Update app.py

app.py

@@ -3,6 +3,7 @@ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, AutoModelForQuest
 from sentence_transformers import SentenceTransformer
 import fitz  # PyMuPDF
 import os
+import torch
 
 # Load the models
 summarization_model_name = 'facebook/bart-large-cnn'
@@ -29,13 +30,13 @@ def summarize_document(document):
 
 # Function to get answer to question
 def get_answer(question, context):
-    inputs = qa_tokenizer(question, context, return_tensors="pt")
+    inputs = qa_tokenizer(question, context, return_tensors="pt", padding=True, truncation=True, max_length=512)
     start_positions, end_positions = qa_model(**inputs)
     answer_start = torch.argmax(start_positions)
     answer_end = torch.argmax(end_positions) + 1
     answer = qa_tokenizer.convert_tokens_to_string(qa_tokenizer.convert_ids_to_tokens(inputs["input_ids"][0][answer_start:answer_end]))
     return answer
-
+    
 # Streamlit app
 st.title("PDF Summarizer and Q&A")
 st.write("Upload a PDF file to get a summary and ask questions about the content.")