Update app.py

app.py

@@ -10,46 +10,48 @@ model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 
 def extract_first_sentence(text):
-    # Use a simple regex to extract the first sentence
-    sentences = re.split(r'(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.|\?)\s', text)
-    if sentences:
-        return sentences[0]
-    else:
-        return text
+  """
+  Extracts the first sentence from the given text.
+  """
+  sentences = re.split(r'(?<!\w\.\w.)(?<![A-Z][a-z]\.)(?<=\.|\?)\s', text)
+  if sentences:
+    return sentences[0]
+  else:
+    return text
 
 def summarize_pdf_abstract(pdf_file):
-    try:
-        reader = PdfReader(pdf_file)
-        abstract_text = ""
-        for page in reader.pages:
-            if "Abstract" in page.extract_text() or "Introduction" in page.extract_text():
-                abstract_text = page.extract_text()
-                break
-
-        inputs = tokenizer(abstract_text, return_tensors="pt")
-        outputs = model.generate(**inputs)
-        summary = tokenizer.decode(outputs[0])
-
-        # Extract only the first sentence
-        summary_sentence = extract_first_sentence(summary)
-
-        # Generate audio
-        speech = gTTS(text=summary_sentence, lang="en")
-        speech_bytes = BytesIO()
-        speech.write_to_fp(speech_bytes)
-
-        return {"summary": summary_sentence, "audio": speech_bytes}
-
-    except Exception as e:
-        raise Exception(str(e))
-
-def play_audio(audio_bytes):
-    return gr.Audio(audio_bytes)
+  """
+  Reads a PDF file, extracts the abstract, summarizes it as the first sentence, and generates audio.
+  """
+  try:
+    reader = PdfReader(pdf_file)
+    abstract_text = ""
+    for page in reader.pages:
+      if "Abstract" in page.extract_text() or "Introduction" in page.extract_text():
+        abstract_text = page.extract_text()
+        break
+
+    inputs = tokenizer(abstract_text, return_tensors="pt")
+    outputs = model.generate(**inputs)
+    summary = tokenizer.decode(outputs[0])
+
+    # Extract only the first sentence
+    summary_sentence = extract_first_sentence(summary)
+
+    # Generate audio
+    speech = gTTS(text=summary_sentence, lang="en")
+    speech_bytes = BytesIO()
+    speech.write_to_fp(speech_bytes)
+
+    return {"summary": summary_sentence, "audio": speech_bytes}
+
+  except Exception as e:
+    raise Exception(str(e))
 
 interface = gr.Interface(
-    fn=summarize_pdf_abstract,
-    inputs=[gr.File(label="Upload PDF")],
-    outputs=[gr.Textbox(label="Summary"), play_audio],
+  fn=summarize_pdf_abstract,
+  inputs=[gr.File(label="Upload PDF")],
+  outputs=[gr.Textbox(label="Summary"), gr.Audio()],
 )
 
 interface.launch(share=True)