Update app.py

app.py

@@ -1,33 +1,44 @@
 import os
 import gradio as gr
-from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
+from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, Settings
+from llama_index.llms.openai import OpenAI
+from llama_index.embeddings.openai import OpenAIEmbedding
 from llama_parse import LlamaParse
+import nest_asyncio
+
+nest_asyncio.apply()
 
 # --- CONFIGURAÇÃO VISUAL ---
 theme_css = """
 body { background-color: #0b0c10; color: #c5c6c7; font-family: 'Roboto', sans-serif; }
-.header-container { 
-    display: flex; align-items: center; justify-content: center; gap: 15px; 
-    padding: 20px; border-bottom: 1px solid #1f2833; margin-bottom: 20px;
-}
+.header-container { display: flex; align-items: center; justify-content: center; gap: 15px; padding: 20px; border-bottom: 1px solid #1f2833; margin-bottom: 20px; }
 .logo-img { height: 60px; width: auto; filter: drop-shadow(0 0 10px rgba(102, 252, 241, 0.5)); }
 .brand-name { font-size: 32px; font-weight: bold; color: #66fcf1; letter-spacing: 4px; font-family: 'Impact', sans-serif; }
 .chatbot-area { height: 500px !important; background-color: #1f2833; border: 1px solid #45a29e; border-radius: 10px; }
 """
 
-# --- VARIÁVEIS GLOBAIS ---
 global_query_engine = None
 
-# --- FUNÇÃO 1: PROCESSAR ---
 def processar_pdf(files, api_key_llama, api_key_openai):
     global global_query_engine
-    if not files:
-        return "⚠️ Por favor, envie um arquivo PDF."
     
+    # Limpa espaços em branco acidentais
+    api_key_openai = api_key_openai.strip()
+    api_key_llama = api_key_llama.strip()
+
+    if not files: return "⚠️ Envie um PDF."
+    if not api_key_openai.startswith("sk-"):
+        return f"⚠️ Erro: A chave digitada não parece uma chave OpenAI válida. Ela começa com: {api_key_openai[:7]}..."
+
+    # FORÇA AS CHAVES NO AMBIENTE
     os.environ["LLAMA_CLOUD_API_KEY"] = api_key_llama
     os.environ["OPENAI_API_KEY"] = api_key_openai
     
     try:
+        # CONFIGURAÇÃO DIRETA (Ignora variáveis de ambiente globais do Hugging Face)
+        Settings.llm = OpenAI(model="gpt-4o", api_key=api_key_openai)
+        Settings.embed_model = OpenAIEmbedding(api_key=api_key_openai)
+        
         parser = LlamaParse(result_type="markdown", language="pt")
         file_extractor = {".pdf": parser}
         filepaths = [f.name if hasattr(f, 'name') else f for f in files]
@@ -36,52 +47,40 @@ def processar_pdf(files, api_key_llama, api_key_openai):
         index = VectorStoreIndex.from_documents(documents)
         global_query_engine = index.as_query_engine()
         
-        return "✅ Sistema COGNILINE Online."
+        return f"✅ CONECTADO! Chave detectada: {api_key_openai[:7]}***"
+        
     except Exception as e:
-        return f"❌ Erro: {str(e)}"
+        return f"❌ Erro Técnico: {str(e)}"
 
-# --- FUNÇÃO 2: RESPONDER ---
 def responder(message, history):
     global global_query_engine
-    if global_query_engine is None:
-        return "⚠️ O sistema está offline. Faça o upload do manual."
+    if global_query_engine is None: return "⚠️ Sistema Offline. Configure acima."
     try:
         response = global_query_engine.query(message)
         return str(response)
     except Exception as e:
         return f"Erro: {str(e)}"
 
-# --- INTERFACE (PADRÃO NOVO) ---
 with gr.Blocks() as demo:
-    
-    # Cabeçalho
     with gr.Row(elem_classes="header-container"):
         if os.path.exists("logo.png"):
             gr.Image("logo.png", elem_classes="logo-img", show_label=False, show_download_button=False)
         gr.Markdown("<div class='brand-name'>COGNILINE</div>")
 
-    # Layout
     with gr.Row():
         with gr.Column(scale=1, min_width=300):
-            gr.Markdown("### ⚙️ Configuração")
+            gr.Markdown("### ⚙️ Painel")
             txt_llama = gr.Textbox(label="LlamaCloud Key", type="password")
-            txt_openai = gr.Textbox(label="OpenAI Key", type="password")
-            file_up = gr.File(label="Manual PDF", file_count="multiple", file_types=[".pdf"])
-            btn_start = gr.Button("INICIAR", variant="primary")
+            # Adicionado o autocomplete="off" para o navegador não interferir
+            txt_openai = gr.Textbox(label="OpenAI Key (sk-...)", type="password")
+            file_up = gr.File(label="PDF", file_count="multiple", file_types=[".pdf"])
+            btn_start = gr.Button("ATIVAR", variant="primary")
             lbl_status = gr.Textbox(label="Status", interactive=False)
 
         with gr.Column(scale=3):
-            # REMOVIDOS OS ARGUMENTOS QUE CAUSAVAM ERRO (retry_btn, clear_btn, etc)
-            # Nas versões novas, o Gradio simplificou a ChatInterface
-            chat = gr.ChatInterface(
-                fn=responder,
-                chatbot=gr.Chatbot(elem_classes="chatbot-area"),
-                textbox=gr.Textbox(placeholder="Digite sua pergunta...", scale=7)
-            )
+            gr.ChatInterface(fn=responder, chatbot=gr.Chatbot(elem_classes="chatbot-area"))
 
     btn_start.click(processar_pdf, inputs=[file_up, txt_llama, txt_openai], outputs=lbl_status)
 
-# --- LANÇAMENTO (AQUI É O SEGREDO DO GRADIO 5/6) ---
 if __name__ == "__main__":
-    # Movemos o CSS e o TEMA para cá conforme o aviso do erro
     demo.launch(css=theme_css, theme=gr.themes.Soft())