app.py

import streamlit as st
from transformers import AutoModelForCausalLM, AutoTokenizer

model_name = "TheBloke/TinyLlama-1.1B-Chat-v0.3-GGUF"

# Load model and tokenizer
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Set model to evaluation mode
model.eval()

st.title("Buddy Christ Chatbot")

user_input = st.text_input("You:", "")
if user_input:
    # Encode the user input
    inputs = tokenizer.encode(user_input, return_tensors="pt", truncation=True, max_length=1000)
    
    # Generate a response using the model
    response = model.generate(inputs, max_length=1000, temperature=1.0, top_k=10, pad_token_id=tokenizer.eos_token_id, gguf_mode=True)
    
    # Decode the response
    response_text = tokenizer.decode(response[0], skip_special_tokens=True)
    
    # Display the response in Streamlit
    st.write("Buddy Christ:", response_text)