Update app.py

app.py

@@ -2,13 +2,12 @@
 import gradio as gr
 import os
 import httpx
-from huggingface_hub import list_models  # ← CORREÇÃO: sem ModelFilter
+from huggingface_hub import list_models
 from datasets import load_dataset
 
 HF_TOKEN = os.getenv("HF_TOKEN")
 
 def search_models(query="legal", language="pt", limit=5):
-    """Busca modelos no HF Hub"""
     try:
         results = list(
             list_models(
@@ -20,38 +19,30 @@ def search_models(query="legal", language="pt", limit=5):
                 token=HF_TOKEN,
             )
         )
-        
         output = ""
         for m in results[:int(limit)]:
             output += f"**{m.modelId}**\n"
             output += f"- Task: {m.pipeline_tag}\n"
             output += f"- Downloads: {m.downloads:,}\n"
             output += f"- URL: https://huggingface.co/{m.modelId}\n\n"
-        
         return output if output else "Nenhum modelo encontrado."
     except Exception as e:
         return f"Erro: {str(e)}"
 
 def analyze_text(text, task="summarization"):
-    """Analisa texto via Inference API"""
     try:
         models = {
             "summarization": "facebook/bart-large-cnn",
             "text-classification": "nlpaueb/legal-bert-base-uncased",
         }
-        
         model_id = models.get(task, "facebook/bart-large-cnn")
         url = f"https://api-inference.huggingface.co/models/{model_id}"
         headers = {"Content-Type": "application/json"}
-        
         if HF_TOKEN:
-            headers["Authorization"] = f"Bearer {os.getenv('HF_TOKEN')}"
-        
+            headers["Authorization"] = f"Bearer {HF_TOKEN}"
         payload = {"inputs": text[:512]}
-        
         with httpx.Client(timeout=60.0) as client:
             resp = client.post(url, headers=headers, json=payload)
-        
         if resp.status_code == 200:
             return str(resp.json())
         else:
@@ -60,7 +51,6 @@ def analyze_text(text, task="summarization"):
         return f"Erro: {str(e)}"
 
 def explore_dataset(dataset_id, n_samples=3):
-    """Explora dataset do HF"""
     try:
         ds = load_dataset(
             dataset_id,
@@ -68,10 +58,8 @@ def explore_dataset(dataset_id, n_samples=3):
             token=HF_TOKEN,
             trust_remote_code=False,
         )
-        
         output = f"**Dataset:** {dataset_id}\n\n"
         output += f"**Colunas:** {', '.join(ds.column_names)}\n\n"
-        
         for i, sample in enumerate(ds.to_list()[:int(n_samples)]):
             output += f"--- Amostra {i+1} ---\n"
             for key, val in sample.items():
@@ -79,12 +67,10 @@ def explore_dataset(dataset_id, n_samples=3):
                     val = val[:300] + "..."
                 output += f"{key}: {val}\n"
             output += "\n"
-        
         return output
     except Exception as e:
         return f"Erro: {str(e)}"
 
-# Interface Gradio
 with gr.Blocks(title="LEX - Assistente Jurídico", theme=gr.themes.Soft()) as demo:
     gr.Markdown("# ⚖️ LEX - Assistente Jurídico MCP")
     gr.Markdown("Powered by Hugging Face Hub + FastMCP")
@@ -98,7 +84,6 @@ with gr.Blocks(title="LEX - Assistente Jurídico", theme=gr.themes.Soft()) as de
                 model_btn = gr.Button("Buscar", variant="primary")
             with gr.Column():
                 model_output = gr.Textbox(label="Resultados", lines=15, interactive=False)
-        
         model_btn.click(fn=search_models, inputs=[model_query, model_lang, model_limit], outputs=model_output)
     
     with gr.Tab("📝 Analisar Texto"):
@@ -113,22 +98,23 @@ with gr.Blocks(title="LEX - Assistente Jurídico", theme=gr.themes.Soft()) as de
                 analyze_btn = gr.Button("Analisar", variant="primary")
             with gr.Column():
                 analyze_output = gr.Textbox(label="Resultado", lines=10, interactive=False)
-        
         analyze_btn.click(fn=analyze_text, inputs=[text_input, task_type], outputs=analyze_output)
     
     with gr.Tab("📊 Explorar Dataset"):
         with gr.Row():
             with gr.Column():
-                dataset_input = gr.Textbox(
-                    label="Dataset ID",
-                    value="joelniklaus/brazilian_court_decisions"
-                )
+                dataset_input = gr.Textbox(label="Dataset ID", value="joelniklaus/brazilian_court_decisions")
                 sample_count = gr.Slider(1, 10, value=3, step=1, label="Amostras")
                 dataset_btn = gr.Button("Explorar", variant="primary")
             with gr.Column():
                 dataset_output = gr.Textbox(label="Dataset Info", lines=15, interactive=False)
-        
         dataset_btn.click(fn=explore_dataset, inputs=[dataset_input, sample_count], outputs=dataset_output)
 
 if __name__ == "__main__":
-    demo.launch()
+    # ✅ CORREÇÃO: Configuração correta para HF Spaces
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=int(os.getenv("PORT", 7860)),
+        share=False,
+        show_error=True
+    )