Add Gradio interface

app.py

@@ -0,0 +1,23 @@
+import gradio as gr
+from tensorflow.keras.models import load_model
+import json
+
+# Load model and tokenizer
+model = load_model('my_model.h5')
+
+with open('tokenizer.json', 'r') as f:
+    tokenizer = json.load(f)
+
+# Define prediction function
+def predict(text):
+    # Implement your tokenization and model prediction logic here
+    # Example:
+    tokens = tokenizer.texts_to_sequences([text])
+    prediction = model.predict(tokens)
+    return prediction
+
+# Set up Gradio interface
+iface = gr.Interface(fn=predict, inputs="text", outputs="text")
+
+# Launch the interface
+iface.launch()