Upload app.py

app.py

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+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+device = "cuda" if torch.cuda.is_available() else "cpu"  # Automatically detect GPU or CPU
+model_name = "tanusrich/Mental_Health_Chatbot"
+
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+'''
+model_save_path = "./model"
+# Save model
+model.save_pretrained(model_save_path)
+
+# Save tokenizer
+tokenizer.save_pretrained(model_save_path)'''
+
+def generate_response(user_input):
+    inputs = tokenizer(user_input, return_tensors="pt").to(device)
+    with torch.no_grad():
+        output = model.generate(
+            **inputs,
+            max_new_tokens=150,
+            temperature=0.7,
+            top_k=50,
+            top_p=0.9,
+            repetition_penalty=1.2,
+            pad_token_id=tokenizer.eos_token_id
+        )
+    response = tokenizer.decode(output[0], skip_special_tokens=True)
+    # Extract only chatbot's latest response
+    chatbot_response = response.split("Chatbot:")[-1].strip()
+
+    # Update conversation history
+    conversation_history += chatbot_response + "\n"
+    return chatbot_response
+
+# Continuous conversation loop
+while True:
+    user_input = input("You: ")  # Take user input
+    if user_input.lower() in ["exit", "quit", "stop"]:
+        print("Chatbot: Goodbye!")
+        break
+
+    response = generate_response(user_input)
+    print("Chatbot:", response)
+    
+    
+'''
+# Example
+user_input = "I'm feeling suicidal."
+response = generate_response(user_input)
+print("Chatbot: ", response)
+'''