youtube-whisper / app.py
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add openrouter api
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import gradio as gr
import yt_dlp
import os
from openai import OpenAI
client = OpenAI(
api_key=os.getenv("OPENAI_API_KEY"),
)
opnerouter_client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key=os.getenv("OPENROUTER_API_KEY"),
)
ydl_opts = {
'outtmpl': 'demo.m4a',
'format': 'm4a/bestaudio/best',
'postprocessors': [{ # Extract audio using ffmpeg
'key': 'FFmpegExtractAudio',
'preferredcodec': 'm4a',
}],
# 'proxy': 'socks5://192.168.2.18:20170',
}
text = ''
def download_audio(url):
if os.path.exists('demo.m4a'):
os.remove('demo.m4a')
with yt_dlp.YoutubeDL(ydl_opts) as ydl:
code = ydl.download([url])
assert code == 0, "Failed to download audio"
with open("demo.m4a", "rb") as f:
transcription = client.audio.transcriptions.create(
model="whisper-1",
file=f,
response_format="text"
)
global text
text = transcription
return transcription
def summarize_text():
prompt = f"Please summarize the following article in 5 sentences or less use the language of the audio: [{text}]"
print(prompt)
completion = opnerouter_client.chat.completions.create(
model="google/gemini-pro",
messages=[
{"role": "user", "content": prompt}
]
)
return completion.choices[0].message.content
with gr.Blocks() as demo:
with gr.Column():
name = gr.Textbox(label="Enter your youtube url")
button_download = gr.Button("Download")
with gr.Row():
output = gr.TextArea(label="Output")
with gr.Column():
button_summary = gr.Button("Summary")
summary = gr.TextArea(label="Summary")
button_download.click(
download_audio,
inputs=[name],
outputs=[output],
)
button_summary.click(
summarize_text,
inputs=[],
outputs=[summary],
)
demo.launch()