import streamlit as st import json import matplotlib.pyplot as plt import time from PIL import Image from streamlit_image_comparison import image_comparison st.set_page_config(layout="wide") # HIN Number +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ from SPARQLWrapper import SPARQLWrapper, JSON from streamlit_agraph import agraph, TripleStore, Node, Edge, Config import json # Function to load JSON data def load_data(filename): with open(filename, 'r') as file: data = json.load(file) return data # Dictionary for color codes color_codes = { "residential": "#ADD8E6", "commercial": "#90EE90", "community_facilities": "#FFFF00", "school": "#FFFF00", "healthcare_facility": "#FFFF00", "green_space": "#90EE90", "utility_infrastructure": "#90EE90", "emergency_services": "#FF0000", "cultural_facilities": "#D8BFD8", "recreational_facilities": "#D8BFD8", "innovation_center": "#90EE90", "elderly_care_home": "#FFFF00", "childcare_centers": "#FFFF00", "places_of_worship": "#D8BFD8", "event_spaces": "#D8BFD8", "guest_housing": "#FFA500", "pet_care_facilities": "#FFA500", "public_sanitation_facilities": "#A0A0A0", "environmental_monitoring_stations": "#90EE90", "disaster_preparedness_center": "#A0A0A0", "outdoor_community_spaces": "#90EE90", # Add other types with their corresponding colors } # Function to draw the grid with optional highlighting def draw_grid(data, highlight_coords=None): fig, ax = plt.subplots(figsize=(12, 12)) nrows, ncols = data['size']['rows'], data['size']['columns'] ax.set_xlim(0, ncols) ax.set_ylim(0, nrows) ax.set_xticks(range(ncols+1)) ax.set_yticks(range(nrows+1)) ax.grid(True) # Draw roads with a specified grey color road_color = "#606060" # Light grey; change to "#505050" for dark grey for road in data.get('roads', []): # Check for roads in the data start, end = road['start'], road['end'] # Determine if the road is vertical or horizontal based on start and end coordinates if start[0] == end[0]: # Vertical road for y in range(min(start[1], end[1]), max(start[1], end[1]) + 1): ax.add_patch(plt.Rectangle((start[0], nrows-y-1), 1, 1, color=road['color'])) else: # Horizontal road for x in range(min(start[0], end[0]), max(start[0], end[0]) + 1): ax.add_patch(plt.Rectangle((x, nrows-start[1]-1), 1, 1, color=road['color'])) # Draw buildings for building in data['buildings']: coords = building['coords'] b_type = building['type'] size = building['size'] color = color_codes.get(b_type, '#FFFFFF') # Default color is white if not specified if highlight_coords and (coords[0], coords[1]) == tuple(highlight_coords): highlighted_color = "#FFD700" # Gold for highlighting ax.add_patch(plt.Rectangle((coords[1], nrows-coords[0]-size), size, size, color=highlighted_color, edgecolor='black', linewidth=2)) else: ax.add_patch(plt.Rectangle((coords[1], nrows-coords[0]-size), size, size, color=color, edgecolor='black', linewidth=1)) ax.text(coords[1]+0.5*size, nrows-coords[0]-0.5*size, b_type, ha='center', va='center', fontsize=8, color='black') ax.set_xlabel('Columns') ax.set_ylabel('Rows') ax.set_title('Village Layout with Color Coding') return fig # Tabs +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ # Create the main app with three tabs tab1, tab2, tab3 = st.tabs(["Interpretive Number","Green Village", "Control Room"]) with tab1: st.header("Engineering Tools") # Divide the page into three columns col1, col2 = st.columns(2) with col1: st.header("Human Interpretive Number (HIN)") st.write("") "How do LLMs interpret us and over “a period” of time what is the result of our interaction with them?" st.write("") image_comparison( img1="./data/robot.jpg", img2="./data/life.jpg", label1="What the LMM Sees (Simulated Life)", label2="What we See (Real Life)", ) with col2: st.header("Custom GPT Engineering Tools") with tab2: st.header("Green Smart Village Application") # Divide the page into three columns col1, col2, col3 = st.columns(3) with col1: st.header("Today's Agenda") st.write("1. Morning Meeting\n2. Review Project Plans\n3. Lunch Break\n4. Site Visit\n5. Evening Wrap-up") st.header("Agent Advisors") st.write("Would you like to optimize your HIN number?") st.header("My Incentive") st.write("Total incentive for HIN optimization") with col2: st.header("Green Smart Village Layout") data = load_data('grid.json') # Ensure this path is correct # Dropdown for selecting a building building_options = [f"{bld['type']} at ({bld['coords'][0]}, {bld['coords'][1]})" for bld in data['buildings']] selected_building = st.selectbox("Select a building to highlight:", options=building_options) selected_index = building_options.index(selected_building) selected_building_coords = data['buildings'][selected_index]['coords'] # Draw the grid with the selected building highlighted fig = draw_grid(data, highlight_coords=selected_building_coords) st.pyplot(fig) # Assuming sensors are defined in your data, display them sensors = data['buildings'][selected_index].get('sensors', []) st.write(f"Sensors in selected building: {', '.join(sensors)}") with col3: st.header("Check Your HIN Number") # config = Config(height=400, width=400, nodeHighlightBehavior=True, highlightColor="#F7A7A6", directed=True, collapsible=True) if sensors: # Check if there are sensors to display graph_store = TripleStore() building_name = f"{data['buildings'][selected_index]['type']} ({selected_building_coords[0]}, {selected_building_coords[1]})" # Iterate through each sensor and create a triple linking it to the building for sensor in sensors: sensor_id = f"Sensor: {sensor}" # Label for sensor nodes # Correctly add the triple without named arguments graph_store.add_triple(building_name, "has_sensor", sensor_id) # Configuration for the graph visualization agraph_config = Config(height=300, width=300, nodeHighlightBehavior=True, highlightColor="#F7A7A6", directed=True, collapsible=True) # Display the graph agraph(nodes=graph_store.getNodes(), edges=graph_store.getEdges(), config=agraph_config) hin_number = st.text_input("Enter your HIN number:") if hin_number: st.write("HIN number details...") # Placeholder for actual HIN number check with tab3: st.header("Control Room")