Move ai-stack and paintplus vendored source under vendor/

Matches the existing vendor/easy-asterisk convention (used by
services/asterisk.sh) instead of two one-off top-level directories that
cluttered the repo root and didn't look like anything else next to
setup.sh, lib/, services/, extras/. Only the two services' own SRC_DIR
path resolution and header comments needed updating — nothing else in
the repo referenced the old ./ai-stack / ./paintplus paths.

Also documents vendor/ in README.md's Layout section.

vendor/paintplus/backend/app/services/local_inpaint.py

@@ -0,0 +1,82 @@
+"""
+Local inpainting operations — LaMa, OpenCV, and background removal.
+All operations use GPU automatically if PyTorch detects one, CPU otherwise.
+"""
+
+from io import BytesIO
+from PIL import Image
+import numpy as np
+import cv2
+
+# Lazy-loaded LaMa model (downloaded on first use, ~100MB)
+_lama = None
+
+
+def get_lama():
+    global _lama
+    if _lama is None:
+        from simple_lama_inpainting import SimpleLama
+        _lama = SimpleLama()
+    return _lama
+
+
+def lama_available() -> bool:
+    try:
+        import simple_lama_inpainting  # noqa: F401
+        return True
+    except ImportError:
+        return False
+
+
+def lama_inpaint(image_bytes: bytes, mask_bytes: bytes) -> bytes:
+    """LaMa structural inpainting — best for object removal and large fills."""
+    lama = get_lama()
+    image = Image.open(BytesIO(image_bytes)).convert("RGB")
+    mask = Image.open(BytesIO(mask_bytes)).convert("L")
+    if mask.size != image.size:
+        mask = mask.resize(image.size, Image.Resampling.LANCZOS)
+    result = lama(image, mask)
+    buf = BytesIO()
+    result.save(buf, format="PNG")
+    return buf.getvalue()
+
+
+def opencv_inpaint(image_bytes: bytes, mask_bytes: bytes, method: str = "telea") -> bytes:
+    """OpenCV fast structural inpainting — CPU only, milliseconds."""
+    image = Image.open(BytesIO(image_bytes)).convert("RGB")
+    mask = Image.open(BytesIO(mask_bytes)).convert("L")
+    if mask.size != image.size:
+        mask = mask.resize(image.size, Image.Resampling.LANCZOS)
+
+    img_np = np.array(image)
+    mask_np = np.array(mask)
+    _, mask_bin = cv2.threshold(mask_np, 127, 255, cv2.THRESH_BINARY)
+
+    flags = cv2.INPAINT_TELEA if method == "telea" else cv2.INPAINT_NS
+    result = cv2.inpaint(img_np, mask_bin, inpaintRadius=3, flags=flags)
+
+    buf = BytesIO()
+    Image.fromarray(result).save(buf, format="PNG")
+    return buf.getvalue()
+
+
+def remove_background_rembg(image_bytes: bytes) -> bytes:
+    """Background removal using rembg."""
+    from rembg import remove
+    return remove(image_bytes)
+
+
+def rembg_available() -> bool:
+    try:
+        import rembg  # noqa: F401
+        return True
+    except ImportError:
+        return False
+
+
+def gpu_available() -> bool:
+    try:
+        import torch
+        return torch.cuda.is_available()
+    except ImportError:
+        return False