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import os
os.system("pip install git+https://github.com/openai/whisper.git")
import whisper
from pytube import YouTube
import gradio as gr
infer_model = whisper.load_model("tiny")
def infer(link: str, add_timestamps: bool) -> str:
audio_path = download_audio(link)
if not audio_path:
return "Unable to process request."
result = infer_model.transcribe(audio_path)
title = "Content"
try:
title = audio_path.split("/")[-1]
title = title.split(".")[0]
except Exception as e:
print(f"Unable to extract title. Exception {e}")
if not add_timestamps:
print(result["text"])
return title + "\n" + result["text"]
result_text = title + "\n"
for segment in result["segments"]:
result_text += f"{float(segment['start']):.2f}s - {float(segment['end']):.2f}s : {segment['text']}\n"
return result_text.strip("\n")
def download_audio(link: str) -> str:
try:
yt = YouTube(link)
stream = yt.streams.get_audio_only()
audio_path = stream.download()
print(audio_path)
return audio_path
except Exception as e:
print(f"Unable to download file. Exception {e}")
return ""
demo = gr.Interface(
fn=infer,
inputs=[gr.Textbox(label = "Youtube Link", placeholder="Copy link here"), gr.Checkbox(value=True, label="Add timestamps?")],
outputs=[gr.Textbox(label = "Transcription", placeholder=" Expected processing time ~ Half the length of video. Hang tight!!")],
examples=[ ["https://www.youtube.com/watch?v=KL2T0XRzWUI", False], ["https://www.youtube.com/watch?v=yGB_K_xlHdI", False], ["https://www.youtube.com/watch?v=dv9sgFHS2Do", True],]
)
demo.launch()
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