Create app.py

app.py

@@ -0,0 +1,156 @@
+import gradio as gr
+import os
+import fitz  # PyMuPDF for PDF extraction
+from pptx import Presentation
+from docx import Document
+from groq import Groq
+
+# Initialize Groq Client
+api_key = os.environ.get("GROQ_API_KEY")  # Use environment variable for the API key
+client = Groq(api_key=api_key)
+
+# File Extraction Functions
+def extract_text_from_pdf(file_path):
+    pdf_text = ""
+    try:
+        pdf_file = fitz.open(file_path)
+        for page_num in range(pdf_file.page_count):
+            page = pdf_file.load_page(page_num)
+            pdf_text += page.get_text()
+    except Exception as e:
+        return f"Error reading PDF: {e}"
+    return pdf_text
+
+def extract_text_from_ppt(file_path):
+    ppt_text = ""
+    try:
+        presentation = Presentation(file_path)
+        for slide in presentation.slides:
+            for shape in slide.shapes:
+                if hasattr(shape, 'text'):
+                    ppt_text += shape.text + "\n"
+    except Exception as e:
+        return f"Error reading PPT: {e}"
+    return ppt_text
+
+def extract_text_from_word(file_path):
+    doc_text = ""
+    try:
+        document = Document(file_path)
+        for paragraph in document.paragraphs:
+            doc_text += paragraph.text + "\n"
+    except Exception as e:
+        return f"Error reading Word file: {e}"
+    return doc_text
+
+def process_files(file_paths):
+    text_data = ""
+    for file_path in file_paths:
+        if file_path.endswith(".pdf"):
+            text_data += extract_text_from_pdf(file_path)
+        elif file_path.endswith(".pptx"):
+            text_data += extract_text_from_ppt(file_path)
+        elif file_path.endswith(".docx"):
+            text_data += extract_text_from_word(file_path)
+        else:
+            text_data += f"Unsupported file format: {file_path}\n"
+    return text_data
+
+# Generate MCQs and Subjective Questions Using Groq
+def generate_questions(text, num_mcqs=5, num_subjective=2, difficulty_mcqs="medium", difficulty_subjective="medium", question_type="mix"):
+    try:
+        num_mcqs = min(num_mcqs, 40)
+        num_subjective = min(num_subjective, 20)
+
+        difficulty_levels = {
+            "easy": "simple questions with direct answers.",
+            "medium": "moderate complexity questions requiring reasoning.",
+            "hard": "challenging questions requiring deep understanding."
+        }
+
+        question_type_map = {
+            "reason": "Generate reasoning-based questions.",
+            "short": "Generate short-answer questions.",
+            "long": "Generate long-answer questions.",
+            "case study": "Generate case study-based questions.",
+            "mix": "Generate a mix of question types."
+        }
+
+        prompt = f"Generate {num_mcqs} multiple choice questions and {num_subjective} subjective questions from the following text: {text}. Include the correct answers for each question. The questions should be {difficulty_levels.get(difficulty_mcqs, 'medium')} for MCQs and {difficulty_levels.get(difficulty_subjective, 'medium')} for Subjective questions. {question_type_map.get(question_type, 'mix')}"
+
+        chat_completion = client.chat.completions.create(
+            messages=[{"role": "user", "content": prompt}],
+            model="llama3-8b-8192",
+        )
+
+        response = chat_completion.choices[0].message.content.strip()
+
+        # Split response into MCQs and Subjective questions
+        mcqs, subjective = "", ""
+        is_subjective_section = False
+
+        for line in response.split("\n"):
+            if "**Subjective Questions**" in line:
+                is_subjective_section = True
+            if is_subjective_section:
+                subjective += line + "\n"
+            else:
+                mcqs += line + "\n"
+
+        return mcqs, subjective
+
+    except Exception as e:
+        return f"Error generating questions: {e}", ""
+
+# Gradio Interface Function
+def process_and_generate(file_paths, raw_text, num_mcqs, num_subjective, difficulty_mcqs, difficulty_subjective, question_type):
+    combined_text = ""
+
+    # Extract text from uploaded files
+    if file_paths:
+        extracted_text = process_files(file_paths)
+        if extracted_text.strip():
+            combined_text += extracted_text
+    
+    # Add raw text if provided
+    if raw_text.strip():
+        if combined_text:
+            combined_text += "\n" + raw_text
+        else:
+            combined_text = raw_text
+    
+    if not combined_text.strip():
+        return "No text provided to generate questions.", "No text provided to generate questions."
+    
+    try:
+        mcqs, subjective = generate_questions(
+            combined_text, num_mcqs, num_subjective, difficulty_mcqs, difficulty_subjective, question_type
+        )
+        return mcqs, subjective
+    except Exception as e:
+        return f"Error generating questions: {e}", f"Error generating questions: {e}"
+
+# Gradio Inputs and Outputs
+inputs = [
+    gr.File(file_count="multiple", type="filepath", label="Upload Files (.pdf, .pptx, .docx)"),
+    gr.Textbox(lines=3, placeholder="Enter raw text here (Optional)...", label="Raw Text"),
+    gr.Slider(minimum=2, maximum=40, value=5, step=1, label="Number of MCQs (Max 40)"),
+    gr.Slider(minimum=2, maximum=20, value=2, step=1, label="Number of Subjective Questions (Max 20)"),
+    gr.Radio(["easy", "medium", "hard"], label="Select Difficulty Level for MCQs", value="medium"),
+    gr.Radio(["easy", "medium", "hard"], label="Select Difficulty Level for Subjective Questions", value="medium"),
+    gr.Radio(["reason", "short", "long", "case study", "mix"], label="Select Type of Question", value="mix")
+]
+
+outputs = [
+    gr.Textbox(label="Generated MCQs", lines=10),
+    gr.Textbox(label="Generated Subjective Questions", lines=10)
+]
+
+# Gradio Interface
+gr.Interface(
+    fn=process_and_generate,
+    inputs=inputs,
+    outputs=outputs,
+    title="MCQ & Subjective Question Generator",
+    live=False
+).launch()