Update app.py

app.py

@@ -13,6 +13,7 @@ from typing import List, Tuple, Optional
 import io
 import tempfile
 import warnings
+import string
 
 warnings.filterwarnings("ignore")
 
@@ -67,15 +68,19 @@ class SafeGeocoder:
 
 # Function to just load the model
 
+
 def load_model():
     try:
-        # Use a simple but complete example to test actual extraction
+        # Generate a random location and text each time
+        random_city = random.choice(["Berlin", "Paris", "London", "Tokyo", "Rome", "Madrid"])
+        random_suffix = ''.join(random.choices(string.ascii_lowercase, k=5))
+        test_text = f"Test in {random_city}_{random_suffix}."
+        
         test_template = '{"test_location": ""}'
-        test_text = "Heute sind wir in Berlin."
         
         prompt = f"<|input|>\n### Template:\n{test_template}\n### Text:\n{test_text}\n\n<|output|>"
         
-        # Send a complete request with a simple test case
+        # Send request with randomized input
         payload = {
             "inputs": prompt,
             "parameters": {
@@ -84,35 +89,29 @@ def load_model():
             }
         }
         
-        
-        # Make the actual request
         response = requests.post(API_URL, headers=headers, json=payload)
         
-        # Check loading status
         if response.status_code == 503:
             response_json = response.json()
             if "error" in response_json and "loading" in response_json["error"]:
                 estimated_time = response_json.get("estimated_time", "unknown")
                 return f"⏳ Modell lädt... (ca. {int(float(estimated_time)) if isinstance(estimated_time, (int, float, str)) else 'unbekannt'} Sekunden)"
         
-        # Verify we got a proper response
         if response.status_code == 200:
             result = response.json()
             
-            # Check for a properly formatted extraction result
             if isinstance(result, list) and len(result) > 0:
                 result_text = result[0].get("generated_text", "")
                 
-                # Look for evidence of a completed extraction
-                if "<|output|>" in result_text and "Berlin" in result_text:
+                # Check if response contains the random city we included
+                if "<|output|>" in result_text and random_city in result_text:
                     return "✅ Modell erfolgreich geladen und getestet! Sie können jetzt mit der Extraktion beginnen."
         
-        # If we get here, the model response wasn't complete
         return "⚠️ Modell-Test nicht erfolgreich. Bitte versuchen Sie es erneut in einigen Sekunden."
             
     except Exception as e:
         return f"❌ Fehler beim Laden des Modells: {str(e)}"
-
+        
 def extract_info(template, text):
     try:
         prompt = f"<|input|>\n### Template:\n{template}\n### Text:\n{text}\n\n<|output|>"