11\

AI聊天机器人.py

@@ -0,0 +1,149 @@
+import tkinter as tk
+
+import threading
+import speech_recognition as sr
+import requests
+import pyttsx3
+from AiChatterbot import talkWithRobot, robotSay
+
+# Initialize speech synthesis object
+talker = pyttsx3.init()
+
+# Initialize speech recognition object
+recognizer = sr.Recognizer()
+
+userName = "admin"
+userPass = "123"
+# Create chat window
+def chat_window():
+    chat_window = tk.Tk()
+    chat_window.title("对话")
+    chat_window.geometry("800x400")
+
+    def send_text_message():
+        message = input_entry.get()
+        chat_text.insert(tk.END, "你: " + message + "\n")
+        response = get_response(message)
+        chat_text.insert(tk.END, "机器人: " + response + "\n")
+        input_entry.delete(0, tk.END)
+        # 语音合成回复并播放
+        talker.say(response)
+        talker.runAndWait()
+
+    def start_voice_recognition(chat_text):
+        with sr.Microphone() as source:
+            print("请说话...")
+            audio = recognizer.listen(source)
+
+        try:
+            print("识别中...")
+            text = recognizer.recognize_google(audio, language="zh-CN")
+            print("你说: " + text)
+
+            # 调用自然语言处理功能获取回复
+            response = get_response(text)
+
+            # 显示用户输入的消息和机器人的回复
+            chat_text.insert(tk.END, "你: " + text + "\n")
+            chat_text.insert(tk.END, "机器人: " + response + "\n")
+
+            # 语音合成回复并播放
+            talker.say(response)
+            talker.runAndWait()
+        except sr.UnknownValueError:
+            print("抱歉, 未能识别，请重试")
+
+    def send_voice_message():
+        start_voice_recognition(chat_text)
+
+    chat_frame = tk.Frame(chat_window)
+    chat_frame.pack(pady=10)
+
+    chat_text = tk.Text(chat_frame)
+    chat_text.pack()
+
+    input_entry = tk.Entry(chat_frame)
+    input_entry.pack(side=tk.LEFT, expand=True, fill=tk.BOTH)
+
+    send_text_button = tk.Button(chat_frame, text="发送", command=send_text_message)
+    send_text_button.pack(side=tk.LEFT)
+
+    send_voice_button = tk.Button(chat_frame, text="语音输入", command=start_voice_recognition)
+    send_voice_button.pack(side=tk.LEFT)
+
+    chat_window.mainloop()
+
+# 启动聊天窗口
+# 创建登录窗口
+def login_window():
+    login_window = tk.Tk()
+    login_window.title("登录")
+
+    # 获取屏幕宽度和高度
+    screen_width = login_window.winfo_screenwidth()
+    screen_height = login_window.winfo_screenheight()
+
+    # 设置窗口居中
+    window_width = 300
+    window_height = 200
+    x = (screen_width - window_width) // 2
+    y = (screen_height - window_height) // 2
+    login_window.geometry(f"{window_width}x{window_height}+{x}+{y}")
+
+    def login():
+        inputName = name_entry.get()
+        inputPass = pass_entry.get()
+
+        if inputName == userName and inputPass == userPass:
+            talker.say("恭喜你登录成功！")
+            talker.runAndWait()
+            login_window.destroy()
+            chat_window()
+        else:
+            talker.say("账号或密码错误，登录失败")
+            talker.runAndWait()
+
+    name_label = tk.Label(login_window, text="用户名:")
+    name_label.pack()
+    name_entry = tk.Entry(login_window)
+    name_entry.pack()
+
+    pass_label = tk.Label(login_window, text="密码:")
+    pass_label.pack()
+    pass_entry = tk.Entry(login_window, show="*")
+    pass_entry.pack()
+
+    login_button = tk.Button(login_window, text="登录", command=login)
+    login_button.pack()
+
+    login_window.mainloop()
+# 自然语言处理功能
+def get_response(message):
+    if "你好" in message:
+        return "你好，有什么可以帮助你的吗？"
+    elif "再见" in message:
+        return "再见，祝你一天愉快！"
+    else:
+        return "抱歉，我不明白你说的是什么。"
+
+
+def send_message():
+    # 获取用户输入的消息
+    chat_text = tk.Text(chat_window)
+    chat_text.pack()
+
+    input_entry = tk.Entry(chat_window)
+    input_entry.pack()
+    message = input_entry.get()
+
+    # 显示用户输入的消息
+    chat_text.insert(tk.END, "You: " + message + "\n")
+
+    # 获取模型生成的回复
+    response = get_response(message)
+
+    # 显示模型生成的回复
+    chat_text.insert(tk.END, "Bot: " + response + "\n")
+
+# 启动登录窗口
+login_window()

AiChatterbot.py

@@ -1,108 +0,0 @@
-import time
-import urllib
-import wave
-import urllib.parse
-import requests
-from pyaudio import PyAudio, paInt16
-from aip import AipSpeech
-import pyttsx3
-from AI聊天机器人 import login_window,chat_window
-
-framerate = 16000  # 采样率
-num_samples = 2000  # 采样点
-channels = 1  # 声道
-sampwidth = 2  # 采样宽度2bytes
-FILEPATH = 'D:/Tool/test/pythonProject6/myvoices.wav'      #该文件目录要存在
-
-#用于接收用户的语音输入, 并生成wav音频文件(wav、pcm、mp3的区别可详情百度)
-class Speak():
-
-    #将音频数据保存到wav文件之中
-    def save_wave_file(self, filepath, data):
-        wf = wave.open(filepath, 'wb')
-        wf.setnchannels(channels)
-        wf.setsampwidth(sampwidth)
-        wf.setframerate(framerate)
-        wf.writeframes(b''.join(data))
-        wf.close()
-
-
-    # 进行语音录制工作
-    def my_record(self):
-        pa = PyAudio()
-        # 打开一个新的音频stream
-        stream = pa.open(format=paInt16, channels=channels,
-                         rate=framerate, input=True, frames_per_buffer=num_samples)
-        my_buf = []  # 存放录音数据
-
-        t = time.time()
-        print('正在讲话...')
-
-        while time.time() < t + 5:  # 设置录音时间（秒）
-            # 循环read，每次read 2000frames
-            string_audio_data = stream.read(num_samples)
-            my_buf.append(string_audio_data)
-
-
-        print('讲话结束')
-        self.save_wave_file(FILEPATH, my_buf)    #保存下录音数据
-        stream.close()
-
-
-APP_ID = '73927317'
-API_KEY = '3jGcj5fLma64CtB3tTEuLcei'
-SECRET_KEY = 'qm8gPCF7DSKpqatx5ZQ8e4OvNLmgdYcG'  # 此处填写自己的密钥
-
-"""调用接口, 调用BaiDu AI 接口进行录音、语音识别"""
-client = AipSpeech('73927317', '3jGcj5fLma64CtB3tTEuLcei',  'qm8gPCF7DSKpqatx5ZQ8e4OvNLmgdYcG')
-
-
-class RobotSay():
-
-    def __init__(self):
-        # 初始化语音
-        self.engine = pyttsx3.init()  # 初始化语音库
-
-        # 设置语速
-        self.rate = self.engine.getProperty('rate')
-        self.engine.setProperty('rate', self.rate - 50)
-
-    def say(self, msg):
-        # 输出语音
-        self.engine.say(msg)  # 合成语音
-        self.engine.runAndWait()
-
-class ReadWav():
-    # 读取文件
-    def get_file_content(self, filePath):
-        with open(filePath, 'rb') as fp:
-            return fp.read()
-
-    def predict(self):
-        # 调用百度AI的接口, 识别本地文件
-        return client.asr(self.get_file_content('D:/Tool/test/pythonProject6/myvoices.wav'), 'wav', 16000, {
-            'dev_pid': 1537,
-        })
-def talkWithRobot(msg):
-    url = 'http://api.qingyunke.com/api.php?key=free&appid=0&msg={}'.format(urllib.parse.quote(msg))
-    html = requests.get(url)
-    return html.json()["content"]
-
-
-robotSay = RobotSay()
-speak = Speak()
-readTalk = ReadWav()
-while True:
-
-    speak.my_record()                               #录音
-
-    text = readTalk.predict()['result'][0]          #调用百度AI接口, 将录音转化为文本信息
-
-    print("本人说:", text)                           #输出文本信息
-    response_dialogue = talkWithRobot(text)         #调用青云客机器人回答文本信息并返回
-    print("青云客说:", response_dialogue)             #输出回答文本信息
-
-    robotSay.say(response_dialogue)                 #播放回答信息
-
-readWav = ReadWav()  # 实例化方法
-print(readWav.predict())