Add openEuler based container image for vLLM Ascend (#489)

### What this PR does / why we need it?

Provide users with openEuler-based vllm images, so modify the quick
start readme

### Does this PR introduce _any_ user-facing change?

None

### How was this patch tested?

There is no need for performing any test.

---------

Signed-off-by: Icey <1790571317@qq.com>

Dockerfile.openEuler

@@ -0,0 +1,47 @@
+#
+# Copyright (c) 2025 Huawei Technologies Co., Ltd. All Rights Reserved.
+# This file is a part of the vllm-ascend project.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#
+
+FROM quay.io/ascend/cann:8.0.0-910b-openeuler22.03-py3.10
+
+RUN yum update -y && \
+    yum install -y python3-pip git vim wget net-tools && \
+    rm -rf /var/cache/yum &&\
+    rm -rf /tmp/*
+
+WORKDIR /workspace
+
+COPY . /workspace/vllm-ascend/  
+
+# Install vLLM
+ARG VLLM_REPO=https://github.com/vllm-project/vllm.git
+ARG VLLM_TAG=main
+
+RUN git clone --depth 1 $VLLM_REPO --branch $VLLM_TAG /workspace/vllm
+RUN VLLM_TARGET_DEVICE="empty" python3 -m pip install /workspace/vllm/ --extra-index https://download.pytorch.org/whl/cpu/
+# In x86, triton will be installed by vllm. But in Ascend, triton doesn't work correctly. we need to uninstall it.
+RUN python3 -m pip uninstall -y triton
+
+# Install vllm-ascend
+RUN python3 -m pip install /workspace/vllm-ascend/ --extra-index https://download.pytorch.org/whl/cpu/
+
+# Install torch-npu
+RUN bash /workspace/vllm-ascend/pta_install.sh
+
+# Install modelscope (for fast download) and ray (for multinode)
+RUN python3 -m pip install modelscope ray
+
+CMD ["/bin/bash"]