Update app.py

app.py

@@ -2,6 +2,8 @@ import gradio as gr
 import torch
 import random
 import os
+import time
+import threading
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 from huggingface_hub import login
 
@@ -13,7 +15,7 @@ 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"
@@ -30,8 +32,7 @@ game_responses = [
     "We need to capture the objective now!",
     "Healing incoming, stay close!",
     "I got eliminated, need a revive!",
-    "Nice strategy, let's keep it up!",
-    "You are a Fucking Bastard",
+    "Nice strategy, let's keep it up!"
 ]
 
 # Function for classification
@@ -44,31 +45,48 @@ 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, user_message=""):
     if history is None:
         history = []
     
+    # Process user input
+    if user_message:
+        classification = classify_message(user_message)
+        blurred_message = "****" if classification == "Hate speech/Offensive" else user_message
+        history.append({"role": "user", "content": f"You: {blurred_message}"})
+    
+    # Generate automated response
     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({"role": "user", "content": f"{username}: {blurred_message}"})
     
-    # Generate automated game response
+    # Generate bot response
     bot_username = "GameMaster"
     bot_response = random.choice(game_responses)
     history.append({"role": "assistant", "content": f"{bot_username}: {bot_response}"})
     
     return history
 
+# Background chat simulation
+def simulate_chat(chatbot):
+    while True:
+        chatbot.update(chat_interface(chatbot.value))
+        time.sleep(2)
+
 # Create Gradio interface
 def main():
     with gr.Blocks() as app:
         gr.Markdown("# Game Chat Hate Speech Detection Simulator")
         chatbot = gr.Chatbot(type="messages")
-        submit = gr.Button("Generate Message")
+        user_input = gr.Textbox(label="Enter your message")
+        log_box = gr.Textbox(label="Classification Log", interactive=False)
+        
+        user_input.submit(chat_interface, inputs=[chatbot, user_input], outputs=[chatbot])
         
-        submit.click(chat_interface, inputs=[chatbot], outputs=[chatbot])
+        # Start chat simulation in a separate thread
+        threading.Thread(target=simulate_chat, args=(chatbot,), daemon=True).start()
     
     app.launch()