Update app.py

app.py

@@ -13,7 +13,7 @@ else:
     raise ValueError("HUGGINGFACE_TOKEN environment variable not set.")
 
 # Load the trained model and tokenizer
-model_name = "chaitravi/hate-speech-classifier"  # Replace with your actual Hugging Face model repo
+model_name = "your-username/hate-speech-classifier"  # Replace with your actual Hugging Face model repo
 model = AutoModelForSequenceClassification.from_pretrained(model_name)
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 device = "cuda" if torch.cuda.is_available() else "cpu"
@@ -43,28 +43,31 @@ def classify_message(message):
     return "Hate speech/Offensive" if prediction == 1 else "Not hate speech/Offensive"
 
 # Chat simulation function
-def chat_interface(history, _):
+def chat_interface(history):
+    if history is None:
+        history = []
+    
     username = random.choice(usernames)
     new_message = random.choice(game_responses)
     classification = classify_message(new_message)
     blurred_message = "****" if classification == "Hate speech/Offensive" else new_message
-    history.append((f"{username}: {new_message}", f"{username}: {blurred_message}"))
+    history.append({"role": "user", "content": f"{username}: {blurred_message}"})
     
     # Generate automated game response
     bot_username = "GameMaster"
     bot_response = random.choice(game_responses)
-    history.append((f"{bot_username}: {bot_response}", f"{bot_username}: {bot_response}"))
+    history.append({"role": "assistant", "content": f"{bot_username}: {bot_response}"})
     
-    return history, history
+    return history
 
 # Create Gradio interface
 def main():
     with gr.Blocks() as app:
         gr.Markdown("# Game Chat Hate Speech Detection Simulator")
-        chatbot = gr.Chatbot()
+        chatbot = gr.Chatbot(type="messages")
         submit = gr.Button("Generate Message")
         
-        submit.click(chat_interface, inputs=[chatbot, None], outputs=[chatbot, chatbot])
+        submit.click(chat_interface, inputs=[chatbot], outputs=[chatbot])
     
     app.launch()