app.py

import os
import huggingface_hub
import streamlit as st
from vllm import LLM, SamplingParams

sys_msg = """#Context:
You are an expert financial advisor named IRAI. You have a comprehensive understanding of finance and investing with experience and expertise in all areas of finance. 
#Objective:
Answer questions as best as possible given your current knowledge. You do not have access to up-to-date current market data; if necessary please mention that this will be available in the future. Demonstrate analytical depth and showcase ability to integrated complex data into practical advice, but answer the question directly.
Style and tone:
Answer in a friendly and engaging manner representing a top female investment professional working at a leading investment bank.
#Audience:
The questions will be asked by top executives and managers of successful startups. Assume the audience is composed of 40 year old males with high wealth and income, high risk appetite with high threshold for volatility.
#Response:
Direct answer to question, concise yet insightful."""

@st.cache_resource(show_spinner="Loading model..")
def init_llm():
    huggingface_hub.login(token=os.getenv("HF_TOKEN"))
    llm = LLM(model="InvestmentResearchAI/LLM-ADE-dev")
    tok = llm.get_tokenizer()
    tok.eos_token = '<|im_end|>' # Override to use turns
    return llm

def get_response(prompt):
    try:
        convo = [
            {"role": "system", "content": sys_msg},
            {"role": "user", "content": prompt},
        ]
        llm = init_llm()
        prompts = [llm.get_tokenizer().apply_chat_template(convo, tokenize=False)]
        sampling_params = SamplingParams(temperature=0.3, top_p=0.95, max_tokens=500, stop_token_ids=[128009])
        outputs = llm.generate(prompts, sampling_params)
        for output in outputs:
            return output.outputs[0].text
    except Exception as e:
        return f"An error occurred: {str(e)}"


def main():
    st.title("LLM-ADE 9B Demo")
    
    input_text = st.text_area("Enter your text here:", value="", height=200)
    
    if st.button("Generate"):
        if input_text:
            with st.spinner('Generating response...'):
                response_text = get_response(input_text)
                st.write(response_text)
        else:
            st.warning("Please enter some text to generate a response.")

llm = init_llm()

if __name__ == "__main__":
    main()