Update app.py

app.py

@@ -50,18 +50,28 @@ def generate_notes(transcript):
     except LookupError:
         sentences = custom_sent_tokenize(transcript)
 
-    long_questions = [f"What is meant by '{sentence}'?" for sentence in sentences[:5]]
-    short_questions = [f"Define '{sentence.split()[0]}'." for sentence in sentences[:5]]
+    # Generate long questions
+    long_questions = [f"Explain the concept discussed in: '{sentence}'." for sentence in sentences[:5]]
 
+    # Generate short questions
+    short_questions = [f"What does '{sentence.split()[0]}' mean in the context of this text?" for sentence in sentences[:5]]
+
+    # Generate MCQs with relevant distractors
     mcqs = []
     for sentence in sentences[:5]:
-        mcq = {
-            "question": f"What is '{sentence.split()[0]}'?",
-            "options": [sentence.split()[0]] + random.sample(["Option 1", "Option 2", "Option 3"], 3),
-            "answer": sentence.split()[0]
-        }
-        mcqs.append(mcq)
-
+        if len(sentence.split()) > 1:  # Ensure there are enough words to create meaningful options
+            key_word = sentence.split()[0]  # Use the first word as a key term
+            distractors = ["Term A", "Term B", "Term C"]  # Replace with relevant terms if needed
+            options = [key_word] + distractors
+            random.shuffle(options)  # Shuffle options for randomness
+            mcq = {
+                "question": f"What is '{key_word}' based on the context?",
+                "options": options,
+                "answer": key_word
+            }
+            mcqs.append(mcq)
+
+    # Generate and save a structured PDF
     pdf_path = create_pdf(transcript, long_questions, short_questions, mcqs)
     return pdf_path
 
@@ -69,24 +79,29 @@ def create_pdf(transcript, long_questions, short_questions, mcqs):
     pdf = FPDF()
     pdf.add_page()
     
+    # Add title
     pdf.set_font("Arial", "B", 16)
-    pdf.cell(200, 10, "Transcription Notes", ln=True, align="C")
+    pdf.cell(200, 10, "Transcription Notes and Questions", ln=True, align="C")
 
+    # Add transcription content
     pdf.set_font("Arial", "", 12)
     pdf.multi_cell(0, 10, f"Transcription:\n{transcript.encode('latin1', 'replace').decode('latin1')}\n\n")
 
+    # Add long questions
     pdf.set_font("Arial", "B", 14)
     pdf.cell(200, 10, "Long Questions", ln=True)
     pdf.set_font("Arial", "", 12)
     for question in long_questions:
         pdf.multi_cell(0, 10, f"- {question.encode('latin1', 'replace').decode('latin1')}\n")
 
+    # Add short questions
     pdf.set_font("Arial", "B", 14)
     pdf.cell(200, 10, "Short Questions", ln=True)
     pdf.set_font("Arial", "", 12)
     for question in short_questions:
         pdf.multi_cell(0, 10, f"- {question.encode('latin1', 'replace').decode('latin1')}\n")
 
+    # Add MCQs
     pdf.set_font("Arial", "B", 14)
     pdf.cell(200, 10, "Multiple Choice Questions (MCQs)", ln=True)
     pdf.set_font("Arial", "", 12)
@@ -121,6 +136,7 @@ iface = gr.Interface(
     inputs=gr.Audio(type="filepath"),
     outputs=gr.File(label="Download PDF with Notes or Error Report"),
     title="Voice to Text Converter and Notes Generator",
+    description="This app converts audio to text and generates academic questions including long, short, and multiple-choice questions."
 )
 
 iface.launch()