Update app.py

app.py

@@ -1,31 +1,29 @@
 import streamlit as st
 from transformers import pipeline
-import requests
-from PyPDF2 import PdfReader
+import PyPDF2
 
 # Load Hugging Face Question Answering model
 qa_pipeline = pipeline("question-answering", model="distilbert-base-cased-distilled-squad")
 
-# Function to download and extract text from PDF
-def extract_text_from_huggingface_pdf(url):
-    response = requests.get(url)
-    with open("document.pdf", "wb") as f:
-        f.write(response.content)
-    pdf_reader = PdfReader("document.pdf")
-    text = ""
-    for page in pdf_reader.pages:
-        text += page.extract_text() + "\n"
+# Function to extract text from PDF
+def extract_text_from_pdf(pdf_path):
+    with open(pdf_path, "rb") as f:
+        pdf_reader = PyPDF2.PdfReader(f)
+        text = ""
+        for page in pdf_reader.pages:
+            text += page.extract_text() + "\n"
     return text
 
-# Hugging Face URL 
-PDF_URL = "https://huggingface.co/spaces/SujathaL/AWS_Restart_Program_Chatbot/blob/main/AWS%20restart%20program%20information.docx.pdf"
-pdf_text = extract_text_from_huggingface_pdf(PDF_URL)
-
 # Streamlit UI
-st.title("Chat with Your PDF")
+st.title("Chat with AWS Restart PDF")
+
+# Use the uploaded PDF file
+pdf_path = "AWS restart program information.docx.pdf"  # Update with your file name
+pdf_text = extract_text_from_pdf(pdf_path)
+st.write("✅ PDF Loaded Successfully!")
 
-# User Question Input
-question = st.text_input("Ask a question about the PDF:")
+# User Input
+question = st.text_input("Ask a question about AWS Restart program:")
 
 if st.button("Get Answer") and question:
     response = qa_pipeline(question=question, context=pdf_text)