Update app.py

app.py

@@ -6,15 +6,24 @@ import gradio as gr
 device = "cpu"
 print("Running on CPU")
 
-# Load the Whisper model on CPU
-model_name = "tiny"  # Change to "base", "small", etc., as needed
-whisper_model = whisper.load_model("tiny")
-
-# Define the transcription function
-def transcribe(audio):
-    # Perform transcription using the Whisper model
-    result = whisper_model.transcribe(audio)
-    return result["text"]
+
+# Load the tiny Whisper model
+model = whisper.load_model("base")
+
+# Load the text summarization model from Hugging Face
+summarizer = pipeline(task="summarization", model="facebook/bart-large-cnn")
+
+# Function to transcribe and summarize the audio file
+def transcribe_and_summarize(audio):
+    # Step 1: Transcribe the audio using Whisper
+    transcription_result = whisper_model.transcribe(audio)
+    transcription = transcription_result['text']
+
+    # Step 2: Summarize the transcription
+    summary = summarizer(transcription, min_length=10, max_length=100)
+    summary_text = summary[0]['summary_text']
+
+    return transcription, summary_text
 
 # Create the Gradio interface
 demo = gr.Interface(