app.py

import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
import os
from memory import update_memory, check_memory

# ✅ Load persona instructions
try:
    with open("persona.txt", "r", encoding="utf-8") as f:
        personality = f.read()
except FileNotFoundError:
    personality = "You are a romantic AI chatbot designed to chat with Moin."

# ✅ Fix: Use Correct Model Name
model_name = "syedmoinms/MoinRomanticBot"  # Correct Hugging Face model path
# model_name = "./MoinRomanticBot"  # Uncomment if using local model folder

# ✅ Load Model & Tokenizer with Hugging Face Authentication
HF_TOKEN = os.getenv("HF_TOKEN")  # Use token if model is private

try:
    tokenizer = AutoTokenizer.from_pretrained(model_name, token=HF_TOKEN)
    model = AutoModelForCausalLM.from_pretrained(
        model_name, 
        token=HF_TOKEN, 
        torch_dtype=torch.float16, 
        device_map="auto"
    )
except Exception as e:
    print(f"❌ Error loading model: {e}")
    exit()

# ✅ Function to Generate Response with Memory
def chatbot(input_text):
    memory_response = check_memory(input_text)
    if memory_response:
        return memory_response
    
    prompt = f"{personality}\nMoin: {input_text}\nAI:"
    inputs = tokenizer(prompt, return_tensors="pt").to("cuda" if torch.cuda.is_available() else "cpu")
    
    with torch.no_grad():
        outputs = model.generate(**inputs, max_length=150)
    
    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
    update_memory(input_text, response)
    
    return response

# ✅ Gradio Interface
iface = gr.Interface(fn=chatbot, inputs="text", outputs="text", title="MoinRomanticBot")

# ✅ Launch App
if __name__ == "__main__":
    iface.launch(server_name="0.0.0.0", server_port=7860)