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import streamlit as st
from langchain_core.messages import AIMessage, HumanMessage
from model import selector
from util import getYamlConfig
from st_copy_to_clipboard import st_copy_to_clipboard
def display_messages():
for i, message in enumerate(st.session_state.chat_history):
if isinstance(message, AIMessage):
with st.chat_message("AI"):
# Display the model from the kwargs
model = message.kwargs.get("model", "Unknown Model") # Get the model, default to "Unknown Model"
st.write(f"**Model :** {model}")
st.markdown(message.content)
st_copy_to_clipboard(message.content,key=f"message_{i}")
elif isinstance(message, HumanMessage):
with st.chat_message("Moi"):
st.write(message.content)
def launchQuery(query: str = None):
# Initialize the assistant's response
full_response = st.write_stream(
st.session_state["assistant"].ask(
query,
prompt_system=st.session_state.prompt_system,
messages=st.session_state["chat_history"] if "chat_history" in st.session_state else [],
variables=st.session_state["data_dict"]
))
# Temporary placeholder AI message in chat history
st.session_state["chat_history"].append(AIMessage(content=full_response, kwargs={"model": st.session_state["assistant"].getReadableModel()}))
st.rerun()
def show_prompts():
yaml_data = getYamlConfig()["prompts"]
expander = st.expander("Prompts pré-définis")
for categroy in yaml_data:
expander.write(categroy.capitalize())
for item in yaml_data[categroy]:
if expander.button(item, key=f"button_{item}"):
launchQuery(item)
def page():
st.subheader("Choisissez ou posez une question")
if "assistant" not in st.session_state:
st.text("Assistant non initialisé")
if "chat_history" not in st.session_state:
st.session_state["chat_history"] = []
st.markdown("<style>iframe{height:50px;}</style>", unsafe_allow_html=True)
# Collpase for default prompts
show_prompts()
# Models selector
selector.ModelSelector()
# Displaying messages
display_messages()
user_query = st.chat_input("")
if user_query is not None and user_query != "":
st.session_state["chat_history"].append(HumanMessage(content=user_query))
# Stream and display response
launchQuery(user_query)
page() |