Update app.py

app.py

@@ -1,3 +1,13 @@
+import subprocess
+import pkg_resources
+import sys
+
+# Atualiza o Gradio silenciosamente antes de importar
+try:
+    subprocess.check_call([sys.executable, '-m', 'pip', 'install', '--upgrade', 'gradio'], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+except:
+    pass
+
 import gradio as gr
 import rdflib
 import requests
@@ -6,123 +16,99 @@ import networkx as nx
 from io import BytesIO
 import base64
 
-# Verificação simples da versão do Gradio no início
-try:
-    import pkg_resources
-    gradio_version = pkg_resources.get_distribution('gradio').version
-    print(f"Gradio version: {gradio_version}")
-except:
-    print("Não foi possível verificar a versão do Gradio")
-
+# Função para carregar e extrair os nomes do arquivo JSON-LD a partir de uma URL
 def load_names_from_url(jsonld_url):
-    """Carrega e extrai os nomes do arquivo JSON-LD."""
-    try:
-        response = requests.get(jsonld_url)
-        data = response.json()
-        names = []
-        for item in data:
-            if 'name' in item:
-                names.append(item['name'])
-        return sorted(names)  # Retorna nomes ordenados
-    except Exception as e:
-        print(f"Erro ao carregar dados: {e}")
-        return []
+    response = requests.get(jsonld_url)
+    data = response.json()
+    
+    names = []
+    for item in data:
+        if 'name' in item:
+            names.append(item['name'])
+    
+    return names
+
+# Carregar nomes do arquivo JSON-LD
+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):
-    """Constrói o grafo a partir dos dados JSON-LD."""
-    try:
-        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."
-        
-        G = nx.DiGraph()
-        
-        # Adicionar nó do Place
-        place_id = selected_data['@id']
-        place_label = f"schema:Place\nName: {selected_data['name']}\nDescription: {selected_data['description'][:30]}..."
-        G.add_node(place_id, label=place_label)
-        
-        # Adicionar nó de GeoCoordinates
-        geo_data = selected_data['geo']
-        geo_id = geo_data['@id']
-        geo_label = f"geo:SpatialThing\nLat: {geo_data['lat']}\nLong: {geo_data['long']}\nFeatureCode: {geo_data['gn:featureCode']}\nFeatureCodeName: {geo_data['gn:featureCodeName']}\nName: {geo_data['gn:name']}"
-        G.add_node(geo_id, label=geo_label)
-        G.add_edge(place_id, geo_id, label="schema:geo")
-        
-        # Adicionar nós de CreativeWork
-        for work in selected_data.get('subjectOf', []):
-            work_id = work['@id']
-            work_label = f"schema:CreativeWork\nHeadline: {work['headline']}\nGenre: {work['genre']}\nDatePublished: {work['datePublished']}\nText: {work['text'][:30]}...\nLanguage: {work['inLanguage']}"
-            G.add_node(work_id, label=work_label)
-            G.add_edge(place_id, work_id, label="schema:subjectOf")
-        
-        return G
-    except Exception as e:
-        return f"Erro ao construir grafo: {e}"
+    response = requests.get(jsonld_url)
+    data = response.json()
+    
+    # Filtrar o local selecionado
+    selected_data = next((item for item in data if item['name'] == selected_name), None)
+    
+    if not selected_data:
+        return "Local não encontrado."
+    
+    G = nx.DiGraph()
+    
+    # Adicionar nó do Place
+    place_id = selected_data['@id']
+    place_label = f"schema:Place\nName: {selected_data['name']}\nDescription: {selected_data['description'][:30]}..."
+    G.add_node(place_id, label=place_label)
+    
+    # Adicionar nó de GeoCoordinates
+    geo_data = selected_data['geo']
+    geo_id = geo_data['@id']
+    geo_label = f"geo:SpatialThing\nLat: {geo_data['lat']}\nLong: {geo_data['long']}\nFeatureCode: {geo_data['gn:featureCode']}\nFeatureCodeName: {geo_data['gn:featureCodeName']}\nName: {geo_data['gn:name']}"
+    G.add_node(geo_id, label=geo_label)
+    G.add_edge(place_id, geo_id, label="schema:geo")
+    
+    # Adicionar nós de CreativeWork
+    for work in selected_data.get('subjectOf', []):
+        work_id = work['@id']
+        work_label = f"schema:CreativeWork\nHeadline: {work['headline']}\nGenre: {work['genre']}\nDatePublished: {work['datePublished']}\nText: {work['text'][:30]}...\nLanguage: {work['inLanguage']}"
+        G.add_node(work_id, label=work_label)
+        G.add_edge(place_id, work_id, label="schema:subjectOf")
+    
+    return G
 
 def run_query_and_visualize(selected_location, jsonld_url):
-    """Executa a consulta e visualiza o resultado."""
-    try:
-        if not selected_location:
-            return '<div style="text-align: center; padding: 20px;">Selecione um local para visualizar o grafo</div>'
-            
-        G = build_graph_from_jsonld(jsonld_url, selected_location)
+    G = build_graph_from_jsonld(jsonld_url, selected_location)
 
-        if isinstance(G, str):  # Caso de erro
-            return f'<div style="color: red; text-align: center; padding: 20px;">{G}</div>'
-        
-        plt.figure(figsize=(15, 10))
-        pos = nx.spring_layout(G, k=1, iterations=50)
-        
-        nx.draw_networkx_nodes(G, pos, node_size=3000, node_color="skyblue", alpha=0.9)
-        nx.draw_networkx_edges(G, pos, width=2, alpha=0.5, edge_color='gray')
-        nx.draw_networkx_labels(G, pos, labels=nx.get_node_attributes(G, 'label'), font_size=9)
-        nx.draw_networkx_edge_labels(G, pos, edge_labels=nx.get_edge_attributes(G, 'label'), font_size=9)
+    if isinstance(G, str):  # Caso de erro
+        return G
+    
+    # Define posições específicas para os nós importantes
+    pos = nx.spring_layout(G)
+    
+    # Desenha o gráfico usando NetworkX e Matplotlib
+    plt.figure(figsize=(15, 10))
+    nx.draw_networkx_nodes(G, pos, node_size=3000, node_color="skyblue", alpha=0.9)
+    nx.draw_networkx_edges(G, pos, width=2, alpha=0.5, edge_color='gray')
+    nx.draw_networkx_labels(G, pos, labels=nx.get_node_attributes(G, 'label'), font_size=9, font_color="black")
+    nx.draw_networkx_edge_labels(G, pos, edge_labels=nx.get_edge_attributes(G, 'label'), font_size=9, font_color="red")
 
-        plt.title(f"Grafo para: {selected_location}", size=15)
-        plt.axis('off')
-        
-        buf = BytesIO()
-        plt.savefig(buf, format='png', dpi=300, bbox_inches='tight')
-        buf.seek(0)
-        img_str = base64.b64encode(buf.read()).decode()
-        plt.close()
+    plt.title("Resultado da Consulta", size=15)
+    plt.axis('off')
+    
+    # Salva o gráfico em um arquivo
+    buf = BytesIO()
+    plt.savefig(buf, format='png')
+    buf.seek(0)
+    img_str = base64.b64encode(buf.read()).decode()
+    graph_html = f'<img src="data:image/png;base64,{img_str}"/>'
+    
+    plt.close()
 
-        return f'<img src="data:image/png;base64,{img_str}" style="width: 100%; max-width: 1200px;"/>'
-    except Exception as e:
-        return f'<div style="color: red; text-align: center; padding: 20px;">Erro ao gerar visualização: {e}</div>'
+    print("Gráfico gerado com sucesso.")
+    return graph_html
 
-# URL do arquivo JSON-LD
-jsonld_url = 'https://huggingface.co/spaces/histlearn/ShowGraph/raw/main/datafile.jsonld'
+with gr.Blocks() as demo:
+    gr.Markdown("# Visualização de Query SPARQL")
 
-# Carrega os nomes iniciais
-names = load_names_from_url(jsonld_url)
+    with gr.Column():
+        selected_location = gr.Dropdown(choices=names, label="Selecione o Local")
+        run_button = gr.Button("Visualizar Grafo")
 
-# Interface Gradio
-with gr.Blocks(css="footer {display: none}") as demo:
-    gr.Markdown("# Visualização de Grafos de Localidades")
-    gr.Markdown("Selecione um local para visualizar seu grafo de relacionamentos e citações.")
+    graph_output = gr.HTML()
 
-    with gr.Column():
-        selected_location = gr.Dropdown(
-            choices=names,
-            label="Selecione o Local",
-            value=names[0] if names else None
-        )
-        view_button = gr.Button("Visualizar Grafo", variant="primary")
-        result_html = gr.HTML(
-            value='<div style="text-align: center; padding: 20px;">Selecione um local e clique em "Visualizar Grafo"</div>'
-        )
+    def on_run_button_click(selected_location):
+        return run_query_and_visualize(selected_location, jsonld_url)
 
-        view_button.click(
-            fn=run_query_and_visualize,
-            inputs=[selected_location, gr.Textbox(value=jsonld_url, visible=False)],
-            outputs=result_html
-        )
+    run_button.click(fn=on_run_button_click, inputs=[selected_location], outputs=graph_output)
 
 if __name__ == "__main__":
     demo.launch()