app.py

import streamlit as st
from src.audio import audio_d
from src.chat import virtual_tutor
from src.OCR import I_OCR
from utils.qa import chain
from utils.qa import chain
import base64
from src.about import virtual_tutor_markdown as sms
from src.pdf_up import process_uploaded_file
from langchain.memory import ConversationBufferWindowMemory
from langchain_community.chat_message_histories import StreamlitChatMessageHistory

memory_storage = StreamlitChatMessageHistory(key="chat_messages")
memory = ConversationBufferWindowMemory(memory_key="chat_history", human_prefix="User", chat_memory=memory_storage, k=3)
image_bg = r"C:\Users\Naresh Kumar Lahajal\Desktop\FINAL\data\image\freepik-export-20240425023906eVmL.jpeg"

def add_bg_from_local(image_file):
    with open(image_file, "rb") as image_file:
        encoded_string = base64.b64encode(image_file.read())
    st.markdown(f"""<style>.stApp {{background-image: url(data:image/{"png"};base64,{encoded_string.decode()});
    background-size: cover}}</style>""", unsafe_allow_html=True)
add_bg_from_local(image_bg)

def get_answer(query):
    response = chain.invoke(query)
    #return response["result"]
    return response
 
# Page 1: Home Page
def home():
    st.header("Welcome")
    #st.set_page_config(layout='wide', page_title="Virtual Tutor")
    st.markdown("""
        <svg width="600" height="100">
            <text x="50%" y="50%" font-family="San serif" font-size="42px" fill="Black" text-anchor="middle" stroke="white"
             stroke-width="0.3" stroke-linejoin="round">Virtual Tutor - CHAT
            </text>
        </svg>
    """, unsafe_allow_html=True)

    if "messages" not in st.session_state:
        st.session_state.messages = [
            {"role": "assistant", "content": "Hi! How may I assist you today?"}
        ]

    st.markdown("""
        <style> 
        .stChatInputContainer > div {
        background-color: #000000;
        }
        </style>
        """, unsafe_allow_html=True)

    for message in st.session_state.messages: # Display the prior chat messages
        with st.chat_message(message["role"]):
            st.write(message["content"])

    for i, msg in enumerate(memory_storage.messages):
        name = "user" if i % 2 == 0 else "assistant"
        st.chat_message(name).markdown(msg.content)

    if user_input := st.chat_input("User Input"):
        with st.chat_message("user"):
            st.markdown(user_input)

        with st.spinner("Generating Response..."):
            with st.chat_message("assistant"):
                response = get_answer(user_input)
                answer = response['result']
                st.markdown(answer)
                message = {"role": "assistant", "content": answer}
                message_u = {"role": "user", "content": user_input}
                st.session_state.messages.append(message_u)
                st.session_state.messages.append(message)

# Page 2: About Page
#def Virtual_CHAT():
#    st.header("Welcome chat")
# Page 3: Contact Page
def Image_Query():
    I_OCR()

def Audio():
    audio_d()

def pdf_():
    process_uploaded_file()

def About():
    st.markdown(sms)
# Page Selector
def main():
    st.sidebar.title("Navigation")
    page = st.sidebar.selectbox("Go to", ["Home", "Image Query","Audio","PDF","ABOUT US"])

    if page == "Home":
        virtual_tutor()
    #elif page == "Virtual Chat":
    #    home()
    elif page == "Image Query":
        Image_Query()
    elif page == "Audio":
        audio_d()
    elif page == "PDF":
        pdf_()
    elif page == "ABOUT US":
        About()

    if st.sidebar.button("Clear Chat History"):
        memory_storage.clear()
        st.session_state.clear()

if __name__ == "__main__":
    main()