Delete app.py

app.py

@@ -1,53 +0,0 @@
-import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
-
-# Load the saved model and tokenizer
-model_path = "GouthamVarma/mentalhealth_coversational_chatbot"  # You'll need to upload your model to HF Hub first
-tokenizer = AutoTokenizer.from_pretrained(model_path)
-model = AutoModelForCausalLM.from_pretrained(
-    model_path,
-    device_map="auto",
-    torch_dtype=torch.float16,
-    trust_remote_code=True
-)
-
-def chat_response(message, history):
-    formatted_prompt = f"User: {message}\nAssistant: "
-    
-    inputs = tokenizer(formatted_prompt, return_tensors="pt", truncation=True, max_length=512)
-    inputs = {k: v.to(model.device) for k, v in inputs.items()}
-    
-    outputs = model.generate(
-        **inputs,
-        max_length=512,
-        num_return_sequences=1,
-        temperature=0.7,
-        do_sample=True,
-        top_p=0.85,
-        top_k=40,
-        no_repeat_ngram_size=3,
-        repetition_penalty=1.3,
-        pad_token_id=tokenizer.eos_token_id
-    )
-    
-    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    response = response.split("Assistant: ")[-1].strip()
-    
-    return response
-
-# Create Gradio Interface
-demo = gr.ChatInterface(
-    fn=chat_response,
-    title="Mental Health Support Assistant",
-    description="A supportive AI assistant trained to provide empathetic responses to mental health concerns. Please note: This is not a replacement for professional mental health support.",
-    theme="soft",
-    examples=[
-        "I've been feeling really anxious lately about work.",
-        "I can't sleep at night because of stress.",
-        "I feel lonely and isolated."
-    ]
-)
-
-if __name__ == "__main__":
-    demo.launch()