ChatDataSet / app.py
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# Importing required packages
import streamlit as st
import openai
import uuid
import time
import os
from PIL import Image
import io
import matplotlib.pyplot as plt
st.set_page_config(page_title="OpenAI - Assistent API")
# Initialize OpenAI client
client = openai.Client()
api_key = os.getenv("OPENAI_API_KEY")
assistant_id = os.getenv("assistant_id")
# Function to handle and display images
def handle_and_display_image(file_id):
api_response = client.files.with_raw_response.retrieve_content(file_id)
if api_response.status_code == 200:
content = api_response.content
with open('image.png', 'wb') as f:
f.write(content)
return Image.open('image.png')
else:
print('Failed to download file.')
return None
# Initialize global session state
if "session_id" not in st.session_state:
st.session_state.session_id = str(uuid.uuid4())
if "run" not in st.session_state:
st.session_state.run = {"status": None}
if "messages" not in st.session_state:
st.session_state.messages = []
if "retry_error" not in st.session_state:
st.session_state.retry_error = 0
# Main function to manage pages
def main():
# Sidebar for page selection
with st.sidebar:
st.title('BinDoc GmbH')
st.markdown("Experience revolutionary interaction with BinDocs Chat App, leveraging state-of-the-art AI technology.")
# Add more sidebar content as needed
page = st.sidebar.selectbox("Choose a page", ["Analysis Bot", "Test Page"])
# Main area content based on page selection
if page == "Analysis Bot":
page1() # Call the function for the first page (to be defined)
elif page == "Test Page":
page2() # Call the function for the second page (to be defined)
def page2():
try:
hide_streamlit_style = """
<style>
#MainMenu {visibility: hidden;}
footer {visibility: hidden;}
</style>
"""
st.markdown(hide_streamlit_style, unsafe_allow_html=True)
# Create columns for layout
col1, col2 = st.columns([3, 1]) # Adjust the ratio to your liking
with col1:
st.title("Test Page with Logo!")
with col2:
# Load and display the image in the right column, which will be the top-right corner of the page
image = Image.open('BinDoc Logo (Quadratisch).png')
st.image(image, use_column_width='always')
except Exception as e:
st.error(f"Upsi, an unexpected error occurred: {e}")
def page1():
st.sidebar.title("OpenAI - Assistant API🤖")
st.sidebar.markdown("**Model:** gpt-4-1106-preview API")
st.sidebar.markdown("**Version:** 1.1")
st.sidebar.markdown("**Session-ID:**")
st.sidebar.markdown(st.session_state.session_id)
st.sidebar.divider()
# Create columns for layout
col1, col2 = st.columns([3, 1]) # Adjust the ratio to your liking
with col1:
st.title('Welcome to MediMetrics!')
st.subheader('powered by :orange[BinDoc GmbH] ')
with col2:
# Load and display the image in the right column
image = Image.open('BinDoc Logo (Quadratisch).png')
st.image(image, use_column_width='always')
# Initialize chat history in session state if not exists
if 'chat_history' not in st.session_state:
st.session_state.chat_history = []
# Function to handle question submission
def submit_question(question):
# Add question to chat history
st.session_state.chat_history.append(("User", question))
process_question(question)
# Function to process the question
def process_question(question):
# Clear the previous run status and chat history
st.session_state.run = None
st.session_state.chat_history = [("User", question)] # Start with the current user question
# Add message to the thread
client.beta.threads.messages.create(
thread_id=st.session_state.thread.id,
role="user",
content=question
)
# Create a new run to process the messages in the thread
st.session_state.run = client.beta.threads.runs.create(
thread_id=st.session_state.thread.id,
assistant_id=st.session_state.assistant.id,
)
# Wait for the run to complete
while not hasattr(st.session_state.run, 'status') or st.session_state.run.status not in ["completed", "failed"]:
time.sleep(1)
st.session_state.run = client.beta.threads.runs.retrieve(
thread_id=st.session_state.thread.id,
run_id=st.session_state.run.id,
)
if st.session_state.run.status == "completed":
# Retrieve the list of messages
st.session_state.messages = client.beta.threads.messages.list(
thread_id=st.session_state.thread.id
)
# Get the latest message from the assistant
last_assistant_message = next((message for message in reversed(st.session_state.messages.data) if message.role == "assistant"), None)
if last_assistant_message:
# Update chat history with the assistant's response
st.session_state.chat_history.append(("Assistant", last_assistant_message.content[0].text.value))
# Example query buttons
col3, col4 = st.columns(2) # Create two columns for buttons
with col3:
if st.button("Plotte mir die Anzahl der Kliniken von 2010 bis 2020."):
submit_question("Plotte mir die Anzahl der Kliniken von 2010 bis 2020.")
if st.button("Erstelle mir ein Bar Chart über die Bettenanzahl zwischen 1994 und 2002."):
submit_question("Erstelle mir ein Bar Chart über die Bettenanzahl zwischen 1994 und 2002.")
with col4:
if st.button("Hat die Bettenanzahl zwischen 2018 und 2021 zu- oder abgenommen?"):
submit_question("Hat die Bettenanzahl zwischen 2018 und 2021 zu- oder abgenommen?")
if st.button("Wie hat sich die Fremdkapitalquote des Malteser Krankenhaus St. Franziskus-Hospital verändert?"):
submit_question("Wie hat sich die Fremdkapitalquote des Malteser Krankenhaus St. Franziskus-Hospital verändert?")
prompt = st.text_input("Wie kann ich dir helfen?")
if st.button("Submit"):
submit_question(prompt)
if "assistant" not in st.session_state:
openai.api_key = api_key
# Load the previously created assistant
st.session_state.assistant = openai.beta.assistants.retrieve(assistant_id)
# Create a new thread for this session
st.session_state.thread = client.beta.threads.create(
metadata={'session_id': st.session_state.session_id}
)
# Display chat history in Streamlit chat format
for role, message in st.session_state.chat_history:
if role == "User":
with st.chat_message("User"):
st.markdown(message)
elif role == "Assistant":
with st.chat_message("Assistant"):
st.markdown(message)
# Check if 'run' object has 'status' attribute
if hasattr(st.session_state.run, 'status'):
# Handle the 'running' status
if st.session_state.run.status == "running":
with st.chat_message('assistant'):
st.write("Thinking ......")
if st.session_state.retry_error < 3:
time.sleep(1) # Short delay to prevent immediate rerun
st.rerun()
# Handle the 'failed' status
elif st.session_state.run.status == "failed":
st.session_state.retry_error += 1
with st.chat_message('assistant'):
if st.session_state.retry_error < 3:
st.write("Run failed, retrying ......")
time.sleep(3) # Longer delay before retrying
st.rerun()
else:
st.error("FAILED: The OpenAI API is currently processing too many requests. Please try again later ......")
# Handle any status that is not 'completed'
elif st.session_state.run.status != "completed":
# Attempt to retrieve the run again
st.session_state.run = client.beta.threads.runs.retrieve(
thread_id=st.session_state.thread.id,
run_id=st.session_state.run.id,
)
if st.session_state.retry_error < 3:
time.sleep(3)
st.rerun()
if __name__ == "__main__":
main()