src/streamlit_app.py

import streamlit as st
from transformers import AutoTokenizer, AutoModelForCausalLM

# Load your model and tokenizer
model_name = "CJHauser/PrisimAI-chat"
tokenizer = AutoTokenizer.from_pretrained(model_name, use_fast=True)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Streamlit App
st.set_page_config(page_title="PrisimAI Chatbot")
st.title("🤖 PrisimAI Chatbot")

# User prompt
user_input = st.text_input("Ask something:", placeholder="e.g. What is AI?")

if user_input:
    with st.spinner("Thinking..."):
        inputs = tokenizer(user_input, return_tensors="pt")
        outputs = model.generate(
            inputs["input_ids"],
            max_length=150,
            do_sample=True,
            temperature=0.7,
            top_p=0.9,
            pad_token_id=tokenizer.eos_token_id
        )
        response = tokenizer.decode(outputs[0], skip_special_tokens=True)

    # Remove the original prompt from the response if repeated
    response = response.replace(user_input, "").strip()

    st.markdown(f"**Response:** {response}")