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import streamlit as st
from transformers import pipeline
from concurrent.futures import ThreadPoolExecutor

# Load models at startup
with st.spinner(text="Loading Models..."):
    base_pipe = pipeline(
        "text-generation",
        model="TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T",
        max_length=512,
    )
    irai_pipe = pipeline(
        "text-generation",
        model="InvestmentResearchAI/LLM-ADE_tiny-v0.001",
        max_length=512,
    )

prompt_template = (
    "<|system|>\n"
    "You are a friendly chatbot who always gives helpful, detailed, and polite answers.</s>\n"
    "<|user|>\n"
    "{input_text}</s>\n"
    "<|assistant|>\n"
)


def generate_base_response(input_text):
    return base_pipe(input_text)[0]["generated_text"]


def generate_irai_response(input_text):
    return (
        irai_pipe(prompt_template.format(input_text=input_text))[0]["generated_text"]
        .split("<|assistant|>")[1]
        .strip()
    )


def generate_response(input_text):
    with ThreadPoolExecutor() as executor:
        try:
            future_base = executor.submit(generate_base_response, input_text)
            future_irai = executor.submit(generate_irai_response, input_text)
            base_resp = future_base.result()
            irai_resp = future_irai.result()
        except Exception as e:
            st.error(f"An error occurred: {e}")
            return None, None
    return base_resp, irai_resp


st.title("IRAI LLM-ADE vs Base Model")
user_input = st.text_area("Enter a financial question:", "")

if st.button("Generate"):
    if user_input:
        with st.spinner(text="Generating text..."):
            base_response, irai_response = generate_response(user_input)
            col1, col2 = st.columns(2)
            with col1:
                st.header("Base Model Response")
                st.text_area("", base_response, height=300)
            with col2:
                st.header("IRAI LLM-ADE Model Response")
                st.text_area("", irai_response, height=300)
    else:
        st.warning("Please enter some text to generate a response.")