import gradio as gr
import rdflib
import requests
import networkx as nx
import plotly.graph_objs as go
from pyvis.network import Network

# Function to load and extract names from the JSON-LD file
def load_names_from_url(jsonld_url):
    response = requests.get(jsonld_url)
    data = response.json()
    return [item['name'] for item in data if 'name' in item]

# Load names from the JSON-LD file
jsonld_url = 'https://huggingface.co/spaces/histlearn/ShowGraph/raw/main/datafile.jsonld'
names = load_names_from_url(jsonld_url)

def build_graph_from_jsonld(jsonld_url, selected_name):
    response = requests.get(jsonld_url)
    data = response.json()
    
    selected_data = next((item for item in data if item['name'] == selected_name), None)
    
    if not selected_data:
        return "Local não encontrado."
    
    net = Network(height="600px", width="100%", bgcolor="#222222", font_color="white")
    
    # Add Place node
    place_id = selected_data['@id']
    place_label = f"Name: {selected_data['name']}\nDescription: {selected_data['description'][:100]}..."
    net.add_node(place_id, label=selected_data['name'], title=place_label, color="#00ffff")
    
    # Add GeoCoordinates node
    geo_data = selected_data['geo']
    geo_id = geo_data['@id']
    geo_label = f"Lat: {geo_data['lat']}\nLong: {geo_data['long']}\nFeatureCode: {geo_data['gn:featureCode']}\nName: {geo_data['gn:name']}"
    net.add_node(geo_id, label="Geo", title=geo_label, color="#ff9999")
    net.add_edge(place_id, geo_id, title="schema:geo")
    
    # Add CreativeWork nodes
    for work in selected_data.get('subjectOf', []):
        work_id = work['@id']
        work_label = f"Headline: {work['headline']}\nGenre: {work['genre']}\nDatePublished: {work['datePublished']}\nText: {work['text'][:100]}..."
        net.add_node(work_id, label=work['headline'], title=work_label, color="#99ff99")
        net.add_edge(place_id, work_id, title="schema:subjectOf")
    
    net.toggle_physics(True)
    net.show_buttons(filter_=['physics'])
    return net

def run_query_and_visualize(selected_location):
    net = build_graph_from_jsonld(jsonld_url, selected_location)
    
    if isinstance(net, str):  # Error case
        return net
    
    # Save the graph as HTML
    net.save_graph("temp_graph.html")
    with open("temp_graph.html", "r", encoding="utf-8") as f:
        graph_html = f.read()
    
    return graph_html

css = """
body {
    background-color: #f0f0f0;
    font-family: Arial, sans-serif;
}
.container {
    max-width: 1200px;
    margin: 0 auto;
    padding: 20px;
}
h1 {
    color: #333;
    text-align: center;
}
.gr-form {
    background-color: white;
    padding: 20px;
    border-radius: 10px;
    box-shadow: 0 0 10px rgba(0,0,0,0.1);
}
"""

with gr.Blocks(css=css) as demo:
    gr.Markdown("# Visualização de Grafos Literários")
    
    with gr.Row():
        with gr.Column(scale=1):
            selected_location = gr.Dropdown(choices=names, label="Selecione o Local")
            run_button = gr.Button("Visualizar Grafo", variant="primary")
        
        with gr.Column(scale=3):
            graph_output = gr.HTML()
    
    def on_run_button_click(selected_location):
        return run_query_and_visualize(selected_location)

    run_button.click(fn=on_run_button_click, inputs=[selected_location], outputs=graph_output)

demo.launch()