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import openai
import gradio as gr
import time
import warnings
import warnings
import os
from gtts import gTTS
warnings.filterwarnings("ignore")
openai.api_key = "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"
def chatgpt_api(input_text):
messages = [
{"role": "system", "content": "You are a helpful assistant."}]
if input_text:
messages.append(
{"role": "user", "content": input_text},
)
chat_completion = openai.ChatCompletion.create(
model="gpt-3.5-turbo", messages=messages
)
reply = chat_completion.choices[0].message.content
return reply
#ffmpeg -f lavfi -i anullsrc=r=44100:cl=mono -t 10 -q:a 9 -acodec libmp3lame Temp.mp3'
def transcribe(audio, text):
language = "en"
if audio is not None:
with open(audio, "rb") as transcript:
prompt = openai.Audio.transcribe("whisper-1", transcript)
s = prompt["text"]
else:
s = text
response = openai.Completion.create(
engine="text-davinci-002",
prompt=s,
max_tokens=60,
n=1,
stop=None,
temperature=0.5,
)
out_result = chatgpt_api(s)
audioobj = gTTS(text = out_result,
lang = language,
slow = False)
audioobj.save("Temp.mp3")
return [s, out_result, "Temp.mp3"]
with gr.Blocks() as demo:
gr.Markdown("Dilip AI")
input1 = gr.inputs.Audio(source="microphone", type = "filepath", label="Use your voice to chat")
input2 = gr.inputs.Textbox(lines=7, label="Chat with AI")
output_1 = gr.Textbox(label="User Input")
output_2 = gr.Textbox(label="Text Output")
output_3 = gr.Audio("Temp.mp3", label="Speech Output")
btn = gr.Button("Run")
btn.click(fn=transcribe, inputs=[input1, input2], outputs=[output_1, output_2, output_3])
demo.launch()
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