fix(images): vendor spacy zh model + nltk data for air-gapped GitHub builds

- runtime: install zh_core_web_sm from vendored wheel (reused from runtime-ray)
  instead of 'python -m spacy download' (GitHub 403 on server)
- runtime / runtime-ray / backend-python: replace nltk.download (GitHub +
  nltk_data.nltk.org unreachable from server) with vendored zips extracted
  to /usr/local/nltk_data/packages/{tokenizers,taggers}

scripts/images/backend-python/Dockerfile

@@ -58,8 +58,9 @@ RUN --mount=type=cache,target=$POETRY_CACHE_DIR \
 # 注意：使用 [default] 确保包含 job submission client
 RUN pip install "ray[default]>=2.9.0"
 
-# 下载 NLTK 数据
-RUN python -c "import nltk; nltk.download(['punkt_tab','averaged_perceptron_tagger_eng'], download_dir='/usr/local/nltk_data')"
+# 下载 NLTK 数据（离线：使用仓库内 vendor 的数据包，服务器无法访问 GitHub）
+COPY scripts/images/common/nltk-data/ /tmp/nltk-data/
+RUN python -c "import zipfile, os; os.makedirs('/usr/local/nltk_data/packages/tokenizers', exist_ok=True); os.makedirs('/usr/local/nltk_data/packages/taggers', exist_ok=True); zipfile.ZipFile('/tmp/nltk-data/punkt_tab.zip').extractall('/usr/local/nltk_data/packages/tokenizers'); zipfile.ZipFile('/tmp/nltk-data/averaged_perceptron_tagger_eng.zip').extractall('/usr/local/nltk_data/packages/taggers')"
 ENV NLTK_DATA=/usr/local/nltk_data
 
 # 复制应用代码

scripts/images/runtime-ray/Dockerfile

@@ -83,6 +83,7 @@ ENV PATH="$PATH:$JAVA_HOME/bin"
 WORKDIR /opt/runtime
 
 COPY scripts/images/runtime-ray/zh_core_web_sm-3.8.0-py3-none-any.whl /tmp/
+COPY scripts/images/common/nltk-data/ /tmp/nltk-data/
 
 ENV UV_LINK_MODE=copy
 
@@ -92,7 +93,7 @@ RUN --mount=type=cache,target=/root/.cache/uv \
     && uv pip install -r /opt/runtime/deepdata/ops/pyproject.toml --system \
     && uv pip install "ray[default]>=2.9.0" --system \
     && uv pip install /tmp/zh_core_web_sm-3.8.0-py3-none-any.whl --system \
-    && python -c "import nltk; nltk.download('punkt_tab'); nltk.download('averaged_perceptron_tagger_eng')" \
+    && python -c "import zipfile, os; os.makedirs('/usr/local/nltk_data/packages/tokenizers', exist_ok=True); os.makedirs('/usr/local/nltk_data/packages/taggers', exist_ok=True); zipfile.ZipFile('/tmp/nltk-data/punkt_tab.zip').extractall('/usr/local/nltk_data/packages/tokenizers'); zipfile.ZipFile('/tmp/nltk-data/averaged_perceptron_tagger_eng.zip').extractall('/usr/local/nltk_data/packages/taggers')" \
     && echo "/usr/local/lib/ops/site-packages" > /usr/local/lib/python3.11/site-packages/ops.pth
 
    

scripts/images/runtime/Dockerfile

@@ -15,6 +15,9 @@ COPY runtime/ops /opt/runtime/deepdata/ops
 COPY runtime/ops/user /opt/runtime/user
 COPY scripts/images/runtime/start.sh /opt/runtime/start.sh
 COPY scripts/images/common/log-rotate-copytruncate.sh /usr/local/bin/log-rotate-copytruncate.sh
+# 🟢 离线安装：spacy 中文模型（复用 runtime-ray 已 vendor 的 wheel）+ nltk 数据包
+COPY scripts/images/runtime-ray/zh_core_web_sm-3.8.0-py3-none-any.whl /tmp/
+COPY scripts/images/common/nltk-data/ /tmp/nltk-data/
 
 ENV PYTHONPATH=/opt/runtime/deepdata/
 ENV UV_EXTRA_INDEX_URL="https://download.pytorch.org/whl/cpu"
@@ -25,8 +28,8 @@ WORKDIR /opt/runtime
 RUN --mount=type=cache,target=/root/.cache/uv \
     uv pip install -e . --system \
     && uv pip install -r /opt/runtime/deepdata/ops/pyproject.toml --system \
-    && python -m spacy download zh_core_web_sm \
-    && python -c "import nltk; nltk.download('punkt_tab'); nltk.download('averaged_perceptron_tagger_eng')" \
+    && uv pip install /tmp/zh_core_web_sm-3.8.0-py3-none-any.whl --system \
+    && python -c "import zipfile, os; os.makedirs('/usr/local/nltk_data/packages/tokenizers', exist_ok=True); os.makedirs('/usr/local/nltk_data/packages/taggers', exist_ok=True); zipfile.ZipFile('/tmp/nltk-data/punkt_tab.zip').extractall('/usr/local/nltk_data/packages/tokenizers'); zipfile.ZipFile('/tmp/nltk-data/averaged_perceptron_tagger_eng.zip').extractall('/usr/local/nltk_data/packages/taggers')" \
     && echo "/usr/local/lib/ops/site-packages" > /usr/local/lib/python3.11/site-packages/ops.pth
 
 RUN ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime \