Update app.py

app.py

@@ -5,12 +5,22 @@ import io
 from typing import Any, Tuple
 import os
 
+
 class Client:
     def __init__(self, server_url: str):
         self.server_url = server_url
 
     def send_request(self, task_name: str, model_name: str, text: str, normalization_type: str) -> Tuple[Any, str]:
-        response = requests.post(self.server_url, json={"task_name": task_name, "model_name": model_name, "text": text, "normalization_type": normalization_type}, timeout=60)
+        response = requests.post(
+            self.server_url, 
+            json={
+                "task_name": task_name, 
+                "model_name": model_name, 
+                "text": text, 
+                "normalization_type": normalization_type
+            }, 
+            timeout=60
+        )
         if response.status_code == 200:
             response_data = response.json()
             img_data = bytes.fromhex(response_data["image"])
@@ -31,7 +41,7 @@ with gr.Blocks() as demo:
             choices=[
                 "facebook/opt-1.3b",
                 "facebook/opt-2.7b",
-                "microsoft/Phi-3-mini-128k-instruct"
+                # "microsoft/Phi-3-mini-128k-instruct"
             ],
             value="facebook/opt-1.3b",
             label="Select Model"
@@ -75,7 +85,13 @@ with gr.Blocks() as demo:
             if task_name == "Tokenwise loss without i-th layer":
                 return "token-wise"
 
+        def check_normalization(task_name: str, normalization_name) -> Tuple[str, str]:
+            if task_name == "Contextualization mesurment" and normalization_name == "token-wise":
+                return ("global", "\nALERT: Cannot apply token-wise normalization to one sentence, setting global normalization\n")
+            return (normalization_name, "")
+        
         task_selector.select(set_default, [task_selector], [normalization_selector])
+        normalization_selector.select(check_normalization, [task_selector, normalization_selector], [normalization_selector, log_output])
         submit.click(
             fn=update_output, 
             inputs=[task_selector, model_selector, text_message, normalization_selector, log_output],