Create app.py

app.py

@@ -0,0 +1,45 @@
+import gradio as gr
+from transformers import pipeline
+
+# Load Whisper pipeline (speech-to-text)
+asr_pipe = pipeline(
+    task="automatic-speech-recognition",
+    model="openai/whisper-small",
+    return_timestamps=True
+)
+
+# Load summarization pipeline
+summarizer = pipeline("summarization", model="google/pegasus-cnn_dailymail")
+
+# Function to transcribe and summarize
+def transcribe_and_summarize(audio_file):
+    if audio_file is None:
+        return "Please upload an audio file.", ""
+    
+    # Transcription
+    transcript = asr_pipe(audio_file)["text"]
+
+    # Summarization (limit to 1024 tokens for safety)
+    if len(transcript) > 1000:
+        transcript = transcript[:1000]  # truncate long transcripts
+    summary = summarizer(transcript, max_length=80, min_length=20, do_sample=False)[0]["summary_text"]
+    
+    return transcript, summary
+
+# Gradio Interface
+with gr.Blocks() as app:
+    gr.Markdown("## 🎙️ Whisper ASR + Summary\nUpload or record audio to get a transcription and summary.")
+
+    with gr.Row():
+        audio_input = gr.Audio(type="filepath", label="Upload or Record Audio")
+    
+    with gr.Row():
+        transcribe_btn = gr.Button("Transcribe & Summarize")
+    
+    with gr.Row():
+        transcript_box = gr.Textbox(label="Transcription", lines=6)
+        summary_box = gr.Textbox(label="Summary", lines=4)
+
+    transcribe_btn.click(fn=transcribe_and_summarize, inputs=audio_input, outputs=[transcript_box, summary_box])
+
+app.launch() #summarize is added but taking lon time and also sumary is not accurate