Add Intel XPU support to installer and qualification profiles

.github/workflows/desktop.yaml

@@ -59,6 +59,10 @@ jobs:
           if (-not $wheel) { throw "Hivemind wheel build produced no artifact" }
           python -m pip install $wheel.FullName
       - name: Install qualified Windows CUDA runtime
+        # Hosted CI runners have no Intel GPU, so CI always bundles the CUDA
+        # build. Local XPU bundles install torch==2.6.0+xpu instead (see
+        # scripts/install.ps1 and scripts/install.sh with DRIFT_DEVICE=xpu);
+        # the verify steps below accept either qualified build.
         if: runner.os == 'Windows'
         run: >-
           python -m pip install
@@ -68,16 +72,16 @@ jobs:
         run: |
           python -m pip install -e "..[api]"
           python -m pip install -e ".[dev]"
-      - name: Verify qualified Windows CUDA runtime
+      - name: Verify qualified Windows GPU runtime
         if: runner.os == 'Windows'
-        run: python -c "import torch; assert torch.__version__ == '2.6.0+cu124'"
+        run: python -c "import torch; assert torch.__version__ in ('2.6.0+cu124', '2.6.0+xpu'), torch.__version__"
       - name: Run protocol and runtime-boundary tests
         working-directory: .
         run: |
           python -m unittest discover -s desktop/tests -v
           communityai-desktop --self-test
-      - name: Reverify qualified CUDA runtime before bundling
-        run: python -c "import torch; assert torch.__version__ == '2.6.0+cu124'"
+      - name: Reverify qualified GPU runtime before bundling
+        run: python -c "import torch; assert torch.__version__ in ('2.6.0+cu124', '2.6.0+xpu'), torch.__version__"
       - name: Build and smoke unsigned public-alpha bundle
         run: >-
           python build_desktop.py

.github/workflows/qualify-model-matrix.yaml

@@ -38,6 +38,11 @@ jobs:
         id: scope
         shell: bash
         run: |
+          # NOTE: "windows-xpu" and "linux-xpu" are registered in
+          # scripts/run_external_model_qualification.py but intentionally not
+          # scheduled here yet: no self-hosted XPU runner is provisioned, and
+          # scheduling a profile with no matching runner would queue forever.
+          # Add them to the public-alpha list once an XPU runner exists.
           if [[ "${{ inputs.qualification_scope }}" == "public-alpha" ]]; then
             echo 'profiles=["windows-cpu","windows-cuda","linux-cpu","linux-cuda"]' >> "$GITHUB_OUTPUT"
           else

README.md

@@ -48,7 +48,7 @@ alpha; the lowest supported hardware configuration has not been certified.
 | --- | --- |
 | **CPU** | 64-bit Intel or AMD (x86-64). Four cores recommended. |
 | **RAM** | 8 GB as a starting point; 16 GB recommended. Sharing needs extra memory for the model parts you contribute. |
-| **GPU** | Optional. NVIDIA CUDA is supported for acceleration and sharing; an RTX 2070 SUPER with 8 GB VRAM has been tested. AMD and Intel GPU acceleration is not included. |
+| **GPU** | Optional. NVIDIA CUDA and Intel XPU are supported for acceleration and sharing; an RTX 2070 SUPER with 8 GB VRAM has been tested. AMD GPU acceleration is not included. |
 | **Disk space** | Start with 20 GB free, preferably on an SSD. The app uses about 4.3 GB on Windows or 5.2 GB on Linux; the small local model adds about 1.8 GB. Sharing requires additional space. |
 | **Operating system** | 64-bit Windows 10 (1809+)/11, Ubuntu 22.04+ or Debian 12+ with a desktop environment. |
 | **Internet** | Required for community inference and initial downloads. The small local model works offline after downloading. |
@@ -72,7 +72,9 @@ updates in the sidebar, then choose **Restart to update** when the download fini
 The online installer downloads and verifies the full package during setup.
 
 For NVIDIA use, install a CUDA 12.4-compatible driver (551.61+ on Windows,
-550.54.14+ on Linux). Python, PyTorch and the CUDA runtime are included.
+550.54.14+ on Linux). For Intel use, install a recent Intel GPU driver with
+XPU/oneAPI support and select the XPU runtime (`DRIFT_DEVICE=xpu`, see the
+installation guide). Python, PyTorch and the matching GPU runtime are included.
 See the [installation guide](https://github.com/flujo-app/CommunityAI/blob/codex/gate14-20260902-b/docs/ALPHA_INSTALL.md)
 for setup, updates and the current alpha limitations.
 

desktop/build_desktop.py

@@ -34,6 +34,11 @@
     "Linux": ("communityai-desktop-linux.tar.gz", "tar.gz"),
     "Windows": ("communityai-desktop-windows.zip", "zip"),
 }
+QUALIFIED_TORCH_BUILDS = (
+    # Qualified node runtimes: NVIDIA CUDA 12.4 and Intel XPU.
+    "2.6.0+cu124",
+    "2.6.0+xpu",
+)
 UNSIGNED_ALPHA_WARNING = (
     "Unsigned public-alpha engineering bundle: verify SHA256SUMS before use. "
     "No publisher signature or authenticated automatic update is provided."
@@ -1059,8 +1064,11 @@ def _verify_desktop_metrics(
     for field in ("drift", "torch", "transformers", "hivemind", "fastapi", "uvicorn", "keyring"):
         if not _is_printable_string(node_runtime.get(field)):
             raise RuntimeError(f"node runtime metric {field} is missing or unsafe")
-    if node_runtime["torch"] != "2.6.0+cu124":
-        raise RuntimeError("node runtime is not the qualified CUDA PyTorch build")
+    if node_runtime["torch"] not in QUALIFIED_TORCH_BUILDS:
+        raise RuntimeError(
+            "node runtime is not a qualified PyTorch build "
+            f"(expected one of {', '.join(QUALIFIED_TORCH_BUILDS)})"
+        )
 
     expected_worker_runtime = {
         "schema_version": 1,

scripts/run_external_model_qualification.py

@@ -56,8 +56,10 @@ class HostProfile:
 HOST_PROFILES: Mapping[str, HostProfile] = {
     "windows-cpu": HostProfile(system="windows", device="cpu"),
     "windows-cuda": HostProfile(system="windows", device="cuda"),
+    "windows-xpu": HostProfile(system="windows", device="xpu"),
     "linux-cpu": HostProfile(system="linux", device="cpu"),
     "linux-cuda": HostProfile(system="linux", device="cuda"),
+    "linux-xpu": HostProfile(system="linux", device="xpu"),
     "macos-cpu": HostProfile(system="macos", device="cpu"),
     "macos-mps": HostProfile(system="macos", device="mps"),
 }
@@ -142,6 +144,10 @@ def require_device(profile: HostProfile) -> None:
 
     if profile.device == "cuda" and not torch.cuda.is_available():
         raise ExternalQualificationError("the CUDA-labelled runner has no available CUDA device")
+    if profile.device == "xpu":
+        xpu = getattr(torch, "xpu", None)
+        if xpu is None or not xpu.is_available():
+            raise ExternalQualificationError("the XPU-labelled runner has no available Intel XPU device")
     if profile.device == "mps":
         mps = getattr(torch.backends, "mps", None)
         if mps is None or not mps.is_available():