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import gradio as gr
import openai, subprocess
import os
# import config
# openai.api_key = config.OPENAI_API_KEY
messages = [{"role": "system", "content": 'You are a therapist. Respond to all input in 25 words or less.'}]
def transcribe(key, audio):
openai.api_key = key
global messages
audio_filename_with_extension = audio + '.wav'
os.rename(audio, audio_filename_with_extension)
audio_file = open(audio_filename_with_extension, "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"]
messages.append(system_message)
#subprocess.call(["say", system_message['content']])
print("output: " + system_message['content'] + "\n")
chat_transcript = ""
for message in messages:
if message['role'] != 'system':
chat_transcript += message['role'] + ": " + message['content'] + "\n\n"
return chat_transcript
# ui = gr.Interface(fn=transcribe, inputs=["text", gr.Audio(source="microphone", type="filepath")], outputs="text").launch()
keyTxt = gr.Textbox(
show_label=True,
placeholder=f"Your API-key...",
type="password",
visible=True,
label="API-Key",
)
ui = gr.Interface(fn=transcribe, inputs=[keyTxt, gr.Audio(source="microphone", type="filepath")], outputs="text").launch()
ui.launch()
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