Update app.py

app.py

@@ -11,22 +11,17 @@ os.environ['KERAS_BACKEND'] = 'tensorflow'
 os.environ['HF_USERNAME'] = 'Grey01'
 
 
-hf_username = huggingface_hub.whoami()['name']
-hf_url = f'hf://{hf_username}/bart_billsum'
 
-# Load your Keras model
-@st.cache_resource 
-def load_model_and_preprocessor():
-    bart_billsum = keras_nlp.models.BartSeq2SeqLM.from_preset(f'hf://{hf_username}/bart_billsum')
-    
-    # Load the default BART preprocessor (assuming you saved its configuration)
-    #preprocessor = keras_nlp.models.BartSeq2SeqLMPreprocessor.from_preset('bart_base_en', encoder_sequence_length=512,
-    
-    #decoder_sequence_length=128,)
-    
-    return model
+from huggingface_hub import whoami
 
-model = load_model_and_preprocessor()
+# Get the username
+hf_username = whoami()['name']
+
+# Define the model repository
+model_repo = f'{hf_username}/bart_billsum'
+
+# Load the Keras NLP model
+bart_billsum = keras_nlp.models.BartSeq2SeqLM.from_preset(model_repo)
 
 st.title("SummarizeIt")
 
@@ -63,7 +58,7 @@ def generate_text(model, input_texts, max_length=200, print_time_taken=False):
     return summary
 
 generated_summaries = generate_text(
-    model,
+    bart_billsum,
     text,  # Pass the list of documents directly
 )
 st.subheader("Generated Summary:")