Update app.py

app.py

@@ -17,20 +17,23 @@ import io
 #Here is the code
 
 summarization = pipeline ('summarization', model = "pszemraj/long-t5-tglobal-base-16384-book-summary")
+synthesiser = pipeline("text-to-speech", model='facebook/mms-tts-eng')
 
 def summarize_and_speech(pdf_file):
-        pdf_bytes_io = io.BytesIO(pdf_file)
-        pdf_reader = PyPDF2.PdfReader(pdf_bytes_io)
-        abstract_text = pdf_reader.pages[0].extract_text()
-        summary = summarization(abstract_text, max_length=13, min_length=10)[0]['summary_text']
-        
-        # Use a text-to-speech model to generate audio
-        synthesiser = pipeline("text-to-speech", "facebook/mms-tts-eng")
-        tts_output = synthesiser(summary)
-        audio_data = tts_output[0]["audio"]
 
+    pdf_bytes_io = io.BytesIO(pdf_file)
+    pdf_reader = PyPDF2.PdfReader(pdf_bytes_io)
+    abstract_text = pdf_reader.pages[0].extract_text()
+    summary = summarization(abstract_text, max_length=13, min_length=10)[0]['summary_text']
+    print(summary)
+
+    # Use a text-to-speech model to generate audio
+    synthesiser = pipeline("text-to-speech", model='facebook/mms-tts-eng')
+    tts_output = synthesiser(summary)
+    audio_data = tts_output[0]["audio"]
+
+    return summary, audio_data
 
-        return summary, audio_data
 
 iface = gr.Interface(
     fn= summarize_and_speech,
@@ -41,5 +44,4 @@ iface = gr.Interface(
     description="Upload a Research Paper PDF File. The model will generate a one line summary of the Abstract section and a speech audio."
 )
 
-iface.launch()
-
+iface.launch()