Update app.py

app.py

@@ -61,16 +61,16 @@ def answer_question(text, question, max_length=512):
 
     start_logits, end_logits = qa_model(inputs)
 
+    # Ensure start_logits is a tensor
+    start_logits = tf.convert_to_tensor(start_logits)
+
     # Check and ensure data type of start_logits:
     if start_logits.dtype not in (tf.float32, tf.int32):
         start_logits = tf.cast(start_logits, tf.float32)  # Example casting to float32
 
     # Verify axis type:
-    if not isinstance(start_logits, tf.Tensor):
-        raise ValueError("start_logits is not a TensorFlow tensor")
-
-    if start_logits.dtype not in (tf.float32, tf.int32):
-        start_logits = tf.cast(start_logits, tf.float32) 
+    if not isinstance(axis, tf.Tensor) or axis.dtype not in (tf.int32, tf.int64):
+        axis = tf.constant(1, dtype=tf.int32)  # Replace with correct axis if needed
 
     # Ensure compatibility for argmax (e.g., non-empty tensor):
     if start_logits.shape[0] == 0:
@@ -84,6 +84,7 @@ def answer_question(text, question, max_length=512):
     return answer if answer else "No answer found."
 
 
+
 ## Streamlit app
 
 st.set_page_config(page_title="Enhanced PDF Summarizer")