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import gradio as gr
import openai
import os
openai.api_key = os.environ.get("OPENAI_API_KEY")
messages = [
{"role": "system", "content": "You are a job interviewer who will be conducting a mock interview for practice. Respond in less than 40 words."},
]
def transcribe(audio):
global messages
print(audio)
audio_file = open(audio, "rb")
transcript = openai.Audio.transcribe("whisper-1", audio_file)
print(transcript)
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})
chat_transcript = ""
for message in messages:
if message['role'] != 'system':
chat_transcript += message['role'] + ": " + message['content'] + "\n\n"
return chat_transcript
#with gr.Blocks() as ui:
#advisor = gr.Image(value=config.UI_IMAGE).style(width=config.UI_IMAGE_WIDTH, height=config.UI_IMAGE_HEIGHT)
ui = gr.Interface(fn=transcribe, inputs=gr.Audio(source="microphone", type="filepath"), outputs="text").launch()
ui.launch()
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