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November 13, 2023 16:28
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This is a simple implementation of transcription with OpenAI Whisper API and Gradio.
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import gradio as gr | |
from openai import OpenAI | |
import os | |
client = OpenAI( | |
api_key=os.getenv("OPENAI_API_KEY"), | |
) | |
DEFAULT_PROMPT = ( | |
"Hello, welcome to my lecture." # To make sure transcription has punctuation | |
) | |
def transcribe(audio_file, prompt): | |
prompt = prompt if prompt else DEFAULT_PROMPT | |
try: | |
with open(audio_file, "rb") as file: | |
response = client.audio.transcriptions.create( | |
file=file, | |
model="whisper-1", | |
prompt=prompt, | |
temperature=0.2, | |
language="en", # ja for Japanese | |
response_format="text", | |
) | |
return response | |
except Exception as e: | |
return f"An error occurred: {str(e)}" | |
# Gradio interface | |
iface = gr.Interface( | |
fn=transcribe, | |
inputs=[ | |
gr.Audio(sources=["upload"], type="filepath"), | |
gr.Textbox(label="Whisper Model Prompt"), | |
], | |
outputs="text", | |
) | |
# Run the Gradio app | |
iface.launch(debug=True) |
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