code: import matplotlib.pyplot as plt
  import numpy as np
  import openai
  import os
  import pyaudio
  import pyttsx3
  import threading
  import tkinter as tk
  import queue
  import wave
  import whisper
  from langchain import OpenAI, SQLDatabase
  from langchain.agents.agent_toolkits import SQLDatabaseToolkit
  from langchain.agents import create_sql_agent
  from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
  from tkinter import scrolledtext
  
  AUDIO_FORMAT = pyaudio.paInt16
  CHANNELS = 1
  FRAME_RATE = 16000
  CHUNK = 1024
  
  # Get OpenAI API key
  openai.api_key = os.environ["OPENAI_API_KEY"]
  
  s2_password = "<password>"
  s2_host = "<host>"
  s2_db = "timeseries_db"
  db = SQLDatabase.from_uri(f"mysql+pymysql://admin:{s2_password}@{s2_host}:3306/{s2_db}")
  
  llm = OpenAI(
      model_name = "gpt-3.5-turbo-instruct",
      temperature = 0,
      verbose = False
  )
  
  toolkit = SQLDatabaseToolkit(db = db, llm = llm)
  
  agent_executor = create_sql_agent(
      llm = OpenAI(
          model_name = "gpt-3.5-turbo-instruct",
          temperature = 0
      ),
      toolkit = toolkit,
      verbose = False
  )
  
  model = whisper.load_model("base.en")
  
  # GUI class
  class AudioRecorderGUI:
      def __init__(self, root):
          self.root = root
          self.root.title("Audio Recorder")
  
          self.start_button = tk.Button(root, text = "Start Recording", command = self.start_recording)
          self.start_button.pack(pady = 10)
  
          self.stop_button = tk.Button(root, text = "Stop Recording", command = self.stop_recording, state = tk.DISABLED)
          self.stop_button.pack(pady = 5)
  
          self.exit_button = tk.Button(root, text = "Exit", command = self.exit_program)
          self.exit_button.pack(pady = 5)
  
          self.transcription_box = scrolledtext.ScrolledText(root, height = 5, width = 60)
          self.transcription_box.pack(padx = 10, pady = 10)
  
          self.recording_timer = None
          self.audio_filename = "audio_recording.wav"
  
          self.fig, self.ax = plt.subplots()
          self.canvas = FigureCanvasTkAgg(self.fig, master = self.root)
          self.canvas_widget = self.canvas.get_tk_widget()
          self.canvas_widget.pack(side = tk.TOP, fill = tk.BOTH, expand = 1)
          self.audio_array = np.array([])
  
          self.update_waveform = False
  
      def update_waveform_plot(self):
          while self.update_waveform and not self.stop_event.is_set():
              data = self.audio_queue.queue[-1] if not self.audio_queue.empty() else np.zeros(1024)
              self.audio_array = np.frombuffer(data, dtype = np.int16)
              self.ax.clear()
              self.ax.plot(self.audio_array, color = "r")
              self.ax.set_title("Real-Time Audio Waveform")
              self.ax.set_xlabel("Time (samples)")
              self.ax.set_ylabel("Amplitude")
              self.ax.set_ylim(-128, 128)
              self.ax.set_xlim(0, len(self.audio_array))
              self.canvas.draw()
              self.root.update()
  
      def speak_audio(self, text):
          engine = pyttsx3.init()
          engine.setProperty("voice", "english_us")
          engine.setProperty("rate", 150)
          engine.say(text)
          engine.runAndWait()
          engine.stop()
  
      def start_recording(self):
          self.transcription_box.delete(1.0, tk.END)
          self.stop_event = threading.Event()
          self.audio_queue = queue.Queue()
  
          self.record_thread = threading.Thread(target = self.record_audio)
          self.record_thread.start()
  
          self.recording_timer = self.root.after(20000, self.stop_recording)
  
          self.update_waveform = True
          self.update_waveform_plot_thread = threading.Thread(target = self.update_waveform_plot)
          self.update_waveform_plot_thread.start()
          
          self.start_button.config(state = tk.DISABLED)
          self.stop_button.config(state = tk.NORMAL)
  
      def stop_recording(self):
          if self.recording_timer:
              self.root.after_cancel(self.recording_timer)
              self.recording_timer = None
  
          self.stop_event.set()
          self.record_thread.join()
  
          transcription = self.transcribe_audio(self.audio_filename)
          self.transcription_box.insert(
              tk.END,
              "Transcription:\n" + transcription + "\n"
          )
          
          speak_thread = threading.Thread(target = self.speak_audio, args = (agent_executor.run(transcription),))
          speak_thread.start()
  
          self.start_button.config(state = tk.NORMAL)
          self.stop_button.config(state = tk.DISABLED)
  
      def record_audio(self):
          audio = pyaudio.PyAudio()
          stream = audio.open(
              format = AUDIO_FORMAT,
              channels = CHANNELS,
              rate = FRAME_RATE,
              input = True,
              frames_per_buffer = CHUNK
          )
  
          while not self.stop_event.is_set():
              data = stream.read(CHUNK)
              self.audio_queue.put(data)
  
          stream.stop_stream()
          stream.close()
          audio.terminate()
  
          with wave.open(self.audio_filename, "wb") as wf:
              wf.setnchannels(CHANNELS)
              wf.setsampwidth(audio.get_sample_size(AUDIO_FORMAT))
              wf.setframerate(FRAME_RATE)
              wf.writeframes(b''.join(list(self.audio_queue.queue)))
  
      def transcribe_audio(self, filename):
          with open(filename, "rb") as audio_file:
              # transcript = openai.Audio.transcribe(
              #     model = "whisper-1",
              #     file = audio_file,
              #     language = "en"
              # )
              transcript = model.transcribe(filename)
              return transcript["text"].strip()
  
      def exit_program(self):
          self.root.destroy()
  
  def main():
      root = tk.Tk()
      app = AudioRecorderGUI(root)
      root.mainloop()
  
  if __name__ == "__main__":
      main()
  
apis: langchain.SQLDatabase.from_uri langchain.agents.agent_toolkits.SQLDatabaseToolkit langchain.OpenAI
extract_api: [((652, 740), 'langchain.SQLDatabase.from_uri', 'SQLDatabase.from_uri', (['f"""mysql+pymysql://admin:{s2_password}@{s2_host}:3306/{s2_db}"""'], {}), "(\n    f'mysql+pymysql://admin:{s2_password}@{s2_host}:3306/{s2_db}')\n", (672, 740), False, 'from langchain import OpenAI, SQLDatabase\n'), ((743, 816), 'langchain.OpenAI', 'OpenAI', ([], {'model_name': '"""gpt-3.5-turbo-instruct"""', 'temperature': '(0)', 'verbose': '(False)'}), "(model_name='gpt-3.5-turbo-instruct', temperature=0, verbose=False)\n", (749, 816), False, 'from langchain import OpenAI, SQLDatabase\n'), ((848, 882), 'langchain.agents.agent_toolkits.SQLDatabaseToolkit', 'SQLDatabaseToolkit', ([], {'db': 'db', 'llm': 'llm'}), '(db=db, llm=llm)\n', (866, 882), False, 'from langchain.agents.agent_toolkits import SQLDatabaseToolkit\n'), ((1073, 1102), 'whisper.load_model', 'whisper.load_model', (['"""base.en"""'], {}), "('base.en')\n", (1091, 1102), False, 'import whisper\n'), ((5634, 5641), 'tkinter.Tk', 'tk.Tk', ([], {}), '()\n', (5639, 5641), True, 'import tkinter as tk\n'), ((933, 991), 'langchain.OpenAI', 'OpenAI', ([], {'model_name': '"""gpt-3.5-turbo-instruct"""', 'temperature': '(0)'}), "(model_name='gpt-3.5-turbo-instruct', temperature=0)\n", (939, 991), False, 'from langchain import OpenAI, SQLDatabase\n'), ((1266, 1335), 'tkinter.Button', 'tk.Button', (['root'], {'text': '"""Start Recording"""', 'command': 'self.start_recording'}), "(root, text='Start Recording', command=self.start_recording)\n", (1275, 1335), True, 'import tkinter as tk\n'), ((1410, 1501), 'tkinter.Button', 'tk.Button', (['root'], {'text': '"""Stop Recording"""', 'command': 'self.stop_recording', 'state': 'tk.DISABLED'}), "(root, text='Stop Recording', command=self.stop_recording, state=\n    tk.DISABLED)\n", (1419, 1501), True, 'import tkinter as tk\n'), ((1571, 1626), 'tkinter.Button', 'tk.Button', (['root'], {'text': '"""Exit"""', 'command': 'self.exit_program'}), "(root, text='Exit', command=self.exit_program)\n", (1580, 1626), True, 'import tkinter as tk\n'), ((1705, 1756), 'tkinter.scrolledtext.ScrolledText', 'scrolledtext.ScrolledText', (['root'], {'height': '(5)', 'width': '(60)'}), '(root, height=5, width=60)\n', (1730, 1756), False, 'from tkinter import scrolledtext\n'), ((1937, 1951), 'matplotlib.pyplot.subplots', 'plt.subplots', ([], {}), '()\n', (1949, 1951), True, 'import matplotlib.pyplot as plt\n'), ((1974, 2019), 'matplotlib.backends.backend_tkagg.FigureCanvasTkAgg', 'FigureCanvasTkAgg', (['self.fig'], {'master': 'self.root'}), '(self.fig, master=self.root)\n', (1991, 2019), False, 'from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg\n'), ((2181, 2193), 'numpy.array', 'np.array', (['[]'], {}), '([])\n', (2189, 2193), True, 'import numpy as np\n'), ((2948, 2962), 'pyttsx3.init', 'pyttsx3.init', ([], {}), '()\n', (2960, 2962), False, 'import pyttsx3\n'), ((3237, 3254), 'threading.Event', 'threading.Event', ([], {}), '()\n', (3252, 3254), False, 'import threading\n'), ((3282, 3295), 'queue.Queue', 'queue.Queue', ([], {}), '()\n', (3293, 3295), False, 'import queue\n'), ((3326, 3368), 'threading.Thread', 'threading.Thread', ([], {'target': 'self.record_audio'}), '(target=self.record_audio)\n', (3342, 3368), False, 'import threading\n'), ((3562, 3612), 'threading.Thread', 'threading.Thread', ([], {'target': 'self.update_waveform_plot'}), '(target=self.update_waveform_plot)\n', (3578, 3612), False, 'import threading\n'), ((4496, 4513), 'pyaudio.PyAudio', 'pyaudio.PyAudio', ([], {}), '()\n', (4511, 4513), False, 'import pyaudio\n'), ((2467, 2502), 'numpy.frombuffer', 'np.frombuffer', (['data'], {'dtype': 'np.int16'}), '(data, dtype=np.int16)\n', (2480, 2502), True, 'import numpy as np\n'), ((4931, 4967), 'wave.open', 'wave.open', (['self.audio_filename', '"""wb"""'], {}), "(self.audio_filename, 'wb')\n", (4940, 4967), False, 'import wave\n'), ((2421, 2435), 'numpy.zeros', 'np.zeros', (['(1024)'], {}), '(1024)\n', (2429, 2435), True, 'import numpy as np\n')]