one liner

Update selfdrived.py
2026-08-27 00:43:47 +08:00 · 2026-08-24 01:37:10 -04:00 · 2026-08-24 01:30:43 -04:00 · 2026-08-24 01:30:43 -04:00 · 2026-08-24 01:30:43 -04:00
35 changed files with 354 additions and 1772 deletions
@@ -0,0 +1,83 @@
+name: Build default big model
+
+on:
+  workflow_dispatch:
+
+env:
+  HF_REPO: sunnypilot/sunnypilot_models_v1
+  HF_DEFAULTS_PATH: models/defaults/big
+
+jobs:
+  resolve_name:
+    runs-on: ubuntu-24.04
+    outputs:
+      model_name: ${{ steps.name.outputs.model_name }}
+      onnx_ref: ${{ steps.name.outputs.onnx_ref }}
+    steps:
+      - uses: actions/checkout@v4
+      - id: name
+        run: |
+          NAME=$(PYTHONPATH=${{ github.workspace }} python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
+          ONNX_REF=$(git log -1 --format='%H' -- openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx)
+          echo "model_name=${NAME}" >> $GITHUB_OUTPUT
+          echo "onnx_ref=$ONNX_REF" >> $GITHUB_OUTPUT
+
+  build_model:
+    needs: resolve_name
+    uses: ./.github/workflows/sunnypilot-build-model.yaml
+    with:
+      upstream_branch: ${{ needs.resolve_name.outputs.onnx_ref }}
+      custom_name: ${{ needs.resolve_name.outputs.model_name }}
+      target_hardware: usbgpu
+    secrets: inherit
+
+  upload_defaults:
+    needs: [ resolve_name, build_model ]
+    runs-on: ubuntu-24.04
+    permissions:
+      id-token: write
+      contents: write
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          submodules: recursive
+      - run: git lfs pull -I "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
+
+      - name: Install huggingface_hub
+        run: pip install --upgrade "huggingface_hub>=0.22.0"
+
+      - name: Download artifact name
+        uses: actions/download-artifact@v4
+        with:
+          name: artifact-name-${{ needs.resolve_name.outputs.model_name }}
+          path: artifact_name
+
+      - name: Read artifact name
+        id: artifact
+        run: |
+          ARTIFACT_NAME=$(cat artifact_name/artifact_name.txt)
+          echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
+
+      - name: Download model artifact
+        uses: actions/download-artifact@v4
+        with:
+          name: ${{ steps.artifact.outputs.artifact_name }}
+          path: output
+
+      - name: Upload to HF and update default_models.json
+        env:
+          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
+          ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
+        run: |
+          rm -f output/artifact_name.txt
+          export PYTHONPATH=$(pwd)
+          python3 release/ci/upload_default_model.py \
+            --hf-repo "${{ env.HF_REPO }}" \
+            --hf-defaults-path "${{ env.HF_DEFAULTS_PATH }}" \
+            --artifact-name "$ARTIFACT_NAME" \
+            --model-dir output \
+            --onnx-path "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" \
+            --onnx-ref "${{ needs.resolve_name.outputs.onnx_ref }}" \
+            --model-name "${{ needs.resolve_name.outputs.model_name }}" \
+            --tinygrad-ref "$(python3 openpilot/sunnypilot/models/tinygrad_ref.py)" \
+            --run-number "${{ github.run_number }}"
@@ -1,501 +0,0 @@
-name: Build default models
-
-on:
-  workflow_dispatch:
-    inputs:
-      target:
-        description: 'Model target to build'
-        required: true
-        type: choice
-        options:
-          - small
-          - big
-          - dm
-  workflow_call:
-    inputs:
-      target:
-        description: 'Model target to build (small, big, or dm)'
-        required: true
-        type: string
-
-concurrency:
-  group: build-default-models-${{ inputs.target }}
-  cancel-in-progress: false
-
-env:
-  HF_REPO: sunnypilot/sunnypilot_models_v1
-
-jobs:
-  resolve:
-    runs-on: ubuntu-24.04
-    outputs:
-      model_name: ${{ steps.resolve.outputs.model_name }}
-      onnx_ref: ${{ steps.resolve.outputs.onnx_ref }}
-      onnx_path: ${{ steps.resolve.outputs.onnx_path }}
-      hf_defaults_path: ${{ steps.resolve.outputs.hf_defaults_path }}
-      tinygrad_ref: ${{ steps.resolve.outputs.tinygrad_ref }}
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: recursive
-
-      - id: resolve
-        run: |
-          export PYTHONPATH=${{ github.workspace }}
-
-          if [ "${{ inputs.target }}" = "big" ]; then
-            NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_BIG_MODEL; print(DEFAULT_BIG_MODEL)")
-            ONNX_PATH="openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
-            HF_DEFAULTS_PATH="models/defaults/big"
-          elif [ "${{ inputs.target }}" = "dm" ]; then
-            ONNX_PATH="openpilot/selfdrive/modeld/models/dmonitoring_model.onnx"
-            HF_DEFAULTS_PATH="models/defaults/dm"
-            NAME="dmonitoring_model ($(git log -1 --format=%cd --date=format:'%B %d, %Y' -- "$ONNX_PATH"))"
-          else
-            NAME=$(python3 -c "from openpilot.sunnypilot.models.model_name import DEFAULT_MODEL; print(DEFAULT_MODEL)")
-            ONNX_PATH="openpilot/selfdrive/modeld/models/driving_supercombo.onnx"
-            HF_DEFAULTS_PATH="models/defaults/small"
-          fi
-
-          ONNX_REF=$(git log -1 --format='%H' -- "$ONNX_PATH")
-          TINYGRAD_REF=$(python3 openpilot/sunnypilot/models/tinygrad_ref.py)
-          if [ -z "$TINYGRAD_REF" ]; then
-            echo "::error::Failed to resolve tinygrad ref"
-            exit 1
-          fi
-
-          echo "model_name=${NAME}" >> $GITHUB_OUTPUT
-          echo "onnx_ref=${ONNX_REF}" >> $GITHUB_OUTPUT
-          echo "onnx_path=${ONNX_PATH}" >> $GITHUB_OUTPUT
-          echo "hf_defaults_path=${HF_DEFAULTS_PATH}" >> $GITHUB_OUTPUT
-          echo "tinygrad_ref=${TINYGRAD_REF}" >> $GITHUB_OUTPUT
-
-  build_small_model:
-    needs: resolve
-    if: ${{ inputs.target == 'small' }}
-    runs-on: [self-hosted, tici]
-    env:
-      SMALL_ONNX: openpilot/selfdrive/modeld/models/driving_supercombo.onnx
-      SMALL_PKL: openpilot/selfdrive/modeld/models/driving_tinygrad.pkl
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: recursive
-
-      - name: Pull ONNX via LFS
-        run: git lfs pull -I "${{ env.SMALL_ONNX }}"
-
-      - name: Set environment variables
-        run: |
-          source /etc/profile
-          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
-          export UV_PYTHON_PREFERENCE=managed
-          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
-          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
-          uv sync --frozen
-          printenv >> $GITHUB_ENV
-
-      - name: Disable powersave
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
-
-      - name: Compile small model with stock compiler
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
-
-          MODEL_SIZE=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
-          CAMERA_RES=$(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')")
-          FRAME_SKIP=$(python3 -c "from openpilot.selfdrive.modeld.constants import ModelConstants as MC; print(MC.MODEL_RUN_FREQ // MC.MODEL_CONTEXT_FREQ)")
-
-          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
-
-          env ${TG_FLAGS} python3 \
-            ${{ github.workspace }}/openpilot/selfdrive/modeld/compile_modeld.py \
-            --onnx ${{ github.workspace }}/${{ env.SMALL_ONNX }} \
-            --model-size $MODEL_SIZE \
-            --camera-resolutions $CAMERA_RES \
-            --frame-skip $FRAME_SKIP \
-            --output ${{ github.workspace }}/${{ env.SMALL_PKL }}
-
-      - name: Chunk small pkl
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH=${{ github.workspace }}
-          python3 -c "
-          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
-          import os
-          pkl = '${{ github.workspace }}/${{ env.SMALL_PKL }}'
-          size = os.path.getsize(pkl)
-          targets = get_chunk_targets(pkl, size)
-          chunk_file(pkl, targets)
-          print(f'Chunked into {len(targets)} files')
-          "
-
-      - name: Prepare output
-        env:
-          MODEL_NAME: ${{ needs.resolve.outputs.model_name }}
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH=${{ github.workspace }}
-          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
-          OUTPUT_DIR="${{ github.workspace }}/small_output"
-          PKL_BASE="driving_tinygrad.pkl"
-          mkdir -p "$OUTPUT_DIR"
-
-          cp "$MODELS_DIR/${PKL_BASE}".chunk* "$OUTPUT_DIR/"
-          cp "$MODELS_DIR/${PKL_BASE}.chunkmanifest" "$OUTPUT_DIR/"
-
-          python3 "${{ github.workspace }}/release/ci/model_generator.py" \
-            --model-dir "$MODELS_DIR" \
-            --output-dir "$OUTPUT_DIR" \
-            --custom-name "$MODEL_NAME" \
-            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}"
-
-          echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
-
-      - name: Upload small model artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: model-${{ needs.resolve.outputs.model_name }}-${{ github.run_number }}
-          path: ${{ github.workspace }}/small_output/
-
-      - name: Upload artifact name file
-        uses: actions/upload-artifact@v4
-        with:
-          name: artifact-name-${{ needs.resolve.outputs.model_name }}
-          path: ${{ github.workspace }}/small_output/artifact_name.txt
-
-      - name: Re-enable powersave
-        if: always()
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
-
-  build_big_model:
-    needs: resolve
-    if: ${{ inputs.target == 'big' }}
-    runs-on: [self-hosted, usbgpu]
-    env:
-      BIG_ONNX: openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx
-      BIG_PKL: openpilot/selfdrive/modeld/models/big_driving_tinygrad.pkl
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: recursive
-
-      - name: Pull big ONNX via LFS
-        run: git lfs pull -I "${{ env.BIG_ONNX }}"
-
-      - name: Set environment variables
-        run: |
-          source /etc/profile
-          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
-          export UV_PYTHON_PREFERENCE=managed
-          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
-          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
-          uv sync --frozen
-          printenv >> $GITHUB_ENV
-
-      - name: Disable powersave
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
-
-      - name: Wait for chestnut PCIe link
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
-          python3 -c "
-          import time
-          from openpilot.system.hardware.chestnut.flash import link_up
-          for i in range(10):
-              if link_up():
-                  print(f'PCIe link up after {i+1} attempt(s)')
-                  break
-              time.sleep(1)
-          else:
-              raise RuntimeError('Chestnut PCIe link not ready after 10 attempts')
-          "
-
-      - name: Compile big model with stock compiler
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
-
-          MODEL_SIZE=$(python3 -c "from openpilot.common.transformations.model import MEDMODEL_INPUT_SIZE as s; print(f'{s[0]}x{s[1]}')")
-          CAMERA_RES=$(python3 -c "from openpilot.common.transformations.camera import _ar_ox_fisheye as a, _os_fisheye as o; print(f'{a.width}x{a.height} {o.width}x{o.height}')")
-          FRAME_SKIP=$(python3 -c "from openpilot.selfdrive.modeld.constants import ModelConstants as MC; print(MC.MODEL_RUN_FREQ // MC.MODEL_CONTEXT_FREQ)")
-
-          TG_FLAGS="DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV=QCOM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
-
-          env ${TG_FLAGS} python3 \
-            ${{ github.workspace }}/openpilot/selfdrive/modeld/compile_modeld.py \
-            --onnx ${{ github.workspace }}/${{ env.BIG_ONNX }} \
-            --model-size $MODEL_SIZE \
-            --camera-resolutions $CAMERA_RES \
-            --frame-skip $FRAME_SKIP \
-            --output ${{ github.workspace }}/${{ env.BIG_PKL }}
-
-      - name: Chunk big pkl
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH=${{ github.workspace }}
-          python3 -c "
-          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
-          import os
-          pkl = '${{ github.workspace }}/${{ env.BIG_PKL }}'
-          size = os.path.getsize(pkl)
-          targets = get_chunk_targets(pkl, size)
-          chunk_file(pkl, targets)
-          print(f'Chunked into {len(targets)} files')
-          "
-
-      - name: Prepare output
-        env:
-          MODEL_NAME: ${{ needs.resolve.outputs.model_name }}
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH=${{ github.workspace }}
-          MODELS_DIR="${{ github.workspace }}/openpilot/selfdrive/modeld/models"
-          OUTPUT_DIR="${{ github.workspace }}/big_output"
-          PKL_BASE="big_driving_tinygrad.pkl"
-          mkdir -p "$OUTPUT_DIR"
-
-          cp "$MODELS_DIR/${PKL_BASE}".chunk* "$OUTPUT_DIR/"
-          cp "$MODELS_DIR/${PKL_BASE}.chunkmanifest" "$OUTPUT_DIR/"
-
-          python3 "${{ github.workspace }}/release/ci/model_generator.py" \
-            --model-dir "$MODELS_DIR" \
-            --output-dir "$OUTPUT_DIR" \
-            --custom-name "$MODEL_NAME" \
-            --upstream-branch "${{ needs.resolve.outputs.onnx_ref }}"
-
-          echo "model-${MODEL_NAME}-${{ github.run_number }}" > "$OUTPUT_DIR/artifact_name.txt"
-
-      - name: Upload big model artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: model-${{ needs.resolve.outputs.model_name }}-${{ github.run_number }}
-          path: ${{ github.workspace }}/big_output/
-
-      - name: Upload artifact name file
-        uses: actions/upload-artifact@v4
-        with:
-          name: artifact-name-${{ needs.resolve.outputs.model_name }}
-          path: ${{ github.workspace }}/big_output/artifact_name.txt
-
-      - name: Re-enable powersave
-        if: always()
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
-
-  upload_defaults:
-    needs: [ resolve, build_small_model, build_big_model, build_dm_model ]
-    if: |
-      ${{
-        !cancelled() &&
-        (inputs.target == 'big' && needs.build_big_model.result == 'success' ||
-         inputs.target == 'small' && needs.build_small_model.result == 'success' ||
-         inputs.target == 'dm' && needs.build_dm_model.result == 'success')
-      }}
-    runs-on: ubuntu-24.04
-    permissions:
-      id-token: write
-      contents: write
-    steps:
-      - uses: actions/checkout@v4
-
-      - name: Pull ONNX via LFS
-        run: git lfs pull -I "${{ needs.resolve.outputs.onnx_path }}"
-
-      - name: Install huggingface_hub
-        run: pip install --upgrade "huggingface_hub>=0.22.0"
-
-      - name: Download artifact name
-        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
-        uses: actions/download-artifact@v4
-        with:
-          name: artifact-name-${{ needs.resolve.outputs.model_name }}
-          path: artifact_name
-
-      - name: Read artifact name
-        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
-        id: artifact
-        run: |
-          ARTIFACT_NAME=$(cat artifact_name/artifact_name.txt)
-          echo "artifact_name=$ARTIFACT_NAME" >> $GITHUB_OUTPUT
-
-      - name: Download model artifact
-        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
-        uses: actions/download-artifact@v4
-        with:
-          name: ${{ steps.artifact.outputs.artifact_name }}
-          path: output
-
-      - name: Upload model to HF
-        if: ${{ inputs.target == 'small' || inputs.target == 'big' }}
-        env:
-          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
-          ARTIFACT_NAME: ${{ steps.artifact.outputs.artifact_name }}
-        run: |
-          rm -f output/artifact_name.txt
-          export PYTHONPATH=$(pwd)
-          python3 release/ci/upload_default_model.py \
-            --hf-repo "${{ env.HF_REPO }}" \
-            --hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
-            --artifact-name "$ARTIFACT_NAME" \
-            --model-dir output \
-            --onnx-path "${{ needs.resolve.outputs.onnx_path }}" \
-            --onnx-ref "${{ needs.resolve.outputs.onnx_ref }}" \
-            --model-name "${{ needs.resolve.outputs.model_name }}" \
-            --tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
-            --run-number "${{ github.run_number }}"
-
-      - name: Download DM artifact
-        if: ${{ inputs.target == 'dm' }}
-        uses: actions/download-artifact@v4
-        with:
-          name: dm-model-${{ github.run_number }}
-          path: dm_output
-
-      - name: Generate DM metadata and upload to HF
-        if: ${{ inputs.target == 'dm' }}
-        env:
-          HF_OIDC_RESOURCE: datasets/${{ env.HF_REPO }}
-        run: |
-          export PYTHONPATH=$(pwd)
-          python3 -c "
-          import json, hashlib
-          from pathlib import Path
-          from datetime import datetime, UTC
-
-          dm_dir = Path('dm_output')
-          manifest = list(dm_dir.glob('*.chunkmanifest'))
-          assert manifest, 'No chunkmanifest found'
-          pkl_name = manifest[0].name.removesuffix('.chunkmanifest')
-          num_chunks = int(manifest[0].read_text().strip())
-
-          chunks = []
-          for i in range(num_chunks):
-              chunk = dm_dir / f'{pkl_name}.chunk{i+1:02d}of{num_chunks:02d}'
-              chunks.append({
-                  'file_name': chunk.name,
-                  'sha256': hashlib.sha256(chunk.read_bytes()).hexdigest()
-              })
-
-          digest = hashlib.sha256()
-          for c in chunks:
-              with open(dm_dir / c['file_name'], 'rb') as f:
-                  while block := f.read(1024*1024):
-                      digest.update(block)
-
-          metadata = {
-              'bundles': [{
-                  'short_name': 'DMMODEL',
-                  'display_name': '${{ needs.resolve.outputs.model_name }}',
-                  'ref': '${{ needs.resolve.outputs.onnx_ref }}',
-                  'runner': 'tinygrad',
-                  'build_time': datetime.now(UTC).strftime('%Y-%m-%dT%H:%M:%SZ'),
-                  'models': [{
-                      'type': 'chunked',
-                      'artifact': {
-                          'file_name': pkl_name,
-                          'download_uri': {'url': '', 'sha256': digest.hexdigest()},
-                          'chunks': chunks
-                      }
-                  }]
-              }]
-          }
-          with open(dm_dir / 'metadata.json', 'w') as f:
-              json.dump(metadata, f, indent=2)
-          print('Generated DM metadata.json')
-          "
-
-          python3 release/ci/upload_default_model.py \
-            --hf-repo "${{ env.HF_REPO }}" \
-            --hf-defaults-path "${{ needs.resolve.outputs.hf_defaults_path }}" \
-            --artifact-name "dm-model-${{ github.run_number }}" \
-            --model-dir dm_output \
-            --onnx-path "${{ needs.resolve.outputs.onnx_path }}" \
-            --onnx-ref "${{ needs.resolve.outputs.onnx_ref }}" \
-            --model-name "${{ needs.resolve.outputs.model_name }}" \
-            --tinygrad-ref "${{ needs.resolve.outputs.tinygrad_ref }}" \
-            --run-number "${{ github.run_number }}"
-
-  build_dm_model:
-    needs: resolve
-    if: ${{ inputs.target == 'dm' }}
-    runs-on: [self-hosted, tici]
-    env:
-      DM_ONNX: openpilot/selfdrive/modeld/models/dmonitoring_model.onnx
-      DM_PKL: openpilot/selfdrive/modeld/models/dmonitoring_model_tinygrad.pkl
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          submodules: recursive
-
-      - name: Pull DM ONNX via LFS
-        run: git lfs pull -I "${{ env.DM_ONNX }}"
-
-      - name: Set environment variables
-        run: |
-          source /etc/profile
-          export UV_PROJECT_ENVIRONMENT=${HOME}/venv
-          export UV_PYTHON_PREFERENCE=managed
-          export UV_PYTHON_INSTALL_DIR=${HOME}/uv/python
-          export VIRTUAL_ENV=$UV_PROJECT_ENVIRONMENT
-          uv sync --frozen
-          printenv >> $GITHUB_ENV
-
-      - name: Disable powersave
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --disable
-
-      - name: Compile DM model
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH="${PYTHONPATH}:${{ github.workspace }}/tinygrad_repo:${{ github.workspace }}"
-
-          TG_FLAGS="DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 OPENPILOT_HACKS=1"
-
-          taskset -c 7 env ${TG_FLAGS} python3 \
-            ${{ github.workspace }}/tinygrad_repo/examples/openpilot/compile3.py \
-            ${{ github.workspace }}/${{ env.DM_ONNX }} \
-            ${{ github.workspace }}/${{ env.DM_PKL }}
-
-      - name: Chunk DM pkl
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          export PYTHONPATH=${{ github.workspace }}
-          python3 -c "
-          from openpilot.common.file_chunker import chunk_file, get_chunk_targets
-          import os
-          pkl = '${{ github.workspace }}/${{ env.DM_PKL }}'
-          size = os.path.getsize(pkl)
-          targets = get_chunk_targets(pkl, size)
-          chunk_file(pkl, targets)
-          print(f'Chunked {pkl} into {len(targets)} chunks')
-          "
-
-      - name: Prepare DM output
-        run: |
-          mkdir -p dm_output
-          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunk* dm_output/
-          cp ${{ github.workspace }}/${{ env.DM_PKL }}.chunkmanifest dm_output/
-
-      - name: Upload DM artifact
-        uses: actions/upload-artifact@v4
-        with:
-          name: dm-model-${{ github.run_number }}
-          path: dm_output/
-
-      - name: Re-enable powersave
-        if: always()
-        run: |
-          source ${UV_PROJECT_ENVIRONMENT}/bin/activate
-          PYTHONPATH=$PYTHONPATH:${{ github.workspace }}/ ${{ github.workspace }}/scripts/manage-powersave.py --enable
-
@@ -1,66 +0,0 @@
-name: Download HF model chunks
-description: Resolve and download model chunks from HuggingFace in parallel
-
-inputs:
-  hf_repo:
-    description: HuggingFace dataset repo
-    required: true
-  models:
-    description: 'JSON array of {hf_path, onnx_hash, canonical} objects'
-    required: true
-  dest_dir:
-    description: Destination directory for downloaded chunks
-    required: true
-
-runs:
-  using: composite
-  steps:
-    - name: Download model chunks
-      shell: bash
-      env:
-        HF_REPO: ${{ inputs.hf_repo }}
-        MODELS_JSON: ${{ inputs.models }}
-        DEST_DIR: ${{ inputs.dest_dir }}
-      run: |
-        set -eo pipefail
-        DOWNLOAD_LIST=$(mktemp)
-
-        resolve_chunks() {
-          local HF_PATH="$1" ONNX_HASH="$2" CANONICAL="$3" DEST_DIR="$4"
-          local JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_PATH}/default_models.json"
-          local DEFAULTS BUNDLE ARTIFACT BASE_URL NUM_CHUNKS
-          DEFAULTS=$(curl -fsSL "$JSON_URL")
-          BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)')
-          ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
-          BASE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url' | sed 's|/[^/]*$||')
-          NUM_CHUNKS=$(echo "$ARTIFACT" | jq -r '.chunks | length')
-
-          mkdir -p "$DEST_DIR"
-          while IFS= read -r CHUNK_NAME; do
-            CHUNK_IDX=$(echo "$CHUNK_NAME" | grep -oP 'chunk\K[0-9]+of[0-9]+' || true)
-            if [ -z "$CHUNK_IDX" ]; then
-              echo "::error::Failed to parse chunk index from: $CHUNK_NAME"
-              return 1
-            fi
-            ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${CHUNK_NAME}', safe=':/'))")
-            printf '%s\t%s\n' "$ENCODED_URL" "${DEST_DIR}/${CANONICAL}.chunk${CHUNK_IDX}" >> "$DOWNLOAD_LIST"
-          done < <(echo "$ARTIFACT" | jq -r '.chunks[].file_name')
-          echo "$NUM_CHUNKS" > "${DEST_DIR}/${CANONICAL}.chunkmanifest"
-        }
-
-        echo "$MODELS_JSON" | jq -c '.[]' | while IFS= read -r model; do
-          HF_PATH=$(echo "$model" | jq -r '.hf_path')
-          ONNX_HASH=$(echo "$model" | jq -r '.onnx_hash')
-          CANONICAL=$(echo "$model" | jq -r '.canonical')
-          resolve_chunks "$HF_PATH" "$ONNX_HASH" "$CANONICAL" "$DEST_DIR"
-        done
-
-        TOTAL=$(wc -l < "$DOWNLOAD_LIST")
-        echo "Downloading $TOTAL chunks with 8 parallel connections..."
-        xargs -P8 -d'\n' -I{} bash -c '
-          URL="${1%%	*}"
-          DEST="${1#*	}"
-          echo "Downloading $(basename "$DEST")"
-          curl -fsSL --retry 3 --retry-delay 5 -o "$DEST" "$URL"
-        ' _ {} < "$DOWNLOAD_LIST"
-        rm -f "$DOWNLOAD_LIST"
@@ -188,7 +188,7 @@ jobs:
          if [ "${{ inputs.target_hardware }}" == "usbgpu" ]; then
            echo "USBGPU build"
            export USBGPU=1
-            TG_FLAGS="DEBUG=1 DEV=USB+AMD:LLVM WARP_DEV=QCOM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
+            TG_FLAGS="DEBUG=2 DEV=USB+AMD:LLVM WARP_DEV=QCOM FLOAT16=1 JIT_BATCH_SIZE=0 GMMU=0 TC_OPT=2"
            OUTPUT_PKL="${{ env.MODELS_DIR }}/big_driving_tinygrad.pkl"
          else
            echo "QCOM build"
@@ -39,8 +39,6 @@ jobs:
      include_big_model: ${{ steps.strategy.outputs.include_big_model }}
    steps:
      - uses: actions/checkout@v4
-        with:
-          fetch-depth: 1
      - name: Extract deploy strategy
        id: strategy
        run: |
@@ -98,8 +96,6 @@ jobs:
      }}
    steps:
      - uses: actions/checkout@v4
-        with:
-          fetch-depth: 1
      - name: Wait for Tests
        uses: ./.github/workflows/wait-for-action # Path to where you place the action
        with:
@@ -123,7 +119,6 @@ jobs:
    steps:
      - uses: actions/checkout@v4
        with:
-          fetch-depth: 1
          submodules: recursive
          ref: ${{ env.SOURCE_BRANCH }}
          repository: ${{ github.event.pull_request.head.repo.fork && github.event.pull_request.head.repo.full_name || github.repository }}
@@ -170,7 +165,7 @@ jobs:
          scons -j1 cache_dir="$SCONS_CACHE" --minimal \
            openpilot/selfdrive/locationd openpilot/sunnypilot/selfdrive/locationd
          echo "Building rest of sunnypilot"
-          SKIP_TINYGRAD_COMPILE=1 /usr/bin/time -v scons -j$(nproc) cache_dir="$SCONS_CACHE" --minimal
+          /usr/bin/time -v scons -j$(nproc) cache_dir="$SCONS_CACHE" --minimal
          touch ${BUILD_DIR}/prebuilt
          if [[ "${{ runner.debug }}" == "1" ]]; then
            ls -la ${BUILD_DIR}
@@ -219,174 +214,59 @@ jobs:
    outputs:
      onnx_sha256: ${{ steps.resolve.outputs.onnx_sha256 }}
    env:
-      GH_REPO: ${{ github.repository }}
      HF_REPO: sunnypilot/sunnypilot_models_v1
      HF_DEFAULTS_PATH: models/defaults/big
    steps:
-      - name: Resolve ONNX hash and tinygrad ref via API
+      - uses: actions/checkout@v4
+        with:
+          ref: ${{ github.head_ref || github.ref_name }}
+
+      - run: git lfs pull -I "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx"
+
+      - name: Check HF defaults and build if needed
        id: resolve
        run: |
-          REF="${{ github.head_ref || github.ref_name }}"
-
-          ONNX_HASH=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
-          echo "ONNX hash: $ONNX_HASH"
-          echo "onnx_sha256=$ONNX_HASH" >> $GITHUB_OUTPUT
-
-          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
-          echo "tinygrad ref: $TINYGRAD_REF"
+          ACTUAL_ONNX_HASH=$(sha256sum "openpilot/selfdrive/modeld/models/big_driving_supercombo.onnx" | cut -d' ' -f1)
+          echo "Repo ONNX hash: $ACTUAL_ONNX_HASH"
+          echo "onnx_sha256=$ACTUAL_ONNX_HASH" >> $GITHUB_OUTPUT

          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"

-          check_defaults() {
+          check_hash() {
            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
-            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
-            [ "$TINYGRAD_MATCH" = "true" ] || return 1
-            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
+            BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ACTUAL_ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
            [ -n "$BUNDLE" ] && [ "$BUNDLE" != "null" ]
          }

-          if check_defaults; then
-            echo "HF defaults match repo ONNX hash and tinygrad ref"
-            exit 0
-          fi
+          if check_hash; then
+            echo "HF defaults match repo ONNX"
+          else
+            echo "No matching model on HF — triggering build"
+            gh workflow run build-default-big-model.yaml --ref "${{ github.head_ref || github.ref_name }}"

-          echo "No matching model on HF — dispatching build"
-          gh workflow run build-default-models.yaml --ref "$REF" -f target=big
+            echo "Waiting for build to start..."
+            sleep 120

-          echo "Polling HF for big model availability..."
-          for i in $(seq 1 90); do
-            sleep 30
-            if check_defaults; then
-              echo "Big model available on HF after $((i * 30))s"
-              exit 0
+            RUN_ID=$(gh run list --workflow=build-default-big-model.yaml --branch="${{ github.head_ref || github.ref_name }}" --limit=1 --json databaseId --jq '.[0].databaseId')
+            if [ -z "$RUN_ID" ] || [ "$RUN_ID" = "null" ]; then
+              echo "::error::Failed to find build-default-big-model run"
+              exit 1
            fi
-            echo "Poll $i/90: not yet available"
-          done

-          echo "::error::Big model not available on HF after 45 minutes"
-          exit 1
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+            echo "Waiting for run $RUN_ID..."
+            gh run watch "$RUN_ID"

-      - name: Cancel run on failure
-        if: failure()
-        run: gh run cancel ${{ github.run_id }}
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-
-  prepare_small_model:
-    needs: [ prepare_strategy ]
-    runs-on: ubuntu-24.04
-    outputs:
-      driving_onnx_sha256: ${{ steps.resolve.outputs.driving_onnx_sha256 }}
-    env:
-      GH_REPO: ${{ github.repository }}
-      HF_REPO: sunnypilot/sunnypilot_models_v1
-      HF_DEFAULTS_PATH: models/defaults/small
-    steps:
-      - name: Resolve ONNX hash and tinygrad ref via API
-        id: resolve
-        run: |
-          REF="${{ github.head_ref || github.ref_name }}"
-
-          DRIVING_HASH=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/driving_supercombo.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
-          echo "Driving ONNX hash: $DRIVING_HASH"
-          echo "driving_onnx_sha256=$DRIVING_HASH" >> $GITHUB_OUTPUT
-
-          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
-          echo "tinygrad ref: $TINYGRAD_REF"
-
-          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
-
-          check_defaults() {
-            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
-            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
-            [ "$TINYGRAD_MATCH" = "true" ] || return 1
-            DRIVING=$(echo "$DEFAULTS" | jq --arg hash "$DRIVING_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
-            [ -n "$DRIVING" ] && [ "$DRIVING" != "null" ] || return 1
-          }
-
-          if check_defaults; then
-            echo "HF defaults match repo ONNX hash and tinygrad ref"
-            exit 0
-          fi
-
-          echo "No matching model on HF — dispatching build"
-          gh workflow run build-default-models.yaml --ref "$REF" -f target=small
-
-          echo "Polling HF for model availability..."
-          for i in $(seq 1 60); do
-            sleep 30
-            if check_defaults; then
-              echo "Model available on HF after $((i * 30))s"
-              exit 0
+            CONCLUSION=$(gh run view "$RUN_ID" --json conclusion --jq '.conclusion')
+            if [ "$CONCLUSION" != "success" ]; then
+              echo "::error::build-default-big-model failed: $CONCLUSION"
+              exit 1
            fi
-            echo "Poll $i/60: not yet available"
-          done

-          echo "::error::Small driving model not available on HF after 30 minutes"
-          exit 1
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-
-      - name: Cancel run on failure
-        if: failure()
-        run: gh run cancel ${{ github.run_id }}
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-
-  prepare_dm_model:
-    needs: [ prepare_strategy ]
-    runs-on: ubuntu-24.04
-    outputs:
-      dm_onnx_sha256: ${{ steps.resolve.outputs.dm_onnx_sha256 }}
-    env:
-      GH_REPO: ${{ github.repository }}
-      HF_REPO: sunnypilot/sunnypilot_models_v1
-      HF_DEFAULTS_PATH: models/defaults/dm
-    steps:
-      - name: Resolve ONNX hash and tinygrad ref via API
-        id: resolve
-        run: |
-          REF="${{ github.head_ref || github.ref_name }}"
-
-          DM_HASH=$(gh api "repos/${GH_REPO}/contents/openpilot/selfdrive/modeld/models/dmonitoring_model.onnx?ref=${REF}" --jq '.content' | base64 -d | grep '^oid sha256:' | cut -d: -f2)
-          echo "DM ONNX hash: $DM_HASH"
-          echo "dm_onnx_sha256=$DM_HASH" >> $GITHUB_OUTPUT
-
-          TINYGRAD_REF=$(gh api "repos/${GH_REPO}/contents/tinygrad_repo?ref=${REF}" --jq '.sha')
-          echo "tinygrad ref: $TINYGRAD_REF"
-
-          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
-
-          check_defaults() {
-            DEFAULTS=$(curl -fsSL "$JSON_URL" 2>/dev/null) || return 1
-            TINYGRAD_MATCH=$(echo "$DEFAULTS" | jq -r --arg ref "$TINYGRAD_REF" '.tinygrad_ref == $ref' 2>/dev/null)
-            [ "$TINYGRAD_MATCH" = "true" ] || return 1
-            DM=$(echo "$DEFAULTS" | jq --arg hash "$DM_HASH" '.bundles[] | select(.onnx_sha256 == $hash)' 2>/dev/null)
-            [ -n "$DM" ] && [ "$DM" != "null" ] || return 1
-          }
-
-          if check_defaults; then
-            echo "HF defaults match DM ONNX hash and tinygrad ref"
-            exit 0
-          fi
-
-          echo "No matching DM model on HF — dispatching build"
-          gh workflow run build-default-models.yaml --ref "$REF" -f target=dm
-
-          echo "Polling HF for DM model availability..."
-          for i in $(seq 1 60); do
-            sleep 30
-            if check_defaults; then
-              echo "DM model available on HF after $((i * 30))s"
-              exit 0
+            if ! check_hash; then
+              echo "::error::HF defaults still don't match after build"
+              exit 1
            fi
-            echo "Poll $i/60: not yet available"
-          done
-
-          echo "::error::DM model not available on HF after 30 minutes"
-          exit 1
+          fi
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

@@ -398,24 +278,23 @@ jobs:

  publish:
    concurrency:
+      # We do a bit of a hack here to avoid canceling the publishing job if a new commit comes in while we're publishing by adding the sha to the group name.
+      # This means that if multiple commits come in while we're publishing, they will be queued up and publish one after the other.
+      # Otherwise, if a job is waiting to be published due to environment wait time, it would be canceled by a new commit and restart the wait time.
      group: ${{ needs.prepare_strategy.outputs.publish_concurrency_group }}
      cancel-in-progress: ${{ needs.prepare_strategy.outputs.cancel_publish_in_progress == 'true' }}
    if: ${{
      always() && !cancelled() &&
      needs.build.result == 'success' &&
      needs.prepare_strategy.result == 'success' &&
-      needs.prepare_small_model.result == 'success' &&
-      needs.prepare_dm_model.result == 'success' &&
      (!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt')) &&
      (needs.prepare_strategy.outputs.include_big_model != 'true' || needs.prepare_chestnut.result == 'success')
      }}
-    needs: [ build, prepare_strategy, prepare_chestnut, prepare_small_model, prepare_dm_model ]
+    needs: [ build, prepare_strategy, prepare_chestnut ]
    runs-on: ubuntu-24.04
    environment: ${{ needs.prepare_strategy.outputs.environment }}
    steps:
      - uses: actions/checkout@v4
-        with:
-          fetch-depth: 1

      - name: Download prebuilt artifact
        uses: actions/download-artifact@v4
@@ -427,16 +306,43 @@ jobs:
          mkdir -p ${{ env.OUTPUT_DIR }}
          tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}

-      - name: Download model chunks from HF
-        uses: ./.github/workflows/download-hf-model-chunks
-        with:
-          hf_repo: sunnypilot/sunnypilot_models_v1
-          dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
-          models: |
-            [
-              {"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
-              {"hf_path": "models/defaults/dm", "onnx_hash": "${{ needs.prepare_dm_model.outputs.dm_onnx_sha256 }}", "canonical": "dmonitoring_model_tinygrad.pkl"}
-            ]
+      - name: Prepare chestnut output
+        if: ${{ needs.prepare_chestnut.result == 'success' }}
+        run: |
+          mkdir -p "${{ github.workspace }}/chestnut_output"
+          tar xzf prebuilt.tar.gz -C "${{ github.workspace }}/chestnut_output"
+
+      - name: Download big model chunks from HF
+        if: ${{ needs.prepare_chestnut.result == 'success' }}
+        env:
+          HF_REPO: sunnypilot/sunnypilot_models_v1
+          HF_DEFAULTS_PATH: models/defaults/big
+        run: |
+          ONNX_HASH="${{ needs.prepare_chestnut.outputs.onnx_sha256 }}"
+          JSON_URL="https://huggingface.co/datasets/${HF_REPO}/resolve/main/${HF_DEFAULTS_PATH}/default_models.json"
+          DEFAULTS=$(curl -fsSL "$JSON_URL")
+          BUNDLE=$(echo "$DEFAULTS" | jq --arg hash "$ONNX_HASH" '.bundles[] | select(.onnx_sha256 == $hash)')
+
+          mkdir -p big_model_chunks
+          ARTIFACT=$(echo "$BUNDLE" | jq -r '.models[0].artifact')
+          BASE_URL=$(echo "$ARTIFACT" | jq -r '.download_uri.url' | sed 's|/[^/]*$||')
+          NUM_CHUNKS=$(echo "$ARTIFACT" | jq -r '.chunks | length')
+
+          CANONICAL="big_driving_tinygrad.pkl"
+          echo "$ARTIFACT" | jq -r '.chunks[].file_name' | while read CHUNK_NAME; do
+            CHUNK_IDX=$(echo "$CHUNK_NAME" | grep -oP 'chunk\K[0-9]+of[0-9]+')
+            CANONICAL_CHUNK="${CANONICAL}.chunk${CHUNK_IDX}"
+            ENCODED_URL=$(python3 -c "import urllib.parse; print(urllib.parse.quote('${BASE_URL}/${CHUNK_NAME}', safe=':/'))")
+            echo "Downloading $CHUNK_NAME -> $CANONICAL_CHUNK"
+            curl -fsSL -o "big_model_chunks/${CANONICAL_CHUNK}" "$ENCODED_URL"
+          done
+
+          echo "$NUM_CHUNKS" > "big_model_chunks/${CANONICAL}.chunkmanifest"
+
+      - name: Inject big model into chestnut
+        if: ${{ needs.prepare_chestnut.result == 'success' }}
+        run: |
+          cp big_model_chunks/* "${{ github.workspace }}/chestnut_output/openpilot/selfdrive/modeld/models/"

      - name: Configure Git
        run: |
@@ -458,6 +364,22 @@ jobs:
            "https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
            "${{ needs.prepare_strategy.outputs.extra_version_identifier }}"

+      - name: Publish chestnut branch
+        if: ${{ needs.prepare_chestnut.result == 'success' }}
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          CHESTNUT_BRANCH="${{ needs.prepare_strategy.outputs.new_branch }}-chestnut"
+          CHESTNUT_DIR="${{ github.workspace }}/chestnut_output"
+
+          ${{ env.CI_DIR }}/publish.sh \
+            "${{ github.workspace }}" \
+            "$CHESTNUT_DIR" \
+            "$CHESTNUT_BRANCH" \
+            "${{ needs.prepare_strategy.outputs.version }}" \
+            "https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
+            "${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
+
      - name: Tag ${{ needs.prepare_strategy.outputs.environment }}
        if: ${{ needs.prepare_strategy.outputs.is_stable_branch == 'true' && (github.event_name != 'push' || !startsWith(github.ref, 'refs/tags/')) }}
        run: |
@@ -465,77 +387,12 @@ jobs:
            git tag -f -a ${TAG} -m "${{ needs.prepare_strategy.outputs.environment }} @ ${{ needs.prepare_strategy.outputs.version }} of build ${{ needs.prepare_strategy.outputs.build }}."
            git push -f origin ${TAG}

-  publish_chestnut:
-    concurrency:
-      group: ${{ needs.prepare_strategy.outputs.publish_concurrency_group }}-chestnut
-      cancel-in-progress: ${{ needs.prepare_strategy.outputs.cancel_publish_in_progress == 'true' }}
-    if: ${{
-      always() && !cancelled() &&
-      needs.build.result == 'success' &&
-      needs.prepare_strategy.result == 'success' &&
-      needs.prepare_small_model.result == 'success' &&
-      needs.prepare_dm_model.result == 'success' &&
-      needs.prepare_chestnut.result == 'success' &&
-      (!contains(github.event_name, 'pull_request') || (github.event.action == 'labeled' && github.event.label.name == 'prebuilt'))
-      }}
-    needs: [ build, prepare_strategy, prepare_chestnut, prepare_small_model, prepare_dm_model ]
-    runs-on: ubuntu-24.04
-    environment: ${{ needs.prepare_strategy.outputs.environment }}
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          fetch-depth: 1
-
-      - name: Download prebuilt artifact
-        uses: actions/download-artifact@v4
-        with:
-          name: prebuilt
-
-      - name: Untar prebuilt
-        run: |
-          mkdir -p ${{ env.OUTPUT_DIR }}
-          tar xzf prebuilt.tar.gz -C ${{ env.OUTPUT_DIR }}
-
-      - name: Download model chunks from HF
-        uses: ./.github/workflows/download-hf-model-chunks
-        with:
-          hf_repo: sunnypilot/sunnypilot_models_v1
-          dest_dir: ${{ env.OUTPUT_DIR }}/openpilot/selfdrive/modeld/models
-          models: |
-            [
-              {"hf_path": "models/defaults/small", "onnx_hash": "${{ needs.prepare_small_model.outputs.driving_onnx_sha256 }}", "canonical": "driving_tinygrad.pkl"},
-              {"hf_path": "models/defaults/dm", "onnx_hash": "${{ needs.prepare_dm_model.outputs.dm_onnx_sha256 }}", "canonical": "dmonitoring_model_tinygrad.pkl"},
-              {"hf_path": "models/defaults/big", "onnx_hash": "${{ needs.prepare_chestnut.outputs.onnx_sha256 }}", "canonical": "big_driving_tinygrad.pkl"}
-            ]
-
-      - name: Configure Git
-        run: |
-          git config --global user.email "github-actions[bot]@users.noreply.github.com"
-          git config --global user.name "github-actions[bot]"
-
-      - name: Publish chestnut branch
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-        run: |
-          CHESTNUT_BRANCH="${{ needs.prepare_strategy.outputs.new_branch }}-chestnut"
-
-          ${{ env.CI_DIR }}/publish.sh \
-            "${{ github.workspace }}" \
-            "${{ env.OUTPUT_DIR }}" \
-            "$CHESTNUT_BRANCH" \
-            "${{ needs.prepare_strategy.outputs.version }}" \
-            "https://x-access-token:${{github.token}}@github.com/sunnypilot/sunnypilot.git" \
-            "${{ needs.prepare_strategy.outputs.extra_version_identifier }}"
-
  notify:
    needs:
    - prepare_strategy
    - build
    - publish
-    - publish_chestnut
    - prepare_chestnut
-    - prepare_small_model
-    - prepare_dm_model
    runs-on: ubuntu-24.04
    if: ${{ (always() && !cancelled() && !failure())
      && needs.publish.result == 'success'
@@ -543,8 +400,6 @@ jobs:
      && (fromJSON(vars.DEV_FEEDBACK_NOTIFICATION_BRANCHES_V2)[github.head_ref || github.ref_name] != null) }}
    steps:
      - uses: actions/checkout@v4
-        with:
-          fetch-depth: 1

      - name: Prepare notification message
        id: message
@@ -195,10 +195,9 @@ inline static std::unordered_map<std::string, ParamKeyAttributes> keys = {

    // Model Manager params
    {"ModelManager_ActiveBundle", {PERSISTENT, JSON}},
-    {"ModelManager_ActiveBundleUSBGPU", {PERSISTENT, JSON}},
-    {"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, JSON}},
+    {"ModelManager_ActiveJson", {CLEAR_ON_MANAGER_START, STRING}},
    {"ModelManager_ClearCache", {CLEAR_ON_MANAGER_START, BOOL}},
-    {"ModelManager_DownloadRef", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, STRING}},
+    {"ModelManager_DownloadIndex", {CLEAR_ON_MANAGER_START | CLEAR_ON_ONROAD_TRANSITION, INT}},
    {"ModelManager_Favs", {PERSISTENT | BACKUP, STRING}},
    {"ModelManager_LastSyncTime", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
    {"ModelManager_LastSyncTime_USBGPU", {CLEAR_ON_MANAGER_START | CLEAR_ON_OFFROAD_TRANSITION, INT, "0"}},
@@ -73,45 +73,44 @@ compile_modeld_script = [
 model_w, model_h = MEDMODEL_INPUT_SIZE
 frame_skip = ModelConstants.MODEL_RUN_FREQ // ModelConstants.MODEL_CONTEXT_FREQ

-if not os.getenv('SKIP_TINYGRAD_COMPILE'):
-  for usbgpu in [False, True] if USBGPU else [False]:
-    target_pkl_path = File(modeld_pkl_path(usbgpu)).abspath
-    # BIG_INTO_SMALL=1 builds the default target from the big model, e.g. to test it without a USB GPU
-    file_prefix, cmd_flags = ('big_', usbgpu_tg_flags) if usbgpu else ('big_' if os.getenv('BIG_INTO_SMALL') else '', tg_flags)
-    driving_onnx_deps = get_existing_chunks(File(f"models/{file_prefix}driving_supercombo.onnx").abspath)
-    camera_res_args = ' '.join(f'{cw}x{ch}' for cw, ch in CAMERA_CONFIGS)
-    # CPU 7 is isolated with isolcpus on AGNOS, so explicitly pin the compiler to it.
-    taskset = 'taskset -c 7 ' if arch == 'comma_arm64' else ''
-    cmd = (f'{cmd_flags} {mac_brew_string} {taskset}python3 {modeld_dir}/compile_modeld.py '
-          f'--model-size {model_w}x{model_h} '
-          f'--camera-resolutions {camera_res_args} '
-          f'--onnx {File(f"models/{file_prefix}driving_supercombo.onnx").abspath} '
-          f'--output {target_pkl_path} --frame-skip {frame_skip}')
-    onnx_sizes_sum = sum(os.path.getsize(f) for f in driving_onnx_deps)
-    chunk_targets = get_chunk_targets(target_pkl_path, estimate_pickle_max_size(onnx_sizes_sum))
-    def do_compile(target, source, env, command=cmd, pkl=target_pkl_path, chunks=chunk_targets):
-      from openpilot.system.hardware.chestnut.flash import link_up
-      # chestnut can enumerate before its PCIe link is up due to varying 12V power behavior across cars
-      for _ in range(10):
-        if link_up():
-          break
-        time.sleep(1)
-      else:
-        print("Chestnut not ready, skipping big model build")
-        return
-      if ret := env.Execute(command):
-        return ret
-      chunk_file(pkl, chunks)
-    def do_chunk(target, source, env, pkl=target_pkl_path, chunks=chunk_targets):
-      chunk_file(pkl, chunks)
-    actions = Action(do_compile, "  [USBGPU] $TARGET") if usbgpu else [cmd, Action(do_chunk, "  [CHUNK] $TARGET")]
-    node = lenv.Command(
-      chunk_targets,
-      tinygrad_files + compile_modeld_script + driving_onnx_deps + [Value(chunk_targets), chunker_file],
-      actions,
-    )
-    if usbgpu:
-      lenv.SideEffect(usbgpu_lock, node)
+for usbgpu in [False, True] if USBGPU else [False]:
+  target_pkl_path = File(modeld_pkl_path(usbgpu)).abspath
+  # BIG_INTO_SMALL=1 builds the default target from the big model, e.g. to test it without a USB GPU
+  file_prefix, cmd_flags = ('big_', usbgpu_tg_flags) if usbgpu else ('big_' if os.getenv('BIG_INTO_SMALL') else '', tg_flags)
+  driving_onnx_deps = get_existing_chunks(File(f"models/{file_prefix}driving_supercombo.onnx").abspath)
+  camera_res_args = ' '.join(f'{cw}x{ch}' for cw, ch in CAMERA_CONFIGS)
+  # CPU 7 is isolated with isolcpus on AGNOS, so explicitly pin the compiler to it.
+  taskset = 'taskset -c 7 ' if arch == 'comma_arm64' else ''
+  cmd = (f'{cmd_flags} {mac_brew_string} {taskset}python3 {modeld_dir}/compile_modeld.py '
+        f'--model-size {model_w}x{model_h} '
+        f'--camera-resolutions {camera_res_args} '
+        f'--onnx {File(f"models/{file_prefix}driving_supercombo.onnx").abspath} '
+        f'--output {target_pkl_path} --frame-skip {frame_skip}')
+  onnx_sizes_sum = sum(os.path.getsize(f) for f in driving_onnx_deps)
+  chunk_targets = get_chunk_targets(target_pkl_path, estimate_pickle_max_size(onnx_sizes_sum))
+  def do_compile(target, source, env, command=cmd, pkl=target_pkl_path, chunks=chunk_targets):
+    from openpilot.system.hardware.chestnut.flash import link_up
+    # chestnut can enumerate before its PCIe link is up due to varying 12V power behavior across cars
+    for _ in range(10):
+      if link_up():
+        break
+      time.sleep(1)
+    else:
+      print("Chestnut not ready, skipping big model build")
+      return
+    if ret := env.Execute(command):
+      return ret
+    chunk_file(pkl, chunks)
+  def do_chunk(target, source, env, pkl=target_pkl_path, chunks=chunk_targets):
+    chunk_file(pkl, chunks)
+  actions = Action(do_compile, "  [USBGPU] $TARGET") if usbgpu else [cmd, Action(do_chunk, "  [CHUNK] $TARGET")]
+  node = lenv.Command(
+    chunk_targets,
+    tinygrad_files + compile_modeld_script + driving_onnx_deps + [Value(chunk_targets), chunker_file],
+    actions,
+  )
+  if usbgpu:
+    lenv.SideEffect(usbgpu_lock, node)

 # get model metadata
 fn = File(f"models/dmonitoring_model").abspath
@@ -143,5 +142,4 @@ def tg_compile(flags, model_name):
     Action(do_chunk, "  [CHUNK] $TARGET")],
  )

-if not os.getenv('SKIP_TINYGRAD_COMPILE'):
-  tg_compile(tg_flags, 'dmonitoring_model')
+tg_compile(tg_flags, 'dmonitoring_model')
@@ -575,7 +575,7 @@ class SelfdriveD(CruiseHelper):
    clear_event_types = set()
    if ET.WARNING not in self.state_machine.current_alert_types:
      clear_event_types.add(ET.WARNING)
-    if self.enabled:
+    if self.enabled or (ET.NO_ENTRY not in (c := self.state_machine.current_alert_types) and (ET.ENABLE in c or ET.USER_DISABLE in c)):
      clear_event_types.add(ET.NO_ENTRY)

    pers = LONGITUDINAL_PERSONALITY_MAP[self.personality]
@@ -168,16 +168,9 @@ class Sidebar(Widget, SidebarSP):
    # Home/Flag button
    flag_pressed = mouse_down and rl.check_collision_point_rec(mouse_pos, HOME_BTN)
    button_img = self._flag_img if ui_state.started else self._home_img
-    button_pos = rl.Vector2(HOME_BTN.x, HOME_BTN.y)
-    icon_opacity = 1.0
-
-    if gui_app.sunnypilot_ui():
-      button_img, button_pos, icon_opacity = SidebarSP._get_home_icon(self, button_img)

    tint = Colors.BUTTON_PRESSED if (ui_state.started and flag_pressed) else Colors.BUTTON_NORMAL
-    if icon_opacity < 1.0:
-      tint = rl.Color(tint[0], tint[1], tint[2], int(255 * icon_opacity))
-    rl.draw_texture_ex(button_img, button_pos, 0.0, 1.0, tint)
+    rl.draw_texture_ex(button_img, rl.Vector2(HOME_BTN.x, HOME_BTN.y), 0.0, 1.0, tint)

    # Microphone button
    if self._recording_audio:
@@ -248,11 +248,8 @@ class MiciHomeLayout(Widget):

    # ***** Center-aligned bottom section icons *****
    self._experimental_icon.set_visible(ui_state.experimental_mode)
-    if gui_app.sunnypilot_ui():
-      self._set_egpu_visibility()
-    else:
-      self._egpu_icon.set_visible(ui_state.sm["deviceState"].chestnutPresent and ui_state.usbgpu_compiled)
-      self._egpu_icon_gray.set_visible(ui_state.sm["deviceState"].chestnutPresent and not ui_state.usbgpu_compiled)
+    self._egpu_icon.set_visible(ui_state.sm["deviceState"].chestnutPresent and ui_state.usbgpu_compiled)
+    self._egpu_icon_gray.set_visible(ui_state.sm["deviceState"].chestnutPresent and not ui_state.usbgpu_compiled)
    self._mic_icon.set_visible(ui_state.recording_audio)
    self._body_icon.set_visible(bool(ui_state.is_body))

@@ -11,8 +11,6 @@ import pyray as rl

 from openpilot.cereal import custom
 from openpilot.sunnypilot.models.default_model import get_default_model
-from openpilot.sunnypilot.models.fetcher import ModelFetcher
-from openpilot.sunnypilot.models.helpers import ACTIVE_BUNDLE_KEYS
 from openpilot.common.constants import CV
 from openpilot.selfdrive.ui.ui_state import device, ui_state
 from openpilot.system.ui.lib.multilang import tr
@@ -70,7 +68,7 @@ class ModelsLayout(Widget):
      callback=self._clear_cache
    )

-    self.cancel_download_item = button_item(tr("Cancel Download"), tr("Cancel"), "", lambda: ui_state.params.remove("ModelManager_DownloadRef"))
+    self.cancel_download_item = button_item(tr("Cancel Download"), tr("Cancel"), "", lambda: ui_state.params.remove("ModelManager_DownloadIndex"))

    self.lane_turn_value_control = option_item_sp(tr("Adjust Lane Turn Speed"), "LaneTurnValue", 500, 2000,
                                                  tr("Set the maximum speed for lane turn desires. Default is 19 mph."),
@@ -117,12 +115,8 @@ class ModelsLayout(Widget):
  def calculate_cache_size():
    cache_size = 0.0
    if os.path.exists(CUSTOM_MODEL_PATH):
-      for file in os.listdir(CUSTOM_MODEL_PATH):
-        try:
-          cache_size += os.path.getsize(os.path.join(CUSTOM_MODEL_PATH, file))
-        except OSError:
-          continue
-    return cache_size / (1024**2)
+      cache_size = sum(os.path.getsize(os.path.join(CUSTOM_MODEL_PATH, file)) for file in os.listdir(CUSTOM_MODEL_PATH)) / (1024**2)
+    return cache_size

  def _clear_cache(self):
    def _callback(response):
@@ -148,7 +142,7 @@ class ModelsLayout(Widget):
    if not bundle:
      return

-    self.cancel_download_item.set_visible(bool(self.model_manager.selectedBundle) and ui_state.params.get("ModelManager_DownloadRef") is not None)
+    self.cancel_download_item.set_visible(bool(self.model_manager.selectedBundle) and ui_state.params.get("ModelManager_DownloadIndex") is not None)

    if (current_time := time.monotonic()) - self.last_cache_calc_time > 0.5:
      self.last_cache_calc_time = current_time
@@ -189,10 +183,9 @@ class ModelsLayout(Widget):
      return
    selected_ref = self.model_dialog.selection_ref
    if selected_ref == "Default":
-      source = ModelFetcher.active_source(ui_state.sm["deviceState"].chestnutPresent)
-      ui_state.params.remove(ACTIVE_BUNDLE_KEYS[source])
+      ui_state.params.remove("ModelManager_ActiveBundle")
    elif selected_bundle := next((bundle for bundle in self.model_manager.availableBundles if bundle.ref == selected_ref), None):
-      ui_state.params.put("ModelManager_DownloadRef", selected_bundle.ref)
+      ui_state.params.put("ModelManager_DownloadIndex", selected_bundle.index)
    self.model_dialog = None

  @staticmethod
@@ -230,7 +223,7 @@ class ModelsLayout(Widget):
    advanced_controls: bool = ui_state.params.get_bool("ShowAdvancedControls")
    turn_desire: bool = ui_state.params.get_bool("LaneTurnDesire")
    live_delay: bool = ui_state.params.get_bool("LagdToggle")
-    camera_offset: bool = ui_state.active_bundle is not None
+    camera_offset: bool = ui_state.params.get("ModelManager_ActiveBundle") is not None

    self.lane_turn_desire_toggle.action_item.set_state(turn_desire)
    self.lane_turn_value_control.set_visible(turn_desire and advanced_controls)
@@ -244,9 +237,8 @@ class ModelsLayout(Widget):
    self._update_lagd_description(live_delay)
    self.model_manager = ui_state.sm["modelManagerSP"]
    self._handle_bundle_download_progress()
-    # read the slot through ui_state, not modelManagerSP: the manager republishes a
-    # tick after a chestnut change, and the stale bundle flashes the wrong model
-    active_name = (ui_state.active_bundle or {}).get("displayName") or f"{get_default_model()} (Default)"
+    default_label = f"{get_default_model()} (Default)"
+    active_name = self.model_manager.activeBundle.displayName if self.model_manager and self.model_manager.activeBundle.ref else default_label
    self.current_model_item.action_item.set_value(active_name)

    if not ui_state.is_offroad():
@@ -4,14 +4,11 @@ Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
 This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
-import math
-
 import pyray as rl
 import time
 from dataclasses import dataclass
 from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.sunnypilot.sunnylink.api import UNREGISTERED_SUNNYLINK_DONGLE_ID
-from openpilot.system.ui.lib.application import gui_app
 from openpilot.system.ui.lib.multilang import tr_noop


@@ -21,9 +18,6 @@ METRIC_MARGIN = 30
 METRIC_START_Y = 300
 HOME_BTN = rl.Rectangle(60, 860, 180, 180)

-EGPU_ICON_WIDTH = 180
-EGPU_ICON_HEIGHT = 133
-

 # Color scheme
 class Colors:
@@ -59,10 +53,6 @@ class MetricData:
 class SidebarSP:
  def __init__(self):
    self._sunnylink_status = MetricData(tr_noop("SUNNYLINK"), tr_noop("OFFLINE"), Colors.WARNING)
-    self._egpu_green_img = gui_app.texture("icons_mici/egpu_green.png", EGPU_ICON_WIDTH, EGPU_ICON_HEIGHT)
-    self._egpu_default_img = gui_app.texture("icons_mici/egpu.png", EGPU_ICON_WIDTH, EGPU_ICON_HEIGHT)
-    self._egpu_orange_img = gui_app.texture("icons_mici/egpu_orange.png", EGPU_ICON_WIDTH, EGPU_ICON_HEIGHT)
-    self._egpu_gray_img = gui_app.texture("icons_mici/egpu_gray.png", EGPU_ICON_WIDTH, EGPU_ICON_HEIGHT)

  def _update_sunnylink_status(self):
    if not ui_state.params.get_bool("SunnylinkEnabled"):
@@ -88,29 +78,6 @@ class SidebarSP:

    self._sunnylink_status.update(tr_noop("SUNNYLINK"), status, color)

-  def _get_home_icon(self, default_img: rl.Texture) -> tuple[rl.Texture, rl.Vector2, float]:
-    default_pos = rl.Vector2(HOME_BTN.x, HOME_BTN.y)
-    if not ui_state.sm["deviceState"].chestnutPresent:
-      return default_img, default_pos, 1.0
-
-    big_model_selected = ui_state.usbgpu_compiled or ui_state.model_runner_tinygrad
-    big_model_failed = ui_state.started and ui_state.big_model_failed
-    loading = ui_state.usbgpu_loading or (big_model_selected and ui_state.started and ui_state.usbgpu_active is None)
-
-    if loading:
-      icon = self._egpu_default_img
-      opacity = 0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0))
-    elif big_model_selected and big_model_failed:
-      icon, opacity = self._egpu_orange_img, 1.0
-    elif big_model_selected:
-      icon, opacity = self._egpu_green_img, 1.0
-    else:
-      icon, opacity = self._egpu_gray_img, 1.0
-
-    x = HOME_BTN.x + (HOME_BTN.width - icon.width) / 2
-    y = HOME_BTN.y + (HOME_BTN.height - icon.height) / 2
-    return icon, rl.Vector2(x, y), opacity
-
  def _draw_metrics_w_sunnylink(self, rect: rl.Rectangle, _temp, _panda, _connect):
    metrics = [_temp, _panda, _connect, self._sunnylink_status]
    start_y = int(rect.y) + METRIC_START_Y
@@ -4,14 +4,8 @@ Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
 This file is part of sunnypilot and is licensed under the MIT License.
 See the LICENSE.md file in the root directory for more details.
 """
-import math
-
-import pyray as rl
-
 from openpilot.selfdrive.ui.mici.layouts.home import MiciHomeLayout
-from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.system.ui.lib.application import FontWeight
-from openpilot.system.ui.widgets.icon_widget import IconWidget
 from openpilot.system.ui.widgets.label import UnifiedLabel


@@ -19,35 +13,3 @@ class MiciHomeLayoutSP(MiciHomeLayout):
  def __init__(self):
    super().__init__()
    self._openpilot_label = UnifiedLabel("sunnypilot", font_size=88, font_weight=FontWeight.AUDIOWIDE, max_width=480, wrap_text=False)
-    self._egpu_icon_default = IconWidget("icons_mici/egpu.png", (50, 37))
-    self._egpu_icon_default.set_visible(False)
-    self._egpu_icon_orange = IconWidget("icons_mici/egpu_orange.png", (50, 37))
-    self._egpu_icon_orange.set_visible(False)
-    gray_idx = self._status_bar_layout.widgets.index(self._egpu_icon_gray)
-    self._status_bar_layout.widgets.insert(gray_idx + 1, self._egpu_icon_default)
-    self._status_bar_layout.widgets.insert(gray_idx + 2, self._egpu_icon_orange)
-
-  def _set_egpu_visibility(self):
-    chestnut = ui_state.sm["deviceState"].chestnutPresent
-    if not chestnut:
-      self._egpu_icon.set_visible(False)
-      self._egpu_icon_default.set_visible(False)
-      self._egpu_icon_orange.set_visible(False)
-      self._egpu_icon_gray.set_visible(False)
-      return
-
-    big_model_selected = ui_state.usbgpu_compiled or ui_state.model_runner_tinygrad
-    big_model_failed = ui_state.started and ui_state.big_model_failed
-    loading = ui_state.usbgpu_loading or (big_model_selected and ui_state.started and ui_state.usbgpu_active is None)
-
-    if loading:
-      self._egpu_icon_default._opacity = 0.35 + 0.65 * (0.5 - 0.5 * math.cos(rl.get_time() * 6.0))
-      self._egpu_icon_default.set_visible(True)
-      self._egpu_icon.set_visible(False)
-      self._egpu_icon_orange.set_visible(False)
-      self._egpu_icon_gray.set_visible(False)
-    else:
-      self._egpu_icon_default.set_visible(False)
-      self._egpu_icon.set_visible(big_model_selected and not big_model_failed)
-      self._egpu_icon_orange.set_visible(big_model_selected and big_model_failed)
-      self._egpu_icon_gray.set_visible(not big_model_selected)
@@ -8,8 +8,6 @@ import pyray as rl

 from openpilot.cereal import custom
 from openpilot.sunnypilot.models.default_model import get_default_model
-from openpilot.sunnypilot.models.fetcher import ModelFetcher
-from openpilot.sunnypilot.models.helpers import ACTIVE_BUNDLE_KEYS
 from openpilot.selfdrive.ui.mici.widgets.button import BigButton
 from openpilot.selfdrive.ui.sunnypilot.layouts.settings.models import ModelsLayout
 from openpilot.selfdrive.ui.ui_state import ui_state, device
@@ -62,7 +60,7 @@ class ModelsLayoutMici(NavScroller):
    self.select_model_btn.set_click_callback(self._show_folders)

    self.cancel_download_btn = BigButton(tr("cancel download"))
-    self.cancel_download_btn.set_click_callback(lambda: ui_state.params.remove("ModelManager_DownloadRef"))
+    self.cancel_download_btn.set_click_callback(lambda: ui_state.params.remove("ModelManager_DownloadIndex"))

    self.main_items = [self.current_model_info, self.select_model_btn, self.cancel_download_btn]
    self._scroller.add_widgets(self.main_items)
@@ -115,12 +113,11 @@ class ModelsLayoutMici(NavScroller):
    gui_app.pop_widgets_to(self)

  def _select_model(self, bundle):
-    ui_state.params.put("ModelManager_DownloadRef", bundle.ref)
+    ui_state.params.put("ModelManager_DownloadIndex", bundle.index)
    self._pop_to_main()

  def _select_default(self):
-    source = ModelFetcher.active_source(ui_state.sm["deviceState"].chestnutPresent)
-    ui_state.params.remove(ACTIVE_BUNDLE_KEYS[source])
+    ui_state.params.remove("ModelManager_ActiveBundle")
    self._pop_to_main()

  def _select_folder(self, folder_name):
@@ -165,9 +162,8 @@ class ModelsLayoutMici(NavScroller):
    self._was_downloading = is_downloading

    self.current_model_info.current_model_header.set_text(tr("active model"))
-    # read the slot through ui_state, not modelManagerSP: the manager republishes a
-    # tick after a chestnut change, and the stale bundle flashes the wrong model
-    model_text = ((ui_state.active_bundle or {}).get("displayName") or f"{get_default_model()} (Default)").lower()
+    default_model_text = f"{get_default_model()} (Default)".lower()
+    model_text = manager.activeBundle.displayName.lower() if manager.activeBundle.ref else default_model_text
    self.current_model_info.current_model_text.set_text(model_text)
    self.current_model_info.info_header.set_text(tr("cache size"))
    self.current_model_info.info_text.set_text(f"{ModelsLayout.calculate_cache_size():.2f} MB")
@@ -7,7 +7,6 @@ See the LICENSE.md file in the root directory for more details.
 import pyray as rl

 from openpilot.selfdrive.ui.mici.onroad.hud_renderer import HudRenderer
-from openpilot.selfdrive.ui.ui_state import ui_state
 from openpilot.selfdrive.ui.sunnypilot.onroad.blind_spot_indicators import BlindSpotIndicators


@@ -22,8 +21,6 @@ class HudRendererSP(HudRenderer):

  def _render(self, rect: rl.Rectangle) -> None:
    super()._render(rect)
-    if ui_state.usbgpu and not ui_state.usbgpu_compiled and ui_state.model_runner_tinygrad:
-      self._draw_model_source(rect)
    self.blind_spot_indicators.render(rect)

  def _has_blind_spot_detected(self) -> bool:
@@ -10,7 +10,6 @@ from openpilot.cereal import messaging, log, custom
 from opendbc.car.structs import car
 from openpilot.common.params import Params
 from openpilot.selfdrive.ui.sunnypilot.layouts.settings.display import OnroadBrightness
-from openpilot.sunnypilot.models.helpers import ACTIVE_BUNDLE_KEYS, get_active_source
 from openpilot.sunnypilot.sunnylink.sunnylink_state import SunnylinkState
 from openpilot.system.ui.lib.application import gui_app
 from openpilot.system.ui.sunnypilot.widgets.screen_saver import ScreenSaverSP
@@ -44,7 +43,6 @@ class UIStateSP:
    self.screensaver_enabled: bool = False

    self.active_bundle = None
-    self.model_runner_tinygrad: bool = False
    self.blindspot: bool = False
    self.chevron_metrics = None
    self.custom_interactive_timeout: int = 0
@@ -152,10 +150,7 @@ class UIStateSP:
      self.has_icbm = self.CP_SP.intelligentCruiseButtonManagementAvailable and self.params.get_bool("IntelligentCruiseButtonManagement")

    self._enforce_constraints()
-    source = get_active_source(usbgpu=self.usbgpu, usbgpu_active=self.usbgpu_active,
-                               usbgpu_loading=self.usbgpu_loading, offroad=self.is_offroad())
-    self.active_bundle = self.params.get(ACTIVE_BUNDLE_KEYS[source])
-    self.model_runner_tinygrad = self.active_bundle is not None and self.active_bundle.get("runner") == "tinygrad"
+    self.active_bundle = self.params.get("ModelManager_ActiveBundle")
    self.blindspot = self.params.get_bool("BlindSpot")
    self.chevron_metrics = self.params.get("ChevronInfo")
    self.custom_interactive_timeout = self.params.get("InteractivityTimeout", return_default=True)
@@ -112,15 +112,6 @@ class UIState(UIStateSP):
  def add_on_body_changed_callbacks(self, callback: Callable[[], None]):
    self._on_body_changed_callbacks.append(callback)

-  @property
-  def big_model_failed(self) -> bool:
-    # Mirrors the onroad HUD's four-condition check so sidebar and home icons reflect the same failure states
-    return (self.usbgpu_active is False or
-            not self.sm['deviceState'].chestnutPresent or
-            (self.usbgpu_active is True and self.sm.recv_frame['modelV2'] > self.started_frame and
-             not self.sm.alive['modelV2']) or
-            (self.usbgpu_active is None and self.sm.recv_frame['modelV2'] > self.started_frame))
-
  @property
  def engaged(self) -> bool:
    return self.started and (self.sm["selfdriveState"].enabled or self.sm["selfdriveStateSP"].mads.enabled)
@@ -7,7 +7,6 @@ See the LICENSE.md file in the root directory for more details.
 """

 import argparse
-import math
 import os
 import tempfile
 import time
@@ -67,15 +66,14 @@ def get_policy_npy_shapes(input_shapes: dict, is_supercombo: bool = False) -> tu
  if desire_key:
    shapes['desire'] = (input_shapes[desire_key][2],)

+  if is_supercombo and 'features_buffer' in input_shapes:
+    fb = input_shapes['features_buffer']
+    shapes['prev_feat'] = (fb[0], fb[2])
+
  for key, shape in input_shapes.items():
    if key not in (desire_key, 'features_buffer') and 'img' not in key:
      shapes[key] = tuple(shape)

-  if is_supercombo and 'features_buffer' in input_shapes:
-    fb = input_shapes['features_buffer']
-    feat_dim = math.prod(fb[2:])
-    shapes['prev_feat'] = (fb[0], feat_dim)
-
  sizes = [int(np.prod(size)) for size in shapes.values()]
  return shapes, sizes

@@ -119,9 +117,8 @@ def generate_queues_and_npy(input_shapes: dict, frame_skip: int, device: str = D
  }

  if features_buffer:
-    feat_dim = math.prod(features_buffer[2:])
    feat_q_len = frame_skip * features_buffer[1] if is_supercombo else frame_skip * (features_buffer[1] - 1) + 1
-    queues['feat_q'] = Tensor(np.zeros((feat_q_len, features_buffer[0], feat_dim),
+    queues['feat_q'] = Tensor(np.zeros((feat_q_len, features_buffer[0], features_buffer[2]),
                       dtype=np.float32), device=device).contiguous().realize()

  queues.update({key: Tensor(value, device='NPY').realize() for key, value in npy_arrays.items() if key in ('tfm', 'big_tfm')})
@@ -186,14 +183,14 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,
    warped_dev = warped.to(Device.DEFAULT)
    Tensor.realize(packed_npy_inputs_dev, warped_dev)

-    img = shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn)
-    big_img = shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn)
+    img = shift_and_sample(img_q, warped_dev[0:1], sample_skip_fn).realize()
+    big_img = shift_and_sample(big_img_q, warped_dev[1:2], sample_skip_fn).realize()

    unpacked_tensors = [tensor.reshape(shape) for tensor, shape in zip(packed_npy_inputs_dev.split(npy_sizes), npy_shapes.values(), strict=True)]
    unpacked_dict = dict(zip(npy_shapes.keys(), unpacked_tensors, strict=True))

    desire_dev = unpacked_dict['desire']
-    desire_buf = shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn)
+    desire_buf = shift_and_sample(desire_q, desire_dev.reshape(1, 1, -1), sample_desire_fn).realize()

    inputs = {desire_key: desire_buf}
    for key, tensor_val in unpacked_dict.items():
@@ -202,7 +199,7 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,

    if 'prev_feat' in unpacked_dict:
      prev_feat_dev = unpacked_dict['prev_feat']
-      inputs['features_buffer'] = shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn).reshape(input_shapes['features_buffer'])
+      inputs['features_buffer'] = shift_and_sample(feat_q, prev_feat_dev.reshape(1, 1, -1), sample_skip_fn).realize()

    if vision_runner:
      vision_out_cast = next(iter(vision_runner({road_key: img, wide_key: big_img}).values())).cast('float32').realize()
@@ -214,7 +211,7 @@ def make_run_policy(vision_runner, policy_runners: list, features_slice: slice,

    inputs.update({road_key: img, wide_key: big_img})
    if 'features_buffer' not in inputs:
-      inputs['features_buffer'] = sample_skip_fn(feat_q).reshape(input_shapes['features_buffer'])
+      inputs['features_buffer'] = sample_skip_fn(feat_q)

    policy_out = next(iter(policy_runners[0](inputs).values())).cast('float32').realize()
    if 'features_buffer' not in inputs and features_slice is not None:
@@ -91,7 +91,7 @@ class ModelState(ModelStateBase):
    if env_pkl and os.path.exists(env_pkl):
      model_bundle = None
    else:
-      model_bundle = get_active_bundle(usbgpu=usbgpu)
+      model_bundle = get_active_bundle()
    self.generation = model_bundle.generation if model_bundle is not None else None
    overrides = {override.key: override.value for override in model_bundle.overrides} if model_bundle else {}

@@ -190,8 +190,8 @@ def tmp_path():

 def patch_modeld(monkeypatch):
  def _patch(bundle):
-    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None, *, usbgpu=None: bundle)
-    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None, *, usbgpu=None: bundle)
+    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None: bundle)
+    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None: bundle)

  return _patch

@@ -59,8 +59,8 @@ class TestFindDrivingPkl(OpenpilotTestCase):
 class TestModelStateCombinedInit(OpenpilotTestCase):
  def test_asserts_when_no_pkl(self, monkeypatch):
    bundle = DummyBundle(models=[], is_20hz=True)
-    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None, *, usbgpu=None: bundle)
-    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None, *, usbgpu=None: bundle)
+    monkeypatch.setattr(helpers, 'get_active_bundle', lambda params=None: bundle)
+    monkeypatch.setattr(modeld_module, 'get_active_bundle', lambda params=None: bundle)
    with self.assertRaisesRegex(AssertionError, "No driving pkl found"):
      ModelState(cam_w=CAM_W, cam_h=CAM_H)

@@ -195,85 +195,3 @@ class TestReadFileChunkedToDisk(OpenpilotTestCase):

      assert out.parent == Path(d)
      assert out.read_bytes() == payload
-
-
-class Test4DFeaturesBuffer(OpenpilotTestCase):
-  def test_get_policy_npy_shapes_4d(self):
-    from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes
-    input_shapes = {
-      'desire_pulse': (1, 25, 8),
-      'features_buffer': (1, 24, 32, 512),  # compare 4d to 3d for regression
-      'traffic_convention': (1, 2),
-      'action_t': (1, 2)
-    }
-    shapes, sizes = get_policy_npy_shapes(input_shapes, is_supercombo=True)
-    assert shapes['prev_feat'] == (1, 16384)
-    assert sizes == [8, 2, 2, 16384]
-
-  def test_get_policy_npy_shapes_3d(self):
-    from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes
-    input_shapes = {
-      'desire_pulse': (1, 25, 8),
-      'features_buffer': (1, 24, 512),
-      'traffic_convention': (1, 2),
-      'action_t': (1, 2)
-    }
-    shapes, sizes = get_policy_npy_shapes(input_shapes, is_supercombo=True)
-    assert shapes['prev_feat'] == (1, 512)
-    assert sizes == [8, 2, 2, 512]
-
-
-class TestStockCompileModeldEquivalence(OpenpilotTestCase):
-  def test_get_policy_npy_shapes_matches_stock(self):
-    from openpilot.selfdrive.modeld.compile_modeld import get_policy_npy_shapes as stock_get_policy_npy_shapes
-    from openpilot.sunnypilot.modeld_v2.compile_modeld import get_policy_npy_shapes as sunny_get_policy_npy_shapes
-
-    stock_input_shapes = {
-      'desire_pulse': (1, 25, 8),
-      'features_buffer': (1, 24, 512), # see below comment
-      'traffic_convention': (1, 2),
-      'action_t': (1, 2),
-    }
-
-    stock_shapes, stock_sizes = stock_get_policy_npy_shapes(stock_input_shapes)
-    sunny_shapes, sunny_sizes = sunny_get_policy_npy_shapes(stock_input_shapes, is_supercombo=True)
-
-    assert sunny_shapes == stock_shapes
-    assert sunny_sizes == stock_sizes
-    assert sunny_shapes['prev_feat'] == (1, 512)
-
-  def test_make_input_queues_full_stock_equivalence(self):
-    from openpilot.selfdrive.modeld.compile_modeld import make_input_queues as stock_make_input_queues
-    from openpilot.sunnypilot.modeld_v2.compile_modeld import make_supercombo_input_queues as sunny_make_supercombo_input_queues
-    input_shapes = {
-      'img': (1, 12, 128, 256),
-      'desire_pulse': (1, 25, 8),
-      'features_buffer': (1, 24, 512),  # when https://github.com/commaai/openpilot/pull/38681 merges, update to 1,24,32,512
-      'traffic_convention': (1, 2),
-      'action_t': (1, 2),
-    }
-    frame_skip = 4
-
-    stock_queues, stock_npy = stock_make_input_queues(input_shapes, frame_skip, device='NPY')
-    sunny_queues, sunny_npy = sunny_make_supercombo_input_queues(input_shapes, frame_skip, device='NPY')
-    assert set(sunny_queues.keys()) == set(stock_queues.keys())
-    for key in stock_queues:
-      assert sunny_queues[key].shape == stock_queues[key].shape, \
-        f"Queue shape mismatch for {key}: sunny {sunny_queues[key].shape} != stock {stock_queues[key].shape}"
-    assert set(sunny_npy.keys()) == set(stock_npy.keys())
-    for key in stock_npy:
-      assert sunny_npy[key].shape == stock_npy[key].shape, \
-        f"Numpy array shape mismatch for {key}: sunny {sunny_npy[key].shape} != stock {stock_npy[key].shape}"
-
-  def test_make_warp_queues_stock_equivalence(self):
-    from openpilot.selfdrive.modeld.compile_modeld import make_warp_input_queues as stock_make_warp_queues
-    from openpilot.sunnypilot.modeld_v2.compile_modeld import make_warp_queues as sunny_make_warp_queues
-    stock_vision_shapes = {'img': (1, 12, 128, 256)}  # for now?
-    stock_queues, stock_npy = stock_make_warp_queues(stock_vision_shapes, frame_skip=4, device='NPY')
-    sunny_queues, sunny_npy = sunny_make_warp_queues(device='NPY')
-
-    assert set(sunny_npy.keys()) == set(stock_npy.keys()) == {'tfm', 'big_tfm'}
-    for key in sunny_npy:
-      assert sunny_npy[key].shape == stock_npy[key].shape == (3, 3)
-
-
@@ -13,6 +13,8 @@ from openpilot.common.params import Params
 from openpilot.common.swaglog import cloudlog
 from openpilot.common.hardware.hw import Paths
 from openpilot.sunnypilot.models.helpers import is_bundle_version_compatible
+from openpilot.selfdrive.modeld.helpers import usbgpu_present
+
 from openpilot.cereal import custom


@@ -138,53 +140,45 @@ class ModelCache:

 class ModelFetcher:
  """Handles fetching and caching of model data from remote source"""
-  MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v21.json"
-  MODEL_URL_USBGPU = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_usbgpu_v22.json"
-
-  MODEL_SOURCES = {
-    "qcom": (MODEL_URL, ""),
-    "usbgpu": (MODEL_URL_USBGPU, "_USBGPU"),
-  }
+  MODEL_URL = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_v20.json"
+  MODEL_URL_USBGPU = "https://raw.githubusercontent.com/sunnypilot/sunnypilot-models/refs/heads/gh-pages/docs/driving_models_usbgpu_v21.json"

  def __init__(self, params: Params):
    self.params = params
    self.model_parser = ModelParser()
-    self.model_caches = {
-      source: ModelCache(params, suffix=suffix)
-      for source, (_, suffix) in self.MODEL_SOURCES.items()
-    }
-    self._refetched: set[str] = set()
-    self.params.put("ModelManager_ActiveJson", {
-      "qcom": self.MODEL_URL,
-      "usbgpu": self.MODEL_URL_USBGPU,
-    }, block=True)
+    self._is_usbgpu: bool | None = None
+    self.model_cache = ModelCache(params)
+    self.model_url = self.MODEL_URL
+    self._update_model_source()

-  @staticmethod
-  def active_source(chestnut_present: bool) -> str:
-    return "usbgpu" if chestnut_present else "qcom"
+  def _update_model_source(self) -> None:
+    """Updates what json to use based on usbgpu availability"""
+    is_usbgpu = usbgpu_present()
+    if is_usbgpu != self._is_usbgpu:
+      self._is_usbgpu = is_usbgpu
+      self.model_cache = ModelCache(self.params, suffix="_USBGPU" if is_usbgpu else "")
+      self.model_url = self.MODEL_URL_USBGPU if is_usbgpu else self.MODEL_URL
+      self.params.put("ModelManager_ActiveJson", self.model_url, block=True)

-  def _fetch_and_cache_models(self, source: str) -> list[custom.ModelManagerSP.ModelBundle] | None:
+  def _fetch_and_cache_models(self) -> list[custom.ModelManagerSP.ModelBundle] | None:
    """Fetches fresh model data from remote and updates cache.
    Returns None on transport errors. Raises on 404 and other fatal HTTP errors.
    """
-    model_url, _ = self.MODEL_SOURCES[source]
    try:
-      response = requests.get(model_url, timeout=10)
+      response = requests.get(self.model_url, timeout=10)

      # Explicitly handle 404 differently
      if response.status_code == 404:
-        cloudlog.error(f"Models URL returned 404 Not Found: {model_url}")
-        raise HTTPError(f"404 Not Found: {model_url}", response=response)
+        cloudlog.error(f"Models URL returned 404 Not Found: {self.model_url}")
+        raise HTTPError(f"404 Not Found: {self.model_url}", response=response)

      # Raise for any other 4xx/5xx
      response.raise_for_status()

      json_data = response.json()
-      parsed = self.model_parser.parse_models(json_data)
-      if parsed:
-        self.model_caches[source].set(json_data)
-        cloudlog.debug(f"Successfully updated models cache for {source}")
-      return parsed
+      self.model_cache.set(json_data)
+      cloudlog.debug("Successfully updated models cache")
+      return self.model_parser.parse_models(json_data)

    except ConnectionError as e:
      cloudlog.warning(f"DNS/connection error while fetching models: {e}")
@@ -197,40 +191,16 @@ class ModelFetcher:

    return None

-  @staticmethod
-  def _cache_matches_source(source: str, cached_data: dict) -> bool:
-    bundles = cached_data.get("bundles", [])
-    if source == "usbgpu":
-      return any(bundle.get("is_big") is True for bundle in bundles)
-    return not any(bundle.get("is_big") is True for bundle in bundles)
-
-  def get_bundles_for_source(self, source: str) -> list[custom.ModelManagerSP.ModelBundle]:
-    if source not in self.MODEL_SOURCES:
-      cloudlog.warning(f"Unknown model source: {source}")
-      return []
-
-    cached_data, is_expired = self.model_caches[source].get()
+  def get_available_bundles(self) -> list[custom.ModelManagerSP.ModelBundle]:
+    """Gets the list of available models, with smart cache handling"""
+    self._update_model_source()
+    cached_data, is_expired = self.model_cache.get()

    if cached_data and not is_expired:
-      # a source is refetched over a mismatch at most once per process: if the fresh
-      # manifest still mismatches, the URL is authoritative and the cache is trusted
-      if self._cache_matches_source(source, cached_data) or source in self._refetched:
-        try:
-          parsed = self.model_parser.parse_models(cached_data)
-        except Exception:
-          cloudlog.warning(f"Failed to parse cached models for {source}; refetching", exc_info=True)
-        else:
-          if parsed:
-            cloudlog.debug(f"Using valid cached models data for source {source}")
-            return parsed
-          # a source-matching cache that yields no valid bundles is stale (e.g. an old
-          # manifest version) - do not trust it, refetch so the source is repopulated
-          cloudlog.warning(f"Cached models for {source} have no valid bundles; refetching")
-      else:
-        self._refetched.add(source)
-        cloudlog.warning(f"Cached models for {source} not valid; refetching once")
+      cloudlog.debug("Using valid cached models data")
+      return self.model_parser.parse_models(cached_data)

-    fetched_bundles = self._fetch_and_cache_models(source)
+    fetched_bundles = self._fetch_and_cache_models()
    if fetched_bundles is not None:
      return fetched_bundles

@@ -238,33 +208,12 @@ class ModelFetcher:
      cloudlog.warning("Failed to fetch fresh data and no cache available")

    cloudlog.warning("Failed to fetch fresh data. Using expired cache as fallback")
-    try:
-      return self.model_parser.parse_models(cached_data)
-    except Exception:
-      return []
-
-
-def get_cached_bundles(params: Params, source: str) -> list[custom.ModelManagerSP.ModelBundle]:
-
-  if source not in ModelFetcher.MODEL_SOURCES:
-    cloudlog.warning(f"Unknown model source: {source}")
-    return []
-  _, suffix = ModelFetcher.MODEL_SOURCES[source]
-  cached_data = params.get(f"ModelManager_ModelsCache{suffix}")
-  if not cached_data:
-    return []
-  try:
-    return ModelParser.parse_models(cached_data)
-  except Exception as e:
-    cloudlog.warning(f"Failed to parse cached models for source {source}: {e}")
-    return []
-
+    return self.model_parser.parse_models(cached_data)

 if __name__ == "__main__":
-  from openpilot.selfdrive.modeld.helpers import usbgpu_present
  params = Params()
  model_fetcher = ModelFetcher(params)
-  bundles = model_fetcher.get_bundles_for_source(ModelFetcher.active_source(usbgpu_present()))
+  bundles = model_fetcher.get_available_bundles()
  for bundle in bundles:
    for model in bundle.models:
      model_overrides = {override.key: override.value for override in bundle.overrides}
@@ -16,20 +16,14 @@ from openpilot.common.params import Params
 from openpilot.common.swaglog import cloudlog
 from openpilot.sunnypilot.models.constants import Meta, MetaSimPose, MetaTombRaider
 from openpilot.common.hardware.hw import Paths
-from openpilot.selfdrive.modeld.helpers import usbgpu_present

 # SET ME TO THE EXACT JSON VERSION WE SET IN SUNNYPILOT_MODELS REPO
-REQUIRED_JSON_VERSION = 18
+REQUIRED_JSON_VERSION = 17

 CUSTOM_MODEL_PATH = Paths.model_root()
 METADATA_PATH = Path(__file__).parent / '../models/supercombo_metadata.pkl'
 ModelManager = custom.ModelManagerSP
-
-ACTIVE_BUNDLE_KEYS = {
-  "qcom": "ModelManager_ActiveBundle",
-  "usbgpu": "ModelManager_ActiveBundleUSBGPU",
-}
-_LAST_VALIDATED_RAW: dict[str, dict | None] = {}
+_LAST_VALIDATED_RAW = None


 def _compute_hash(file_path: str) -> str | None:
@@ -92,11 +86,11 @@ def _bundle_needs_reset(active_bundle: custom.ModelManagerSP.ModelBundle, availa
  if available_bundles is not None:
    matching_bundle = None
    for bundle in available_bundles:
-      if active_bundle.ref and bundle.ref:
+      if getattr(active_bundle, 'ref', None) and getattr(bundle, 'ref', None):
        if active_bundle.ref == bundle.ref:
          matching_bundle = bundle
          break
-      elif active_bundle.internalName == bundle.internalName:
+      elif getattr(active_bundle, 'internalName', None) == getattr(bundle, 'internalName', None):
        matching_bundle = bundle
        break

@@ -104,79 +98,47 @@ def _bundle_needs_reset(active_bundle: custom.ModelManagerSP.ModelBundle, availa
      return True
    if active_bundle.minimumSelectorVersion != matching_bundle.minimumSelectorVersion:
      return True
-    if active_bundle.runner != matching_bundle.runner:
-      return True
+
+    active_runner = getattr(active_bundle, 'runner', None)
+    matching_runner = getattr(matching_bundle, 'runner', None)
+    if active_runner is not None and matching_runner is not None:
+      if getattr(active_runner, 'raw', active_runner) != getattr(matching_runner, 'raw', matching_runner):
+        return True
    if set(_bundle_artifacts(active_bundle)) != set(_bundle_artifacts(matching_bundle)):
      return True

  return not _bundle_is_valid_locally(active_bundle)


-def _parse_active_bundle(raw_bundle) -> "custom.ModelManagerSP.ModelBundle | None":
-  try:
-    if isinstance(raw_bundle, dict) and raw_bundle and is_bundle_version_compatible(raw_bundle):
-      return custom.ModelManagerSP.ModelBundle(**raw_bundle)
-  except Exception:
-    pass
-  return None
-
-
-def get_selected_bundle(params: Params | None = None, source: str = "qcom") -> "custom.ModelManagerSP.ModelBundle | None":
-  params = params or Params()
-  return _parse_active_bundle(params.get(ACTIVE_BUNDLE_KEYS[source]))
-
-
-def get_active_source(usbgpu: bool | None = None, usbgpu_active: bool | None = None,
-                      usbgpu_loading: bool | None = None, offroad: bool | None = None) -> str:
-  if usbgpu is None:
-    usbgpu = usbgpu_present()
-  state_valid = usbgpu_active is not None or usbgpu_loading is not None or offroad is not None
-  big_active = usbgpu and (not state_valid or usbgpu_active or usbgpu_loading or offroad)
-  return "usbgpu" if big_active else "qcom"
-
-
-def get_active_bundle(params: Params | None = None, *, usbgpu: bool | None = None) -> "custom.ModelManagerSP.ModelBundle | None":
-  # no cross-slot fallback: an empty active slot means the hardware default, which
-  # only stock modeld can run - modeld_v2 requires a real bundle
-  params = params or Params()
-  return get_selected_bundle(params, get_active_source(usbgpu=usbgpu))
-
-
-def resolve_bundle_by_ref(
-  ref: str, source_bundles: dict[str, list[custom.ModelManagerSP.ModelBundle]],
-) -> "tuple[custom.ModelManagerSP.ModelBundle, str] | None":
-  for source, bundles in source_bundles.items():
-    for bundle in bundles:
-      if bundle.ref == ref:
-        return bundle, source
-  return None
-
-
-def _validate_active_bundle(params: Params, source: str, available_bundles: list[custom.ModelManagerSP.ModelBundle] | None = None) -> None:
+def validate_active_bundle(params: Params, available_bundles: list[custom.ModelManagerSP.ModelBundle] | None = None) -> None:
  global _LAST_VALIDATED_RAW

-  key = ACTIVE_BUNDLE_KEYS[source]
-  raw_bundle = params.get(key)
+  raw_bundle = params.get("ModelManager_ActiveBundle")
  if not raw_bundle:
    return

-  if _LAST_VALIDATED_RAW.get(key) == raw_bundle:
+  if raw_bundle == _LAST_VALIDATED_RAW:
    return

-  active_bundle = _parse_active_bundle(raw_bundle)
+  active_bundle = get_active_bundle(params, raw_bundle_dict=raw_bundle)
  if active_bundle is None or _bundle_needs_reset(active_bundle, available_bundles):
-    cloudlog.warning(f"Active model bundle invalid for {source}; resetting to default")
-    params.remove(key)
-    _LAST_VALIDATED_RAW[key] = None
+    cloudlog.warning("Active model bundle invalid; resetting to default")
+    params.remove("ModelManager_ActiveBundle")
+    params.put("ModelRunnerTypeCache", int(custom.ModelManagerSP.Runner.stock), block=True)
+    _LAST_VALIDATED_RAW = None
  else:
-    _LAST_VALIDATED_RAW[key] = raw_bundle
+    _LAST_VALIDATED_RAW = raw_bundle


-def validate_active_bundles(params: Params, source_bundles: dict[str, list[custom.ModelManagerSP.ModelBundle]]) -> None:
-  # an empty list means the fetch failed, not that the catalog dropped the bundle
-  for source, bundles in source_bundles.items():
-    _validate_active_bundle(params, source, bundles or None)
-  get_active_model_runner(params, force_check=True)
+def get_active_bundle(params: Params | None = None, raw_bundle_dict: dict | bytes | None = None) -> "custom.ModelManagerSP.ModelBundle | None":
+  params = params or Params()
+  try:
+    active_bundle_dict = raw_bundle_dict if raw_bundle_dict is not None else (params.get("ModelManager_ActiveBundle") or {})
+    if isinstance(active_bundle_dict, dict) and active_bundle_dict and is_bundle_version_compatible(active_bundle_dict):
+      return custom.ModelManagerSP.ModelBundle(**active_bundle_dict)
+  except Exception:
+    pass
+  return None


 def get_active_model_runner(params: Params | None = None, force_check: bool = False) -> int:
@@ -17,8 +17,7 @@ from openpilot.common.hardware.hw import Paths

 from openpilot.cereal import messaging, custom
 from openpilot.sunnypilot.models.fetcher import ModelFetcher
-from openpilot.sunnypilot.models.helpers import (ACTIVE_BUNDLE_KEYS, get_active_bundle, get_selected_bundle,
-                                                  resolve_bundle_by_ref, validate_active_bundles, verify_file)
+from openpilot.sunnypilot.models.helpers import get_active_bundle, validate_active_bundle, verify_file

 # (connect, read) seconds. read is per-request inactivity, not a total cap
 DOWNLOAD_TIMEOUT = (30, 30)
@@ -31,12 +30,9 @@ class ModelManagerSP:
    self.params = Params()
    self.model_fetcher = ModelFetcher(self.params)
    self.pm = messaging.PubMaster(["modelManagerSP"])
-    self.sm = messaging.SubMaster(["deviceState"])
-    self.chestnut_present = False
    self.available_models: list[custom.ModelManagerSP.ModelBundle] = []
-    self.source_models: dict[str, list[custom.ModelManagerSP.ModelBundle]] = {}
    self.selected_bundle: custom.ModelManagerSP.ModelBundle = None
-    self.active_bundle: custom.ModelManagerSP.ModelBundle = get_active_bundle(self.params, usbgpu=self.chestnut_present)
+    self.active_bundle: custom.ModelManagerSP.ModelBundle = get_active_bundle(self.params)
    self._chunk_size = 128 * 1000  # 128 KB chunks
    self._download_start_times: dict[str, float] = {}  # Track start time per model

@@ -80,7 +76,7 @@ class ModelManagerSP:
          f.write(chunk)
          bytes_downloaded += len(chunk)

-          if self.params.get("ModelManager_DownloadRef") is None:
+          if self.params.get("ModelManager_DownloadIndex") is None:
            raise Exception("Download cancelled")

          if total_size > 0:
@@ -118,7 +114,7 @@ class ModelManagerSP:
            for data in response.iter_content(chunk_size=self._chunk_size):
              f.write(data)
              chunk_downloaded += len(data)
-              if self.params.get("ModelManager_DownloadRef") is None:
+              if self.params.get("ModelManager_DownloadIndex") is None:
                raise Exception("Download cancelled")
              intra = chunk_downloaded / max(chunk_size, 1)
              progress = min(99.0, ((i + intra) / num_chunks) * 100)
@@ -220,7 +216,8 @@ class ModelManagerSP:
    model_manager_state.availableBundles = self.available_models
    self.pm.send('modelManagerSP', msg)

-  async def _download_bundle(self, model_bundle: custom.ModelManagerSP.ModelBundle, destination_path: str, source: str) -> None:
+  async def _download_bundle(self, model_bundle: custom.ModelManagerSP.ModelBundle, destination_path: str) -> None:
+    """Downloads all models in a bundle"""
    self.selected_bundle = model_bundle
    self.selected_bundle.status = custom.ModelManagerSP.DownloadStatus.downloading
    for model in self.selected_bundle.models:
@@ -242,9 +239,10 @@ class ModelManagerSP:
          seen_artifacts.add(artifact.fileName)
          await self._process_artifact(artifact, destination_path)

-      self.selected_bundle.status = custom.ModelManagerSP.DownloadStatus.downloaded
-      self.params.put(ACTIVE_BUNDLE_KEYS[source], model_bundle.to_dict(), block=True)
-      self.active_bundle = get_active_bundle(self.params, usbgpu=self.chestnut_present)
+      self.active_bundle = self.selected_bundle
+      self.active_bundle.status = custom.ModelManagerSP.DownloadStatus.downloaded
+      self.params.put("ModelManager_ActiveBundle", self.active_bundle.to_dict(), block=True)
+      self.selected_bundle = None

    except Exception:
      if self.selected_bundle is not None:
@@ -254,9 +252,9 @@ class ModelManagerSP:
    finally:
      self._report_status()

-  def download(self, model_bundle: custom.ModelManagerSP.ModelBundle, destination_path: str, source: str) -> None:
+  def download(self, model_bundle: custom.ModelManagerSP.ModelBundle, destination_path: str) -> None:
    """Main entry point for downloading a model bundle"""
-    asyncio.run(self._download_bundle(model_bundle, destination_path, source))
+    asyncio.run(self._download_bundle(model_bundle, destination_path))

  def main_thread(self) -> None:
    """Main thread for model management"""
@@ -264,22 +262,20 @@ class ModelManagerSP:

    while True:
      try:
-        self.sm.update(0)
-        self.chestnut_present = self.sm['deviceState'].chestnutPresent
-        self.source_models = {source: self.model_fetcher.get_bundles_for_source(source) for source in ModelFetcher.MODEL_SOURCES}
-        self.available_models = self.source_models[ModelFetcher.active_source(self.chestnut_present)]
-        validate_active_bundles(self.params, self.source_models)
-        self.active_bundle = get_active_bundle(self.params, usbgpu=self.chestnut_present)
+        self.available_models = self.model_fetcher.get_available_bundles()
+        validate_active_bundle(self.params, self.available_models)
+        self.active_bundle = get_active_bundle(self.params)

-        if (ref_to_download := self.params.get("ModelManager_DownloadRef")) is not None:
-          if resolved := resolve_bundle_by_ref(ref_to_download, self.source_models):
-            model_to_download, source = resolved
+        if (index_to_download := self.params.get("ModelManager_DownloadIndex")) is not None:
+          if self.active_bundle and self.active_bundle.index == index_to_download:
+            self.params.remove("ModelManager_DownloadIndex")
+          elif model_to_download := next((model for model in self.available_models if model.index == index_to_download), None):
            try:
-              self.download(model_to_download, Paths.model_root(), source)
+              self.download(model_to_download, Paths.model_root())
            except Exception as e:
              cloudlog.exception(e)
            finally:
-              self.params.remove("ModelManager_DownloadRef")
+              self.params.remove("ModelManager_DownloadIndex")
              self.selected_bundle = None

        if self.params.get("ModelManager_ClearCache"):
@@ -298,14 +294,12 @@ class ModelManagerSP:
    Clears the model cache directory of all files except those in the active model bundle.
    """

-    # Get list of files used by both slots' selected bundles (either may become
-    # the truly active bundle depending on hardware availability)
+    # Get list of files used by active model bundle
    active_files = []
-    for source in ACTIVE_BUNDLE_KEYS:
-      if selected_bundle := get_selected_bundle(self.params, source):
-        for model in selected_bundle.models:
-          if model.artifact.fileName:
-            active_files.append(model.artifact.fileName)
+    if self.active_bundle is not None: # When the default model is active
+      for model in self.active_bundle.models:
+        if hasattr(model, 'artifact') and model.artifact.fileName:
+          active_files.append(model.artifact.fileName)

    # Remove all files except active ones (including their chunk files)
    model_dir = Paths.model_root()
@@ -11,7 +11,6 @@ import http.server
 import os
 import tempfile
 import threading
-import time
 import unittest
 from typing import Any
 from unittest import mock
@@ -24,10 +23,6 @@ from openpilot.common.test import OpenpilotTestCase
 from openpilot.common.file_chunker import get_chunk_name, get_manifest_path
 from openpilot.selfdrive.test.helpers import http_server_context
 from openpilot.sunnypilot.models import manager as manager_module
-from openpilot.sunnypilot.models.fetcher import ModelFetcher, get_cached_bundles
-from openpilot.sunnypilot.models import helpers
-from openpilot.sunnypilot.models.helpers import (get_active_bundle, get_active_source, get_selected_bundle,
-                                                  resolve_bundle_by_ref, validate_active_bundles)
 from openpilot.sunnypilot.models.manager import ModelManagerSP

 CHUNK_BODIES = [b'A' * 5000, b'B' * 5000, b'C' * 3000]
@@ -108,7 +103,6 @@ class ManagerDownloadTestBase(OpenpilotTestCase):
    self.manager.selected_bundle = None
    self.manager.active_bundle = None
    self.manager.available_models = []
-    self.manager.chestnut_present = False
    self.manager._chunk_size = 1024
    self.manager._download_start_times = {}

@@ -255,85 +249,6 @@ class TestManagerDownload(ManagerDownloadTestBase):
        assert self.manager._download_start_times == {}
    self.run_with_server(body)

-  def test_download_ref_present_keeps_download_alive(self):
-    """A pending download request (DownloadRef set) must not be cancelled mid-transfer."""
-    def body():
-      artifact = self.make_artifact(chunked=True)
-      base_path = os.path.join(self.dest, artifact.fileName)
-      self.manager.params.get.side_effect = lambda key: b"ref" if key == "ModelManager_DownloadRef" else None
-      asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
-      assert os.path.isfile(get_manifest_path(base_path))
-    self.run_with_server(body)
-
-  def test_cancellation_via_download_ref(self):
-    """Removing DownloadRef mid-transfer cancels the download."""
-    def body():
-      artifact = self.make_artifact(chunked=True)
-      base_path = os.path.join(self.dest, artifact.fileName)
-      checks = {"n": 0}
-
-      def get(key):
-        if key == "ModelManager_DownloadRef":
-          checks["n"] += 1
-          return b"ref" if checks["n"] <= 2 else None
-        return b"0"
-
-      self.manager.params.get.side_effect = get
-      with self.assertRaises(Exception) as ctx:
-        asyncio.run(self.manager._download_chunked(artifact.downloadUri.uri, base_path, artifact))
-      assert 'cancelled' in str(ctx.exception).lower()
-      assert not os.path.isfile(get_manifest_path(base_path))
-    self.run_with_server(body)
-
-  def _make_params_with_store(self):
-    params = mock.MagicMock()
-    store = {}
-
-    def get(key, *args, **kwargs):
-      return store.get(key, b"0")  # b"0" -> download not cancelled
-
-    def put(key, value, *args, **kwargs):
-      store[key] = value
-
-    params.get.side_effect = get
-    params.put.side_effect = put
-    return params, store
-
-  def test_download_writes_qcom_slot(self):
-    """A download resolved to the qcom source writes the qcom active bundle slot only."""
-    def body():
-      artifact = self.make_artifact(chunked=True)
-      self._bundle.ref = "test-ref"
-      self._bundle.minimumSelectorVersion = 18
-      params, store = self._make_params_with_store()
-      self.manager.params = params
-      asyncio.run(self.manager._download_bundle(self._bundle, self.dest, "qcom"))
-
-      assert "ModelManager_ActiveBundle" in store, "qcom download must write the qcom slot"
-      assert "ModelManager_ActiveBundleUSBGPU" not in store, "qcom download must not touch the usbgpu slot"
-      assert self.manager.selected_bundle.status == custom.ModelManagerSP.DownloadStatus.downloaded
-      assert self.manager.active_bundle is not None and self.manager.active_bundle.ref == "test-ref"
-      assert self.manager.active_bundle.status == custom.ModelManagerSP.DownloadStatus.downloaded
-      chunk_names = [get_chunk_name(artifact.fileName, i, len(artifact.chunks)) for i in range(len(artifact.chunks))]
-      missing = [c for c in chunk_names if not os.path.isfile(os.path.join(self.dest, c))]
-      assert missing == [], f"chunks missing from the cache: {missing}"
-    self.run_with_server(body)
-
-  def test_download_writes_usbgpu_slot(self):
-    """A download resolved to the usbgpu source writes the usbgpu active bundle slot only."""
-    def body():
-      self.make_artifact(chunked=True)
-      self._bundle.ref = "big-ref"
-      self._bundle.minimumSelectorVersion = 18
-      params, store = self._make_params_with_store()
-      self.manager.params = params
-      asyncio.run(self.manager._download_bundle(self._bundle, self.dest, "usbgpu"))
-
-      assert "ModelManager_ActiveBundleUSBGPU" in store, "usbgpu download must write the usbgpu slot"
-      assert "ModelManager_ActiveBundle" not in store, "usbgpu download must not touch the qcom slot"
-      assert self.manager.selected_bundle.status == custom.ModelManagerSP.DownloadStatus.downloaded
-    self.run_with_server(body)
-

 class TestManagerImports(OpenpilotTestCase):
  """Catches undeclared dependencies. aiohttp lived only in the AGNOS venv; 19.6 dropped
@@ -352,352 +267,6 @@ class TestManagerImports(OpenpilotTestCase):
    assert connect > 0 and read > 0, "requests defaults to no timeout; downloads would hang forever"


-class TestResolveBundleByRef(OpenpilotTestCase):
-  """A ref resolves to (bundle, source) across both hardware manifests. Refs are
-  unique per manifest and never overlap across sources, so a ref maps to exactly
-  one slot. Shared by the manager's download flow and the settings UI."""
-
-  @staticmethod
-  def _bundle(ref: str):
-    bundle = custom.ModelManagerSP.ModelBundle.new_message()
-    bundle.ref = ref
-    return bundle
-
-  def test_qcom_ref_resolves_to_qcom_slot(self):
-    small = self._bundle("small")
-    assert resolve_bundle_by_ref("small", {"qcom": [small], "usbgpu": []}) == (small, "qcom")
-
-  def test_usbgpu_ref_resolves_to_usbgpu_slot(self):
-    big = self._bundle("big")
-    assert resolve_bundle_by_ref("big", {"qcom": [], "usbgpu": [big]}) == (big, "usbgpu")
-
-  def test_unknown_ref_returns_none(self):
-    source_bundles = {"qcom": [self._bundle("small")], "usbgpu": []}
-    assert resolve_bundle_by_ref("nope", source_bundles) is None
-
-
-def manifest_bundle(short_name: str, ref: str, index: int = 0, is_big: bool = False) -> dict:
-  """Minimal manifest bundle dict, version-compatible (no chunks to avoid disk side effects).
-  Big (usbgpu) bundles carry `is_big: true` in the manifest JSON."""
-  return {
-    "index": index,
-    "short_name": short_name,
-    "display_name": short_name.upper(),
-    "generation": 1,
-    "environment": "release",
-    "runner": "tinygrad",
-    "is_big": is_big,
-    "minimum_selector_version": "18",
-    "ref": ref,
-    "models": [{
-      "type": "supercombo",
-      "artifact": {
-        "file_name": f"{short_name}.pkl",
-        "download_uri": {"url": f"https://example.com/{short_name}.pkl", "sha256": "s"},
-      },
-    }],
-  }
-
-
-def fresh_sync_time() -> int:
-  return int(time.monotonic() * 1e9)
-
-
-class TestModelFetcherSources(OpenpilotTestCase):
-  """Both manifests are always maintained: get_bundles_for_source exposes either
-  source by name, and active_source picks which one matches the attached hardware."""
-
-  def _make_params(self, qcom_manifest, usbgpu_manifest):
-    params = mock.MagicMock()
-
-    def get(key):
-      if key == "ModelManager_ModelsCache":
-        return qcom_manifest
-      if key == "ModelManager_ModelsCache_USBGPU":
-        return usbgpu_manifest
-      if key in ("ModelManager_LastSyncTime", "ModelManager_LastSyncTime_USBGPU"):
-        return fresh_sync_time()
-      return None
-
-    params.get.side_effect = get
-    return params
-
-  def test_active_source_follows_chestnut_presence(self):
-    assert ModelFetcher.active_source(False) == "qcom"
-    assert ModelFetcher.active_source(True) == "usbgpu"
-
-  def test_get_bundles_for_source_returns_each_source(self):
-    params = self._make_params({"bundles": [manifest_bundle("small", "aaa")]},
-                               {"bundles": [manifest_bundle("big", "bbb", is_big=True)]})
-    fetcher = ModelFetcher(params)
-    assert [bundle.ref for bundle in fetcher.get_bundles_for_source("qcom")] == ["aaa"]
-    assert [bundle.ref for bundle in fetcher.get_bundles_for_source("usbgpu")] == ["bbb"]
-
-  def test_get_bundles_for_source_unknown(self):
-    assert ModelFetcher(mock.MagicMock()).get_bundles_for_source("bogus") == []
-
-  def test_get_cached_bundles_parses_source(self):
-    params = self._make_params({"bundles": [manifest_bundle("small", "aaa")]},
-                               {"bundles": [manifest_bundle("big", "bbb", is_big=True)]})
-    qcom_bundles = get_cached_bundles(params, "qcom")
-    usbgpu_bundles = get_cached_bundles(params, "usbgpu")
-    assert [b.ref for b in qcom_bundles] == ["aaa"]
-    assert [b.ref for b in usbgpu_bundles] == ["bbb"]
-    assert qcom_bundles[0].displayName == "SMALL"
-
-  def test_get_cached_bundles_empty_when_missing(self):
-    params = mock.MagicMock()
-    params.get.return_value = None
-    assert get_cached_bundles(params, "qcom") == []
-    assert get_cached_bundles(params, "usbgpu") == []
-
-  def test_get_cached_bundles_unknown_source(self):
-    assert get_cached_bundles(mock.MagicMock(), "bogus") == []
-
-  def test_active_json_has_both_urls(self):
-    params = mock.MagicMock()
-    ModelFetcher(params)
-    active_json_calls = [call for call in params.put.call_args_list if call.args[0] == "ModelManager_ActiveJson"]
-    assert active_json_calls, "expected ModelManager_ActiveJson to be written"
-    assert active_json_calls[-1].args[1] == {
-      "qcom": ModelFetcher.MODEL_URL,
-      "usbgpu": ModelFetcher.MODEL_URL_USBGPU,
-    }
-
-
-
-class TestSourceCacheIntegrity(OpenpilotTestCase):
-  """Each source's cached manifest must contain only that source's models; the
-  `is_big` flag in the JSON marks the big (usbgpu) models. A mismatched cache is
-  legacy data from before the per-source split (the active manifest was cached
-  under the unsuffixed key regardless of hardware) and is refetched. This
-  replaces the old one-time bundle migration."""
-
-  def _make_params(self, qcom_manifest, usbgpu_manifest):
-    params = mock.MagicMock()
-
-    def get(key):
-      if key == "ModelManager_ModelsCache":
-        return qcom_manifest
-      if key == "ModelManager_ModelsCache_USBGPU":
-        return usbgpu_manifest
-      if key in ("ModelManager_LastSyncTime", "ModelManager_LastSyncTime_USBGPU"):
-        return fresh_sync_time()
-      return None
-
-    params.get.side_effect = get
-    return params
-
-  def _fetched(self, *bundles):
-    return ModelFetcher(mock.MagicMock()).model_parser.parse_models({"bundles": list(bundles)})
-
-  def test_qcom_cache_with_big_models_is_refetched(self):
-    """Legacy: the unsuffixed cache holds the big manifest. is_big confirms it is
-    the wrong set for qcom, so a fresh fetch replaces it."""
-    params = self._make_params({"bundles": [manifest_bundle("big", "bbb", is_big=True)]},
-                               {"bundles": [manifest_bundle("big2", "ccc", is_big=True)]})
-    fetcher = ModelFetcher(params)
-    fetched = self._fetched(manifest_bundle("small", "aaa"))
-    with mock.patch.object(fetcher, "_fetch_and_cache_models", return_value=fetched):
-      bundles = fetcher.get_bundles_for_source("qcom")
-    assert [bundle.ref for bundle in bundles] == ["aaa"]
-
-  def test_usbgpu_cache_without_big_models_is_refetched(self):
-    params = self._make_params({"bundles": [manifest_bundle("small", "aaa")]},
-                               {"bundles": [manifest_bundle("big2", "ccc")]})
-    fetcher = ModelFetcher(params)
-    fetched = self._fetched(manifest_bundle("big", "bbb", is_big=True))
-    with mock.patch.object(fetcher, "_fetch_and_cache_models", return_value=fetched):
-      bundles = fetcher.get_bundles_for_source("usbgpu")
-    assert [bundle.ref for bundle in bundles] == ["bbb"]
-
-  def test_matching_caches_are_used_without_fetch(self):
-    params = self._make_params({"bundles": [manifest_bundle("small", "aaa")]},
-                               {"bundles": [manifest_bundle("big", "bbb", is_big=True)]})
-    fetcher = ModelFetcher(params)
-    with mock.patch.object(fetcher, "_fetch_and_cache_models", side_effect=AssertionError("cache should be used")):
-      assert [bundle.ref for bundle in fetcher.get_bundles_for_source("qcom")] == ["aaa"]
-      assert [bundle.ref for bundle in fetcher.get_bundles_for_source("usbgpu")] == ["bbb"]
-
-  def test_stale_version_cache_is_refetched(self):
-    """A source-matching cache whose bundles are all filtered by the selector version
-    check parses to zero valid bundles; it is stale (e.g. an old manifest) and must be
-    refetched instead of silently returning an empty list forever."""
-    stale = manifest_bundle("small", "aaa")
-    stale["minimum_selector_version"] = "16"
-    params = self._make_params({"bundles": [stale]},
-                               {"bundles": [manifest_bundle("big", "bbb", is_big=True)]})
-    fetcher = ModelFetcher(params)
-    fetched = self._fetched(manifest_bundle("small2", "ddd"))
-    with mock.patch.object(fetcher, "_fetch_and_cache_models", return_value=fetched) as fetch:
-      bundles = fetcher.get_bundles_for_source("qcom")
-    fetch.assert_called_once_with("qcom")
-    assert [bundle.ref for bundle in bundles] == ["ddd"]
-
-  def test_mismatched_refetch_happens_once(self):
-    """If the fresh manifest still fails the source check, the URL is authoritative:
-    trust it instead of refetching at 1 Hz forever."""
-    params = self._make_params({"bundles": [manifest_bundle("big", "bbb", is_big=True)]},
-                               {"bundles": [manifest_bundle("big2", "ccc", is_big=True)]})
-    fetcher = ModelFetcher(params)
-    fetched = self._fetched(manifest_bundle("big", "bbb", is_big=True))
-    with mock.patch.object(fetcher, "_fetch_and_cache_models", return_value=fetched) as fetch:
-      first = fetcher.get_bundles_for_source("qcom")
-      second = fetcher.get_bundles_for_source("qcom")
-    fetch.assert_called_once_with("qcom")
-    assert [bundle.ref for bundle in first] == ["bbb"]
-    assert [bundle.ref for bundle in second] == ["bbb"]
-
-  def test_corrupt_cache_is_refetched(self):
-    """A cache that fails to parse (e.g. truncated/foreign JSON) must trigger a
-    refetch instead of raising every loop and never recovering."""
-    corrupt = {"bundles": [{"short_name": "broken"}]}  # missing required fields
-    params = self._make_params(corrupt, {"bundles": [manifest_bundle("big", "bbb", is_big=True)]})
-    fetcher = ModelFetcher(params)
-    fetched = self._fetched(manifest_bundle("small", "aaa"))
-    with mock.patch.object(fetcher, "_fetch_and_cache_models", return_value=fetched) as fetch:
-      bundles = fetcher.get_bundles_for_source("qcom")
-    fetch.assert_called_once_with("qcom")
-    assert [bundle.ref for bundle in bundles] == ["aaa"]
-
-
-class TestActiveBundleValidation(OpenpilotTestCase):
-  """Validation is per-slot: a failed fetch (empty bundle list) must not reset a slot,
-  and resetting one slot must not stomp the runner cache derived from the other."""
-
-  def setUp(self):
-    super().setUp()
-    helpers._LAST_VALIDATED_RAW.clear()
-
-  @staticmethod
-  def _raw_bundle(ref: str, runner: int | None = None) -> dict:
-    bundle = custom.ModelManagerSP.ModelBundle.new_message()
-    bundle.ref = ref
-    bundle.minimumSelectorVersion = 18
-    if runner is not None:
-      bundle.runner = runner
-    return bundle.to_dict()
-
-  def _params(self, qcom=None, usbgpu=None):
-    params = mock.MagicMock()
-
-    def get(key, *args, **kwargs):
-      return {"ModelManager_ActiveBundle": qcom, "ModelManager_ActiveBundleUSBGPU": usbgpu}.get(key)
-
-    params.get.side_effect = get
-    return params
-
-  def test_empty_catalog_does_not_reset_slot(self):
-    params = self._params(qcom=self._raw_bundle("small"))
-    with mock.patch("openpilot.sunnypilot.models.helpers.usbgpu_present", return_value=False):
-      validate_active_bundles(params, {"qcom": [], "usbgpu": []})
-    params.remove.assert_not_called()
-
-  def test_reset_recomputes_runner_from_surviving_slot(self):
-    tinygrad = int(custom.ModelManagerSP.Runner.tinygrad)
-    big_raw = self._raw_bundle("big", runner=tinygrad)
-    params = self._params(qcom=self._raw_bundle("gone"), usbgpu=big_raw)
-    catalog = {"qcom": [custom.ModelManagerSP.ModelBundle(**self._raw_bundle("other"))],
-               "usbgpu": [custom.ModelManagerSP.ModelBundle(**big_raw)]}
-    with mock.patch("openpilot.sunnypilot.models.helpers.usbgpu_present", return_value=True):
-      validate_active_bundles(params, catalog)
-    params.remove.assert_called_once_with("ModelManager_ActiveBundle")
-    runner_puts = [call for call in params.put.call_args_list if call.args[0] == "ModelRunnerTypeCache"]
-    assert [call.args[1] for call in runner_puts] == [tinygrad]
-
-
-class TestActiveBundleSelection(OpenpilotTestCase):
-  """The effective active bundle is the active source's slot: usbgpu when a GPU is
-  present, qcom otherwise. An empty active slot means the hardware default (stock
-  runner), never the other slot's pick - modeld_v2 requires a real bundle."""
-
-  @staticmethod
-  def _raw_bundle(ref: str) -> dict:
-    bundle = custom.ModelManagerSP.ModelBundle.new_message()
-    bundle.ref = ref
-    bundle.minimumSelectorVersion = 18
-    return bundle.to_dict()
-
-  def _params(self, qcom=None, usbgpu=None):
-    params = mock.MagicMock()
-
-    def get(key, *args, **kwargs):
-      if key == "ModelManager_ActiveBundle":
-        return qcom
-      if key == "ModelManager_ActiveBundleUSBGPU":
-        return usbgpu
-      return None
-
-    params.get.side_effect = get
-    return params
-
-  def test_selected_bundle_is_per_slot(self):
-    params = self._params(qcom=self._raw_bundle("small"), usbgpu=self._raw_bundle("big"))
-    assert get_selected_bundle(params, "qcom").ref == "small"
-    assert get_selected_bundle(params, "usbgpu").ref == "big"
-
-  def test_no_gpu_uses_qcom_slot(self):
-    params = self._params(qcom=self._raw_bundle("small"), usbgpu=self._raw_bundle("big"))
-    with mock.patch("openpilot.sunnypilot.models.helpers.usbgpu_present", return_value=False):
-      assert get_active_bundle(params).ref == "small"
-
-  def test_gpu_uses_usbgpu_slot(self):
-    params = self._params(qcom=self._raw_bundle("small"), usbgpu=self._raw_bundle("big"))
-    with mock.patch("openpilot.sunnypilot.models.helpers.usbgpu_present", return_value=True):
-      assert get_active_bundle(params).ref == "big"
-
-  def test_gpu_without_big_selection_is_hardware_default(self):
-    params = self._params(qcom=self._raw_bundle("small"), usbgpu=None)
-    with mock.patch("openpilot.sunnypilot.models.helpers.usbgpu_present", return_value=True):
-      assert get_active_bundle(params) is None
-
-
-class TestEffectiveSource(OpenpilotTestCase):
-  """One gate decides the active source. With no flags it is runtime truth (GPU
-  attached); display callers (mici) pass the ui_state flags, which additionally
-  require the big model to be loading, active, or the device offroad. The active
-  bundle is simply the selected bundle of that source."""
-
-  @staticmethod
-  def _raw_bundle(ref: str) -> dict:
-    bundle = custom.ModelManagerSP.ModelBundle.new_message()
-    bundle.ref = ref
-    bundle.minimumSelectorVersion = 18
-    return bundle.to_dict()
-
-  def test_runtime_no_gpu(self):
-    with mock.patch("openpilot.sunnypilot.models.helpers.usbgpu_present", return_value=False):
-      assert get_active_source() == "qcom"
-
-  def test_runtime_gpu_present(self):
-    with mock.patch("openpilot.sunnypilot.models.helpers.usbgpu_present", return_value=True):
-      assert get_active_source() == "usbgpu"
-
-  def test_display_offroad_gpu_present_shows_big(self):
-    assert get_active_source(usbgpu=True, usbgpu_active=False, usbgpu_loading=False, offroad=True) == "usbgpu"
-
-  def test_display_onroad_gpu_loading_shows_big(self):
-    assert get_active_source(usbgpu=True, usbgpu_active=False, usbgpu_loading=True, offroad=False) == "usbgpu"
-
-  def test_display_onroad_gpu_active_shows_big(self):
-    assert get_active_source(usbgpu=True, usbgpu_active=True, usbgpu_loading=False, offroad=False) == "usbgpu"
-
-  def test_display_onroad_gpu_idle_shows_small(self):
-    assert get_active_source(usbgpu=True, usbgpu_active=False, usbgpu_loading=False, offroad=False) == "qcom"
-
-  def test_display_active_none_is_idle(self):
-    assert get_active_source(usbgpu=True, usbgpu_active=None, usbgpu_loading=False, offroad=False) == "qcom"
-
-  def test_active_bundle_follows_source(self):
-    params = mock.MagicMock()
-    params.get.side_effect = lambda key: {"ModelManager_ActiveBundle": self._raw_bundle("small"),
-                                          "ModelManager_ActiveBundleUSBGPU": self._raw_bundle("big")}.get(key)
-    with mock.patch("openpilot.sunnypilot.models.helpers.usbgpu_present", return_value=False):
-      assert get_active_bundle(params).ref == "small"
-    assert get_selected_bundle(params, get_active_source(usbgpu=True, usbgpu_active=False,
-                                                         usbgpu_loading=False, offroad=True)).ref == "big"
-
-
@unittest.skipUnless(os.environ.get('RUN_INTEGRATION_TESTS'), 'requires external network')
 class TestLiveModelManifest(OpenpilotTestCase):
  """Every artifact and chunk URL in the published manifest must resolve."""
@@ -1,11 +1,13 @@
 import requests

+from openpilot.common.params import Params
 from openpilot.sunnypilot.models.tinygrad_ref import get_tinygrad_ref
 from openpilot.sunnypilot.models.fetcher import ModelFetcher
 from openpilot.common.test import OpenpilotTestCase

 def fetch_tinygrad_ref():
-  response = requests.get(ModelFetcher.MODEL_URL, timeout=10)
+  fetcher = ModelFetcher(Params())
+  response = requests.get(fetcher.model_url, timeout=10)
  response.raise_for_status()
  json_data = response.json()
  return json_data.get("tinygrad_ref")
@@ -28,6 +28,7 @@ from websocket import (ABNF, WebSocket, WebSocketException, WebSocketTimeoutExce
                       create_connection, WebSocketConnectionClosedException)

 import openpilot.cereal.messaging as messaging
+from openpilot.selfdrive.modeld.helpers import usbgpu_present
 from openpilot.sunnypilot.models.model_name import DEFAULT_MODEL, DEFAULT_BIG_MODEL
 from openpilot.sunnypilot.selfdrive.car.sync_sunnylink_params import update_car_list_param
 from openpilot.sunnypilot.sunnylink.api import SunnylinkApi
@@ -181,8 +182,10 @@ def getParamsMetadata() -> str:
    schema = generate_schema()
    schema["capabilities"] = generate_capabilities()
    schema["capability_labels"] = CAPABILITY_LABELS
-    schema["default_model"] = DEFAULT_MODEL
-    schema["default_big_model"] = DEFAULT_BIG_MODEL
+    # mirrors get_default_model() — ui_state unavailable in sunnylinkd process
+    show_big = (usbgpu_present()
+                and (params.get_bool("UsbGpuActive") or params.get_bool("UsbGpuLoading") or params.get_bool("IsOffroad")))
+    schema["default_model"] = DEFAULT_BIG_MODEL if show_big else DEFAULT_MODEL
    schema["usbgpu_active"] = params.get_bool("UsbGpuActive")
    raw = json.dumps(schema, separators=(",", ":")).encode("utf-8")
    return base64.b64encode(gzip.compress(raw)).decode("utf-8")
@@ -65,7 +65,6 @@ def sp_stats(end_event):
    'MadsSteeringMode',
    'MadsUnifiedEngagementMode',
    'ModelManager_ActiveBundle',
-    'ModelManager_ActiveBundleUSBGPU',
    'ModelManager_Favs',
    'EnableSunnylinkUploader',
    'SunnylinkEnabled',
@@ -84,21 +84,6 @@ def _migrate_tesla_mads_screen_button(_params):
    cloudlog.exception(f"Error migrating TeslaMadsScreenButton: {e}")


-def _migrate_model_bundle_slots(_params):
-  # Pre-split, a chestnut user's big-model selection lived in the single
-  # ActiveBundle. Seed both slots; validation drops whichever does not match
-  # its own manifest.
-  try:
-    if _params.get("ModelManager_ActiveBundleUSBGPU") is not None:
-      return
-    if (bundle := _params.get("ModelManager_ActiveBundle")) is None:
-      return
-    _params.put("ModelManager_ActiveBundleUSBGPU", bundle, block=True)
-    cloudlog.info("params_migration: seeded ModelManager_ActiveBundleUSBGPU from ModelManager_ActiveBundle")
-  except Exception as e:
-    cloudlog.exception(f"Error migrating model bundle slots: {e}")
-
-
 def run_migration(_params):
  # migrate OnroadScreenOffBrightness
  if _params.get("OnroadScreenOffBrightnessMigrated") != ONROAD_BRIGHTNESS_MIGRATION_VERSION:
@@ -135,6 +120,3 @@ def run_migration(_params):

  # seed TeslaMadsScreenButton for existing Tesla installs
  _migrate_tesla_mads_screen_button(_params)
-
-  # seed the usbgpu model slot from the pre-split single slot
-  _migrate_model_bundle_slots(_params)
@@ -1,36 +0,0 @@
-"""
-Copyright (c) 2021-, Haibin Wen, sunnypilot, and a number of other contributors.
-
-This file is part of sunnypilot and is licensed under the MIT License.
-See the LICENSE.md file in the root directory for more details.
-"""
-
-from openpilot.common.params import Params
-from openpilot.common.test import OpenpilotTestCase
-from openpilot.sunnypilot.system.params_migration import _migrate_model_bundle_slots
-
-
-class TestModelBundleSlotMigration(OpenpilotTestCase):
-  """Pre-split, a chestnut user's big-model selection lived in the single ActiveBundle.
-  The migration seeds both slots; per-source validation later drops whichever does not
-  match its own manifest."""
-
-  def test_seeds_usbgpu_slot_from_active_bundle(self):
-    params = Params()
-    bundle = {"ref": "big", "minimumSelectorVersion": 18}
-    params.put("ModelManager_ActiveBundle", bundle, block=True)
-    _migrate_model_bundle_slots(params)
-    assert params.get("ModelManager_ActiveBundleUSBGPU") == bundle
-    assert params.get("ModelManager_ActiveBundle") == bundle
-
-  def test_noop_when_usbgpu_slot_already_set(self):
-    params = Params()
-    params.put("ModelManager_ActiveBundle", {"ref": "small"}, block=True)
-    params.put("ModelManager_ActiveBundleUSBGPU", {"ref": "big"}, block=True)
-    _migrate_model_bundle_slots(params)
-    assert params.get("ModelManager_ActiveBundleUSBGPU") == {"ref": "big"}
-
-  def test_noop_when_no_selection(self):
-    params = Params()
-    _migrate_model_bundle_slots(params)
-    assert params.get("ModelManager_ActiveBundleUSBGPU") is None
@@ -8,26 +8,12 @@ from collections.abc import Callable

 import pyray as rl

-from openpilot.system.ui.lib.application import gui_app, FontWeight
+from openpilot.system.ui.lib.application import FontWeight
 from openpilot.system.ui.sunnypilot.lib.styles import style
 from openpilot.system.ui.sunnypilot.widgets.list_view import ButtonActionSP
-from openpilot.system.ui.widgets.label import ScrollState, UnifiedLabel
+from openpilot.system.ui.widgets.label import UnifiedLabel
 from openpilot.system.ui.widgets.list_view import BUTTON_WIDTH, BUTTON_HEIGHT, TEXT_PADDING, _resolve_value

-SCROLL_SPEED = 1.2  # stock is 0.8, boosted 50% to compensate for larger font (50 vs 32)
-SCROLL_REFERENCE_FPS = 60.
-
-
-class UnifiedLabelSP(UnifiedLabel):
-  # stock scroll formula (0.8 / 60 * fps) is inverted — pre-correct so speed is constant px/sec
-  def _render(self, _):
-    if self._needs_scroll and self._scroll_state == ScrollState.SCROLLING:
-      fps = gui_app.target_fps
-      wrong_step = 0.8 / SCROLL_REFERENCE_FPS * fps
-      correct_step = SCROLL_SPEED * SCROLL_REFERENCE_FPS / fps
-      self._scroll_offset -= (correct_step - wrong_step)
-    super()._render(_)
-

 class NoElideButtonAction(ButtonActionSP):
  def get_width_hint(self):
@@ -35,12 +21,14 @@ class NoElideButtonAction(ButtonActionSP):


 class ScrollingButtonAction(ButtonActionSP):
+  """ButtonActionSP whose value scrolls instead of eliding when it doesn't fit."""
+
  def __init__(self, text: str | Callable[[], str], width: int = style.BUTTON_ACTION_WIDTH,
               enabled: bool | Callable[[], bool] = True):
    super().__init__(text=text, width=width, enabled=enabled)
-    self._value_label = UnifiedLabelSP("", font_size=style.ITEM_TEXT_FONT_SIZE, font_weight=FontWeight.NORMAL,
-                                       text_color=self._value_color, scroll=True,
-                                       alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)
+    self._value_label = UnifiedLabel("", font_size=style.ITEM_TEXT_FONT_SIZE, font_weight=FontWeight.NORMAL,
+                                     text_color=self._value_color, scroll=True,
+                                     alignment_vertical=rl.GuiTextAlignmentVertical.TEXT_ALIGN_MIDDLE)

  def set_value(self, value: str | Callable[[], str], color: rl.Color = style.ITEM_TEXT_VALUE_COLOR):
    if self.value != _resolve_value(value, ""):
@@ -136,7 +136,7 @@ def generate_chunked_model(driving_pkl: Path) -> dict:


 def create_metadata_json(models: list, output_dir: Path, custom_name=None, short_name=None, is_20hz=False, upstream_branch="unknown",
-                         onnx_sha256=None, is_big=False) -> None:
+                         onnx_sha256=None) -> None:
  bundle_json = {
    "short_name": short_name,
    "display_name": custom_name or upstream_branch,
@@ -149,7 +149,6 @@ def create_metadata_json(models: list, output_dir: Path, custom_name=None, short
    "generation": "-1",
    "build_time": datetime.now(UTC).strftime("%Y-%m-%dT%H:%M:%SZ"),
    "overrides": {},
-    "is_big": is_big,
    "models": models,
  }

@@ -187,8 +186,6 @@ if __name__ == "__main__":
    print(f"No driving_tinygrad.pkl found in {_output_dir}", file=sys.stderr)
    sys.exit(1)

-  is_big = _driving_pkl.name.startswith('big_')
-
  if _pkl:
    new_pkl = _output_dir / f"driving_{_pkl}_tinygrad.pkl"
    if not new_pkl.exists():
@@ -199,4 +196,4 @@ if __name__ == "__main__":
  _model_metadata = generate_chunked_model(_driving_pkl)
  _onnx_sha256 = _hash_onnx_files(Path(args.model_dir))
  create_metadata_json([_model_metadata], _output_dir, args.custom_name, _short_name, args.is_20hz, args.upstream_branch,
-                       onnx_sha256=_onnx_sha256, is_big=is_big)
+                       onnx_sha256=_onnx_sha256)
@@ -47,7 +47,7 @@ git rm -rf $OUTPUT_DIR/.git || true # Doing cleanup, but it might fail if the .g
 git remote remove origin || true # ensure cleanup
 git remote add origin $GIT_ORIGIN
 #git push origin -d $DEV_BRANCH || true # Ensuring we delete the remote branch if it exists as we are wiping it out
-git fetch --depth 1 origin $DEV_BRANCH || (git checkout -b $DEV_BRANCH && git commit --allow-empty -m "sunnypilot v$VERSION release" && git push -u origin $DEV_BRANCH)
+git fetch origin $DEV_BRANCH || (git checkout -b $DEV_BRANCH && git commit --allow-empty -m "sunnypilot v$VERSION release" && git push -u origin $DEV_BRANCH)

 echo "[-] committing version $VERSION T=$SECONDS"
 git add -f .
Author	SHA1	Message	Date
royjr	1c3558e017	one liner	2026-08-24 01:37:10 -04:00
royjr	bf567847de	Update selfdrived.py	2026-08-24 01:30:43 -04:00
royjr	bd1d54e239	Update selfdrived.py	2026-08-24 01:30:43 -04:00
royjr	8d49466b62	alert-dedup	2026-08-24 01:30:43 -04:00