代码部署说明
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@@ -0,0 +1,17 @@
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.git
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.pytest_cache
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.ruff_cache
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.venv
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__pycache__
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*.py[cod]
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*.pyo
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*.zip
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# Runtime state is mounted from the host in Docker deployments.
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.deer-flow
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logs
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# Local/offline artifacts should not be baked into the runtime image.
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docker-data
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dist
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wheelhouse
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@@ -0,0 +1,52 @@
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# Backend Docker Offline Deployment
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Build once on an online Linux server:
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```bash
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cd offline-backend-20260512/backend
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chmod +x build-backend-image.sh save-backend-image.sh start-backend-docker.sh
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./build-backend-image.sh
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./save-backend-image.sh
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```
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The build script defaults to Aliyun for apt packages and Tsinghua for Python packages:
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```bash
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APT_MIRROR=mirrors.aliyun.com \
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UV_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple/ \
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./build-backend-image.sh
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```
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The Docker build installs the pinned `requirements-offline.txt` with pip from
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the configured Python mirror, so the dependency image contains the backend
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runtime dependencies and can be moved to an offline machine.
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Move `dist/deerflow-backend-offline.tar` plus this backend directory to the
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offline machine, then load and start:
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```bash
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docker load -i deerflow-backend-offline.tar
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./start-backend-docker.sh 8001
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```
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Useful overrides:
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```bash
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BACKEND_PORT=9001 ./start-backend-docker.sh
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IMAGE_NAME=your-image:tag ./start-backend-docker.sh 9001
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DATA_DIR=/data/deerflow-backend ./start-backend-docker.sh
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```
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The startup script bind-mounts these host paths:
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- backend code: current backend directory -> `/app/backend`
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- config: `docker-data/config/config.yaml`, `extensions_config.json`, `.env`
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- agents and SQLite/runtime data: `docker-data/.deer-flow`
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- skills: `docker-data/skills`
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- logs: `docker-data/logs`
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Edit files under `docker-data/` on the host, then restart the container:
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```bash
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docker restart deerflow-backend
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```
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@@ -0,0 +1,108 @@
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# Backend-only DeerFlow image for offline delivery.
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#
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# Build online once, then export with:
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# docker save deerflow-backend-offline:latest -o deerflow-backend-offline.tar
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#
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# Runtime code/config/data are bind-mounted by start-backend-docker.sh so the
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# customer can edit code, agents, skills, config.yaml, .env, and SQLite data
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# without rebuilding this dependency image.
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ARG PYTHON_IMAGE=python:3.12-slim-bookworm
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FROM ${PYTHON_IMAGE} AS builder
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ARG APT_MIRROR=mirrors.aliyun.com
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ARG UV_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple/
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ARG UV_VERSION=0.7.20
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ARG UV_NO_CACHE=1
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ARG UV_COMPILE_BYTECODE=0
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ENV UV_PROJECT_ENVIRONMENT=/opt/venv \
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UV_INDEX_URL=${UV_INDEX_URL} \
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UV_LINK_MODE=copy \
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UV_NO_CACHE=${UV_NO_CACHE} \
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UV_COMPILE_BYTECODE=${UV_COMPILE_BYTECODE} \
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PIP_DISABLE_PIP_VERSION_CHECK=1 \
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PYTHONDONTWRITEBYTECODE=1 \
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PYTHONUNBUFFERED=1
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WORKDIR /build/backend
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RUN if [ -n "${APT_MIRROR}" ]; then \
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sed -i "s|deb.debian.org|${APT_MIRROR}|g" /etc/apt/sources.list.d/debian.sources 2>/dev/null || true; \
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sed -i "s|security.debian.org|${APT_MIRROR}|g" /etc/apt/sources.list.d/debian.sources 2>/dev/null || true; \
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sed -i "s|deb.debian.org|${APT_MIRROR}|g" /etc/apt/sources.list 2>/dev/null || true; \
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sed -i "s|security.debian.org|${APT_MIRROR}|g" /etc/apt/sources.list 2>/dev/null || true; \
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fi \
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&& apt-get update \
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&& apt-get install -y --no-install-recommends \
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build-essential \
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ca-certificates \
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curl \
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git \
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&& rm -rf /var/lib/apt/lists/* \
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&& python -m pip install --no-cache-dir -i "${UV_INDEX_URL}" "uv==${UV_VERSION}"
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ARG UV_HTTP_TIMEOUT=300
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ARG UV_CONCURRENT_DOWNLOADS=4
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ARG UV_CONCURRENT_INSTALLS=4
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ARG UV_CONCURRENT_BUILDS=2
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ENV UV_HTTP_TIMEOUT=${UV_HTTP_TIMEOUT} \
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UV_CONCURRENT_DOWNLOADS=${UV_CONCURRENT_DOWNLOADS} \
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UV_CONCURRENT_INSTALLS=${UV_CONCURRENT_INSTALLS} \
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UV_CONCURRENT_BUILDS=${UV_CONCURRENT_BUILDS}
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COPY pyproject.toml uv.lock README.md requirements-offline.txt ./
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COPY packages ./packages
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RUN python -m venv /opt/venv \
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&& /opt/venv/bin/python -m pip install --no-cache-dir --upgrade -i "${UV_INDEX_URL}" pip setuptools wheel \
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&& sed -E '/--hash=/d; s/[[:space:]]+\\$//; s|^-e[[:space:]]+./packages/harness$|./packages/harness|' requirements-offline.txt > /tmp/requirements-docker.txt \
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&& /opt/venv/bin/pip install --no-cache-dir -i "${UV_INDEX_URL}" -r /tmp/requirements-docker.txt \
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&& /opt/venv/bin/pip install --no-cache-dir -i "${UV_INDEX_URL}" "asyncmy>=0.2.11"
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COPY . .
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FROM ${PYTHON_IMAGE} AS runtime
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ARG APT_MIRROR=mirrors.aliyun.com
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ENV PATH=/opt/venv/bin:$PATH \
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PYTHONPATH=/app/backend:/app/backend/packages/harness \
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PYTHONDONTWRITEBYTECODE=1 \
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PYTHONUNBUFFERED=1 \
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DEER_FLOW_PROJECT_ROOT=/app/backend \
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DEER_FLOW_HOME=/app/backend/.deer-flow \
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DEER_FLOW_CONFIG_PATH=/app/backend/config.yaml \
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DEER_FLOW_EXTENSIONS_CONFIG_PATH=/app/backend/extensions_config.json \
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DEER_FLOW_SKILLS_PATH=/app/backend/skills \
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BACKEND_PORT=8001
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WORKDIR /app/backend
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RUN if [ -n "${APT_MIRROR}" ]; then \
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sed -i "s|deb.debian.org|${APT_MIRROR}|g" /etc/apt/sources.list.d/debian.sources 2>/dev/null || true; \
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sed -i "s|security.debian.org|${APT_MIRROR}|g" /etc/apt/sources.list.d/debian.sources 2>/dev/null || true; \
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sed -i "s|deb.debian.org|${APT_MIRROR}|g" /etc/apt/sources.list 2>/dev/null || true; \
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sed -i "s|security.debian.org|${APT_MIRROR}|g" /etc/apt/sources.list 2>/dev/null || true; \
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fi \
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&& apt-get update \
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&& apt-get install -y --no-install-recommends \
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ca-certificates \
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curl \
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docker.io \
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libmagic1 \
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nodejs \
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npm \
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poppler-utils \
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tini \
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&& rm -rf /var/lib/apt/lists/*
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COPY --from=builder /opt/venv /opt/venv
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COPY --from=builder /build/backend /app/backend
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EXPOSE 8001
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ENTRYPOINT ["tini", "--"]
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CMD ["sh", "-c", "cd /app/backend && exec uvicorn app.gateway.app:app --host 0.0.0.0 --port ${BACKEND_PORT:-8001}"]
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@@ -0,0 +1,32 @@
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#!/usr/bin/env bash
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set -euo pipefail
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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IMAGE_NAME="${IMAGE_NAME:-deerflow-backend-offline:latest}"
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APT_MIRROR="${APT_MIRROR:-mirrors.aliyun.com}"
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UV_INDEX_URL="${UV_INDEX_URL:-https://pypi.tuna.tsinghua.edu.cn/simple/}"
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UV_HTTP_TIMEOUT="${UV_HTTP_TIMEOUT:-300}"
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UV_NO_CACHE="${UV_NO_CACHE:-1}"
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UV_COMPILE_BYTECODE="${UV_COMPILE_BYTECODE:-0}"
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UV_CONCURRENT_DOWNLOADS="${UV_CONCURRENT_DOWNLOADS:-4}"
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UV_CONCURRENT_INSTALLS="${UV_CONCURRENT_INSTALLS:-4}"
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UV_CONCURRENT_BUILDS="${UV_CONCURRENT_BUILDS:-2}"
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PYTHON_IMAGE="${PYTHON_IMAGE:-python:3.12-slim-bookworm}"
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cd "${SCRIPT_DIR}"
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docker build \
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-f Dockerfile.backend-offline \
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-t "${IMAGE_NAME}" \
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--build-arg "PYTHON_IMAGE=${PYTHON_IMAGE}" \
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--build-arg "APT_MIRROR=${APT_MIRROR}" \
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--build-arg "UV_INDEX_URL=${UV_INDEX_URL}" \
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--build-arg "UV_HTTP_TIMEOUT=${UV_HTTP_TIMEOUT}" \
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--build-arg "UV_NO_CACHE=${UV_NO_CACHE}" \
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--build-arg "UV_COMPILE_BYTECODE=${UV_COMPILE_BYTECODE}" \
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--build-arg "UV_CONCURRENT_DOWNLOADS=${UV_CONCURRENT_DOWNLOADS}" \
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--build-arg "UV_CONCURRENT_INSTALLS=${UV_CONCURRENT_INSTALLS}" \
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--build-arg "UV_CONCURRENT_BUILDS=${UV_CONCURRENT_BUILDS}" \
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.
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echo "Built image: ${IMAGE_NAME}"
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@@ -0,0 +1,13 @@
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#!/usr/bin/env bash
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set -euo pipefail
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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IMAGE_NAME="${IMAGE_NAME:-deerflow-backend-offline:latest}"
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OUT_DIR="${OUT_DIR:-${SCRIPT_DIR}/dist}"
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OUT_FILE="${OUT_FILE:-${OUT_DIR}/deerflow-backend-offline.tar}"
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mkdir -p "${OUT_DIR}"
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docker save "${IMAGE_NAME}" -o "${OUT_FILE}"
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echo "Saved image: ${OUT_FILE}"
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echo "Offline load command: docker load -i ${OUT_FILE}"
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@@ -0,0 +1,102 @@
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#!/usr/bin/env bash
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set -euo pipefail
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SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
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IMAGE_NAME="${IMAGE_NAME:-deerflow-backend-offline:latest}"
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CONTAINER_NAME="${CONTAINER_NAME:-deerflow-backend}"
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BACKEND_PORT="${1:-${BACKEND_PORT:-8001}}"
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CODE_DIR="${CODE_DIR:-${SCRIPT_DIR}}"
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DATA_DIR="${DATA_DIR:-${SCRIPT_DIR}/docker-data}"
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CONFIG_DIR="${CONFIG_DIR:-${DATA_DIR}/config}"
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RUNTIME_DIR="${RUNTIME_DIR:-${DATA_DIR}/.deer-flow}"
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SKILLS_DIR="${SKILLS_DIR:-${DATA_DIR}/skills}"
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KNOWLEDGE_DIR="${KNOWLEDGE_DIR:-${DATA_DIR}/knowledge}"
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LOGS_DIR="${LOGS_DIR:-${DATA_DIR}/logs}"
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CONFIG_FILE="${CONFIG_DIR}/config.yaml"
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EXTENSIONS_FILE="${CONFIG_DIR}/extensions_config.json"
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LANGGRAPH_FILE="${CONFIG_DIR}/langgraph.json"
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ENV_FILE="${CONFIG_DIR}/.env"
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copy_if_missing() {
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local src="$1"
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local dst="$2"
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if [[ ! -e "${dst}" && -e "${src}" ]]; then
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mkdir -p "$(dirname "${dst}")"
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cp -a "${src}" "${dst}"
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fi
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}
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copy_dir_if_missing() {
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local src="$1"
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local dst="$2"
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if [[ ! -e "${dst}" && -d "${src}" ]]; then
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mkdir -p "$(dirname "${dst}")"
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cp -a "${src}" "${dst}"
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fi
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}
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mkdir -p "${CONFIG_DIR}" "${RUNTIME_DIR}/data" "${LOGS_DIR}"
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copy_if_missing "${CODE_DIR}/config.yaml" "${CONFIG_FILE}"
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copy_if_missing "${CODE_DIR}/extensions_config.json" "${EXTENSIONS_FILE}"
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copy_if_missing "${CODE_DIR}/langgraph.json" "${LANGGRAPH_FILE}"
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copy_if_missing "${CODE_DIR}/.env" "${ENV_FILE}"
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touch "${ENV_FILE}"
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copy_dir_if_missing "${CODE_DIR}/skills" "${SKILLS_DIR}"
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mkdir -p "${SKILLS_DIR}"
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copy_dir_if_missing "${CODE_DIR}/knowledge" "${KNOWLEDGE_DIR}"
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mkdir -p "${KNOWLEDGE_DIR}"
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copy_dir_if_missing "${CODE_DIR}/.deer-flow/agents" "${RUNTIME_DIR}/agents"
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copy_dir_if_missing "${CODE_DIR}/.deer-flow/channels" "${RUNTIME_DIR}/channels"
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copy_dir_if_missing "${CODE_DIR}/.deer-flow/users" "${RUNTIME_DIR}/users"
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copy_if_missing "${CODE_DIR}/.deer-flow/SOUL.md" "${RUNTIME_DIR}/SOUL.md"
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copy_if_missing "${CODE_DIR}/.deer-flow/USER.md" "${RUNTIME_DIR}/USER.md"
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copy_if_missing "${CODE_DIR}/.deer-flow/system_settings.json" "${RUNTIME_DIR}/system_settings.json"
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if docker ps -a --format '{{.Names}}' | grep -Fxq "${CONTAINER_NAME}"; then
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docker rm -f "${CONTAINER_NAME}" >/dev/null
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fi
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DOCKER_ARGS=(
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run -d
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--name "${CONTAINER_NAME}"
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--restart unless-stopped
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-p "${BACKEND_PORT}:${BACKEND_PORT}"
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--add-host host.docker.internal:host-gateway
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-e "BACKEND_PORT=${BACKEND_PORT}"
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-e "DEER_FLOW_GATEWAY_PORT=${BACKEND_PORT}"
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-e "DEER_FLOW_PROJECT_ROOT=/app/backend"
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-e "DEER_FLOW_HOME=/app/backend/.deer-flow"
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-e "DEER_FLOW_HOST_BASE_DIR=${RUNTIME_DIR}"
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-e "DEER_FLOW_CONFIG_PATH=/app/backend/config.yaml"
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-e "DEER_FLOW_EXTENSIONS_CONFIG_PATH=/app/backend/extensions_config.json"
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-e "DEER_FLOW_SKILLS_PATH=/app/backend/skills"
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-v "${CODE_DIR}:/app/backend"
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-v "${CONFIG_FILE}:/app/backend/config.yaml"
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-v "${EXTENSIONS_FILE}:/app/backend/extensions_config.json"
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-v "${LANGGRAPH_FILE}:/app/backend/langgraph.json"
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-v "${ENV_FILE}:/app/backend/.env"
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-v "${RUNTIME_DIR}:/app/backend/.deer-flow"
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-v "${SKILLS_DIR}:/app/backend/skills"
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-v "${KNOWLEDGE_DIR}:/app/backend/knowledge"
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-v "${LOGS_DIR}:/app/backend/logs"
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)
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if [[ -S /var/run/docker.sock ]]; then
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DOCKER_ARGS+=(-v /var/run/docker.sock:/var/run/docker.sock)
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fi
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DOCKER_ARGS+=("${IMAGE_NAME}")
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docker "${DOCKER_ARGS[@]}"
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echo "Started ${CONTAINER_NAME}"
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echo "Backend: http://127.0.0.1:${BACKEND_PORT}"
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echo "Config: ${CONFIG_DIR}"
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echo "Data: ${DATA_DIR}"
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@@ -0,0 +1,403 @@
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# DeerFlow 后台离线部署说明
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本文档只说明“后台服务”的离线部署，不包含前端。
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## 1. 当前服务器文件位置
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当前已经在服务器上准备好的部署目录是：
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```bash
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/opt/deerflow-backend
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```
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主要文件和目录如下：
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```text
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/opt/deerflow-backend/
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├── dist/deerflow-backend-offline.tar # 离线 Docker 镜像包
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├── start-backend-docker.sh # 启动脚本
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├── save-backend-image.sh # 镜像导出脚本
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├── build-backend-image.sh # 在线构建脚本
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├── config.yaml # 默认配置模板
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├── extensions_config.json # 默认扩展配置模板
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├── langgraph.json # LangGraph 配置
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├── .env # 环境变量文件，没有则启动脚本会创建空文件
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├── .deer-flow/agents/ # 默认智能体模板目录
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├── skills/ # 默认技能模板目录
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└── docker-data/ # 实际运行时挂载数据，启动后生成
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```
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当前服务器已验证：
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```bash
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cd /opt/deerflow-backend
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./start-backend-docker.sh 8001
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```
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健康检查：
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```bash
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curl http://127.0.0.1:8001/health
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curl http://127.0.0.1:8001/api/health
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```
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## 2. 客户现场更换部署目录
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客户现场可以换任意部署目录，不需要改脚本。把整个 `deerflow-backend` 目录放到目标位置即可。
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示例：客户现场部署到 `/data/deerflow-backend`
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```bash
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DEPLOY_DIR=/data/deerflow-backend
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mkdir -p "$DEPLOY_DIR"
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# 将交付的 deerflow-backend 目录内容放到 $DEPLOY_DIR
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cd "$DEPLOY_DIR"
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chmod +x *.sh
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```
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加载离线镜像：
|
||||
|
||||
```bash
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docker load -i dist/deerflow-backend-offline.tar
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||||
```
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||||
启动后台，端口可改：
|
||||
|
||||
```bash
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./start-backend-docker.sh 8001
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||||
```
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||||
|
||||
如果客户现场要用 `9001` 端口：
|
||||
|
||||
```bash
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./start-backend-docker.sh 9001
|
||||
```
|
||||
|
||||
脚本会自动把当前目录作为代码目录，把数据放到：
|
||||
|
||||
```text
|
||||
$DEPLOY_DIR/docker-data
|
||||
```
|
||||
|
||||
## 3. 数据、配置、智能体、技能目录
|
||||
|
||||
启动后，实际可修改的文件都在宿主机目录，不在容器内部。
|
||||
|
||||
默认目录如下：
|
||||
|
||||
```text
|
||||
$DEPLOY_DIR/docker-data/config # 配置目录
|
||||
$DEPLOY_DIR/docker-data/.deer-flow # 运行时目录：智能体、用户数据、SQLite 数据
|
||||
$DEPLOY_DIR/docker-data/skills # 技能目录
|
||||
$DEPLOY_DIR/docker-data/knowledge # 知识库目录
|
||||
$DEPLOY_DIR/docker-data/logs # 日志目录
|
||||
```
|
||||
|
||||
配置文件位置：
|
||||
|
||||
```text
|
||||
$DEPLOY_DIR/docker-data/config/config.yaml
|
||||
$DEPLOY_DIR/docker-data/config/extensions_config.json
|
||||
$DEPLOY_DIR/docker-data/config/langgraph.json
|
||||
$DEPLOY_DIR/docker-data/config/.env
|
||||
```
|
||||
|
||||
智能体目录：
|
||||
|
||||
```text
|
||||
$DEPLOY_DIR/docker-data/.deer-flow/agents
|
||||
```
|
||||
|
||||
技能目录：
|
||||
|
||||
```text
|
||||
$DEPLOY_DIR/docker-data/skills/public
|
||||
$DEPLOY_DIR/docker-data/skills/custom
|
||||
```
|
||||
|
||||
SQLite 聊天/checkpointer 数据库目录：
|
||||
|
||||
```text
|
||||
$DEPLOY_DIR/docker-data/.deer-flow/data
|
||||
$DEPLOY_DIR/docker-data/.deer-flow/.deer-flow/data
|
||||
```
|
||||
|
||||
注意：当前部署使用 **MySQL 业务库 + SQLite 聊天/checkpointer 库**，不使用 PostgreSQL。SQLite 运行时可能同时有以下文件，备份或替换时要一起处理：
|
||||
|
||||
```text
|
||||
deerflow.db
|
||||
deerflow.db-wal
|
||||
deerflow.db-shm
|
||||
```
|
||||
|
||||
## 4. 客户现场加载智能体和技能
|
||||
|
||||
推荐流程：
|
||||
|
||||
1. 先启动一次，让目录自动生成。
|
||||
2. 停止容器。
|
||||
3. 复制客户的智能体、技能、SQLite 聊天库文件，并配置 MySQL 地址。
|
||||
4. 再启动容器。
|
||||
|
||||
命令示例：
|
||||
|
||||
```bash
|
||||
cd "$DEPLOY_DIR"
|
||||
./start-backend-docker.sh 8001
|
||||
docker rm -f deerflow-backend
|
||||
```
|
||||
|
||||
复制智能体：
|
||||
|
||||
```bash
|
||||
mkdir -p "$DEPLOY_DIR/docker-data/.deer-flow/agents"
|
||||
cp -a /path/to/customer-agents/. "$DEPLOY_DIR/docker-data/.deer-flow/agents/"
|
||||
```
|
||||
|
||||
复制技能：
|
||||
|
||||
```bash
|
||||
mkdir -p "$DEPLOY_DIR/docker-data/skills/public"
|
||||
mkdir -p "$DEPLOY_DIR/docker-data/skills/custom"
|
||||
|
||||
cp -a /path/to/customer-skills/public/. "$DEPLOY_DIR/docker-data/skills/public/"
|
||||
cp -a /path/to/customer-skills/custom/. "$DEPLOY_DIR/docker-data/skills/custom/"
|
||||
```
|
||||
|
||||
重新启动：
|
||||
|
||||
```bash
|
||||
cd "$DEPLOY_DIR"
|
||||
./start-backend-docker.sh 8001
|
||||
```
|
||||
|
||||
如果只更新技能或智能体，不换数据库，也可以复制后直接重启：
|
||||
|
||||
```bash
|
||||
docker restart deerflow-backend
|
||||
```
|
||||
|
||||
## 5. 修改或替换 SQLite 聊天/checkpointer 数据库
|
||||
|
||||
SQLite 只保存聊天运行时、LangGraph checkpointer、部分本地运行数据。业务表使用 MySQL，MySQL 地址见第 6 节。
|
||||
|
||||
最稳的方式是停容器后整体替换运行时目录：
|
||||
|
||||
```bash
|
||||
cd "$DEPLOY_DIR"
|
||||
docker rm -f deerflow-backend
|
||||
|
||||
mv docker-data/.deer-flow docker-data/.deer-flow.bak.$(date +%Y%m%d%H%M%S)
|
||||
cp -a /path/to/customer-dot-deer-flow "$DEPLOY_DIR/docker-data/.deer-flow"
|
||||
|
||||
./start-backend-docker.sh 8001
|
||||
```
|
||||
|
||||
如果只替换数据库文件，至少要处理这两个目录里的 `deerflow.db*`：
|
||||
|
||||
```text
|
||||
$DEPLOY_DIR/docker-data/.deer-flow/data/deerflow.db*
|
||||
$DEPLOY_DIR/docker-data/.deer-flow/.deer-flow/data/deerflow.db*
|
||||
```
|
||||
|
||||
操作示例：
|
||||
|
||||
```bash
|
||||
cd "$DEPLOY_DIR"
|
||||
docker rm -f deerflow-backend
|
||||
|
||||
mkdir -p docker-data/.deer-flow/data
|
||||
mkdir -p docker-data/.deer-flow/.deer-flow/data
|
||||
|
||||
cp -a /path/to/db-main/deerflow.db* docker-data/.deer-flow/data/
|
||||
cp -a /path/to/db-runtime/deerflow.db* docker-data/.deer-flow/.deer-flow/data/
|
||||
|
||||
./start-backend-docker.sh 8001
|
||||
```
|
||||
|
||||
不要在容器运行时直接覆盖 SQLite 文件，容易损坏 WAL 数据。
|
||||
|
||||
## 6. 修改配置和数据库配置
|
||||
|
||||
默认配置会在第一次启动时复制到：
|
||||
|
||||
```text
|
||||
$DEPLOY_DIR/docker-data/config/config.yaml
|
||||
```
|
||||
|
||||
要改配置，改这个文件，不要进容器改。
|
||||
|
||||
本项目现场部署按 **MySQL + SQLite** 使用：
|
||||
|
||||
- MySQL：业务表，例如用户、智能体、技能、任务、菜单、按钮、敏感词、轻应用等。
|
||||
- SQLite：聊天运行时和 LangGraph checkpointer，继续放在挂载出来的 `.deer-flow` 目录。
|
||||
- 不使用 PostgreSQL，不要配置 `database.backend: postgres`，也不要配置 `POSTGRES_URL`。
|
||||
|
||||
MySQL 地址主要改两个文件：
|
||||
|
||||
```text
|
||||
$DEPLOY_DIR/docker-data/config/config.yaml
|
||||
$DEPLOY_DIR/docker-data/config/.env
|
||||
```
|
||||
|
||||
`config.yaml` 里的数据库配置建议改成：
|
||||
|
||||
```yaml
|
||||
database:
|
||||
backend: mysql
|
||||
sqlite_dir: .deer-flow/data
|
||||
mysql_url: $MYSQL_DATABASE_URL
|
||||
pool_size: 20
|
||||
max_overflow: 20
|
||||
pool_timeout: 30
|
||||
echo_sql: false
|
||||
|
||||
checkpointer:
|
||||
type: sqlite
|
||||
connection_string: .deer-flow/data/deerflow.db
|
||||
```
|
||||
|
||||
然后在 `.env` 里写 MySQL 连接地址：
|
||||
|
||||
```bash
|
||||
MYSQL_DATABASE_URL=mysql+asyncmy://deerflow:密码@192.168.1.10:3306/deerflow?charset=utf8mb4
|
||||
```
|
||||
|
||||
把上面示例里的内容换成客户现场真实值：
|
||||
|
||||
```text
|
||||
deerflow # MySQL 用户名
|
||||
密码 # MySQL 密码
|
||||
192.168.1.10 # MySQL 服务器 IP
|
||||
3306 # MySQL 端口
|
||||
deerflow # MySQL 数据库名
|
||||
```
|
||||
|
||||
如果 MySQL 就装在 Docker 宿主机这台服务器上，容器里不要写 `127.0.0.1`，建议写：
|
||||
|
||||
```bash
|
||||
MYSQL_DATABASE_URL=mysql+asyncmy://deerflow:密码@host.docker.internal:3306/deerflow?charset=utf8mb4
|
||||
```
|
||||
|
||||
如果密码里有特殊字符，需要做 URL 编码，常见示例：
|
||||
|
||||
```text
|
||||
@ 写成 %40
|
||||
# 写成 %23
|
||||
% 写成 %25
|
||||
空格 写成 %20
|
||||
```
|
||||
|
||||
MySQL 数据库建议提前建好：
|
||||
|
||||
```sql
|
||||
CREATE DATABASE deerflow CHARACTER SET utf8mb4 COLLATE utf8mb4_unicode_ci;
|
||||
```
|
||||
|
||||
如果 MySQL 用户有建库权限，服务启动时也会尝试自动创建缺失的数据库。客户现场更稳的做法是先建库、导入 MySQL 备份，再启动后台。
|
||||
|
||||
如果客户现场已有 MySQL 备份，先在客户 MySQL 中导入：
|
||||
|
||||
```bash
|
||||
mysql -h 192.168.1.10 -P 3306 -u deerflow -p deerflow < deerflow_mysql.sql
|
||||
```
|
||||
|
||||
SQLite 聊天库仍按第 5 节复制到：
|
||||
|
||||
```text
|
||||
$DEPLOY_DIR/docker-data/.deer-flow/data/deerflow.db*
|
||||
$DEPLOY_DIR/docker-data/.deer-flow/.deer-flow/data/deerflow.db*
|
||||
```
|
||||
|
||||
如果需要把数据目录单独放到别的位置，不需要改 `config.yaml`，启动时指定 `DATA_DIR` 更稳：
|
||||
|
||||
```bash
|
||||
cd "$DEPLOY_DIR"
|
||||
DATA_DIR=/data/deerflow-backend-data ./start-backend-docker.sh 8001
|
||||
```
|
||||
|
||||
此时实际目录变成：
|
||||
|
||||
```text
|
||||
/data/deerflow-backend-data/config
|
||||
/data/deerflow-backend-data/.deer-flow
|
||||
/data/deerflow-backend-data/skills
|
||||
/data/deerflow-backend-data/knowledge
|
||||
/data/deerflow-backend-data/logs
|
||||
```
|
||||
|
||||
如果客户现场部署目录变化，只需要换 `DEPLOY_DIR` 或把整包放到新目录；MySQL 地址仍然只改 `$DEPLOY_DIR/docker-data/config/.env`，SQLite/智能体/技能仍然跟着 `DATA_DIR` 走。
|
||||
|
||||
如果要改 `.env`，位置是：
|
||||
|
||||
```text
|
||||
$DEPLOY_DIR/docker-data/config/.env
|
||||
```
|
||||
|
||||
修改配置后重启：
|
||||
|
||||
```bash
|
||||
cd "$DEPLOY_DIR"
|
||||
docker rm -f deerflow-backend
|
||||
./start-backend-docker.sh 8001
|
||||
```
|
||||
|
||||
## 7. 常用运维命令
|
||||
|
||||
查看容器：
|
||||
|
||||
```bash
|
||||
docker ps -a --filter name=deerflow-backend
|
||||
```
|
||||
|
||||
查看日志：
|
||||
|
||||
```bash
|
||||
docker logs -f --tail 200 deerflow-backend
|
||||
```
|
||||
|
||||
停止：
|
||||
|
||||
```bash
|
||||
docker rm -f deerflow-backend
|
||||
```
|
||||
|
||||
重启：
|
||||
|
||||
```bash
|
||||
docker restart deerflow-backend
|
||||
```
|
||||
|
||||
重新启动并换端口：
|
||||
|
||||
```bash
|
||||
cd "$DEPLOY_DIR"
|
||||
./start-backend-docker.sh 9001
|
||||
```
|
||||
|
||||
检查接口：
|
||||
|
||||
```bash
|
||||
curl http://127.0.0.1:8001/health
|
||||
curl http://127.0.0.1:8001/api/health
|
||||
```
|
||||
|
||||
## 8. 交付清单
|
||||
|
||||
客户离线部署至少需要：
|
||||
|
||||
```text
|
||||
deerflow-backend/
|
||||
├── dist/deerflow-backend-offline.tar
|
||||
├── start-backend-docker.sh
|
||||
├── config.yaml
|
||||
├── extensions_config.json
|
||||
├── langgraph.json
|
||||
├── .env
|
||||
├── .deer-flow/agents/
|
||||
├── skills/
|
||||
└── 其他后台代码文件
|
||||
```
|
||||
|
||||
客户机器需要提前安装好 Docker。离线部署时不需要再下载 Python 依赖，依赖已经包含在 Docker 镜像里。
|
||||
Reference in new issue
Block a user