Update app.py

app.py

@@ -19,7 +19,7 @@ tokenizer = AutoTokenizer.from_pretrained(base_model_name)
 
 #gr.load("models/samidh/cope-gemma2b-hs-2c-skr-s1.5.9.d25", hf_token=os.environ['HF_TOKEN']).launch()
 
-prompt = """
+PROMPT = """
 INSTRUCTIONS
 ============
 
@@ -43,20 +43,22 @@ ANSWER
 """
 
 # Function to make predictions
-def predict(policy, content):
-    input_text = prompt.format(policy=policy, content=content)
+def predict(content, policy):
+    input_text = PROMPT.format(policy=policy, content=content)
+    print(input_text)
     inputs = tokenizer.encode(input_text, return_tensors="pt")
     outputs = model.generate(inputs, max_new_tokens=1)
     decoded_output = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return decoded_output[-1]
+    print(decoded_output)
+    return decoded_output
 
 # Create Gradio interface
 iface = gr.Interface(
     fn=predict,
-    inputs=[gr.Textbox(label="Policy", lines=10), gr.Textbox(label="Content", lines=2)], 
+    inputs=[gr.Textbox(gr.Textbox(label="Content", lines=2), label="Policy", lines=10)], 
     outputs="label",
     title="CoPE Demo",
-    description="Type something and the model will classify your text."
+    description="See if the given content violates your given policy."
 )
 
 # Launch the app