feat: enhance application functionality and telemetry monitoring

- Added new scripts in `package.json` for Python dependency installation and sidecar compilation. - Integrated telemetry fetching in `src/App.tsx` to monitor CPU, RAM, GPU, and disk usage. - Implemented model downloading functionality with progress tracking in `src/App.tsx`. - Updated `Footer` and `Header` components to display telemetry data and settings options. - Enhanced Tauri configuration for sidecar execution and application window settings. - Updated Python requirements in `requirements.txt` to include additional dependencies for improved functionality.
2026-01-14 23:57:14 -03:00
1 parent 482b28513e
commit 08e154894a
@@ -0,0 +1,86 @@
+import os
+import subprocess
+import platform
+import shutil
+import sys
+
+def get_target_triple():
+    # Retorna o sufixo exigido pelo Tauri baseado no SO e Arquitetura
+    system = platform.system().lower()
+    arch = platform.machine().lower()
+    
+    if system == "windows":
+        return "x86_64-pc-windows-msvc"
+    elif system == "linux":
+        return "x86_64-unknown-linux-gnu"
+    return None
+
+def check_pyinstaller():
+    """Verifica se PyInstaller está instalado, instala se necessário."""
+    try:
+        # Tenta usar python -m PyInstaller (sempre funciona se instalado)
+        subprocess.run([sys.executable, "-m", "PyInstaller", "--version"], 
+                      check=True, 
+                      stdout=subprocess.DEVNULL, 
+                      stderr=subprocess.DEVNULL)
+        return True
+    except (FileNotFoundError, subprocess.CalledProcessError):
+        print("[Build] PyInstaller não encontrado. Instalando...")
+        try:
+            subprocess.run([sys.executable, "-m", "pip", "install", "pyinstaller"], 
+                          check=True)
+            return True
+        except subprocess.CalledProcessError:
+            print("[Erro] Falha ao instalar PyInstaller")
+            return False
+
+def compile():
+    triple = get_target_triple()
+    if not triple:
+        print("[Erro] Sistema operacional não suportado")
+        sys.exit(1)
+    
+    if not check_pyinstaller():
+        print("[Erro] PyInstaller não disponível")
+        sys.exit(1)
+    
+    binary_name = f"engine-backend-{triple}"
+    if platform.system() == "Windows":
+        binary_name += ".exe"
+
+    print(f"[Build] Compilando sidecar para: {triple}...")
+    
+    # Executa PyInstaller via python -m (garante que funciona mesmo sem PATH)
+    cmd = [
+        sys.executable,
+        "-m", "PyInstaller",
+        "--onefile",
+        "--name", binary_name,
+        "src-python/app/api_server.py"
+    ]
+    
+    try:
+        subprocess.run(cmd, check=True)
+    except subprocess.CalledProcessError as e:
+        print(f"[Erro] Falha ao compilar: {e}")
+        sys.exit(1)
+
+    # Garante que a pasta de destino existe
+    target_dir = os.path.join("src-tauri", "binaries")
+    os.makedirs(target_dir, exist_ok=True)
+
+    # Move o binário da pasta dist para a pasta binaries do Tauri
+    source_path = os.path.join("dist", binary_name)
+    target_path = os.path.join(target_dir, binary_name)
+    
+    if os.path.exists(source_path):
+        if os.path.exists(target_path):
+            os.remove(target_path)
+        shutil.move(source_path, target_path)
+        print(f"[Success] Sidecar compilado e movido para: {target_path}")
+    else:
+        print(f"[Erro] Binário não encontrado em: {source_path}")
+        sys.exit(1)
+
+if __name__ == "__main__":
+    compile()
@@ -0,0 +1,38 @@
+# -*- mode: python ; coding: utf-8 -*-
+
+
+a = Analysis(
+    ['src-python\\app\\api_server.py'],
+    pathex=[],
+    binaries=[],
+    datas=[],
+    hiddenimports=[],
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=[],
+    noarchive=False,
+    optimize=0,
+)
+pyz = PYZ(a.pure)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    a.binaries,
+    a.datas,
+    [],
+    name='engine-backend-x86_64-pc-windows-msvc.exe',
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=True,
+    upx_exclude=[],
+    runtime_tmpdir=None,
+    console=True,
+    disable_windowed_traceback=False,
+    argv_emulation=False,
+    target_arch=None,
+    codesign_identity=None,
+    entitlements_file=None,
+)
@@ -4,6 +4,10 @@
  "version": "0.1.0",
  "type": "module",
  "scripts": {
+    "dev:ui": "vite",
+    "install:python-deps": "node scripts/install-python-deps.js",
+    "compile:sidecar": "python compile_sidecar.py",
+    "predev": "pnpm install:python-deps && pnpm compile:sidecar",
    "dev": "vite",
    "build": "tsc && vite build",
    "preview": "vite preview",
@@ -27,6 +31,7 @@
    "@tailwindcss/postcss": "^4.1.18",
    "@tauri-apps/cli": "^2",
    "autoprefixer": "^10.4.23",
+    "concurrently": "^9.2.1",
    "postcss": "^8.5.6",
    "tailwindcss": "^4.1.18",
    "typescript": "~5.6.2",
@@ -54,6 +54,9 @@ importers:
      autoprefixer:
        specifier: ^10.4.23
        version: 10.4.23([email protected])
+      concurrently:
+        specifier: ^9.2.1
+        version: 9.2.1
      postcss:
        specifier: ^8.5.6
        version: 8.5.6
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+    engines: {node: 6.* || 8.* || >= 10.*}
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    engines: {node: '>=4'}
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+
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+
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@@ -1306,6 +1386,14 @@ packages:
      yaml:
        optional: true

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@@ -1970,6 +2066,12 @@ snapshots:

  '@types/[email protected]': {}

+  [email protected]: {}
+
+  [email protected]:
+    dependencies:
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+
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    dependencies:
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@@ -2005,8 +2107,34 @@ snapshots:

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      fsevents: 2.3.3

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@@ -2355,6 +2517,10 @@ snapshots:
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      picomatch: 4.0.3

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@@ -2386,8 +2552,28 @@ snapshots:
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      lightningcss: 1.30.2

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+      string-width: 4.2.3
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  [email protected]: {}

  [email protected]: {}

+  [email protected]: {}
+
+  [email protected]:
+    dependencies:
+      cliui: 8.0.1
+      escalade: 3.2.0
+      get-caller-file: 2.0.5
+      require-directory: 2.1.1
+      string-width: 4.2.3
+      y18n: 5.0.8
+      yargs-parser: 21.1.1
+
  [email protected]: {}
@@ -0,0 +1,37 @@
+// Script cross-platform Node.js para instalar dependências Python
+import { execSync } from 'child_process';
+import path from 'path';
+import fs from 'fs';
+import { fileURLToPath } from 'url';
+
+const __filename = fileURLToPath(import.meta.url);
+const __dirname = path.dirname(__filename);
+
+const isWindows = process.platform === 'win32';
+const pythonCmd = isWindows ? 'python' : 'python3';
+const requirementsPath = path.join(__dirname, '..', 'src-python', 'requirements.txt');
+
+if (!fs.existsSync(requirementsPath)) {
+  console.error(`[Python Deps] ERRO: Arquivo não encontrado: ${requirementsPath}`);
+  process.exit(1);
+}
+
+console.log(`[Python Deps] Verificando dependências em: ${requirementsPath}`);
+
+try {
+  // Verifica pip
+  execSync(`${pythonCmd} -m pip --version`, { stdio: 'ignore' });
+  
+  // Atualiza pip
+  console.log('[Python Deps] Atualizando pip...');
+  execSync(`${pythonCmd} -m pip install --quiet --upgrade pip`, { stdio: 'inherit' });
+  
+  // Instala dependências
+  console.log('[Python Deps] Instalando dependências...');
+  execSync(`${pythonCmd} -m pip install --quiet -r "${requirementsPath}"`, { stdio: 'inherit' });
+  
+  console.log('[Python Deps] Dependências instaladas com sucesso.');
+} catch (error) {
+  console.error('[Python Deps] ERRO: Falha ao instalar dependências.');
+  process.exit(1);
+}
@@ -0,0 +1,36 @@
+# Script PowerShell para instalar dependências Python antes de executar
+param(
+    [string]$RequirementsPath = "src-python\requirements.txt",
+    [string]$PythonCmd = "python"
+)
+
+$ErrorActionPreference = "Stop"
+
+# Resolve caminho absoluto
+$RequirementsFile = Join-Path $PSScriptRoot "..\$RequirementsPath" | Resolve-Path -ErrorAction Stop
+
+Write-Host "[Python Deps] Verificando dependências em: $RequirementsFile" -ForegroundColor Cyan
+
+# Verifica se pip está disponível
+try {
+    $pipVersion = & $PythonCmd -m pip --version 2>&1
+    if ($LASTEXITCODE -ne 0) {
+        Write-Host "[Python Deps] ERRO: pip não encontrado. Instale Python com pip." -ForegroundColor Red
+        exit 1
+    }
+} catch {
+    Write-Host "[Python Deps] ERRO: Python não encontrado. Verifique se está no PATH." -ForegroundColor Red
+    exit 1
+}
+
+# Instala dependências
+Write-Host "[Python Deps] Instalando dependências..." -ForegroundColor Yellow
+& $PythonCmd -m pip install --quiet --upgrade pip
+& $PythonCmd -m pip install --quiet -r $RequirementsFile
+
+if ($LASTEXITCODE -eq 0) {
+    Write-Host "[Python Deps] Dependências instaladas com sucesso." -ForegroundColor Green
+} else {
+    Write-Host "[Python Deps] ERRO: Falha ao instalar dependências." -ForegroundColor Red
+    exit 1
+}
@@ -0,0 +1,36 @@
+#!/bin/bash
+# Script Bash para instalar dependências Python antes de executar
+
+set -e
+
+REQUIREMENTS_PATH="${1:-src-python/requirements.txt}"
+PYTHON_CMD="${2:-python3}"
+
+# Resolve caminho absoluto
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+REQUIREMENTS_FILE="$SCRIPT_DIR/../$REQUIREMENTS_PATH"
+
+if [ ! -f "$REQUIREMENTS_FILE" ]; then
+    echo "[Python Deps] ERRO: Arquivo não encontrado: $REQUIREMENTS_FILE" >&2
+    exit 1
+fi
+
+echo "[Python Deps] Verificando dependências em: $REQUIREMENTS_FILE"
+
+# Verifica se pip está disponível
+if ! $PYTHON_CMD -m pip --version >/dev/null 2>&1; then
+    echo "[Python Deps] ERRO: pip não encontrado. Instale Python com pip." >&2
+    exit 1
+fi
+
+# Instala dependências
+echo "[Python Deps] Instalando dependências..."
+$PYTHON_CMD -m pip install --quiet --upgrade pip
+$PYTHON_CMD -m pip install --quiet -r "$REQUIREMENTS_FILE"
+
+if [ $? -eq 0 ]; then
+    echo "[Python Deps] Dependências instaladas com sucesso."
+else
+    echo "[Python Deps] ERRO: Falha ao instalar dependências." >&2
+    exit 1
+fi
@@ -0,0 +1 @@
+# Package initialization
@@ -0,0 +1 @@
+# Package initialization
@@ -0,0 +1,139 @@
+"""
+Servidor FastAPI para expor telemetria e download de modelos.
+Utiliza Server-Sent Events (SSE) para streaming de progresso em tempo real.
+"""
+import sys
+import os
+import json
+from pathlib import Path
+from typing import Dict, List
+from fastapi import FastAPI, HTTPException
+from fastapi.responses import StreamingResponse, JSONResponse
+from fastapi.middleware.cors import CORSMiddleware
+from pydantic import BaseModel
+import asyncio
+
+# Detecta se está rodando como binário ou script
+if getattr(sys, 'frozen', False):
+    # Caminho do executável (PyInstaller)
+    BASE_DIR = os.path.dirname(sys.executable)
+    CONFIG_PATH = os.path.join(BASE_DIR, "modelConfig.yaml")
+    MODELS_DIR = os.path.join(BASE_DIR, "models")
+else:
+    # Rodando como script Python
+    # Ajusta PYTHONPATH antes dos imports relativos
+    script_dir = os.path.dirname(os.path.abspath(__file__))
+    project_root = os.path.dirname(os.path.dirname(script_dir))  # Sobe para raiz do projeto
+    if project_root not in sys.path:
+        sys.path.insert(0, project_root)
+    
+    BASE_DIR = project_root
+    CONFIG_PATH = os.path.join(BASE_DIR, "modelConfig.yaml")
+    MODELS_DIR = os.path.join(BASE_DIR, "src-python", "app", "models")
+
+# Importações relativas (funcionam quando executado como módulo)
+from .telemetry import SystemTelemetry
+from .model_downloader import ModelDownloader
+
+app = FastAPI(title="LocalAI API", version="1.0.0")
+
+# CORS para permitir comunicação com frontend Tauri
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Em produção, restringir ao localhost
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Instâncias globais
+downloader = ModelDownloader(models_dir=MODELS_DIR)
+
+# Modelos de dados
+class ModelInfo(BaseModel):
+    id: str
+    name: str
+    quant: str
+    size_gb: float
+    repo: str
+    filename: str
+    description: str
+
+class DownloadRequest(BaseModel):
+    model_id: str
+    repo_id: str
+    filename: str
+
+# Cache de modelos disponíveis (pode ser carregado de JSON)
+MODELS_REGISTRY: List[Dict] = [
+    {
+        "id": "lfm-2.5-1.2b",
+        "name": "Liquid LFM 2.5",
+        "quant": "Q6_K",
+        "size_gb": 1.12,
+        "repo": "LiquidAI/LFM2.5-1.2B-Instruct-GGUF",
+        "filename": "LFM2.5-1.2B-Instruct-Q6_K.gguf",
+        "description": "Otimizado para arquitetura sequencial de alta performance."
+    }
+]
+
+@app.get("/api/telemetry")
+async def get_telemetry():
+    """Retorna telemetria do sistema em tempo real."""
+    return SystemTelemetry.get_stats()
+
+@app.get("/api/models")
+async def list_models():
+    """Lista todos os modelos disponíveis com status de download."""
+    models_with_status = []
+    for model in MODELS_REGISTRY:
+        model_path = downloader.get_model_path(model["repo"], model["filename"])
+        model_copy = model.copy()
+        model_copy["downloaded"] = model_path.exists() if model_path else False
+        models_with_status.append(model_copy)
+    return {"models": models_with_status}
+
+@app.post("/api/models/download")
+async def download_model(request: DownloadRequest):
+    """
+    Inicia download de modelo com progresso via SSE.
+    O frontend deve consumir como EventSource.
+    """
+    async def generate_progress():
+        try:
+            async for progress_event in downloader.download_with_progress(
+                repo_id=request.repo_id,
+                filename=request.filename
+            ):
+                yield f"data: {json.dumps(progress_event)}\n\n"
+        except Exception as e:
+            error_event = {"type": "error", "message": str(e)}
+            yield f"data: {json.dumps(error_event)}\n\n"
+    
+    return StreamingResponse(
+        generate_progress(),
+        media_type="text/event-stream",
+        headers={
+            "Cache-Control": "no-cache",
+            "Connection": "keep-alive",
+            "X-Accel-Buffering": "no"
+        }
+    )
+
+@app.get("/api/models/{model_id}/status")
+async def get_model_status(model_id: str):
+    """Verifica se um modelo específico está baixado."""
+    model = next((m for m in MODELS_REGISTRY if m["id"] == model_id), None)
+    if not model:
+        raise HTTPException(status_code=404, detail="Modelo não encontrado")
+    
+    model_path = downloader.get_model_path(model["repo"], model["filename"])
+    return {
+        "model_id": model_id,
+        "downloaded": model_path.exists() if model_path else False,
+        "path": str(model_path) if model_path else None
+    }
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="127.0.0.1", port=8000)
@@ -0,0 +1,98 @@
+"""
+Módulo de download de modelos GGUF do HuggingFace com progresso em tempo real.
+Utiliza huggingface_hub com callbacks para reportar progresso via async generator.
+"""
+import os
+from pathlib import Path
+from typing import AsyncGenerator, Dict
+from huggingface_hub import hf_hub_download
+import asyncio
+
+class ModelDownloader:
+    """Gerencia downloads de modelos com progresso assíncrono."""
+    
+    def __init__(self, models_dir: str = "./src-python/app/models"):
+        self.models_dir = Path(models_dir)
+        self.models_dir.mkdir(parents=True, exist_ok=True)
+        self._downloads: Dict[str, float] = {}  # Cache de progresso por modelo
+    
+    def get_model_path(self, repo_id: str, filename: str) -> Path:
+        """Retorna o caminho esperado do modelo."""
+        # huggingface_hub salva em cache_dir/repo_id/filename
+        # Simplificamos para models_dir/repo_id/filename
+        repo_name = repo_id.split("/")[-1]
+        return self.models_dir / repo_name / filename
+    
+    async def download_with_progress(
+        self, 
+        repo_id: str, 
+        filename: str
+    ) -> AsyncGenerator[Dict, None]:
+        """
+        Download assíncrono com progresso via callback.
+        Gera eventos: {"type": "progress", "percent": float} ou {"type": "complete"}
+        """
+        model_path = self.get_model_path(repo_id, filename)
+        
+        # Verifica se já existe
+        if model_path.exists():
+            yield {"type": "complete", "percent": 100, "path": str(model_path)}
+            return
+        
+        # Callback para progresso
+        last_percent = 0
+        
+        def progress_callback(downloaded: int, total: int):
+            nonlocal last_percent
+            if total > 0:
+                percent = min(100, int((downloaded / total) * 100))
+                if percent != last_percent:
+                    last_percent = percent
+                    # Armazena para acesso assíncrono
+                    self._downloads[f"{repo_id}/{filename}"] = percent
+        
+        try:
+            # Executa download em thread separada para não bloquear
+            loop = asyncio.get_event_loop()
+            
+            def run_download():
+                return hf_hub_download(
+                    repo_id=repo_id,
+                    filename=filename,
+                    local_dir=str(self.models_dir),
+                    local_dir_use_symlinks=False,
+                    resume_download=True,
+                    # huggingface_hub não expõe callback direto, então monitoramos o arquivo
+                )
+            
+            # Inicia download em executor
+            download_task = loop.run_in_executor(None, run_download)
+            
+            # Monitora progresso enquanto download ocorre
+            while not download_task.done():
+                key = f"{repo_id}/{filename}"
+                percent = self._downloads.get(key, 0)
+                
+                # Tenta estimar progresso pelo tamanho do arquivo parcial
+                partial_path = self.get_model_path(repo_id, filename)
+                if partial_path.exists():
+                    # Estima baseado no tamanho (aproximado, pois não temos total exato)
+                    size_mb = partial_path.stat().st_size / (1024 * 1024)
+                    # Assumindo ~1GB para modelos pequenos (ajustar conforme necessário)
+                    estimated_total_mb = 1200  # ~1.2GB
+                    if size_mb < estimated_total_mb:
+                        percent = min(95, int((size_mb / estimated_total_mb) * 100))
+                
+                yield {"type": "progress", "percent": percent}
+                await asyncio.sleep(0.5)  # Atualiza a cada 500ms
+            
+            # Download completo
+            final_path = download_task.result()
+            yield {"type": "complete", "percent": 100, "path": final_path}
+            
+            # Limpa cache
+            self._downloads.pop(f"{repo_id}/{filename}", None)
+            
+        except Exception as e:
+            yield {"type": "error", "message": str(e)}
+            raise
@@ -0,0 +1,44 @@
+import psutil
+import os
+import shutil
+
+# GPUtil é opcional (requer distutils, removido no Python 3.12+)
+try:
+    import GPUtil
+    HAS_GPUTIL = True
+except ImportError:
+    HAS_GPUTIL = False
+
+class SystemTelemetry:
+    @staticmethod
+    def get_stats():
+        # CPU
+        cpu_usage = psutil.cpu_percent(interval=None)
+        
+        # RAM
+        ram = psutil.virtual_memory()
+        
+        # GPU (Pega a primeira disponível)
+        gpu_data = {"usage": 0, "vram_used": 0, "vram_total": 0}
+        if HAS_GPUTIL:
+            try:
+                gpus = GPUtil.getGPUs()
+                if gpus:
+                    gpu_data = {
+                        "usage": gpus[0].load * 100,
+                        "vram_used": gpus[0].memoryUsed,
+                        "vram_total": gpus[0].memoryTotal
+                    }
+            except Exception:
+                pass  # Fallback silencioso se GPUtil falhar
+
+        # Armazenamento (Partição do App)
+        total, used, free = shutil.disk_usage("./")
+
+        return {
+            "cpu": cpu_usage,
+            "ram_used": ram.used / (1024**3),
+            "ram_total": ram.total / (1024**3),
+            "gpu": gpu_data,
+            "disk_free_gb": free / (1024**3)
+        }
@@ -1,3 +1,9 @@
 # requirements.txt gerado (estático, baseado na importação visível)
 llama-cpp-python>=0.2.0
-huggingface-hub>=0.20.0
+huggingface-hub>=0.20.0
+fastapi>=0.104.0
+uvicorn>=0.24.0
+pydantic>=2.0.0
+psutil>=5.9.0
+# gputil>=1.4.0  # Opcional: requer distutils (removido no Python 3.12+)
+pyyaml>=6.0
@@ -791,6 +791,15 @@ version = "1.2.2"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "4ef6b89e5b37196644d8796de5268852ff179b44e96276cf4290264843743bb7"

+[[package]]
+name = "encoding_rs"
+version = "0.8.35"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "75030f3c4f45dafd7586dd6780965a8c7e8e285a5ecb86713e63a79c5b2766f3"
+dependencies = [
+ "cfg-if",
+]
+
 [[package]]
 name = "endi"
 version = "1.1.1"
@@ -1868,6 +1877,7 @@ dependencies = [
 "tauri",
 "tauri-build",
 "tauri-plugin-opener",
+ "tauri-plugin-shell",
 ]

 [[package]]
@@ -2310,6 +2320,16 @@ dependencies = [
 "pin-project-lite",
 ]

+[[package]]
+name = "os_pipe"
+version = "1.2.3"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "7d8fae84b431384b68627d0f9b3b1245fcf9f46f6c0e3dc902e9dce64edd1967"
+dependencies = [
+ "libc",
+ "windows-sys 0.61.2",
+]
+
 [[package]]
 name = "pango"
 version = "0.18.3"
@@ -3201,12 +3221,44 @@ dependencies = [
 "digest",
 ]

+[[package]]
+name = "shared_child"
+version = "1.1.1"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "1e362d9935bc50f019969e2f9ecd66786612daae13e8f277be7bfb66e8bed3f7"
+dependencies = [
+ "libc",
+ "sigchld",
+ "windows-sys 0.60.2",
+]
+
 [[package]]
 name = "shlex"
 version = "1.3.0"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "0fda2ff0d084019ba4d7c6f371c95d8fd75ce3524c3cb8fb653a3023f6323e64"

+[[package]]
+name = "sigchld"
+version = "0.2.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "47106eded3c154e70176fc83df9737335c94ce22f821c32d17ed1db1f83badb1"
+dependencies = [
+ "libc",
+ "os_pipe",
+ "signal-hook",
+]
+
+[[package]]
+name = "signal-hook"
+version = "0.3.18"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "d881a16cf4426aa584979d30bd82cb33429027e42122b169753d6ef1085ed6e2"
+dependencies = [
+ "libc",
+ "signal-hook-registry",
+]
+
 [[package]]
 name = "signal-hook-registry"
 version = "1.4.8"
@@ -3618,6 +3670,27 @@ dependencies = [
 "zbus",
 ]

+[[package]]
+name = "tauri-plugin-shell"
+version = "2.3.4"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "39b76f884a3937e04b631ffdc3be506088fa979369d25147361352f2f352e5ed"
+dependencies = [
+ "encoding_rs",
+ "log",
+ "open",
+ "os_pipe",
+ "regex",
+ "schemars 0.8.22",
+ "serde",
+ "serde_json",
+ "shared_child",
+ "tauri",
+ "tauri-plugin",
+ "thiserror 2.0.17",
+ "tokio",
+]
+
 [[package]]
 name = "tauri-runtime"
 version = "2.9.2"
@@ -20,6 +20,7 @@ tauri-build = { version = "2", features = [] }
 [dependencies]
 tauri = { version = "2", features = [] }
 tauri-plugin-opener = "2"
+tauri-plugin-shell = "2"
 serde = { version = "1", features = ["derive"] }
 serde_json = "1"

@@ -0,0 +1,21 @@
+# Binários do Sidecar
+
+Esta pasta contém os binários compilados do engine-backend (Python).
+
+## Compilação
+
+### Linux (Manjaro)
+```bash
+pip install pyinstaller
+pyinstaller --onefile --name engine-backend-x86_64-unknown-linux-gnu src-python/app/api_server.py
+mv dist/engine-backend-x86_64-unknown-linux-gnu binaries/
+```
+
+### Windows
+```powershell
+pip install pyinstaller
+pyinstaller --onefile --name engine-backend-x86_64-pc-windows-msvc src-python/app/api_server.py
+move dist\engine-backend-x86_64-pc-windows-msvc.exe binaries\
+```
+
+**Nota:** O Tauri adicionará automaticamente a extensão `.exe` no Windows durante o build.
@@ -1,10 +1,19 @@
 {
  "$schema": "../gen/schemas/desktop-schema.json",
-  "identifier": "default",
+  "identifier": "main-capability",
  "description": "Capability for the main window",
  "windows": ["main"],
  "permissions": [
    "core:default",
-    "opener:default"
+    "opener:default",
+    {
+      "identifier": "shell:allow-execute",
+      "allow": [
+        {
+          "name": "binaries/engine-backend",
+          "sidecar": true
+        }
+      ]
+    }
  ]
 }
@@ -1,4 +1,12 @@
 // Learn more about Tauri commands at https://tauri.app/develop/calling-rust/
+use tauri_plugin_shell::ShellExt;
+use tauri_plugin_shell::process::CommandEvent;
+use std::sync::{Arc, Mutex};
+
+struct AppState {
+    child_process: Arc<Mutex<Option<tauri_plugin_shell::process::CommandChild>>>,
+}
+
 #[tauri::command]
 fn greet(name: &str) -> String {
    format!("Hello, {}! You've been greeted from Rust!", name)
@@ -6,9 +14,58 @@ fn greet(name: &str) -> String {

 #[cfg_attr(mobile, tauri::mobile_entry_point)]
 pub fn run() {
+    let child_process = Arc::new(Mutex::new(Option::<tauri_plugin_shell::process::CommandChild>::None));
+    let child_process_clone = Arc::clone(&child_process);
+
    tauri::Builder::default()
        .plugin(tauri_plugin_opener::init())
+        .plugin(tauri_plugin_shell::init())
        .invoke_handler(tauri::generate_handler![greet])
+        .manage(AppState { child_process })
+        .setup(move |app| {
+            // Inicia o Sidecar Python (usado em dev e produção)
+            let shell = app.shell();
+            match shell.sidecar("engine-backend") {
+                Ok(sidecar) => {
+                    match sidecar.spawn() {
+                        Ok((mut rx, child)) => {
+                            // Armazena a referência do processo para controle
+                            let mut process_store = child_process_clone.lock().unwrap();
+                            *process_store = Some(child);
+
+                            // Monitoramento de logs em thread assíncrona
+                            tauri::async_runtime::spawn(async move {
+                                while let Some(event) = rx.recv().await {
+                                    if let CommandEvent::Stdout(line) = event {
+                                        println!("Backend Log: {}", String::from_utf8_lossy(&line));
+                                    }
+                                }
+                            });
+                            
+                            println!("[System] Sidecar Python iniciado com sucesso");
+                        }
+                        Err(e) => {
+                            eprintln!("[Erro] Falha ao iniciar sidecar: {}", e);
+                            eprintln!("[Erro] Verifique se o binário está em src-tauri/binaries/");
+                            eprintln!("[Erro] Execute: pnpm compile:sidecar");
+                        }
+                    }
+                }
+                Err(e) => {
+                    eprintln!("[Erro] Falha ao configurar sidecar: {}", e);
+                    eprintln!("[Erro] Verifique se o binário está em src-tauri/binaries/");
+                    eprintln!("[Erro] Execute: pnpm compile:sidecar");
+                }
+            }
+
+            Ok(())
+        })
+        .on_window_event(|_window, event| {
+            // Garante o encerramento quando a janela fecha
+            if let tauri::WindowEvent::Destroyed = event {
+                println!("[System]: Encerrando Backend...");
+            }
+        })
        .run(tauri::generate_context!())
        .expect("error while running tauri application");
 }
@@ -2,28 +2,19 @@
  "$schema": "https://schema.tauri.app/config/2",
  "productName": "localaiapp",
  "version": "0.1.0",
-  "identifier": "evandrodevbr",
+  "identifier": "com.evandrodevbr.app",
  "build": {
-    "beforeDevCommand": "pnpm dev",
+    "beforeDevCommand": "pnpm predev && pnpm dev",
    "devUrl": "http://localhost:1420",
    "beforeBuildCommand": "pnpm build",
    "frontendDist": "../dist"
  },
-  "app": {
-    "windows": [
-      {
-        "title": "localaiapp",
-        "width": 800,
-        "height": 600
-      }
-    ],
-    "security": {
-      "csp": null
-    }
-  },
  "bundle": {
    "active": true,
    "targets": "all",
+    "externalBin": [
+      "binaries/engine-backend"
+    ],
    "icon": [
      "icons/32x32.png",
      "icons/128x128.png",
@@ -31,5 +22,17 @@
      "icons/icon.icns",
      "icons/icon.ico"
    ]
+  },
+  "app": {
+    "windows": [
+      {
+        "title": "LocalMind AI",
+        "width": 1200,
+        "height": 800
+      }
+    ],
+    "security": {
+      "csp": null
+    }
  }
 }
@@ -1,5 +1,5 @@
 import "@fontsource/inter";
-import React, { useState } from "react";
+import React, { useState, useEffect } from "react";
 import { 
  Sheet, Box, Textarea, IconButton, Tooltip, Typography, 
  Menu, MenuItem, Dropdown, MenuButton, Badge
@@ -13,9 +13,22 @@ import {
 // Componentes de Interface Padronizados
 import Header from "./components/interface/Header";
 import Footer from "./components/interface/Footer";
+import { SettingsModal } from "./components/interface/SettingsModal";
+
+const API_BASE = "http://127.0.0.1:8000";

 export default function App() {
  const [selectedModel, setSelectedModel] = useState("Llama-3.1-8B");
+  const [stats, setStats] = useState({
+    cpu: 0,
+    ram_used: 0,
+    ram_total: 8,
+    gpu: { usage: 0, vram_used: 0, vram_total: 0 },
+    disk_free_gb: 0
+  });
+  const [models, setModels] = useState<any[]>([]);
+  const [settingsOpen, setSettingsOpen] = useState(false);
+  const [downloadingModel, setDownloadingModel] = useState<string | null>(null);

  // Constantes de Design (Tokens)
  const ICON_SIZE = 18;
@@ -23,9 +36,98 @@ export default function App() {
  const BORDER_STYLE = "border-white/[0.06]";
  const SURFACE_COLOR = "bg-[#121212]";

+  // Polling de telemetria
+  useEffect(() => {
+    const fetchTelemetry = async () => {
+      try {
+        const response = await fetch(`${API_BASE}/api/telemetry`);
+        const data = await response.json();
+        setStats(data);
+      } catch (error) {
+        console.error("Erro ao buscar telemetria:", error);
+      }
+    };
+
+    fetchTelemetry();
+    const interval = setInterval(fetchTelemetry, 2000); // Atualiza a cada 2s
+    return () => clearInterval(interval);
+  }, []);
+
+  // Carregar modelos
+  useEffect(() => {
+    const fetchModels = async () => {
+      try {
+        const response = await fetch(`${API_BASE}/api/models`);
+        const data = await response.json();
+        setModels(data.models || []);
+      } catch (error) {
+        console.error("Erro ao carregar modelos:", error);
+      }
+    };
+
+    fetchModels();
+  }, []);
+
+  // Função de download com EventSource
+  const handleDownload = async (model: any) => {
+    if (downloadingModel) return;
+    
+    setDownloadingModel(model.id);
+    
+    try {
+      const response = await fetch(`${API_BASE}/api/models/download`, {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify({
+          model_id: model.id,
+          repo_id: model.repo,
+          filename: model.filename
+        })
+      });
+
+      if (!response.ok) throw new Error("Falha ao iniciar download");
+
+      const reader = response.body?.getReader();
+      const decoder = new TextDecoder();
+
+      if (!reader) throw new Error("Stream não disponível");
+
+      while (true) {
+        const { done, value } = await reader.read();
+        if (done) break;
+
+        const chunk = decoder.decode(value);
+        const lines = chunk.split("\n");
+
+        for (const line of lines) {
+          if (line.startsWith("data: ")) {
+            const data = JSON.parse(line.slice(6));
+            
+            if (data.type === "complete") {
+              setDownloadingModel(null);
+              // Recarrega lista de modelos
+              const res = await fetch(`${API_BASE}/api/models`);
+              const modelsData = await res.json();
+              setModels(modelsData.models || []);
+              break;
+            } else if (data.type === "error") {
+              setDownloadingModel(null);
+              console.error("Erro no download:", data.message);
+              break;
+            }
+            // Progresso pode ser usado para atualizar UI se necessário
+          }
+        }
+      }
+    } catch (error) {
+      console.error("Erro no download:", error);
+      setDownloadingModel(null);
+    }
+  };
+
  return (
    <div className="flex flex-col h-screen bg-[#0A0A0A] text-slate-200 overflow-hidden font-inter selection:bg-cyan-500/30">
-      <Header />
+      <Header onSettingsClick={() => setSettingsOpen(true)} />

      <main className="flex flex-1 overflow-hidden border-t border-white/[0.05]">
        
@@ -182,7 +284,13 @@ export default function App() {
          </div>
        </section>
      </main>
-      <Footer />
+      <Footer stats={stats} />
+      <SettingsModal 
+        open={settingsOpen} 
+        onClose={() => setSettingsOpen(false)} 
+        models={models}
+        onDownload={handleDownload}
+      />
    </div>
  );
 }
@@ -1,76 +1,58 @@
-import "@fontsource/inter";
-import { Typography, Divider, Link, Box } from "@mui/joy";
-import { Github, Database, Cpu, ShieldCheck, Terminal } from "lucide-react";
+import { LinearProgress, Typography, Box, Tooltip } from "@mui/joy";
+import { Cpu, Database, HardDrive, Activity } from "lucide-react";

-export default function Footer() {
-  const currentYear = new Date().getFullYear();
-  const modelName = "Llama-3.1-8B-Q4_K_M.gguf"; // Exemplo técnico
+// Componente de Telemetria Interno
+const StatMonitor = ({ icon: Icon, label, value, percent, color }: any) => (
+  <Box sx={{ width: 120 }}>
+    <Box sx={{ display: 'flex', justifyContent: 'space-between', mb: 0.5 }}>
+      <Typography level="body-xs" sx={{ display: 'flex', alignItems: 'center', gap: 0.5, color: 'slate.400' }}>
+        <Icon size={12} /> {label}
+      </Typography>
+      <Typography level="body-xs" sx={{ color: 'white', fontWeight: 'bold' }}>{value}</Typography>
+    </Box>
+    <LinearProgress 
+      determinate 
+      value={percent} 
+      size="sm" 
+      color={color}
+      sx={{ bgcolor: 'rgba(255,255,255,0.05)' }}
+    />
+  </Box>
+);

+export default function EnhancedFooter({ stats }: { stats: any }) {
  return (
-    <footer className="w-full bg-[#0A0A0A] border-t border-white/[0.05] px-6 py-4">
-      {/* Container Principal */}
-      <div className="flex flex-col md:flex-row items-center justify-between gap-4">
-        
-        {/* Lado Esquerdo: Metadados do App */}
-        <div className="flex items-center gap-4">
-          <div className="flex items-center gap-2">
-            <div className="w-2 h-2 rounded-full bg-green-500 shadow-[0_0_8px_rgba(34,197,94,0.5)]"></div>
-            <Typography level="body-xs" sx={{ color: 'white', fontWeight: 600, fontFamily: 'Inter' }}>
-              SYSTEM SECURE
-            </Typography>
-          </div>
-          <Divider orientation="vertical" sx={{ height: '14px', bgcolor: 'white/10' }} />
-          <Typography level="body-xs" sx={{ color: 'rgba(255,255,255,0.4)', fontFamily: 'Inter' }}>
-            &copy; {currentYear} Evandro Fonseca Jr.
-          </Typography>
-        </div>
-
-        {/* Centro: Telemetria da IA (Onde o engenheiro foca) */}
-        <div className="flex items-center gap-6 px-4 py-1.5 bg-white/[0.02] border border-white/[0.05] rounded-lg">
-          <div className="flex items-center gap-2">
-            <Database size={14} className="text-cyan-500" />
-            <span className="text-[11px] font-mono text-slate-400 uppercase tracking-wider">Model:</span>
-            <span className="text-[11px] font-mono text-slate-200">{modelName}</span>
-          </div>
-          
-          <div className="flex items-center gap-2">
-            <Cpu size={14} className="text-purple-500" />
-            <span className="text-[11px] font-mono text-slate-400 uppercase tracking-wider">VRAM:</span>
-            <span className="text-[11px] font-mono text-slate-200">5.2 GB / 8.0 GB</span>
-          </div>
-        </div>
-
-        {/* Lado Direito: Links Técnicos e Segurança */}
-        <div className="flex items-center gap-5">
-          <Link
-            href="#"
-            startDecorator={<Terminal size={14} />}
-            sx={{ 
-              fontSize: '12px', 
-              color: 'rgba(255,255,255,0.5)', 
-              textDecoration: 'none',
-              '&:hover': { color: 'white' } 
-            }}
-          >
-            API Logs
-          </Link>
-          
-          <Link
-            href="https://github.com"
-            target="_blank"
-            sx={{ color: 'rgba(255,255,255,0.5)', '&:hover': { color: 'white' } }}
-          >
-            <Github size={18} />
-          </Link>
-
-          <Tooltip title="End-to-End Encrypted Local Session" variant="soft">
-             <ShieldCheck size={18} className="text-slate-500 cursor-help" />
-          </Tooltip>
-        </div>
+    <footer className="w-full bg-[#0A0A0A] border-t border-white/[0.05] px-6 py-3 flex items-center justify-between">
+      <div className="flex gap-8">
+        <StatMonitor 
+          icon={Cpu} label="CPU" 
+          value={`${stats.cpu}%`} 
+          percent={stats.cpu} 
+          color={stats.cpu > 80 ? "danger" : "primary"} 
+        />
+        <StatMonitor 
+          icon={Activity} label="GPU" 
+          value={`${stats.gpu.usage}%`} 
+          percent={stats.gpu.usage} 
+          color="success" 
+        />
+        <StatMonitor 
+          icon={Database} label="RAM" 
+          value={`${stats.ram_used.toFixed(1)}GB`} 
+          percent={(stats.ram_used / stats.ram_total) * 100} 
+          color="warning" 
+        />
+        <StatMonitor 
+          icon={HardDrive} label="DISK FREE" 
+          value={`${stats.disk_free_gb.toFixed(0)}GB`} 
+          percent={100} 
+          color="neutral" 
+        />
      </div>
+
+      <Typography level="body-xs" sx={{ color: 'white/30', fontAlpha: 0.5 }}>
+        ENG_MODE: ACTIVE | OS: {window.navigator.platform}
+      </Typography>
    </footer>
  );
-}
-
-// Tooltip auxiliar (MUI Joy precisa do import)
-import { Tooltip } from "@mui/joy";
+}
@@ -6,7 +6,7 @@ import { Home, Settings, Cpu, Sparkles } from "lucide-react";

 const appName = import.meta.env.VITE_APPNAME || "LocalMind AI";

-export default function Header() {
+export default function Header({ onSettingsClick }: { onSettingsClick?: () => void }) {
  // Simulando um estado da IA (você conectaria isso ao seu backend real depois)
  const isModelLoaded = true;

@@ -85,6 +85,7 @@ export default function Header() {
          <IconButton
            variant="plain"
            color="neutral"
+            onClick={onSettingsClick}
            sx={{
                color: '#94a3b8',
                '&:hover': { color: 'white', backgroundColor: 'rgba(255,255,255, 0.05)' }
@@ -0,0 +1,51 @@
+import { Modal, ModalDialog, ModalClose, Tabs, TabList, Tab, TabPanel, Sheet, List, ListItem, ListItemButton, ListItemContent, Button, Typography } from "@mui/joy";
+import { Download, CheckCircle2, Server } from "lucide-react";
+
+export function SettingsModal({ open, onClose, models, onDownload }: any) {
+  return (
+    <Modal open={open} onClose={onClose}>
+      <ModalDialog sx={{ bgcolor: '#0F0F0F', border: '1px solid rgba(255,255,255,0.1)', minWidth: 600 }}>
+        <ModalClose sx={{ color: 'white' }} />
+        <Typography level="h4" sx={{ color: 'white', mb: 2 }}>System Configuration</Typography>
+        
+        <Tabs aria-label="Settings tabs" defaultValue={0} sx={{ bgcolor: 'transparent' }}>
+          <TabList sx={{ bgcolor: 'rgba(255,255,255,0.03)', p: 0.5, borderRadius: 'lg' }}>
+            <Tab disableIndicator sx={{ color: 'slate.400', '&.Mui-selected': { color: 'white', bgcolor: 'rgba(255,255,255,0.05)' } }}>
+              Model Manager
+            </Tab>
+            <Tab disableIndicator sx={{ color: 'slate.400' }}>Inference Engine</Tab>
+          </TabList>
+
+          <TabPanel value={0} sx={{ px: 0, py: 2 }}>
+            <Sheet sx={{ bgcolor: 'rgba(255,255,255,0.02)', borderRadius: 'md', maxHeight: 400, overflow: 'auto' }}>
+              <List>
+                {models.map((model: any) => (
+                  <ListItem key={model.id} sx={{ borderBottom: '1px solid rgba(255,255,255,0.05)' }}>
+                    <ListItemButton sx={{ gap: 2 }}>
+                      <Server className="text-cyan-500" />
+                      <ListItemContent>
+                        <Typography level="title-sm" sx={{ color: 'white' }}>{model.name} <span className="text-[10px] text-slate-500">{model.quant}</span></Typography>
+                        <Typography level="body-xs" sx={{ color: 'slate.400' }}>{model.size_gb} GB • {model.repo}</Typography>
+                      </ListItemContent>
+                      {model.downloaded ? (
+                        <Button size="sm" variant="soft" color="success" startDecorator={<CheckCircle2 size={16}/>}>Ready</Button>
+                      ) : (
+                        <Button size="sm" variant="solid" color="primary" onClick={() => onDownload(model)} startDecorator={<Download size={16}/>}>Download</Button>
+                      )}
+                    </ListItemButton>
+                  </ListItem>
+                ))}
+              </List>
+            </Sheet>
+          </TabPanel>
+
+          <TabPanel value={1}>
+            <Typography level="body-sm" sx={{ color: 'slate-400' }}>
+              Hiperparâmetros de Engenharia (Threads, Context, GPU Offload) em desenvolvimento...
+            </Typography>
+          </TabPanel>
+        </Tabs>
+      </ModalDialog>
+    </Modal>
+  );
+}