Create app.py

app.py

@@ -1,41 +1,15 @@
-import gradio as gr
-from transformers import pipeline
-import pdf2image
-import pytesseract
-
-# Initialize model
-qa_model = pipeline("question-answering")
-
-def process_pdf(pdf_file):
-    # Convert PDF to text
-    text = extract_text_from_pdf(pdf_file)
-    return text
-
-def answer_question(question, context):
-    # Get answer from model
-    answer = qa_model(question=question, context=context)
-    return answer['answer']
-
-# Create interface
-with gr.Blocks() as demo:
-    gr.Markdown("# My Study Assistant")
-    
-    # File upload
-    file_input = gr.File(label="Upload PDF")
-    
-    # Text display
-    text_output = gr.Textbox(label="Extracted Text")
-    
-    # Chat interface
-    question = gr.Textbox(label="Ask a question")
-    answer = gr.Textbox(label="Answer")
-    
-    # Buttons
-    upload_btn = gr.Button("Process PDF")
-    ask_btn = gr.Button("Ask")
-    
-    # Set up actions
-    upload_btn.click(process_pdf, inputs=file_input, outputs=text_output)
-    ask_btn.click(answer_question, inputs=[question, text_output], outputs=answer)
-
-demo.launch()
+STUDY_PROMPTS = {
+    "analyze": """
+    Analyze this text following these rules:
+    1. Identify key concepts
+    2. Break down complex terms
+    3. Provide examples
+    4. Link to prerequisites
+    """,
+    "practice": """
+    Create practice materials:
+    1. Generate questions
+    2. Provide sample problems
+    3. Include answer explanations
+    """
+}