Update app.py

app.py

@@ -20,10 +20,14 @@ nlp = spacy.load('en_core_web_sm')
 # Available backend options are: "jax", "torch", "tensorflow".
 import os
 os.environ["KERAS_BACKEND"] = "jax"
-	
+
+# Ensure the necessary libraries are correctly imported
 import keras
 
-model = keras.saving.load_model("hf://ARI-HIPA-AI-Team/keras_model")
+# Load the model from the Hugging Face repository
+model_path = "https://huggingface.co/Zmorell/HIPA_2/resolve/main/saved_keras_model.keras"
+model = tf.keras.models.load_model(model_path)
+print(f"Model loaded from {model_path}")
 
 def preprocess_text(text):
     text = re.sub(r'[^a-zA-Z0-9\s]', '', text)  # Only remove non-alphanumeric characters except spaces
@@ -39,8 +43,10 @@ def preprocess_text(text):
 
 def predict(text):
     inputs = preprocess_text(text)
+    # Ensure the input shape matches what the model expects
+    inputs = tf.convert_to_tensor([inputs])
     outputs = model(inputs)
-    return "This text is a violation = " + outputs
+    return "This text is a violation = " + str(outputs[0][0].numpy())
 
 demo = gr.Interface(fn=predict, inputs="text", outputs="text")
-demo.launch()   
+demo.launch()