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import time
import streamlit as st
def display_chat_history(model_name: str):
for message in st.session_state[model_name]:
with st.chat_message(message["role"]):
st.markdown(message["content"])
def chat_input(model_name: str):
if prompt := st.chat_input("Say something"):
# Display user message in chat message container
st.chat_message("user").markdown(prompt)
# Add user message to chat history
st.session_state[model_name].append({"role": "user", "content": prompt})
return prompt
def display_bot_msg(model_name: str, bot_response: str):
# Display assistant response in chat message container
with st.chat_message("assistant"):
message_placeholder = st.empty()
full_response = ""
# simulate the chatbot "thinking" before responding
# (or stream its response)
for chunk in bot_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)
# st.markdown(response)
# Add assistant response to chat history
st.session_state[model_name].append(
{"model_name": model_name, "role": "assistant", "content": full_response}
)
# @st.cache_data
def chatbox(model_name: str, model: None):
# Display chat messages from history on app rerun
for message in st.session_state.messages:
if (message["model_name"] == model_name):
with st.chat_message(message["role"]):
st.markdown(message["content"])
if prompt := st.chat_input("Say something"):
# Display user message in chat message container
st.chat_message("user").markdown(prompt)
# Add user message to chat history
st.session_state.messages.append({"model_name": model_name, "role": "user", "content": prompt})
with st.spinner("Processing your query..."):
bot_response = model.get_response(prompt)
print("bot: ", bot_response)
# Display assistant response in chat message container
with st.chat_message("assistant"):
message_placeholder = st.empty()
full_response = ""
# simulate the chatbot "thinking" before responding
# (or stream its response)
for chunk in bot_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)
# st.markdown(response)
# Add assistant response to chat history
st.session_state.messages.append(
{"model_name": model_name, "role": "assistant", "content": full_response}
)
# Scroll to the bottom of the chat container
# st.markdown(
# """
# <script>
# const chatContainer = document.getElementsByClassName("css-1n76uvr")[0];
# chatContainer.scrollTop = chatContainer.scrollHeight;
# </script>
# """,
# unsafe_allow_html=True,
# )
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