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import gradio as gr
import openai
from decouple import config
from gtts import gTTS
import os
import pydub
import io
import config
openai.api_key = config.API_KEYS['openai']
# The Models Job or role
messages = [
{"role": "system", "content": "You are a helpful assistant."},
]
# Main method goes here
def decipher(audio):
global messages
# Using openAI's speech to text model
audio_file = open(audio, "rb")
transcript = openai.Audio.transcribe("whisper-1", audio_file)
messages.append({"role": "user", "content": transcript["text"]})
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})
# Convert the text to audio using gTTS
tts = gTTS(text=system_message, lang='en')
audio_data = io.BytesIO()
tts.write_to_fp(audio_data)
# Convert the audio to a playable format using pydub
audio_data.seek(0)
audio = pydub.AudioSegment.from_file(audio_data, format="mp3")
# Play the audio using VLC
player = pydub.playback.play
player(audio)
chat_transcript = ""
for message in messages:
if message['role'] != 'system':
chat_transcript += message['role'] + ": " + message['content'] + "\n\n"
return chat_transcript
# Using Gradio's audio Interface
interface = gr.Interface(fn=decipher, inputs=gr.Audio(
source="microphone", type="filepath"), outputs="text")
interface.launch()
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