镜像构建历史
# 2025-05-18 19:09:19 0.00B 设置默认要执行的命令
CMD ["bash" "start.sh"]
# 2025-05-18 19:09:19 0.00B 设置环境变量 DOCKER
ENV DOCKER=true
# 2025-05-18 19:09:19 0.00B 设置环境变量 WEBUI_BUILD_VERSION
ENV WEBUI_BUILD_VERSION=56740ab8d6ac617d84b45750667ff8fc3b9c92c9
# 2025-05-18 19:09:19 0.00B 定义构建参数
ARG BUILD_HASH=56740ab8d6ac617d84b45750667ff8fc3b9c92c9
# 2025-05-18 19:09:19 0.00B 指定运行容器时使用的用户
USER 0:0
# 2025-05-18 19:09:19 0.00B 指定检查容器健康状态的命令
HEALTHCHECK &{["CMD-SHELL" "curl --silent --fail http://localhost:${PORT:-8080}/health | jq -ne 'input.status == true' || exit 1"] "0s" "0s" "0s" "0s" '\x00'}
# 2025-05-18 19:09:19 0.00B 声明容器运行时监听的端口
EXPOSE map[8080/tcp:{}]
# 2025-05-18 19:09:19 70.25MB 复制新文件或目录到容器中
COPY --chown=0:0 ./backend . # buildkit
# 2025-05-18 19:09:18 4.16KB 复制新文件或目录到容器中
COPY --chown=0:0 /app/package.json /app/package.json # buildkit
# 2025-05-18 19:09:18 170.83KB 复制新文件或目录到容器中
COPY --chown=0:0 /app/CHANGELOG.md /app/CHANGELOG.md # buildkit
# 2025-05-18 19:09:18 313.33MB 复制新文件或目录到容器中
COPY --chown=0:0 /app/build /app/build # buildkit
# 2025-05-18 01:57:48 9.10GB 执行命令并创建新的镜像层
RUN |7 USE_CUDA=true USE_OLLAMA=false USE_CUDA_VER=cu128 USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 USE_RERANKING_MODEL= UID=0 GID=0 /bin/sh -c pip3 install --no-cache-dir uv && if [ "$USE_CUDA" = "true" ]; then pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir && uv pip install --system -r requirements.txt --no-cache-dir && python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])"; python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; else pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir && uv pip install --system -r requirements.txt --no-cache-dir && python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])"; python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; fi; chown -R $UID:$GID /app/backend/data/ # buildkit
# 2025-05-18 01:55:36 2.39KB 复制新文件或目录到容器中
COPY --chown=0:0 ./backend/requirements.txt ./requirements.txt # buildkit
# 2025-05-10 23:05:53 1.02GB 执行命令并创建新的镜像层
RUN |7 USE_CUDA=true USE_OLLAMA=false USE_CUDA_VER=cu128 USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 USE_RERANKING_MODEL= UID=0 GID=0 /bin/sh -c if [ "$USE_OLLAMA" = "true" ]; then apt-get update && apt-get install -y --no-install-recommends git build-essential pandoc netcat-openbsd curl && apt-get install -y --no-install-recommends gcc python3-dev && apt-get install -y --no-install-recommends ffmpeg libsm6 libxext6 && apt-get install -y --no-install-recommends curl jq && curl -fsSL https://ollama.com/install.sh | sh && rm -rf /var/lib/apt/lists/*; else apt-get update && apt-get install -y --no-install-recommends git build-essential pandoc gcc netcat-openbsd curl jq && apt-get install -y --no-install-recommends gcc python3-dev && apt-get install -y --no-install-recommends ffmpeg libsm6 libxext6 && rm -rf /var/lib/apt/lists/*; fi # buildkit
# 2025-05-10 23:05:10 0.00B 执行命令并创建新的镜像层
RUN |7 USE_CUDA=true USE_OLLAMA=false USE_CUDA_VER=cu128 USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 USE_RERANKING_MODEL= UID=0 GID=0 /bin/sh -c chown -R $UID:$GID /app $HOME # buildkit
# 2025-05-10 23:05:10 36.00B 执行命令并创建新的镜像层
RUN |7 USE_CUDA=true USE_OLLAMA=false USE_CUDA_VER=cu128 USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 USE_RERANKING_MODEL= UID=0 GID=0 /bin/sh -c echo -n 00000000-0000-0000-0000-000000000000 > $HOME/.cache/chroma/telemetry_user_id # buildkit
# 2025-05-10 23:05:10 0.00B 执行命令并创建新的镜像层
RUN |7 USE_CUDA=true USE_OLLAMA=false USE_CUDA_VER=cu128 USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 USE_RERANKING_MODEL= UID=0 GID=0 /bin/sh -c mkdir -p $HOME/.cache/chroma # buildkit
# 2025-05-10 23:05:10 0.00B 执行命令并创建新的镜像层
RUN |7 USE_CUDA=true USE_OLLAMA=false USE_CUDA_VER=cu128 USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 USE_RERANKING_MODEL= UID=0 GID=0 /bin/sh -c if [ $UID -ne 0 ]; then if [ $GID -ne 0 ]; then addgroup --gid $GID app; fi; adduser --uid $UID --gid $GID --home $HOME --disabled-password --no-create-home app; fi # buildkit
# 2025-05-10 23:05:10 0.00B 设置环境变量 HOME
ENV HOME=/root
# 2025-05-10 23:05:10 0.00B 设置工作目录为/app/backend
WORKDIR /app/backend
# 2025-05-10 23:05:10 0.00B 设置环境变量 HF_HOME
ENV HF_HOME=/app/backend/data/cache/embedding/models
# 2025-05-10 23:05:10 0.00B 设置环境变量 TIKTOKEN_ENCODING_NAME TIKTOKEN_CACHE_DIR
ENV TIKTOKEN_ENCODING_NAME=cl100k_base TIKTOKEN_CACHE_DIR=/app/backend/data/cache/tiktoken
# 2025-05-10 23:05:10 0.00B 设置环境变量 RAG_EMBEDDING_MODEL RAG_RERANKING_MODEL SENTENCE_TRANSFORMERS_HOME
ENV RAG_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 RAG_RERANKING_MODEL= SENTENCE_TRANSFORMERS_HOME=/app/backend/data/cache/embedding/models
# 2025-05-10 23:05:10 0.00B 设置环境变量 WHISPER_MODEL WHISPER_MODEL_DIR
ENV WHISPER_MODEL=base WHISPER_MODEL_DIR=/app/backend/data/cache/whisper/models
# 2025-05-10 23:05:10 0.00B 设置环境变量 OPENAI_API_KEY WEBUI_SECRET_KEY SCARF_NO_ANALYTICS DO_NOT_TRACK ANONYMIZED_TELEMETRY
ENV OPENAI_API_KEY= WEBUI_SECRET_KEY= SCARF_NO_ANALYTICS=true DO_NOT_TRACK=true ANONYMIZED_TELEMETRY=false
# 2025-05-10 23:05:10 0.00B 设置环境变量 OLLAMA_BASE_URL OPENAI_API_BASE_URL
ENV OLLAMA_BASE_URL=/ollama OPENAI_API_BASE_URL=
# 2025-05-10 23:05:10 0.00B 设置环境变量 ENV PORT USE_OLLAMA_DOCKER USE_CUDA_DOCKER USE_CUDA_DOCKER_VER USE_EMBEDDING_MODEL_DOCKER USE_RERANKING_MODEL_DOCKER
ENV ENV=prod PORT=8080 USE_OLLAMA_DOCKER=false USE_CUDA_DOCKER=true USE_CUDA_DOCKER_VER=cu128 USE_EMBEDDING_MODEL_DOCKER=sentence-transformers/all-MiniLM-L6-v2 USE_RERANKING_MODEL_DOCKER=
# 2025-05-10 23:05:10 0.00B 定义构建参数
ARG GID=0
# 2025-05-10 23:05:10 0.00B 定义构建参数
ARG UID=0
# 2025-05-10 23:05:10 0.00B 定义构建参数
ARG USE_RERANKING_MODEL=
# 2025-05-10 23:05:10 0.00B 定义构建参数
ARG USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2
# 2025-05-10 23:05:10 0.00B 定义构建参数
ARG USE_CUDA_VER=cu128
# 2025-05-10 23:05:10 0.00B 定义构建参数
ARG USE_OLLAMA=false
# 2025-05-10 23:05:10 0.00B 定义构建参数
ARG USE_CUDA=true
# 2025-05-09 06:27:23 0.00B 设置默认要执行的命令
CMD ["python3"]
# 2025-05-09 06:27:23 36.00B 执行命令并创建新的镜像层
RUN /bin/sh -c set -eux; for src in idle3 pip3 pydoc3 python3 python3-config; do dst="$(echo "$src" | tr -d 3)"; [ -s "/usr/local/bin/$src" ]; [ ! -e "/usr/local/bin/$dst" ]; ln -svT "$src" "/usr/local/bin/$dst"; done # buildkit
# 2025-05-09 06:27:23 45.81MB 执行命令并创建新的镜像层
RUN /bin/sh -c set -eux; savedAptMark="$(apt-mark showmanual)"; apt-get update; apt-get install -y --no-install-recommends dpkg-dev gcc gnupg libbluetooth-dev libbz2-dev libc6-dev libdb-dev libffi-dev libgdbm-dev liblzma-dev libncursesw5-dev libreadline-dev libsqlite3-dev libssl-dev make tk-dev uuid-dev wget xz-utils zlib1g-dev ; wget -O python.tar.xz "https://www.python.org/ftp/python/${PYTHON_VERSION%%[a-z]*}/Python-$PYTHON_VERSION.tar.xz"; echo "$PYTHON_SHA256 *python.tar.xz" | sha256sum -c -; wget -O python.tar.xz.asc "https://www.python.org/ftp/python/${PYTHON_VERSION%%[a-z]*}/Python-$PYTHON_VERSION.tar.xz.asc"; GNUPGHOME="$(mktemp -d)"; export GNUPGHOME; gpg --batch --keyserver hkps://keys.openpgp.org --recv-keys "$GPG_KEY"; gpg --batch --verify python.tar.xz.asc python.tar.xz; gpgconf --kill all; rm -rf "$GNUPGHOME" python.tar.xz.asc; mkdir -p /usr/src/python; tar --extract --directory /usr/src/python --strip-components=1 --file python.tar.xz; rm python.tar.xz; cd /usr/src/python; gnuArch="$(dpkg-architecture --query DEB_BUILD_GNU_TYPE)"; ./configure --build="$gnuArch" --enable-loadable-sqlite-extensions --enable-optimizations --enable-option-checking=fatal --enable-shared $(test "$gnuArch" != 'riscv64-linux-musl' && echo '--with-lto') --with-ensurepip ; nproc="$(nproc)"; EXTRA_CFLAGS="$(dpkg-buildflags --get CFLAGS)"; LDFLAGS="$(dpkg-buildflags --get LDFLAGS)"; LDFLAGS="${LDFLAGS:--Wl},--strip-all"; make -j "$nproc" "EXTRA_CFLAGS=${EXTRA_CFLAGS:-}" "LDFLAGS=${LDFLAGS:-}" ; rm python; make -j "$nproc" "EXTRA_CFLAGS=${EXTRA_CFLAGS:-}" "LDFLAGS=${LDFLAGS:--Wl},-rpath='\$\$ORIGIN/../lib'" python ; make install; cd /; rm -rf /usr/src/python; find /usr/local -depth \( \( -type d -a \( -name test -o -name tests -o -name idle_test \) \) -o \( -type f -a \( -name '*.pyc' -o -name '*.pyo' -o -name 'libpython*.a' \) \) \) -exec rm -rf '{}' + ; ldconfig; apt-mark auto '.*' > /dev/null; apt-mark manual $savedAptMark; find /usr/local -type f -executable -not \( -name '*tkinter*' \) -exec ldd '{}' ';' | awk '/=>/ { so = $(NF-1); if (index(so, "/usr/local/") == 1) { next }; gsub("^/(usr/)?", "", so); printf "*%s\n", so }' | sort -u | xargs -r dpkg-query --search | cut -d: -f1 | sort -u | xargs -r apt-mark manual ; apt-get purge -y --auto-remove -o APT::AutoRemove::RecommendsImportant=false; rm -rf /var/lib/apt/lists/*; export PYTHONDONTWRITEBYTECODE=1; python3 --version; pip3 install --disable-pip-version-check --no-cache-dir --no-compile 'setuptools==65.5.1' 'wheel<0.46' ; pip3 --version # buildkit
# 2025-05-09 06:27:23 0.00B 设置环境变量 PYTHON_SHA256
ENV PYTHON_SHA256=849da87af4df137710c1796e276a955f7a85c9f971081067c8f565d15c352a09
# 2025-05-09 06:27:23 0.00B 设置环境变量 PYTHON_VERSION
ENV PYTHON_VERSION=3.11.12
# 2025-05-09 06:27:23 0.00B 设置环境变量 GPG_KEY
ENV GPG_KEY=A035C8C19219BA821ECEA86B64E628F8D684696D
# 2025-05-09 06:27:23 9.23MB 执行命令并创建新的镜像层
RUN /bin/sh -c set -eux; apt-get update; apt-get install -y --no-install-recommends ca-certificates netbase tzdata ; rm -rf /var/lib/apt/lists/* # buildkit
# 2025-05-09 06:27:23 0.00B 设置环境变量 LANG
ENV LANG=C.UTF-8
# 2025-05-09 06:27:23 0.00B 设置环境变量 PATH
ENV PATH=/usr/local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
# 2025-04-28 08:00:00 74.83MB
# debian.sh --arch 'amd64' out/ 'bookworm' '@1745798400'
镜像信息
{
"Id": "sha256:e535d19c7a4ceb3bd1527eb9f0ab349d8a9f3b59050ae257dbdde35861b9763c",
"RepoTags": [
"ghcr.io/open-webui/open-webui:git-56740ab-cuda",
"swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/open-webui/open-webui:git-56740ab-cuda"
],
"RepoDigests": [
"ghcr.io/open-webui/open-webui@sha256:0ebdae9d047619c97c3d6d3247f9f8b9ac94c301fb7253980a04e72efd80e4f5",
"swr.cn-north-4.myhuaweicloud.com/ddn-k8s/ghcr.io/open-webui/open-webui@sha256:db9c9392393798f8ca7ebb870a6d28f143500001722d720fd1c52802616ca2ab"
],
"Parent": "",
"Comment": "buildkit.dockerfile.v0",
"Created": "2025-05-18T11:09:19.22132161Z",
"Container": "",
"ContainerConfig": null,
"DockerVersion": "",
"Author": "",
"Config": {
"Hostname": "",
"Domainname": "",
"User": "0:0",
"AttachStdin": false,
"AttachStdout": false,
"AttachStderr": false,
"ExposedPorts": {
"8080/tcp": {}
},
"Tty": false,
"OpenStdin": false,
"StdinOnce": false,
"Env": [
"PATH=/usr/local/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin",
"LANG=C.UTF-8",
"GPG_KEY=A035C8C19219BA821ECEA86B64E628F8D684696D",
"PYTHON_VERSION=3.11.12",
"PYTHON_SHA256=849da87af4df137710c1796e276a955f7a85c9f971081067c8f565d15c352a09",
"ENV=prod",
"PORT=8080",
"USE_OLLAMA_DOCKER=false",
"USE_CUDA_DOCKER=true",
"USE_CUDA_DOCKER_VER=cu128",
"USE_EMBEDDING_MODEL_DOCKER=sentence-transformers/all-MiniLM-L6-v2",
"USE_RERANKING_MODEL_DOCKER=",
"OLLAMA_BASE_URL=/ollama",
"OPENAI_API_BASE_URL=",
"OPENAI_API_KEY=",
"WEBUI_SECRET_KEY=",
"SCARF_NO_ANALYTICS=true",
"DO_NOT_TRACK=true",
"ANONYMIZED_TELEMETRY=false",
"WHISPER_MODEL=base",
"WHISPER_MODEL_DIR=/app/backend/data/cache/whisper/models",
"RAG_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2",
"RAG_RERANKING_MODEL=",
"SENTENCE_TRANSFORMERS_HOME=/app/backend/data/cache/embedding/models",
"TIKTOKEN_ENCODING_NAME=cl100k_base",
"TIKTOKEN_CACHE_DIR=/app/backend/data/cache/tiktoken",
"HF_HOME=/app/backend/data/cache/embedding/models",
"HOME=/root",
"WEBUI_BUILD_VERSION=56740ab8d6ac617d84b45750667ff8fc3b9c92c9",
"DOCKER=true"
],
"Cmd": [
"bash",
"start.sh"
],
"Healthcheck": {
"Test": [
"CMD-SHELL",
"curl --silent --fail http://localhost:${PORT:-8080}/health | jq -ne 'input.status == true' || exit 1"
]
},
"ArgsEscaped": true,
"Image": "",
"Volumes": null,
"WorkingDir": "/app/backend",
"Entrypoint": null,
"OnBuild": null,
"Labels": {
"org.opencontainers.image.created": "2025-05-18T11:05:23.139Z",
"org.opencontainers.image.description": "User-friendly AI Interface (Supports Ollama, OpenAI API, ...)",
"org.opencontainers.image.licenses": "NOASSERTION",
"org.opencontainers.image.revision": "56740ab8d6ac617d84b45750667ff8fc3b9c92c9",
"org.opencontainers.image.source": "https://github.com/open-webui/open-webui",
"org.opencontainers.image.title": "open-webui",
"org.opencontainers.image.url": "https://github.com/open-webui/open-webui",
"org.opencontainers.image.version": "dev-cuda"
}
},
"Architecture": "amd64",
"Os": "linux",
"Size": 10632028155,
"GraphDriver": {
"Data": {
"LowerDir": "/var/lib/docker/overlay2/0fb0a3f7d71e70af16368b9727799f373af4eb9be9daf874403b412f46eb74d8/diff:/var/lib/docker/overlay2/377cbeea4dbd33e87393a4796660e6a02dfc4df37717b290060c06f037274f8e/diff:/var/lib/docker/overlay2/213a74ada1ebaff7fc4eec6c0eb093b7110b21ac2579fa1ab8e1afa7fba8ee42/diff:/var/lib/docker/overlay2/c7975f45dad9bc22f5bb11ff57ee64c245a0630c395c8416f388180faed50f24/diff:/var/lib/docker/overlay2/9b50a6c5e3c7a08ee248a0f699ee3f483ae040cb19165974df8f59d62f5b9961/diff:/var/lib/docker/overlay2/84adb55d8ea3ed04fb47442a157e60bb40428387496ca5cb6a72569ec2e085ec/diff:/var/lib/docker/overlay2/066b9963436fa97fb081fbb3f2af48ac5e23a224650b32036c0ea0f1c6495de7/diff:/var/lib/docker/overlay2/97027d9d5b032a0bddbb37d34f2070e86dc6b2b3973519105bacbb72620d5868/diff:/var/lib/docker/overlay2/10f5479b5aa086a7808aa380a2275e995c6b6abdd7811ac124844d0d02877700/diff:/var/lib/docker/overlay2/7247da32226649cbfe460f05723375f00e7453ae8d6a45a665fd88ce2a33e065/diff:/var/lib/docker/overlay2/93a3af32fe030005a157c6c3eb4a6ee9189866898d42e0b69ec9552d1ac9ba9c/diff:/var/lib/docker/overlay2/efbc997e3c2c7d97f6228d1f69b233f5cb442659b34a5a53830a98355940c003/diff:/var/lib/docker/overlay2/476da35ebccb03ca9e3a37afee4c7ad53b89641bc58bc6e63b2871411befe05f/diff:/var/lib/docker/overlay2/a998f3658222ce6e8902b534e396ed893baf36aa2d9563a50b76fcad7af12a69/diff:/var/lib/docker/overlay2/cd9cb36f82b4a6a570304a082a3d97b369643777f7f7b25df6d47ffb3b3d36ab/diff",
"MergedDir": "/var/lib/docker/overlay2/9b6749ef37726e6fbfc07c6daaf43642d8ac4c3d2d58f102f2b91d12b5714cc4/merged",
"UpperDir": "/var/lib/docker/overlay2/9b6749ef37726e6fbfc07c6daaf43642d8ac4c3d2d58f102f2b91d12b5714cc4/diff",
"WorkDir": "/var/lib/docker/overlay2/9b6749ef37726e6fbfc07c6daaf43642d8ac4c3d2d58f102f2b91d12b5714cc4/work"
},
"Name": "overlay2"
},
"RootFS": {
"Type": "layers",
"Layers": [
"sha256:6c4c763d22d0c5f9b2c5901dfa667fbbc4713cee6869336b8fd5022185071f1c",
"sha256:adb057d02f88ea76ce8ccd9a9b12c418c315af74d44ec242212df209eb62f560",
"sha256:91bd78b864ed8711350ab463a5d123ea251c61161da4456b13662a6e8e7a4dbc",
"sha256:23aa89a8a4248fb42847aba2e81e7e2472d8c536da4e245f6f73573d4d9042fb",
"sha256:0635883bf07116e5f14f0fb12ee431ff1df7de2d3025555af79bb821b34ad7de",
"sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
"sha256:99a6235bc1dfdeb97b52c5af93e1bd3fd097114007df6761fad287bce554064b",
"sha256:5ceb65c9119bfc9ac28dbc78e79b6c6b54791f084db1f7e1c1e5932b1a729d53",
"sha256:5f70bf18a086007016e948b04aed3b82103a36bea41755b6cddfaf10ace3c6ef",
"sha256:861bc8c474a4dbbc6cc05ea82d62b3e2db0a7bb166905a5e13dcd85a04b507fe",
"sha256:e2431413f76c08b6a42825f05777b3ff05cadc8c6017d6974e2c0f2c1197a5d7",
"sha256:f3ebb9cb4406ba12ea558761852567af66baa31033ad18fce6e09a3445319a38",
"sha256:86f30ed4fffaff581ad87c090e51c7a3adaa339941923ffbab5b343ba502e096",
"sha256:bc56b24b1853af500c0a16b44d46b28ad75b590023c12d6ad3ae893678a9f1fd",
"sha256:5429f445f1b65338975fddfaf94789b616cf4a3c682551f7435e4420779451f9",
"sha256:f0f563a4a46b912b005c6e2fb991bf3f5bd94cbc5ecdad62e55ba2808ff1b92c"
]
},
"Metadata": {
"LastTagTime": "2025-05-19T00:25:20.015998652+08:00"
}
}