import streamlit as st
import random
import time

st.header(" VERIFYING SCIENTIFIC CLAIMS ")

st.caption("Version 0.1")

# Initialize chat history
if "messages" not in st.session_state:
    st.session_state.messages = [{"role": "assistant", "content": "Let's start verifying the claims here! 👇"}]

# 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"])

def retriever(query: str):
    """Simulate a 'retriever' step, searching for relevant information."""
    with st.chat_message("assistant"):
        placeholder = st.empty()
        text=""
        message = "Retriving the documents related to the claim..."
        for chunk in message.split():
            text += chunk + " "
            time.sleep(0.05)
            # Add a blinking cursor to simulate typing
            placeholder.markdown(text + "▌")
        placeholder.markdown(text)
    # You could return retrieved info here.
    return message

def reasoner(info: str):
    """Simulate a 'reasoner' step, thinking about how to answer."""
    with st.chat_message("assistant"):
        placeholder = st.empty()
        text=""
        message = "Reasoning and verifying the claim..."
        for chunk in message.split():
            text += chunk + " "
            time.sleep(0.05)
            # Add a blinking cursor to simulate typing
            placeholder.markdown(text + "▌")
        placeholder.markdown(text)
    # You could return reasoning info here.
    return message

# Accept user input
if prompt := st.chat_input("40mg/day dosage of folic acid and 2mg/day dosage of vitamin B12 does not affect chronic kidney disease (CKD) progression."):
    # Add user message to chat history
    st.session_state.messages.append({"role": "user", "content": prompt})
    # Display user message in chat message container
    with st.chat_message("user"):
        st.markdown(prompt)

    #Calling retriever
    retriever(prompt)

    #Calling reasoner
    reasoner(prompt)

    # Display assistant response in chat message container
    with st.chat_message("assistant"):
        message_placeholder = st.empty()
        full_response = ""
        assistant_response = random.choice(
            [
                "The claim is correct.",
                "The claim is incorrect.",
            ]
        )

        # Simulate stream of response with milliseconds delay
        for chunk in assistant_response.split():
            full_response += chunk + " "
            time.sleep(0.05)
            # Add a blinking cursor to simulate typing
            message_placeholder.markdown(full_response + "▌")
        message_placeholder.markdown(full_response)
    # Add assistant response to chat history
    st.session_state.messages.append({"role": "assistant", "content": full_response})