app.py

import gradio as gr
import whisper
from transformers import pipeline

# Load models
model = whisper.load_model("base")
summarizer = pipeline("summarization", model="t5-small")

# Function to transcribe and summarize
def transcribe_and_summarize(audio_file):
    # Transcription
    result = model.transcribe(audio_file)
    transcription = result["text"]
    
    # Summarization
    summary = summarizer(transcription, max_length=50, min_length=10, do_sample=False)[0]["summary_text"]
    return transcription, summary

# Gradio Interface
inputs = gr.Audio(type="filepath", label="Upload your audio file")
outputs = [
    gr.Textbox(label="Transcription"),
    gr.Textbox(label="Summary")
]

app = gr.Interface(
    fn=transcribe_and_summarize,
    inputs=inputs,
    outputs=outputs,
    title="Audio Transcription and Summarization",
    description="Upload an audio file to get its transcription and a summarized version of the content."
)

# Launch the app
app.launch()