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import openai
import streamlit as st
import subprocess
import requests
st.title("Income Tax Advisory")
# Initialize session state if it doesn't exist
if "messages" not in st.session_state:
st.session_state.messages = []
# Display previous chat messages
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"], unsafe_allow_html=True)
# Get user input
if prompt := st.chat_input("Ask me anything related to income tax..."):
# Add user message to session state
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.markdown(prompt)
# Get assistant response
with st.expander("Assistant Response", expanded=True):
with st.spinner("I'm thinking..."):
# Define the URL of the API endpoint
url = "http://localhost:3000/send_to_backend"
# Define the data you want to send in the request body
data = {"userMsg": prompt}
# Make the POST request
response = requests.post(url, json=data)
# Check if the request was successful (status code 200)
if response.status_code == 200:
# Render the assistant response with markdown and allow HTML
assistant_response = (response.json())['response']
if assistant_response not in [msg.get("content") for msg in st.session_state.messages if msg.get("role") == "assistant"]:
st.markdown(assistant_response, unsafe_allow_html=True)
# Add assistant's response to session state
st.session_state.messages.append({"role": "assistant", "content": assistant_response})
else:
st.error(f"Error: {response.status_code}")
# Specify the path to the Python file you want to run
file_path = 'api.py'
# Run the Python file
subprocess.run(['python',file_path]) |