Update app.py

app.py

@@ -7,6 +7,7 @@ import re
 import torch
 import pickle
 import json
+import gradio as gr
 
 # Define paths
 MODEL_PATH = "spam_model.pth"
@@ -57,7 +58,8 @@ print("✅ Model and vocabulary loaded successfully!")
 def simple_tokenize(text):
     return re.findall(r"\b\w+\b", text.lower())
     
-def predict(text, model, vocab, max_len=100):
+def predict(text):
+    max_len=100
     model.eval()
     tokens = simple_tokenize(text.lower())
     token_ids = [vocab.get(word, vocab['<UNK>']) for word in tokens]
@@ -67,8 +69,12 @@ def predict(text, model, vocab, max_len=100):
     with torch.no_grad():
         output = model(input_tensor).squeeze().item()
     
-    return "Spam" if output > 0.5 else "Ham"
+    predicted_label = "Spam" if output > 0.5 else "Ham"
+    return f"Predicted Class : {predicted_label} "
 
-# Test prediction
-sample_text = "FreeMsg Hey there darling it's been 3 week's now and no word back! I'd like some fun you up for it still? Tb ok! XxX std chgs to send, £1.50 to rcv"
-print(f"Prediction: {predict(sample_text, model, vocab)}")
+gr.Interface(
+    fn=predict,
+    inputs="text",
+    outputs="text",
+    title="Encoder Spam Classifier"
+).launch()