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import os
import streamlit as st
import re
import time
from PIL import Image
import ast
import numpy as np
def reset_conversation():
st.session_state.messages = []
def display_mask_image(image_path):
if os.path.isfile(image_path):
image = Image.open(image_path)
st.image(image, caption='Final Mask', use_column_width=True)
def tyre_synap_bot(filter_agent,image_file_path):
if "messages" not in st.session_state:
st.session_state.messages = []
print("Found image file path: ",image_file_path)
# Display chat messages from history on app rerun
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
# React to user input
if prompt := st.chat_input("What is up?"):
# Display user message in chat message container
st.chat_message("user").markdown(prompt)
# Add user message to chat history
st.session_state.messages.append({"role": "user", "content": prompt})
ai_response = filter_agent.invoke(
{
"input": f'{prompt}, provided image path: {image_file_path}'
}
)
# ai_response = filter_agent.run(f'{prompt} provided image path :{image_file_path}')
response = f"Echo: {ai_response['output']}"
with st.chat_message("assistant"):
message_placeholder = st.empty()
full_response = ""
if os.path.isfile('final_mask.png'):
display_mask_image('final_mask.png')
# if ('Segmentation image' in ai_response['output']) or ('Predicted_image' in ai_response['output']):
for chunk in re.split(r'(\s+)', response):
full_response += chunk + " "
time.sleep(0.01)
# Add a blinking cursor to simulate typing
message_placeholder.markdown(full_response + "▌")
# Add assistant response to chat history
st.session_state.messages.append({"role": "assistant", "content": full_response})
st.button('Reset Chat', on_click=reset_conversation)
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