app.py

import os
import gradio as gr
import openai
from gtts import gTTS


openai.api_key = os.environ["OPEN_AI_KEY"]

def transcribe(audio): 
 audio_file = open(audio, "rb") 
 # Call the transcribe method with the file-like object
 transcript = openai.Audio.transcribe("whisper-1", audio_file)
 
 return transcript["text"]



 
with gr.Blocks() as demo:
 messages = gr.State(value=[{"role": "system", "content": "You are a therapist. Respond in less than 5 sentences."}])

 def botResponse(user_input, messages):
 messages.append({"role": "user", "content": user_input})
 response = openai.ChatCompletion.create(
 model="gpt-3.5-turbo",
 messages=messages
 )
 
 system_message = response["choices"][0]["message"]["content"]
 messages.append({"role": "assistant", "content": system_message})
 
 chat_transcript = ""
 for message in messages:
 if (message["role"] != "system"):
 chat_transcript += message["role"] + ": " + message["content"] + "\n\n"
 
 return chat_transcript

 def giveVoice(message, messages):
 bot_message=message
 response = messages[-1]
 print(response)
 
 myobj = gTTS(text=bot_message)
 myobj.save("temp.mp3")
 
 dir = os.getcwd()
 new_path = os.path.join(dir, "temp.mp3")
 
 return new_path

 with gr.Row():
 with gr.Column():
 user_audio = gr.Audio(source="microphone", type="filepath", label="Input Phrase")
 submit_btn = gr.Button(value="Transcribe")
 with gr.Column():
 user_transcript = gr.Text(label="User Transcript")
 gpt_transcript = gr.Text(label="Chat Transcript")
 gpt_voice = gr.Audio(label="Voice Response")
 submit_btn.click(transcribe, user_audio, user_transcript)
 user_transcript.change(botResponse, [user_transcript, messages], gpt_transcript)
 gpt_transcript.change(giveVoice, [gpt_transcript, messages], gpt_voice)
 
 

demo.launch(share=False)