Create app.py

app.py

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+import gradio as gr
+from PyPDF2 import PdfReader
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from langchain import PromptTemplate
+from langchain import LLMChain
+from langchain_together import Together
+import re
+from docx import Document
+import os
+
+# Initialize Together API key
+os.environ['TOGETHER_API_KEY'] = "c2f52626b97118b71c0c36f66eda4f5957c8fc475e760c3d72f98ba07d3ed3b5"
+checkpoint = "sshleifer/distilbart-cnn-12-6"
+llama3 = Together(model="meta-llama/Llama-3-70b-chat-hf", max_tokens=2500)
+tokenizer = AutoTokenizer.from_pretrained(checkpoint)
+model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)
+def Summary_BART(text):
+    inputs = tokenizer(text, max_length=1024, truncation=True, return_tensors="pt")
+    summary_ids = model.generate(inputs["input_ids"])
+    summary = tokenizer.batch_decode(summary_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)
+    return summary[0]
+
+def DocToQuizz(file, difficulty_level):
+    # Read the PDF content
+    reader = PdfReader(file)
+    text = ""
+    for page in reader.pages:
+        text += page.extract_text()
+    summary = Summary_BART(text)
+
+    # Define the prompt template for generating questions
+    mcq_template = """
+    Generate 20 different questions based on the following summary: {summary}
+    The difficulty level of the questions should be: {difficulty_level}
+
+    For the multiple-choice questions (MCQs), please provide the following for each question:
+    1. Question
+       - Use varied question formats such as:
+         - "How does...", "Why is...", "In what way...", "Which of the following...", "When does...", etc.
+       - Ensure questions are logically phrased and relevant to the content.
+    2. Correct answer
+    3. Three plausible incorrect answer options
+    4. Format: "Question: <question text>\nCorrect answer: <correct answer>\nIncorrect answers: <option1>, <option2>, <option3>"
+
+    For the short questions, please provide:
+    1. Question
+       - Use varied question formats to encourage conceptual understanding and avoid repetition.
+       - Ensure the short questions do not overlap in content with the MCQs.
+    2. Short, concise answer
+    3. Format: "SQ: <question text>\nAnswer: <answer>"
+
+    Generate 10 MCQs and 10 unique short questions in total, ensuring diverse question structures and logical phrasing.
+    """
+    prompt = PromptTemplate(
+        input_variables=['summary', 'difficulty_level'],
+        template=mcq_template
+    )
+    
+    Generated_mcqs = LLMChain(llm=llama3, prompt=prompt)
+
+    response = Generated_mcqs.invoke({
+        "summary": summary,
+        "difficulty_level": difficulty_level
+    })
+
+    response_text = response['text']
+
+    # Extract MCQs and Short Questions
+    mcq_pattern = r'\d+\.\s*Question:\s*(.*?)\nCorrect answer:\s*(.*?)\nIncorrect answers:\s*(.*?)\n'
+    short_question_pattern = r'\d+\.\s*SQ:\s*(.*?)\n'
+
+    mcqs = re.findall(mcq_pattern, response_text, re.DOTALL)
+    short_questions = re.findall(short_question_pattern, response_text, re.DOTALL)
+
+    # Initialize a Word document
+    doc = Document()
+    doc.add_heading("Physics Questions", level=1)
+
+    # Add a section for MCQs with options
+    doc.add_heading("Multiple Choice Questions (MCQs)", level=2)
+    for idx, (question, correct_answer, incorrect_answers) in enumerate(mcqs, start=1):
+        # Split incorrect answers
+        incorrect_answers = incorrect_answers.split(', ')
+
+        # Add question and options to the document
+        doc.add_paragraph(f"Q{idx}: {question.strip()}", style="List Number")
+        doc.add_paragraph(f"A) {correct_answer.strip()}", style="List Bullet")
+        for i, incorrect in enumerate(incorrect_answers, start=2):
+            doc.add_paragraph(f"{chr(64 + i)}) {incorrect.strip()}", style="List Bullet")
+
+    # Add a page break and section for Short Questions
+    doc.add_page_break()
+    doc.add_heading("Short Questions", level=2)
+    for idx, question in enumerate(short_questions, start=1):
+        doc.add_paragraph(f"{idx}. {question.strip()}", style="Body Text")
+
+    # Save the document
+    doc.save("Physics_Questions.docx")
+    return "Physics_Questions.docx"
+
+# Get list of PDF files in the directory
+pdf_files = ['output_range_1.pdf','output_range_2.pdf','output_range_3.pdf','output_range_4.pdf','output_range_5.pdf','output_range_6.pdf','output_range_7.pdf','output_range_8.pdf','output_range_9.pdf']
+difficulty_levels = ["Easy", "Medium", "Hard"]
+
+# Gradio Interface
+def generate_quiz(file, difficulty_level):
+    output_file = DocToQuizz(file, difficulty_level)
+    return output_file
+
+interface = gr.Interface(
+    fn=generate_quiz,
+    inputs=[
+        gr.Dropdown(pdf_files, label="Select PDF File"),
+        gr.Dropdown(difficulty_levels, label="Select Difficulty Level",value='output_range_1.pdf')
+    ],
+    outputs=gr.File(label="Download Quiz Document"),
+    title="Quiz Generator",
+    description="Select a PDF file and difficulty level to generate quiz questions."
+)
+
+# Launch the interface
+interface.launch(debug=True)