feat: shared hardware environment layer (env_config.py) for multi-backend inference

New shared library at skills/lib/env_config.py:
- HardwareEnv.detect(): auto-detect CUDA, ROCm, MPS, Intel, CPU
- export_model(): auto-export to TensorRT/ONNX/CoreML/OpenVINO
- load_optimized(): load cached model with PyTorch fallback

detect.py: replaced inline CoreML logic with HardwareEnv (2 lines)
deploy.sh: uses env_config for hardware detection + generalized pre-conversion
New: requirements_intel.txt (OpenVINO)
Updated: requirements_cuda (tensorrt), rocm (onnxruntime-rocm), cpu (onnxruntime)

Author: solderzzc

skills/detection/yolo-detection-2026/deploy.sh

@@ -4,6 +4,8 @@
 # Probes the system for Python, GPU backends, and installs the minimum
 # viable stack. Called by Aegis skill-runtime-manager during installation.
 #
+# Uses skills/lib/env_config.py for hardware detection and model optimization.
+#
 # Exit codes:
 #   0  = success
 #   1  = fatal error (no Python found and cannot install)
@@ -13,6 +15,7 @@ set -euo pipefail
 
 SKILL_DIR="$(cd "$(dirname "$0")" && pwd)"
 VENV_DIR="$SKILL_DIR/.venv"
+LIB_DIR="$(cd "$SKILL_DIR/../../lib" 2>/dev/null && pwd || echo "")"
 LOG_PREFIX="[YOLO-2026-deploy]"
 
 log()  { echo "$LOG_PREFIX $*" >&2; }
@@ -21,7 +24,6 @@ emit() { echo "$1"; }  # JSON to stdout for Aegis to parse
 # ─── Step 1: Find or install Python ─────────────────────────────────────────
 
 find_python() {
-    # Check common Python 3 locations
     for cmd in python3.12 python3.11 python3.10 python3.9 python3; do
         if command -v "$cmd" &>/dev/null; then
             local ver
@@ -36,7 +38,6 @@ find_python() {
         fi
     done
 
-    # Check conda
     if command -v conda &>/dev/null; then
         log "No system Python >=3.9 found, but conda is available"
         log "Creating conda environment..."
@@ -48,7 +49,6 @@ find_python() {
         return 0
     fi
 
-    # Check pyenv
     if command -v pyenv &>/dev/null; then
         log "No system Python >=3.9 found, using pyenv..."
         pyenv install -s 3.11.9
@@ -76,55 +76,60 @@ if [ ! -d "$VENV_DIR" ]; then
     "$PYTHON_CMD" -m venv "$VENV_DIR"
 fi
 
-# Activate venv
 # shellcheck disable=SC1091
 source "$VENV_DIR/bin/activate"
 PIP="$VENV_DIR/bin/pip"
 
-# Upgrade pip
 "$PIP" install --upgrade pip -q 2>/dev/null || true
 
 emit '{"event": "progress", "stage": "venv", "message": "Virtual environment ready"}'
 
-# ─── Step 3: Detect compute backend ─────────────────────────────────────────
+# ─── Step 3: Detect hardware via env_config ─────────────────────────────────
 
 BACKEND="cpu"
 
-detect_gpu() {
-    # NVIDIA CUDA
+if [ -n "$LIB_DIR" ] && [ -f "$LIB_DIR/env_config.py" ]; then
+    log "Detecting hardware via env_config.py..."
+    DETECT_OUTPUT=$("$VENV_DIR/bin/python" -c "
+import sys
+sys.path.insert(0, '$LIB_DIR')
+from env_config import HardwareEnv
+env = HardwareEnv.detect()
+print(env.backend)
+" 2>&1) || true
+
+    # The last line of output is the backend name
+    BACKEND=$(echo "$DETECT_OUTPUT" | tail -1)
+
+    # Validate backend value
+    case "$BACKEND" in
+        cuda|rocm|mps|intel|cpu) ;;
+        *)
+            log "env_config returned unexpected backend '$BACKEND', falling back to heuristic"
+            BACKEND="cpu"
+            ;;
+    esac
+
+    log "env_config detected backend: $BACKEND"
+else
+    log "env_config.py not found, using heuristic detection..."
+
+    # Fallback: inline GPU detection (same as before)
     if command -v nvidia-smi &>/dev/null; then
-        local cuda_ver
         cuda_ver=$(nvidia-smi --query-gpu=driver_version --format=csv,noheader 2>/dev/null | head -1)
         if [ -n "$cuda_ver" ]; then
             BACKEND="cuda"
             log "Detected NVIDIA GPU (driver: $cuda_ver)"
-            return 0
         fi
-    fi
-
-    # AMD ROCm
-    if command -v rocm-smi &>/dev/null || [ -d "/opt/rocm" ]; then
+    elif command -v rocm-smi &>/dev/null || [ -d "/opt/rocm" ]; then
         BACKEND="rocm"
         log "Detected AMD ROCm"
-        return 0
-    fi
-
-    # Apple Silicon MPS
-    if [ "$(uname)" = "Darwin" ]; then
-        local arch
-        arch=$(uname -m)
-        if [ "$arch" = "arm64" ]; then
-            BACKEND="mps"
-            log "Detected Apple Silicon (MPS)"
-            return 0
-        fi
+    elif [ "$(uname)" = "Darwin" ] && [ "$(uname -m)" = "arm64" ]; then
+        BACKEND="mps"
+        log "Detected Apple Silicon (MPS)"
     fi
+fi
 
-    log "No GPU detected, using CPU backend"
-    return 0
-}
-
-detect_gpu
 emit "{\"event\": \"progress\", \"stage\": \"gpu\", \"backend\": \"$BACKEND\", \"message\": \"Compute backend: $BACKEND\"}"
 
 # ─── Step 4: Install requirements ────────────────────────────────────────────
@@ -142,39 +147,50 @@ emit "{\"event\": \"progress\", \"stage\": \"install\", \"message\": \"Installin
 
 "$PIP" install -r "$REQ_FILE" -q 2>&1 | tail -5 >&2
 
-# ─── Step 5: CoreML pre-conversion (MPS only) ───────────────────────────────
+# ─── Step 5: Pre-convert model to optimized format ───────────────────────────
 
-if [ "$BACKEND" = "mps" ]; then
-    log "Pre-converting default model to CoreML for ANE acceleration..."
-    emit '{"event": "progress", "stage": "coreml", "message": "Converting model to CoreML (~30s)..."}'
+if [ "$BACKEND" != "cpu" ] || [ -f "$SKILL_DIR/requirements_cpu.txt" ]; then
+    log "Pre-converting model to optimized format for $BACKEND..."
+    emit "{\"event\": \"progress\", \"stage\": \"optimize\", \"message\": \"Converting model for $BACKEND (~30-120s)...\"}"
 
     "$VENV_DIR/bin/python" -c "
-from ultralytics import YOLO
-model = YOLO('yolo26n.pt')
-exported = model.export(format='coreml', half=True, nms=False)
-print(f'CoreML model exported: {exported}')
+import sys
+sys.path.insert(0, '$LIB_DIR')
+from env_config import HardwareEnv
+env = HardwareEnv.detect()
+
+if env.framework_ok:
+    from ultralytics import YOLO
+    model = YOLO('yolo26n.pt')
+    result = env.export_model(model, 'yolo26n')
+    if result:
+        print(f'Optimized model exported: {result}')
+    else:
+        print('Export skipped or failed — will use PyTorch at runtime')
+else:
+    print(f'Optimized runtime not available for {env.backend} — will use PyTorch')
 " 2>&1 | while read -r line; do log "$line"; done
 
     if [ $? -eq 0 ]; then
-        emit '{"event": "progress", "stage": "coreml", "message": "CoreML conversion complete"}'
+        emit "{\"event\": \"progress\", \"stage\": \"optimize\", \"message\": \"Model optimization complete\"}"
     else
-        log "WARNING: CoreML conversion failed, will use PyTorch MPS at runtime"
-        emit '{"event": "progress", "stage": "coreml", "message": "CoreML conversion failed — PyTorch MPS fallback"}'
+        log "WARNING: Model optimization failed, will use PyTorch at runtime"
+        emit "{\"event\": \"progress\", \"stage\": \"optimize\", \"message\": \"Optimization failed — PyTorch fallback\"}"
     fi
 fi
 
 # ─── Step 6: Verify installation ────────────────────────────────────────────
 
 log "Verifying installation..."
 "$VENV_DIR/bin/python" -c "
-from ultralytics import YOLO
-import torch
-device = 'cpu'
-if torch.cuda.is_available(): device = 'cuda'
-elif hasattr(torch.backends, 'mps') and torch.backends.mps.is_available(): device = 'mps'
-print(f'OK: ultralytics loaded, torch device={device}')
+import sys
+sys.path.insert(0, '$LIB_DIR')
+from env_config import HardwareEnv
+import json
+
+env = HardwareEnv.detect()
+print(json.dumps(env.to_dict(), indent=2))
 " 2>&1 | while read -r line; do log "$line"; done
 
 emit "{\"event\": \"complete\", \"backend\": \"$BACKEND\", \"message\": \"YOLO 2026 skill installed ($BACKEND backend)\"}"
 log "Done! Backend: $BACKEND"
-

skills/detection/yolo-detection-2026/requirements_cpu.txt

@@ -4,6 +4,8 @@
 torch>=2.4.0
 torchvision>=0.19.0
 ultralytics>=8.3.0
+onnxruntime>=1.18
 numpy>=1.24.0
 opencv-python-headless>=4.8.0
 Pillow>=10.0.0
+

skills/detection/yolo-detection-2026/requirements_cuda.txt

@@ -4,6 +4,8 @@
 torch>=2.4.0
 torchvision>=0.19.0
 ultralytics>=8.3.0
+tensorrt>=10.0
 numpy>=1.24.0
 opencv-python-headless>=4.8.0
 Pillow>=10.0.0
+

skills/detection/yolo-detection-2026/requirements_intel.txt

@@ -0,0 +1,9 @@
+# YOLO 2026 — Intel (OpenVINO) requirements
+# Supports Intel CPUs, iGPUs, and NPUs (Meteor Lake+)
+torch>=2.4.0
+torchvision>=0.19.0
+ultralytics>=8.3.0
+openvino>=2024.0
+numpy>=1.24.0
+opencv-python-headless>=4.8.0
+Pillow>=10.0.0

skills/detection/yolo-detection-2026/requirements_rocm.txt

@@ -4,6 +4,8 @@
 torch>=2.4.0
 torchvision>=0.19.0
 ultralytics>=8.3.0
+onnxruntime-rocm>=1.18
 numpy>=1.24.0
 opencv-python-headless>=4.8.0
 Pillow>=10.0.0
+