Update app.py

app.py

@@ -28,13 +28,13 @@ MODEL_CONFIGS = {
 # Global dictionary to store loaded models in memory
 MODEL_CACHE = {}
 
-def get_loaded_models(game_type):
+def get_loaded_models(game_identifier):
     """
     Lazy-loads models into memory. If the model is already in the cache, 
     it returns it instantly. Otherwise, it loads it from disk, caches it, and returns it.
     """
-    if game_type not in MODEL_CACHE:
-        file_prefix = game_type.lower().replace(" ", "_").replace("'", "")
+    if game_identifier not in MODEL_CACHE:
+        file_prefix = game_identifier.lower().replace(" ", "_").replace("'", "")
         
         # Load SentencePiece Model
         sp = spm.SentencePieceProcessor()
@@ -45,13 +45,13 @@ def get_loaded_models(game_type):
         interpreter.allocate_tensors()
         
         # Store in cache
-        MODEL_CACHE[game_type] = {
+        MODEL_CACHE[game_identifier] = {
             "sp": sp,
             "interpreter": interpreter,
             "vocab_size": sp.GetPieceSize()
         }
         
-    return MODEL_CACHE[game_type]
+    return MODEL_CACHE[game_identifier]
 
 def custom_pad_sequences(sequences, maxlen, padding='pre', value=0):
     padded_sequences = np.full((len(sequences), maxlen), value)
@@ -125,7 +125,8 @@ def generate_random_name(interpreter, vocab_size, sp, max_length=10, temperature
         
     return normalized_name.strip()
 
-def generateNames(game_type, amount, max_length=30, temperature=0.5, seed_text=""):
+# Note: Preserving the exact parameter names (like 'type') to ensure the API contract remains unbroken
+def generateNames(type, amount, max_length=30, temperature=0.5, seed_text=""):
     hate_speech = detect_hate_speech(seed_text)
     profanity = detect_profanity([seed_text], language='All')
     
@@ -140,14 +141,14 @@ def generateNames(game_type, amount, max_length=30, temperature=0.5, seed_text="
             gr.Warning('Offensive speech detected in the seed text, using an empty seed text.')
             seed_text = ''
 
-    if game_type not in MODEL_CONFIGS:
+    if type not in MODEL_CONFIGS:
         return pd.DataFrame([], columns=['Names'])
 
     # Fetch max sequence length
-    max_seq_len = MODEL_CONFIGS[game_type]
+    max_seq_len = MODEL_CONFIGS[type]
     
     # Fetch cached models (loads them instantly if already cached)
-    cached_data = get_loaded_models(game_type)
+    cached_data = get_loaded_models(type)
     sp = cached_data["sp"]
     interpreter = cached_data["interpreter"]
     vocab_size = cached_data["vocab_size"]
@@ -200,10 +201,15 @@ demo = gr.Interface(
         gr.Slider(0.1, 1, value=0.5, label='Temperature', info='Controls randomness of generation, higher values = more creative, lower values = more probalistic'), 
         gr.Textbox('', label='Seed text (optional)', info='The starting text to begin with', max_lines=1)
     ],
-    outputs=[gr.Dataframe(row_count=(2, "dynamic"), column_count=(1, "fixed"), label="Generated Names", headers=["Names"])],
+    # Removed row_count and column_count to prevent the dataframe from aggressively paginating or limiting the array visualization
+    outputs=[gr.Dataframe(label="Generated Names", headers=["Names"])],
     title='Dungen - Name Generator',
-    description='A fun game-inspired name generator. For an example of how to create, and train your model, like this one, head over to: https://github.com/Infinitode/OPEN-ARC/tree/main/Project-5-TWNG. There you will find our base model, the dataset we used, and implementation code in the form of a Jupyter Notebook (exported from Kaggle). Use on the web: https://infinitode.netlify.app/experiments/dungen-ai.'
+    description=(
+        "A fun game-inspired name generator. For an example of how to create, and train your model, like this one, head over to: https://github.com/Infinitode/OPEN-ARC/tree/main/Project-5-TWNG. There you will find our base model, the dataset we used, and implementation code in the form of a Jupyter Notebook (exported from Kaggle).\n\n"
+        "Try Dungen online: [Dungen AI | Advanced Neural Name Generator](https://infinitode.netlify.app/experiments/dungen-ai/)"
+    )
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    # Added ssr_mode=False to bypass the new Gradio 5 Async loop teardown bug
+    demo.launch(ssr_mode=False)