app.py

import streamlit as st
from openai import OpenAI
from app_kb_handler import *


model = "gpt-3.5-turbo"

# ------------------------------------------------------------------------------------------------
# SIDEBAR
# ------------------------------------------------------------------------------------------------
st.sidebar.title('OpenAI Knowledge Base of Irembo')
st.sidebar.write('This chat bot is build with RAG architecture and OpenAI as LLM. All the Knowledge Base have been crawl automatically from the website https://support.irembo.gov.rw/ ')


def onchange_openai_key():
    print(st.session_state.openai_key) 

openai_key = st.sidebar.text_input('OpenAI key', on_change=onchange_openai_key, key='openai_key')

def submit_openai_key(model=model):
    if(openai_key == None or openai_key==''):
        st.sidebar.write('Please provide the key before')
        return
    else:
        client = OpenAI(api_key=openai_key)
        model = model
        completion = client.chat.completions.create(
            model=model,  
            messages=[
                {"role": "system", "content": "You are an assistant giving simple and short answer for question of child"},
                {"role": "user", "content": "count from 0 to 10"}
            ]
        )        
        st.sidebar.write(f'Simple count : {completion.choices[0].message.content}')

submit_key = st.sidebar.button(label='Submit', on_click=submit_openai_key)



# ------------------------------------------------------------------------------------------------
# CHAT TITLE
# ------------------------------------------------------------------------------------------------

st.title('OpenAI Knowledge Base of Irembo')
st.write(f'Ask any question regarding using Irembo platform to apply for any services.')

def askQuestion(model=model, question=''):
    if(openai_key == None or openai_key==''):
        print('Please provide the key before')
        return 'LLM API is not defined. Please provide the key before'
    else:
        if "df" not in st.session_state:
            st.session_state.df = get_embeddings()
        return answer_question(api_key=openai_key, question=f'{question}', df=st.session_state.df, model=model)



# Initialize chat history
if "messages" not in st.session_state:
    st.session_state.messages = []

# Display chat messages from history on app rerun
for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

# React to user input
if prompt := st.chat_input("What is up?"):
    with st.status('Running', expanded=True) as status:
        # Display user message in chat message container
        st.chat_message("user").markdown(prompt)
        # Add user message to chat history
        st.session_state.messages.append({"role": "user", "content": prompt})

        response = askQuestion(question=prompt)
        # Display assistant response in chat message container
        with st.chat_message("assistant"):
            st.markdown(response)
            
        # Add assistant response to chat history
        st.session_state.messages.append({"role": "assistant", "content": response})
        status.update(label='Reponse of last question', state="complete", expanded=True)