Update src/streamlit_app.py

src/streamlit_app.py

@@ -6,7 +6,7 @@ import streamlit as st
 import fitz  # PyMuPDF
 from transformers import pipeline
 
-# Security headers and config
+# Security configuration
 st.set_page_config(
     page_title="PrepPal",
     page_icon="📘",
@@ -14,8 +14,9 @@ st.set_page_config(
     menu_items={'About': "PrepPal - AI-powered PDF summarizer"}
 )
 
+# Fix for 403 errors
 st.markdown("""
-<meta http-equiv="Content-Security-Policy" content="default-src 'self'; script-src 'self' 'unsafe-inline'; style-src 'self' 'unsafe-inline'; img-src 'self' data:;">
+    <meta http-equiv="Content-Security-Policy" content="default-src 'self'; script-src 'self' 'unsafe-inline'; style-src 'self' 'unsafe-inline'; img-src 'self' data:;">
 """, unsafe_allow_html=True)
 
 @st.cache_resource
@@ -23,31 +24,33 @@ def load_summarizer():
     try:
         return pipeline(
             "summarization", 
-            model="facebook/bart-large-cnn",  # Reliable medium-size model
-            device=-1  # Force CPU
+            model="facebook/bart-large-cnn",  # Reliable model
+            device=-1  # Force CPU for Hugging Face Spaces
         )
     except Exception as e:
         st.error(f"Model loading failed: {str(e)}")
         return None
 
-def extract_text(uploaded_file):
-    text = ""
+def safe_extract_text(uploaded_file):
+    """Secure PDF text extraction with temp files"""
     try:
-        # Save to temp file first (fixes 403 issues)
+        # First save to temporary file
         with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp:
             tmp.write(uploaded_file.getbuffer())
             tmp_path = tmp.name
         
+        # Process from filesystem
         with fitz.open(tmp_path) as doc:
             text = "\n".join([page.get_text() for page in doc])
         
+        # Clean up
         os.unlink(tmp_path)
         return text.strip()
     except Exception as e:
         st.error(f"PDF processing error: {str(e)}")
         return ""
 
-def summarize(text, model, max_chunk=1500):
+def summarize_text(text, model, max_chunk=1500):
     if not text or not model:
         return ""
     
@@ -65,11 +68,10 @@ def summarize(text, model, max_chunk=1500):
     
     return "\n".join(summary)
 
-# Main App with all 3 tabs
+# Main App with all tabs
 def main():
     st.title("📘 PrepPal - Study Assistant")
     
-    # Create all three tabs
     tab1, tab2, tab3 = st.tabs(["📄 Summarize Notes", "❓ Ask a Doubt", "💬 Feedback"])
     
     with tab1:
@@ -84,21 +86,21 @@ def main():
         )
         
         if uploaded_file:
-            if uploaded_file.size > 10_000_000:  # 10MB limit
+            if uploaded_file.size > 10_000_000:
                 st.error("File too large (max 10MB)")
             else:
                 with st.spinner("Extracting text..."):
-                    text = extract_text(uploaded_file)
+                    text = safe_extract_text(uploaded_file)
                 
                 if text:
                     with st.expander("View extracted text"):
                         st.text(text[:1000] + "...")
                     
-                    if st.button("Generate Summary", key="summarize_btn"):
+                    if st.button("Generate Summary"):
                         with st.spinner("Summarizing..."):
                             model = load_summarizer()
                             if model:
-                                summary = summarize(text, model)
+                                summary = summarize_text(text, model)
                                 
                                 st.subheader("AI Summary")
                                 st.write(summary)
@@ -107,32 +109,19 @@ def main():
                                     "Download Summary",
                                     data=summary,
                                     file_name="summary.txt",
-                                    mime="text/plain",
-                                    key="download_btn"
+                                    mime="text/plain"
                                 )
     
     with tab2:
         st.header("Ask a Question")
-        st.write("Coming Soon: Ask questions about your uploaded documents")
-        st.image("https://via.placeholder.com/600x200?text=Question+Answering+Feature+Coming+Soon", 
-                caption="AI question answering will be available in the next update")
-        
-        # Placeholder for future functionality
-        question = st.text_input("What would you like to ask about your document?")
-        if question:
-            st.info("This feature is currently in development. Please check back soon!")
+        st.info("This feature will allow you to ask questions about your documents")
+        st.write("Coming in the next update!")
     
     with tab3:
         st.header("Your Feedback")
-        st.write("Help us improve PrepPal")
-        
-        feedback = st.text_area("What do you think about PrepPal?")
-        if st.button("Submit Feedback", key="feedback_btn"):
-            if feedback:
-                st.success("Thank you for your feedback! We'll use this to improve the app.")
-                # In a real app, you would store this feedback somewhere
-            else:
-                st.warning("Please enter your feedback before submitting")
+        feedback = st.text_area("How can we improve PrepPal?")
+        if st.button("Submit Feedback"):
+            st.success("Thank you! Your feedback has been recorded.")
 
 if __name__ == "__main__":
     main()