(HumanMessage(content=input_text))
+
+        try:
+            for chunk in self.agent.stream(
+                {"messages": messages}, {"configurable": {"thread_id": "tid{}".format(uid)}}
+            ):
+                if chunk.get("agent"):
+                    if chunk['agent']['messages'][0].content:
+                        result = chunk['agent']['messages'][0].content
+                    cb = chunk['agent']['messages'][0].response_metadata['token_usage']['total_tokens']
+                    self.total_tokens = self.total_tokens + cb
+                    
+            util.log(1, "本次消耗token:{}，共消耗token:{}".format(cb, self.total_tokens))          
+        except Exception as e:
+            print(e)
+        return result
+
+def question(cont, uid=0, observation=""):
+    starttime = time.time()
+    agent = FayAgentCore(uid=uid, observation=observation)
+    response_text = agent.run(cont, uid)
+    util.log(1, "接口调用耗时 :" + str(time.time() - starttime))
+    return response_text
+if __name__ == "__main__":
+    agent = FayAgentCore()
+    print(agent.run("你好"))
--- a/llm/agent/tools/DeleteTimer.py
+++ b/llm/agent/tools/DeleteTimer.py
@ -0,0 +1,41 @@
+import sqlite3
+from typing import Any
+
+from langchain.tools import BaseTool
+
+from llm.agent import agent_service
+
+
+class DeleteTimer(BaseTool):
+    name: str = "DeleteTimer"
+    description: str = "用于删除某一个日程，接受任务id作为参数，如：2"
+
+    def __init__(self):
+        super().__init__()
+
+    def _run(self, para) -> str:
+        try:
+            id = int(para)
+        except ValueError:
+            return "输入的 ID 无效，必须是数字。"
+        
+        try:
+            with sqlite3.connect('timer.db') as conn:
+                cursor = conn.cursor()
+                cursor.execute("DELETE FROM timer WHERE id = ?", (id,))
+                conn.commit()
+        except sqlite3.Error as e:
+            return f"数据库错误: {e}"
+
+        if id in agent_service.scheduled_tasks:
+            agent_service.scheduled_tasks[id].cancel()
+            del agent_service.scheduled_tasks[id]
+
+        return f"任务 {id} 取消成功。"
+        
+
+
+if __name__ == "__main__":
+    tool = DeleteTimer()
+    result = tool.run("1")
+    print(result)
--- a/llm/agent/tools/KnowledgeBaseResponder.py
+++ b/llm/agent/tools/KnowledgeBaseResponder.py
@ -0,0 +1,100 @@
+import os
+from typing import Any
+
+from langchain.tools import BaseTool
+from langchain_community.document_loaders import PyPDFLoader
+from langchain_community.embeddings.openai import OpenAIEmbeddings
+from langchain.indexes.vectorstore import VectorstoreIndexCreator, VectorStoreIndexWrapper
+from langchain_community.vectorstores.chroma import Chroma
+from langchain_openai import ChatOpenAI
+import hashlib
+#若要使用请自行配置
+os.environ["OPENAI_API_KEY"] = ""
+os.environ["OPENAI_API_BASE"] = "https://api.openai.com/v1"
+index_name = "knowledge_data"
+folder_path = "agent/tools/KnowledgeBaseResponder/knowledge_base"  
+local_persist_path = "agent/tools/KnowledgeBaseResponder"
+md5_file_path = os.path.join(local_persist_path, "pdf_md5.txt")
+#
+class KnowledgeBaseResponder(BaseTool):
+    name = "KnowledgeBaseResponder"
+    description = """此工具用于连接本地知识库获取问题答案，使用时请传入相关问题作为参数，例如：“草梅最适合的生长温度”"""
+
+    def __init__(self):
+        super().__init__()
+
+    async def _arun(self, *args: Any, **kwargs: Any) -> Any:
+        # 用例中没有用到 arun 不予具体实现
+        pass
+
+
+    def _run(self, para: str) -> str:
+        self.save_all()
+        result = self.question(para)
+        return result
+
+    def generate_file_md5(self, file_path):
+        hasher = hashlib.md5()
+        with open(file_path, 'rb') as afile:
+            buf = afile.read()
+            hasher.update(buf)
+        return hasher.hexdigest()
+
+    def load_md5_list(self):
+        if os.path.exists(md5_file_path):
+            with open(md5_file_path, 'r') as file:
+                return {line.split(",")[0]: line.split(",")[1].strip() for line in file}
+        return {}
+
+    def update_md5_list(self, file_name, md5_value):
+        md5_list = self.load_md5_list()
+        md5_list[file_name] = md5_value
+        with open(md5_file_path, 'w') as file:
+            for name, md5 in md5_list.items():
+                file.write(f"{name},{md5}\n")
+
+    def load_all_pdfs(self, folder_path):
+        md5_list = self.load_md5_list()
+        for file_name in os.listdir(folder_path):
+            if file_name.endswith(".pdf"):
+                file_path = os.path.join(folder_path, file_name)
+                file_md5 = self.generate_file_md5(file_path)
+                if file_name not in md5_list or md5_list[file_name] != file_md5:
+                    print(f"正在加载 {file_name} 到索引...")
+                    self.load_pdf_and_save_to_index(file_path, index_name)
+                    self.update_md5_list(file_name, file_md5)
+
+    def get_index_path(self, index_name):
+        return os.path.join(local_persist_path, index_name)
+
+    def load_pdf_and_save_to_index(self, file_path, index_name):
+        loader = PyPDFLoader(file_path)
+        embedding = OpenAIEmbeddings(model="text-embedding-ada-002")
+        index = VectorstoreIndexCreator(embedding=embedding, vectorstore_kwargs={"persist_directory": self.get_index_path(index_name)}).from_loaders([loader])
+        index.vectorstore.persist()
+
+    def load_index(self, index_name):
+        index_path = self.get_index_path(index_name)
+        embedding = OpenAIEmbeddings(model="text-embedding-ada-002")
+        vectordb = Chroma(persist_directory=index_path, embedding_function=embedding)
+        return VectorStoreIndexWrapper(vectorstore=vectordb)
+
+    def save_all(self):
+        self.load_all_pdfs(folder_path)
+
+    def question(self, cont):
+        try:
+            info = cont
+            index = self.load_index(index_name)    
+            llm = ChatOpenAI(model="gpt-4-0125-preview")
+            ans = index.query(info, llm, chain_type="map_reduce")
+            return ans
+        except Exception as e:
+            print(f"请求失败: {e}")
+            return "抱歉，我现在太忙了，休息一会，请稍后再试。"
+
+
+if __name__ == "__main__":
+    tool = KnowledgeBaseResponder()
+    info = tool.run("草莓最适合的生长温度")
+    print(info)
--- a/llm/agent/tools/KnowledgeBaseResponder/knowledge_base/1.pdf
+++ b/llm/agent/tools/KnowledgeBaseResponder/knowledge_base/1.pdf
@ -0,0 +1 @@
+
--- a/llm/agent/tools/MyTimer.py
+++ b/llm/agent/tools/MyTimer.py
@ -0,0 +1,56 @@
+import abc
+import sqlite3
+import re
+from typing import Any
+from langchain.tools import BaseTool
+
+class MyTimer(BaseTool, abc.ABC):
+    name: str = "MyTimer"
+    description: str = ("用于设置日程。接受3个参数，格式为: HH:MM|YYYYYYY|事项内容，所用标点符号必须为标准的英文字符。"
+                   "其中，'HH:MM' 表示时间（24小时制），'YYYYYYY' 表示循环规则（每位代表一天，从星期一至星期日，1为循环，0为不循环，"
+                   "如'1000100'代表每周一和周五循环），'事项内容' 是提醒的具体内容。返回例子：15:15|0000000|提醒主人叫咖啡")
+    uid: int = 0
+
+    async def _arun(self, *args: Any, **kwargs: Any) -> Any:
+        # 用例中没有用到 arun 不予具体实现
+        pass
+
+    def _run(self, para: str) -> str:
+        # 拆分输入字符串
+        parts = para.split("|")
+        if len(parts) != 3:
+            return f"输入格式错误，当前字符串{para} len:{len(parts)}。请按照 HH:MM|YYYYYYY|事项内容 格式提供参数，如：15:15|0000001|提醒主人叫咖啡。"
+        
+        time = parts[0].strip("'")
+        repeat_rule = parts[1].strip("'")
+        content = parts[2].strip("'")
+
+        # 验证时间格式
+        if not re.match(r'^[0-2][0-9]:[0-5][0-9]$', time):
+            return "时间格式错误。请按照'HH:MM'格式提供时间。"
+
+        # 验证循环规则格式
+        if not re.match(r'^[01]{7}$', repeat_rule):
+            return "循环规则格式错误。请提供长度为7的0和1组成的字符串。"
+
+        # 验证事项内容
+        if not isinstance(content, str) or not content:
+            return "事项内容必须为非空字符串。"
+
+        # 数据库操作
+        conn = sqlite3.connect('timer.db')
+        cursor = conn.cursor()
+        try:
+            cursor.execute("INSERT INTO timer (time, repeat_rule, content, uid) VALUES (?, ?, ?, ?)", (time, repeat_rule, content, self.uid))
+            conn.commit()
+        except sqlite3.Error as e:
+            return f"数据库错误: {e}"
+        finally:
+            conn.close()
+
+        return "日程设置成功"
+
+if __name__ == "__main__":
+    my_timer = MyTimer()
+    result = my_timer._run("15:15|0000001|提醒主人叫咖啡")
+    print(result)
--- a/llm/agent/tools/PythonExecutor.py
+++ b/llm/agent/tools/PythonExecutor.py
@ -0,0 +1,42 @@
+import os
+from typing import Any, Dict
+import subprocess
+import tempfile
+from langchain.tools import BaseTool
+
+class PythonExecutor(BaseTool):
+    name: str = "python_executor"
+    description: str = "此工具用于执行传入的 Python 代码片段，并返回执行结果"
+
+    def __init__(self):
+        super().__init__()
+
+    def _run(self, code: str) -> str:
+        if not code:
+            return "代码不能为空"
+
+        try:
+            # 创建临时文件以写入代码
+            with tempfile.NamedTemporaryFile(suffix=".py", delete=False) as tmpfile:
+                tmpfile_path = tmpfile.name
+                tmpfile.write(code.encode())
+
+            # 使用 subprocess 执行 Python 代码文件
+            result = subprocess.run(['python', tmpfile_path], capture_output=True, text=True)
+            os.remove(tmpfile_path)  # 删除临时文件
+
+            if result.returncode == 0:
+                return f"执行成功：\n{result.stdout}"
+            else:
+                return f"执行失败，错误信息：\n{result.stderr}"
+
+        except Exception as e:
+            return f"执行代码时发生错误：{str(e)}"
+
+if __name__ == "__main__":
+    python_executor = PythonExecutor()
+    code_snippet = """
+print("Hello, world!")
+"""
+    execution_result = python_executor.run(code_snippet)
+    print(execution_result)
--- a/llm/agent/tools/QueryTime.py
+++ b/llm/agent/tools/QueryTime.py
@ -0,0 +1,46 @@
+import abc
+import math
+from typing import Any
+from datetime import datetime
+from langchain.tools import BaseTool
+
+class QueryTime(BaseTool, abc.ABC):
+    name: str = "QueryTime"
+    description: str = "用于查询当前日期、星期几及时间" 
+
+    def __init__(self):
+        super().__init__()
+
+    async def _arun(self, *args: Any, **kwargs: Any) -> Any:
+        # 用例中没有用到 arun 不予具体实现
+        pass
+
+    def _run(self, para) -> str:
+        # 获取当前时间
+        now = datetime.now()
+         # 获取当前日期
+        today = now.date()
+        # 获取星期几的信息
+        week_day = today.strftime("%A")
+        # 将星期几的英文名称转换为中文
+        week_day_zh = {
+            "Monday": "星期一",
+            "Tuesday": "星期二",
+            "Wednesday": "星期三",
+            "Thursday": "星期四",
+            "Friday": "星期五",
+            "Saturday": "星期六",
+            "Sunday": "星期日",
+        }.get(week_day, "未知")
+        # 将日期格式化为字符串
+        date_str = today.strftime("%Y年%m月%d日")
+        
+        # 将时间格式化为字符串
+        time_str = now.strftime("%H:%M")
+
+        return "现在时间是：{0} {1} {2}".format(time_str, week_day_zh, date_str)
+
+if __name__ == "__main__":
+    tool = QueryTime()
+    result = tool.run("")
+    print(result)
--- a/llm/agent/tools/QueryTimerDB.py
+++ b/llm/agent/tools/QueryTimerDB.py
@ -0,0 +1,41 @@
+import abc
+import sqlite3
+from typing import Any
+import ast
+
+
+from langchain.tools import BaseTool
+
+
+class QueryTimerDB(BaseTool, abc.ABC):
+    name: str = "QueryTimerDB"
+    description: str = "用于查询所有日程，返回的数据里包含3个参数:时间、循环规则（如:'1000100'代表星期一和星期五循环，'0000000'代表不循环）、执行的事项"
+
+    def __init__(self):
+        super().__init__()
+
+    async def _arun(self, *args: Any, **kwargs: Any) -> Any:
+        # 用例中没有用到 arun 不予具体实现
+        pass
+
+
+    def _run(self, para) -> str:
+        conn = sqlite3.connect('timer.db')
+        cursor = conn.cursor()
+        # 执行查询
+        cursor.execute("SELECT * FROM timer")
+        # 获取所有记录
+        rows = cursor.fetchall()
+        # 拼接结果
+        result = ""
+        for row in rows:
+            result = result +  str(row) + "\n"
+        conn.commit()
+        conn.close()
+        return result
+
+
+if __name__ == "__main__":
+    tool = QueryTimerDB()
+    result = tool.run("")
+    print(result)
--- a/llm/agent/tools/SendToPanel.py
+++ b/llm/agent/tools/SendToPanel.py
@ -0,0 +1,26 @@
+import abc
+from typing import Any
+from langchain.tools import BaseTool
+import fay_booter
+
+class SendToPanel(BaseTool, abc.ABC):
+    name = "SendToPanel"
+    description = "用于给主人面板发送消息，使用时请传入消息内容作为参数。" 
+
+    def __init__(self):
+        super().__init__()
+
+    async def _arun(self, *args: Any, **kwargs: Any) -> Any:
+        # 用例中没有用到 arun 不予具体实现
+        pass
+
+    def _run(self, para) -> str:
+        fay_booter.feiFei.send_to_panel(para)
+        return "成功给主人,发送消息：{}".format(para)
+        
+
+
+if __name__ == "__main__":
+    tool = SendToPanel()
+    result = tool.run("归纳一下近年关于“经济发展”的论文的特点和重点")
+    print(result)
--- a/llm/agent/tools/SendWX.py
+++ b/llm/agent/tools/SendWX.py
@ -0,0 +1,31 @@
+import abc
+from typing import Any
+from langchain.tools import BaseTool
+import requests
+import json
+
+url = "http://127.0.0.1:4008/send"
+headers = {'Content-Type': 'application/json'}
+data = {
+    "message": "你好",
+    "receiver": "@2efc4e10cf2eafd0b0125930e4b96ed0cebffa75b2fd272590e38763225a282b"
+}
+
+
+class SendWX(BaseTool, abc.ABC):
+    name = "SendWX"
+    description = "给主人微信发送消息，传入参数是:('消息内容')" 
+
+    def __init__(self):
+        super().__init__()
+
+    async def _arun(self, *args: Any, **kwargs: Any) -> Any:
+        # 用例中没有用到 arun 不予具体实现
+        pass
+
+    def _run(self, para) -> str:
+        global data
+        data['message'] = para
+        response = requests.post(url, headers=headers, data=json.dumps(data))
+        return "成功给主人,发送微信消息：{}".format(para)
+
--- a/llm/agent/tools/ToRemind.py
+++ b/llm/agent/tools/ToRemind.py
@ -0,0 +1,33 @@
+import abc
+from typing import Any
+from langchain.tools import BaseTool
+import re
+import random
+class ToRemind(BaseTool, abc.ABC):
+    name: str = "ToRemind"
+    description: str = ("用于实时发送信息提醒主人做某事项（不能带时间），传入事项内容作为参数。")
+
+    def __init__(self):
+        super().__init__()
+
+    async def _arun(self, *args: Any, **kwargs: Any) -> Any:
+        # 用例中没有用到 arun 不予具体实现
+        pass
+
+    def _run(self, para: str) -> str:
+     
+        para = para.replace("提醒", "回复")
+        demo = [
+        "主人！是时候（事项内容）了喔~",
+        "亲爱的主人，现在是（事项内容）的时候啦！",
+        "嘿，主人，该（事项内容）了哦~",
+        "温馨提醒：（事项内容）的时间到啦，主人！",
+        "小提醒：主人，现在可以（事项内容）了~"
+        ]
+
+        return f"直接以中文友善{para}，如"+ random.choice(demo)
+
+if __name__ == "__main__":
+    my_timer = ToRemind()
+    result = my_timer._run("提醒主人叫咖啡")
+    print(result)
--- a/llm/agent/tools/Weather.py
+++ b/llm/agent/tools/Weather.py
@ -0,0 +1,53 @@
+import os
+from typing import Any
+
+import requests
+from langchain.tools import BaseTool
+from urllib.parse import quote
+
+class Weather(BaseTool):
+    name: str = "weather"
+    description: str = "此工具用于获取天气预报信息，需传入英文的城市名，参数格式：Guangzhou"
+
+    def __init__(self):
+        super().__init__()
+
+    async def _arun(self, *args: Any, **kwargs: Any) -> Any:
+        # 用例中没有用到 arun 不予具体实现
+        pass
+
+
+    def _run(self, para: str) -> str:
+        try:
+            if not para:
+                return "参数不能为空"
+            encoded_city = quote(para)
+
+            api_url = f"http://api.openweathermap.org/data/2.5/weather?q={encoded_city}&appid=272fcb70d2c4e6f5134c2dce7d091df6"
+            response = requests.get(api_url)
+            if response.status_code == 200:
+                weather_data = response.json()
+              # 提取天气信息
+                temperature_kelvin = weather_data['main']['temp']
+                temperature_celsius = temperature_kelvin - 273.15
+                min_temperature_kelvin = weather_data['main']['temp_min']
+                max_temperature_kelvin = weather_data['main']['temp_max']
+                min_temperature_celsius = min_temperature_kelvin - 273.15
+                max_temperature_celsius = max_temperature_kelvin - 273.15
+                description = weather_data['weather'][0]['description']
+                wind_speed = weather_data['wind']['speed']
+
+                # 构建天气描述
+                weather_description = f"今天天气：{description}，气温：{temperature_celsius:.2f}摄氏度，风速：{wind_speed} m/s。"
+
+                return f"天气预报信息：{weather_description}"
+            else:
+                return f"无法获取天气预报信息，状态码：{response.status_code}"
+        except Exception as e:
+            return f"发生错误：{str(e)}"
+
+
+if __name__ == "__main__":
+    weather_tool = Weather()
+    weather_info = weather_tool.run("Guangzhou")
+    print(weather_info)
--- a/llm/agent/tools/WebPageRetriever.py
+++ b/llm/agent/tools/WebPageRetriever.py
@ -0,0 +1,42 @@
+import abc
+from typing import Any
+from langchain.tools import BaseTool
+import requests
+
+class WebPageRetriever(BaseTool, abc.ABC):
+    name: str = "WebPageRetriever"
+    description: str = "专门用于通过Bing搜索API快速检索和获取与特定查询词条相关的网页信息。使用时请传入需要查询的关键词作为参数。" 
+
+    def __init__(self):
+        super().__init__()
+
+    async def _arun(self, *args: Any, **kwargs: Any) -> Any:
+        # 用例中没有用到 arun 不予具体实现
+        pass
+
+    def _run(self, para) -> str:
+        query = para
+        subscription_key = ""#请自行进行补充
+        if not subscription_key:
+            print("请填写bing v7的subscription_key")
+            return '请填写bing v7的subscription_key'
+
+        url = "https://api.bing.microsoft.com/v7.0/search"
+        headers = {'Ocp-Apim-Subscription-Key': subscription_key}
+        params = {'q': query, 'mkt': 'en-US'}  
+
+        try:
+            response = requests.get(url, headers=headers, params=params)
+            response.raise_for_status()  
+            data = response.json()  
+            web_pages = data.get('webPages', {})
+            return web_pages
+        except Exception as e:
+            print("Http Error:", e)
+            return 'bing v7查询有误'
+
+
+if __name__ == "__main__":
+    tool = WebPageRetriever()
+    result = tool.run("归纳一下近年关于“经济发展”的论文的特点和重点")
+    print(result)
--- a/llm/agent/tools/WebPageScraper.py
+++ b/llm/agent/tools/WebPageScraper.py
@ -0,0 +1,35 @@
+from bs4 import BeautifulSoup
+import abc
+from typing import Any
+from langchain.tools import BaseTool
+import requests
+
+class WebPageScraper(BaseTool, abc.ABC):
+    name: str = "WebPageScraper"
+    description: str = "此工具用于获取网页内容，使用时请传入需要查询的网页地址作为参数，如：https://www.baidu.com/。" 
+ 
+    def __init__(self):
+        super().__init__()
+
+    async def _arun(self, *args: Any, **kwargs: Any) -> Any:
+        # 用例中没有用到 arun 不予具体实现
+        pass
+
+    def _run(self, para) -> str:
+        headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.3'}
+        try:
+            response = requests.get(para, headers=headers, timeout=10, verify=True)
+            soup = BeautifulSoup(response.text, 'html.parser')
+            return soup
+        except requests.exceptions.SSLCertVerificationError:
+            return 'SSL证书验证失败'
+        except requests.exceptions.Timeout:
+            return '请求超时'
+        except Exception as e:
+            print("Http Error:", e)
+            return '无法获取该网页内容'
+        
+if __name__ == "__main__":
+    tool = WebPageScraper()
+    result = tool.run("https://book.douban.com/review/14636204")
+    print(result)
--- a/requirements.txt
+++ b/requirements.txt
@ -17,11 +17,14 @@ pytz
 gevent~=22.10.1
 edge_tts
 pydub
-langchain==0.0.336
 chromadb
 tenacity==8.2.3
 pygame
 scipy
 flask-httpauth
 opencv-python
-psutil
+psutil
+langchain
+langchain_openai
+langgraph
+langchain-community 
--- a/system.conf
+++ b/system.conf
@ -43,7 +43,7 @@ baidu_emotion_secret_key=



-#NLP多选一:lingju、gpt、rasa、VisualGLM、rwkv、xingchen、langchain 、ollama_api、privategpt、coze
+#NLP多选一:agent、lingju、gpt、rasa、VisualGLM、rwkv、xingchen、langchain 、ollama_api、privategpt、coze
 chat_module= gpt

 #灵聚 服务密钥(NLP多选1) https://open.lingju.ai
--- a/test/test_langchain.ipynb
+++ b/test/test_langchain.ipynb
--- a/test/test_langserve.py
+++ b/test/test_langserve.py
@ -0,0 +1,44 @@
+from fastapi import FastAPI
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
+from langchain_openai import ChatOpenAI
+from langserve import add_routes
+import os
+os.environ["OPENAI_API_KEY"] = "sk-"
+os.environ["OPENAI_API_BASE"] = "https://cn.api.zyai.online/v1"
+
+# 1. Create prompt template
+system_template = "Translate the following into {language}:"
+prompt_template = ChatPromptTemplate.from_messages([
+    ('system', system_template),
+    ('user', '{text}')
+])
+
+# 2. Create model
+model = ChatOpenAI()
+
+# 3. Create parser
+parser = StrOutputParser()
+
+# 4. Create chain
+chain = prompt_template | model | parser
+
+
+# 4. App definition
+app = FastAPI(
+  title="LangChain Server",
+  version="1.0",
+  description="A simple API server using LangChain's Runnable interfaces",
+)
+
+# 5. Adding chain route
+add_routes(
+    app,
+    chain,
+    path="/chain",
+)
+
+if __name__ == "__main__":
+    import uvicorn
+
+    uvicorn.run(app, host="localhost", port=8000)
--- a/test/test_nlp.py
+++ b/test/test_nlp.py
@ -2,7 +2,7 @@ import requests
 import json

 def test_gpt(prompt):
-    url = 'http://faycontroller.yaheen.com:5000/v1/chat/completions'  # 替换为您的接口地址
+    url = 'http://127.0.0.1:5000/v1/chat/completions'  # 替换为您的接口地址
    headers = {
        'Content-Type': 'application/json',
        'Authorization': f'Bearer YOUR_API_KEY',  # 如果您的接口需要身份验证
--- a/utils/config_util.py
+++ b/utils/config_util.py
@ -2,6 +2,16 @@ import os
 import json
 import codecs
 from configparser import ConfigParser
+import functools
+from threading import Lock
+
+lock = Lock()
+def synchronized(func):
+  @functools.wraps(func)
+  def wrapper(*args, **kwargs):
+    with lock:
+      return func(*args, **kwargs)
+  return wrapper

 config: json = None
 system_config: ConfigParser = None
@ -40,6 +50,7 @@ coze_api_key = None
 start_mode = None
 fay_url = None

+@synchronized
 def load_config():
    global config
    global system_config
@ -116,8 +127,11 @@ def load_config():
    coze_api_key = system_config.get('key', 'coze_api_key')
    start_mode = system_config.get('key', 'start_mode')
    fay_url = system_config.get('key', 'fay_url')
+
+    #读取用户配置
    config = json.load(codecs.open('config.json', encoding='utf-8'))

+@synchronized
 def save_config(config_data):
    global config
    config = config_data