Update app.py

app.py

@@ -2,12 +2,14 @@ import os
 import uvicorn
 import base64
 import nest_asyncio
+import shutil
 import logging
 import tempfile
 import io
 import requests
-from typing import List, Optional
-from fastapi import FastAPI, UploadFile, File
+# CORREÇÃO: Adicionado 'Any' na lista de imports
+from typing import List, Optional, Any
+from fastapi import FastAPI, UploadFile, File, Form
 from fastapi.responses import HTMLResponse
 from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
@@ -23,7 +25,7 @@ from llama_index.embeddings.huggingface import HuggingFaceEmbedding
 from llama_parse import LlamaParse
 
 logging.basicConfig(level=logging.INFO)
-logger = logging.getLogger("CognilineCore")
+logger = logging.getLogger("CognilineOmni")
 
 HF_TOKEN = os.getenv("HF_TOKEN")
 LLAMA_KEY = os.getenv("LLAMA_KEY")
@@ -38,12 +40,11 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# --- 1. MOTOR DE VISÃO ---
+# --- 1. VISÃO ---
 class VisionCore:
     def __init__(self, token):
         self.api_url = "https://api-inference.huggingface.co/models/Salesforce/blip-image-captioning-large"
         self.headers = {"Authorization": f"Bearer {token}"}
-    
     def see(self, image_b64):
         try:
             if "," in image_b64: image_b64 = image_b64.split(",")[1]
@@ -52,9 +53,9 @@ class VisionCore:
             if response.status_code == 200:
                 result = response.json()
                 if isinstance(result, list) and len(result) > 0:
-                    return f"[SISTEMA VISUAL]: {result[0].get('generated_text', 'Objeto detetado.')}"
+                    return f"[VISÃO]: {result[0].get('generated_text', 'Objeto técnico.')}"
             return "[Erro Visual: API ocupada]"
-        except Exception as e: return f"[Erro: {str(e)}]"
+        except Exception as e: return f"[Erro Vision: {str(e)}]"
 
 # --- 2. BUSCA WEB ---
 def search_web(query):
@@ -76,7 +77,7 @@ class DoubleBrainLLM(CustomLLM):
     def metadata(self) -> LLMMetadata: return LLMMetadata(model_name=self.model_name, num_output=2048, context_window=8192)
     @llm_completion_callback()
     def complete(self, prompt: str, **kwargs) -> CompletionResponse:
-        sys = "Sistema COGNILINE. Regra: Use APENAS LaTeX ($...$) para fórmulas. Responda em Português Técnico."
+        sys = "Sistema COGNILINE. 1. Use APENAS LaTeX ($...$) para fórmulas. 2. Responda em Português Técnico."
         msgs = [{"role": "system", "content": sys}, {"role": "user", "content": prompt}]
         try:
             resp = self.client.chat_completion(model=self.model_name, messages=msgs, max_tokens=1536, temperature=0.2)
@@ -143,7 +144,7 @@ async def api_ask(q: Q):
 async def home():
     try:
         with open("index.html", "r", encoding="utf-8") as f: html = f.read()
-    except: return HTMLResponse("<h1>ERRO: Crie o arquivo index.html na aba Files!</h1>")
+    except: return HTMLResponse("<h1>ERRO CRÍTICO: Crie o arquivo index.html na aba Files!</h1>")
     
     logo = ""
     if os.path.exists("CGL.png"):