Add Qwen2.5 tokenizer compatibility engine and runner workflow

.gitea/workflows/docker-build-push.yml

@@ -0,0 +1,98 @@
+name: Build and verify Qwen2.5 compatibility engines
+
+on:
+  push:
+    tags:
+      - "v*"
+
+jobs:
+  docker:
+    runs-on: amd64-ubuntu-24.04
+    steps:
+      - name: Clone tagged source
+        run: |
+          git clone "${{ gitea.server_url }}/${{ gitea.repository }}.git" .
+          git checkout "${{ gitea.ref_name }}"
+
+      - name: Run compatibility tests
+        run: python3 -m unittest discover -s tests -q
+
+      - name: Load image metadata
+        run: |
+          set -eu
+          set -a
+          . .gitea/workflows/task_info.env
+          set +a
+          test -n "$FRAMEWORK"
+          test -n "$TASK_TYPE"
+          test -n "$GPU_TYPES"
+          echo "FRAMEWORK=$FRAMEWORK" >> "$GITEA_ENV"
+          echo "TASK_TYPE=$TASK_TYPE" >> "$GITEA_ENV"
+          echo "GPU_TYPES=$GPU_TYPES" >> "$GITEA_ENV"
+
+      - name: Validate GPU and task metadata
+        run: |
+          set -eu
+          test -n "${FIXED_TOKEN:-}" || { echo "FIXED_TOKEN is missing"; exit 1; }
+          for gpu in $GPU_TYPES; do
+            response="$(curl --silent --show-error --fail-with-body --location --get \
+              'https://modelhub.org.cn/adminApi/image-verify/validate' \
+              --header "Xc-Token: $FIXED_TOKEN" \
+              --data-urlencode "gpuType=$gpu" \
+              --data-urlencode "taskType=$TASK_TYPE")"
+            VALIDATE_RESPONSE="$response" python3 -c 'import json,os,sys; body=json.loads(os.environ["VALIDATE_RESPONSE"]); sys.exit(0 if body.get("code")==0 and body.get("data") is True else 1)'
+            echo "validated gpuType=$gpu taskType=$TASK_TYPE"
+          done
+
+      - name: Log in to Docker registry
+        run: |
+          set -eu
+          test -n "${DOCKER_REGISTRY:-}"
+          test -n "${DOCKER_USERNAME:-}"
+          test -n "${DOCKER_PASSWORD:-}"
+          printf '%s' "$DOCKER_PASSWORD" | docker login "$DOCKER_REGISTRY" \
+            -u "$DOCKER_USERNAME" --password-stdin
+
+      - name: Build and push target images
+        run: |
+          set -eu
+          image_name="$(printf '%s' '${{ gitea.repository }}' | tr '[:upper:]' '[:lower:]' | tr '_' '-')"
+          image_base="$DOCKER_REGISTRY/$DOCKER_USERNAME/$image_name"
+          a100_image="$image_base:${{ gitea.ref_name }}-nvidia-a100"
+          cambricon_image="$image_base:${{ gitea.ref_name }}-cambricon-mlu370"
+
+          docker build \
+            --build-arg BASE_IMAGE=harbor.4pd.io/dooke/vllm/vllm/vllm-openai:v0.11.0 \
+            -t "$a100_image" .
+          docker build \
+            --build-arg BASE_IMAGE=harbor.4pd.io/hardcore-tech/cambricon-mlu370-pytorch:v25.01-20260228 \
+            -t "$cambricon_image" .
+
+          for image in "$a100_image" "$cambricon_image"; do
+            success=0
+            for attempt in 1 2 3; do
+              if docker push "$image"; then success=1; break; fi
+              echo "docker push attempt $attempt failed for $image"
+              sleep 30
+            done
+            test "$success" -eq 1
+          done
+          echo "A100_IMAGE=$a100_image" >> "$GITEA_ENV"
+          echo "CAMBRICON_IMAGE=$cambricon_image" >> "$GITEA_ENV"
+
+      - name: Notify ModelHub image verification
+        run: |
+          set -eu
+          for gpu in $GPU_TYPES; do
+            case "$gpu" in
+              Nvidia-A100) image="$A100_IMAGE" ;;
+              Cambricon_mlu-370-x4|Cambricon_mlu-370-x8) image="$CAMBRICON_IMAGE" ;;
+              *) echo "unknown GPU target: $gpu"; exit 1 ;;
+            esac
+            payload="$(GPU_TYPE="$gpu" IMAGE="$image" REPO_URL='${{ gitea.server_url }}/${{ gitea.repository }}' TAG='${{ gitea.ref_name }}' ACTOR='${{ gitea.actor }}' python3 -c 'import json, os; print(json.dumps({"framework": os.environ["FRAMEWORK"], "gpuType": os.environ["GPU_TYPE"], "imageUrl": os.environ["IMAGE"], "taskType": os.environ["TASK_TYPE"], "createBy": os.environ["ACTOR"], "repoUrl": os.environ["REPO_URL"], "tag": os.environ["TAG"]}))')"
+            curl --silent --show-error --fail-with-body --location \
+              --request POST 'https://modelhub.org.cn/adminApi/image-verify' \
+              --header "Xc-Token: $FIXED_TOKEN" \
+              --header 'Content-Type: application/json' \
+              --data-raw "$payload"
+          done