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import gradio as gr
import yt_dlp
import os
from openai import OpenAI
import anthropic
client = OpenAI(
api_key=os.getenv("OPENAI_API_KEY"),
)
claude_client = anthropic.Anthropic()
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',
}
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"
)
print(transcription)
return transcription
def summarize_text():
text = output.value
prompt = f"Please summarize the following article in 5 sentences or less: [{text}]"
print(prompt)
message = claude_client.messages.create(
model="claude-3-haiku-20240307",
max_tokens=1000,
temperature=0.0,
# system="Respond only in mandarin",
messages=[
{"role": "user", "content": prompt}
]
)
return message.content[0].text
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() |