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[GH-ISSUE #10734] ModuleNotFoundError: No module named 'backend' #31539

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opened 2026-04-25 05:26:53 -05:00 by GiteaMirror · 0 comments
GiteaMirror commented 2026-04-25 05:26:53 -05:00
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Originally created by @wubucheng on GitHub (Feb 25, 2025).
Original GitHub issue: https://github.com/open-webui/open-webui/issues/10734

I tried to build a docker image from local source code, but after the build was successful, an error occurred during runtime: ModuleNotFoundError: No module named 'backend'

my docker-compose.yml

services:
  open-webui:
    build:
      context: .
      dockerfile: Dockerfile
    container_name: open-webui
    volumes:
      - open-webui:/app/backend/data
    ports:
      - ${OPEN_WEBUI_PORT-3000}:8080
    environment:
      - 'WEBUI_SECRET_KEY='
    extra_hosts:
      - host.docker.internal:host-gateway
    restart: unless-stopped

volumes:
  open-webui: {}

my dockerfile

# syntax=docker/dockerfile:1
# Initialize device type args
# use build args in the docker build command with --build-arg="BUILDARG=true"
ARG USE_CUDA=false
ARG USE_OLLAMA=false
# Tested with cu117 for CUDA 11 and cu121 for CUDA 12 (default)
ARG USE_CUDA_VER=cu121
# any sentence transformer model; models to use can be found at https://huggingface.co/models?library=sentence-transformers
# Leaderboard: https://huggingface.co/spaces/mteb/leaderboard 
# for better performance and multilangauge support use "intfloat/multilingual-e5-large" (~2.5GB) or "intfloat/multilingual-e5-base" (~1.5GB)
# IMPORTANT: If you change the embedding model (sentence-transformers/all-MiniLM-L6-v2) and vice versa, you aren't able to use RAG Chat with your previous documents loaded in the WebUI! You need to re-embed them.
ARG USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2
ARG USE_RERANKING_MODEL=""

# Tiktoken encoding name; models to use can be found at https://huggingface.co/models?library=tiktoken
ARG USE_TIKTOKEN_ENCODING_NAME="cl100k_base"

ARG BUILD_HASH=dev-build
# Override at your own risk - non-root configurations are untested
ARG UID=0
ARG GID=0

######## WebUI frontend ########
FROM --platform=$BUILDPLATFORM node:22-alpine3.20 AS build
ARG BUILD_HASH
ENV NODE_OPTIONS=--max-old-space-size=4096

WORKDIR /app

COPY package.json package-lock.json ./
RUN npm ci

COPY . .
ENV APP_BUILD_HASH=${BUILD_HASH}
RUN npm run build

######## WebUI backend ########
FROM python:3.11-slim-bookworm AS base

# Use args
ARG USE_CUDA
ARG USE_OLLAMA
ARG USE_CUDA_VER
ARG USE_EMBEDDING_MODEL
ARG USE_RERANKING_MODEL
ARG UID
ARG GID

## Basis ##
ENV ENV=prod \
    PORT=8080 \
    # pass build args to the build
    USE_OLLAMA_DOCKER=${USE_OLLAMA} \
    USE_CUDA_DOCKER=${USE_CUDA} \
    USE_CUDA_DOCKER_VER=${USE_CUDA_VER} \
    USE_EMBEDDING_MODEL_DOCKER=${USE_EMBEDDING_MODEL} \
    USE_RERANKING_MODEL_DOCKER=${USE_RERANKING_MODEL}

## Basis URL Config ##
ENV OLLAMA_BASE_URL="/ollama" \
    OPENAI_API_BASE_URL=""

## API Key and Security Config ##
ENV OPENAI_API_KEY="" \
    WEBUI_SECRET_KEY="" \
    SCARF_NO_ANALYTICS=true \
    DO_NOT_TRACK=true \
    ANONYMIZED_TELEMETRY=false

#### Other models #########################################################
## whisper TTS model settings ##
ENV WHISPER_MODEL="base" \
    WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models"

## RAG Embedding model settings ##
ENV RAG_EMBEDDING_MODEL="$USE_EMBEDDING_MODEL_DOCKER" \
    RAG_RERANKING_MODEL="$USE_RERANKING_MODEL_DOCKER" \
    SENTENCE_TRANSFORMERS_HOME="/app/backend/data/cache/embedding/models"

## Tiktoken model settings ##
ENV TIKTOKEN_ENCODING_NAME="cl100k_base" \
    TIKTOKEN_CACHE_DIR="/app/backend/data/cache/tiktoken"

## Hugging Face download cache ##
ENV HF_HOME="/app/backend/data/cache/embedding/models"

## Torch Extensions ##
# ENV TORCH_EXTENSIONS_DIR="/.cache/torch_extensions"

#### Other models ##########################################################

WORKDIR /app/backend

ENV HOME=/root
# Create user and group if not root
RUN 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

RUN mkdir -p $HOME/.cache/chroma
RUN echo -n 00000000-0000-0000-0000-000000000000 > $HOME/.cache/chroma/telemetry_user_id

# Make sure the user has access to the app and root directory
RUN chown -R $UID:$GID /app $HOME



# install python dependencies
COPY --chown=$UID:$GID ./backend/requirements.txt ./requirements.txt

RUN pip3 install uv && \
    if [ "$USE_CUDA" = "true" ]; then \
    # If you use CUDA the whisper and embedding model will be downloaded on first use
    pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/$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/



# copy embedding weight from build
# RUN mkdir -p /root/.cache/chroma/onnx_models/all-MiniLM-L6-v2
# COPY --from=build /app/onnx /root/.cache/chroma/onnx_models/all-MiniLM-L6-v2/onnx

# copy built frontend files
COPY --chown=$UID:$GID --from=build /app/build /app/build
COPY --chown=$UID:$GID --from=build /app/CHANGELOG.md /app/CHANGELOG.md
COPY --chown=$UID:$GID --from=build /app/package.json /app/package.json

# copy backend files
COPY --chown=$UID:$GID ./backend .

EXPOSE 8080

HEALTHCHECK CMD curl --silent --fail http://localhost:${PORT:-8080}/health | jq -ne 'input.status == true' || exit 1

USER $UID:$GID

ARG BUILD_HASH
ENV WEBUI_BUILD_VERSION=${BUILD_HASH}
ENV DOCKER=true

CMD [ "bash", "start.sh"]

I just modified this.file ，other not changed. When I execute docker-comopse up,occurred this problem.

My docker image successful builded

Image Image

ERROR MESSAGE

Image
Originally created by @wubucheng on GitHub (Feb 25, 2025). Original GitHub issue: https://github.com/open-webui/open-webui/issues/10734 I tried to build a docker image from local source code, but after the build was successful, an error occurred during runtime: ModuleNotFoundError: No module named 'backend' ## my docker-compose.yml ``` services: open-webui: build: context: . dockerfile: Dockerfile container_name: open-webui volumes: - open-webui:/app/backend/data ports: - ${OPEN_WEBUI_PORT-3000}:8080 environment: - 'WEBUI_SECRET_KEY=' extra_hosts: - host.docker.internal:host-gateway restart: unless-stopped volumes: open-webui: {} ``` ## my dockerfile ``` # syntax=docker/dockerfile:1 # Initialize device type args # use build args in the docker build command with --build-arg="BUILDARG=true" ARG USE_CUDA=false ARG USE_OLLAMA=false # Tested with cu117 for CUDA 11 and cu121 for CUDA 12 (default) ARG USE_CUDA_VER=cu121 # any sentence transformer model; models to use can be found at https://huggingface.co/models?library=sentence-transformers # Leaderboard: https://huggingface.co/spaces/mteb/leaderboard # for better performance and multilangauge support use "intfloat/multilingual-e5-large" (~2.5GB) or "intfloat/multilingual-e5-base" (~1.5GB) # IMPORTANT: If you change the embedding model (sentence-transformers/all-MiniLM-L6-v2) and vice versa, you aren't able to use RAG Chat with your previous documents loaded in the WebUI! You need to re-embed them. ARG USE_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2 ARG USE_RERANKING_MODEL="" # Tiktoken encoding name; models to use can be found at https://huggingface.co/models?library=tiktoken ARG USE_TIKTOKEN_ENCODING_NAME="cl100k_base" ARG BUILD_HASH=dev-build # Override at your own risk - non-root configurations are untested ARG UID=0 ARG GID=0 ######## WebUI frontend ######## FROM --platform=$BUILDPLATFORM node:22-alpine3.20 AS build ARG BUILD_HASH ENV NODE_OPTIONS=--max-old-space-size=4096 WORKDIR /app COPY package.json package-lock.json ./ RUN npm ci COPY . . ENV APP_BUILD_HASH=${BUILD_HASH} RUN npm run build ######## WebUI backend ######## FROM python:3.11-slim-bookworm AS base # Use args ARG USE_CUDA ARG USE_OLLAMA ARG USE_CUDA_VER ARG USE_EMBEDDING_MODEL ARG USE_RERANKING_MODEL ARG UID ARG GID ## Basis ## ENV ENV=prod \ PORT=8080 \ # pass build args to the build USE_OLLAMA_DOCKER=${USE_OLLAMA} \ USE_CUDA_DOCKER=${USE_CUDA} \ USE_CUDA_DOCKER_VER=${USE_CUDA_VER} \ USE_EMBEDDING_MODEL_DOCKER=${USE_EMBEDDING_MODEL} \ USE_RERANKING_MODEL_DOCKER=${USE_RERANKING_MODEL} ## Basis URL Config ## ENV OLLAMA_BASE_URL="/ollama" \ OPENAI_API_BASE_URL="" ## API Key and Security Config ## ENV OPENAI_API_KEY="" \ WEBUI_SECRET_KEY="" \ SCARF_NO_ANALYTICS=true \ DO_NOT_TRACK=true \ ANONYMIZED_TELEMETRY=false #### Other models ######################################################### ## whisper TTS model settings ## ENV WHISPER_MODEL="base" \ WHISPER_MODEL_DIR="/app/backend/data/cache/whisper/models" ## RAG Embedding model settings ## ENV RAG_EMBEDDING_MODEL="$USE_EMBEDDING_MODEL_DOCKER" \ RAG_RERANKING_MODEL="$USE_RERANKING_MODEL_DOCKER" \ SENTENCE_TRANSFORMERS_HOME="/app/backend/data/cache/embedding/models" ## Tiktoken model settings ## ENV TIKTOKEN_ENCODING_NAME="cl100k_base" \ TIKTOKEN_CACHE_DIR="/app/backend/data/cache/tiktoken" ## Hugging Face download cache ## ENV HF_HOME="/app/backend/data/cache/embedding/models" ## Torch Extensions ## # ENV TORCH_EXTENSIONS_DIR="/.cache/torch_extensions" #### Other models ########################################################## WORKDIR /app/backend ENV HOME=/root # Create user and group if not root RUN 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 RUN mkdir -p $HOME/.cache/chroma RUN echo -n 00000000-0000-0000-0000-000000000000 > $HOME/.cache/chroma/telemetry_user_id # Make sure the user has access to the app and root directory RUN chown -R $UID:$GID /app $HOME # install python dependencies COPY --chown=$UID:$GID ./backend/requirements.txt ./requirements.txt RUN pip3 install uv && \ if [ "$USE_CUDA" = "true" ]; then \ # If you use CUDA the whisper and embedding model will be downloaded on first use 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/ # copy embedding weight from build # RUN mkdir -p /root/.cache/chroma/onnx_models/all-MiniLM-L6-v2 # COPY --from=build /app/onnx /root/.cache/chroma/onnx_models/all-MiniLM-L6-v2/onnx # copy built frontend files COPY --chown=$UID:$GID --from=build /app/build /app/build COPY --chown=$UID:$GID --from=build /app/CHANGELOG.md /app/CHANGELOG.md COPY --chown=$UID:$GID --from=build /app/package.json /app/package.json # copy backend files COPY --chown=$UID:$GID ./backend . EXPOSE 8080 HEALTHCHECK CMD curl --silent --fail http://localhost:${PORT:-8080}/health | jq -ne 'input.status == true' || exit 1 USER $UID:$GID ARG BUILD_HASH ENV WEBUI_BUILD_VERSION=${BUILD_HASH} ENV DOCKER=true CMD [ "bash", "start.sh"] ``` I just modified this.file ，other not changed. When I execute `docker-comopse up`,occurred this problem. My docker image successful builded <img width="977" alt="Image" src="https://github.com/user-attachments/assets/d5c2a6e0-53c6-4a21-b21c-8b0d082a002d" /> <img width="945" alt="Image" src="https://github.com/user-attachments/assets/cf2054ae-0130-4566-b3c7-9601a1668824" /> **ERROR MESSAGE** <img width="1358" alt="Image" src="https://github.com/user-attachments/assets/4765af25-70e2-4b47-9ddd-64cabffc2fec" />
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Reference: github-starred/open-webui#31539
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