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import os
import streamlit as st
from langchain_core.messages import AIMessage, HumanMessage
from modules.graph import invoke_our_graph
from modules.st_callable_util import get_streamlit_cb # Utility function to get a Streamlit callback handler with context
# Streamlit UI
st.title("Paintrek Medical Assistant")
st.markdown("Chat with an AI-powered health assistant.")
# Initialize the expander state
if "expander_open" not in st.session_state:
st.session_state.expander_open = True
# Check if the OpenAI API key is set
if not os.getenv('GOOGLE_API_KEY'):
# If not, display a sidebar input for the user to provide the API key
st.sidebar.header("GOOGLE_API_KEY Setup")
api_key = st.sidebar.text_input(label="API Key", type="password", label_visibility="collapsed")
os.environ["GOOGLE_API_KEY"] = api_key
# If no key is provided, show an info message and stop further execution and wait till key is entered
if not api_key:
st.info("Please enter your GOOGLE_API_KEY in the sidebar.")
st.stop()
# Capture user input from chat input
prompt = st.chat_input()
# Toggle expander state based on user input
if prompt is not None:
st.session_state.expander_open = False # Close the expander when the user starts typing
# st write magic
with st.expander(label="Paintrek Bot", expanded=st.session_state.expander_open):
"""
At any time you can type 'q' or 'quit' to quit.
"""
# Initialize chat messages in session state
if "messages" not in st.session_state:
st.session_state["messages"] = [AIMessage(content="Welcome to the Paintrek world. I am a health assistant, an interactive clinical recording system. I will ask you questions about your pain and related symptoms and record your responses. I will then store this information securely. At any time, you can type `q` to quit.")]
# Loop through all messages in the session state and render them as a chat on every st.refresh mech
for msg in st.session_state.messages:
# https://docs.streamlit.io/develop/api-reference/chat/st.chat_message
# we store them as AIMessage and HumanMessage as its easier to send to LangGraph
if isinstance(msg, AIMessage):
st.chat_message("assistant").write(msg.content)
elif isinstance(msg, HumanMessage):
st.chat_message("user").write(msg.content)
# Handle user input if provided
if prompt:
st.session_state.messages.append(HumanMessage(content=prompt))
st.chat_message("user").write(prompt)
with st.chat_message("assistant"):
# create a new placeholder for streaming messages and other events, and give it context
st_callback = get_streamlit_cb(st.container())
response = invoke_our_graph(st.session_state.messages, [st_callback])
st.session_state.messages.append(AIMessage(content=response["messages"][-1].content)) # Add that last message to the st_message_state
st.write(response["messages"][-1].content) # Write the message inside the chat_message context
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