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| import gradio as gr | |
| import pandas as pd | |
| from mcq_generator import ImprovedMCQGenerator, is_suitable_for_students | |
| import io | |
| import tempfile | |
| import os | |
| def generate_mcqs_ui(paragraph, num_questions): | |
| if not paragraph.strip(): | |
| return None, None, "⚠️ Please enter a valid paragraph." | |
| if not is_suitable_for_students(paragraph): | |
| return None, None, "❌ The paragraph is not suitable for MCQ generation (due to bias/toxicity/short length)." | |
| try: | |
| mcqs = mcq_generator.generate_mcqs(paragraph, num_questions) | |
| # Create pretty formatted MCQ list | |
| pretty_mcqs = [] | |
| for idx, mcq in enumerate(mcqs): | |
| options = "" | |
| for opt_idx, option in enumerate(mcq['options']): | |
| options += f"<b>{chr(65+opt_idx)}.</b> {option}<br>" | |
| question_html = f"<div style='margin-bottom:20px; padding:10px; border:1px solid #ccc; border-radius:10px; background:#f9f9f9;'>" | |
| question_html += f"<b>Q{idx+1}:</b> {mcq['question']}<br><br>{options}" | |
| question_html += f"<i><b>Answer:</b> {chr(65+mcq['answer_index'])}</i>" | |
| question_html += "</div>" | |
| pretty_mcqs.append(question_html) | |
| # Prepare text output and CSV data | |
| txt_output = "" | |
| csv_data = [] | |
| for idx, mcq in enumerate(mcqs): | |
| txt_output += f"Q{idx+1}: {mcq['question']}\n" | |
| for opt_idx, option in enumerate(mcq['options']): | |
| txt_output += f" {chr(65+opt_idx)}. {option}\n" | |
| txt_output += f"Answer: {chr(65+mcq['answer_index'])}\n\n" | |
| csv_data.append({ | |
| 'Question': mcq['question'], | |
| 'Option A': mcq['options'][0], | |
| 'Option B': mcq['options'][1], | |
| 'Option C': mcq['options'][2], | |
| 'Option D': mcq['options'][3], | |
| 'Answer': chr(65+mcq['answer_index']) | |
| }) | |
| # Create in-memory text file | |
| txt_buffer = io.StringIO() | |
| txt_buffer.write(txt_output) | |
| txt_buffer.seek(0) | |
| # Create in-memory CSV file | |
| csv_buffer = io.StringIO() | |
| pd.DataFrame(csv_data).to_csv(csv_buffer, index=False) | |
| csv_buffer.seek(0) | |
| # Return Gradio-compatible downloadable files | |
| txt_file = gr.File(value=txt_buffer, file_name="mcqs.txt", file_type="text/plain") | |
| csv_file = gr.File(value=csv_buffer, file_name="mcqs.csv", file_type="text/csv") | |
| return pretty_mcqs, [txt_file, csv_file], "✅ MCQs generated successfully!" | |
| except Exception as e: | |
| return None, None, f"❌ Error generating MCQs: {str(e)}" | |
| demo.launch(share=True, server_name="0.0.0.0", server_port=7860) | |