app.py

import gradio as gr
from gradio_folium import Folium
from folium import Map
import pandas as pd
import pathlib
import os # for file search of csv files

# Function to list all CSV files in the current directory
def list_csv_files():
    path = pathlib.Path(__file__).parent
    return [f for f in os.listdir(path) if f.endswith('.csv')]

# Function to load data from selected CSV and update the map
def update_map(csv_file):
    df = pd.read_csv(pathlib.Path(__file__).parent / csv_file)
    return df, Folium(value=Map(location=[df.iloc[0]['Latitude'], df.iloc[0]['Longitude']], zoom_start=10), height=400)

# Function to update location on map based on selected data row
def select2(data: gr.Dataframe):
    row = data.iloc[0, :]
    return Map(location=[row['Latitude'], row['Longitude']], zoom_start=10)

# select function with input dataframe and data where gradio Selects the Data then put data index 0 into df.iloc, then Map that location
def select(df, data: gr.SelectData):
    row = df.iloc[data.index[0], :]
    return Map(location=[row['Latitude'], row['Longitude']])
    
# Gradio Blocks
with gr.Blocks() as demo:
    gr.Markdown("# 🗺️ Explore AI Data Maps with Gradio and Folium\n"
                "Install this custom component with `pip install gradio_folium` - wheel files in this directory")

    # Map
    map_component = Folium(height=400)
    
    # Select box for CSV files
    csv_files = list_csv_files()
    csv_selector = gr.Dropdown(label="🏞️🏙️ Select CSV File 🗺️✈️", choices=csv_files)

    # Dataframe and map components
    data = gr.Dataframe(
        row_count=(5,'static'), 
        interactive=False
    )
    # Button to reload data and map
    reload_button = gr.Button("🔄 Reload 🌍📍📂", elem_id="reload_button")

    # Interaction logic
    csv_selector.change(update_map, inputs=csv_selector, outputs=[data, map_component])
    data.select(select, inputs=data, outputs=map_component)
    reload_button.click(update_map, inputs=csv_selector, outputs=[data, map_component])

# Launch the app
demo.launch()