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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})
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