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76 lines
3.7 KiB
Docker
76 lines
3.7 KiB
Docker
# docsgpt-sandbox: the always-on code-execution runner.
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#
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# One container runs a Jupyter Kernel Gateway; each sandbox session is an
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# in-process kernel (a child process), NOT a child container. This image does
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# NOT mount the Docker socket and never spawns containers — that avoids the
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# host-root risk of Docker-in-Docker and is the core security win.
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#
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# The app (backend/worker) is the CLIENT and reaches this service over
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# HTTP + WebSocket via SANDBOX_GATEWAY_URL.
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#
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# Pre-baked doc libs are all permissive (MIT/BSD/Apache) for speed/reliability;
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# runtime `pip install` still works because egress is open. PyMuPDF and any
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# other AGPL lib are intentionally excluded; Docling is deferred to its own slice.
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#
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# HARDENING (separate slice — NOT done here): run under the gVisor `runsc`
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# runtime, add network-layer SSRF blocks (drop RFC1918 / link-local /
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# 169.254.169.254), seccomp profile, read-only root FS + quota'd scratch dir,
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# and cgroup CPU/mem/PID caps wired from SANDBOX_MEMORY / SANDBOX_CPUS.
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FROM python:3.12-slim
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# Non-root user for the runner (untrusted code runs as this UID).
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RUN useradd --create-home --uid 10001 sandbox
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# Exact pins for reproducible builds and no license drift (all MIT/BSD/Apache).
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RUN pip install --no-cache-dir \
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jupyter-kernel-gateway==3.0.1 \
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ipykernel==6.29.5 \
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python-pptx==1.0.2 \
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python-docx==1.1.2 \
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openpyxl==3.1.5 \
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reportlab==4.2.5 \
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pandas==2.2.3 \
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matplotlib==3.9.2
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# Docling (MIT) — OFF by default because it pulls torch + models and makes the
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# image multi-GB. NOTE: document parsing now runs on the Celery `parsing` worker
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# (see read_document / parse_document_worker), NOT in this sandbox, so this
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# INSTALL_DOCLING build-arg path is effectively unused for the read_document flow;
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# it remains only for sandbox code that opts into Docling explicitly. The build
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# mechanics are kept for that case. Docling is MIT and uses its own PDF backend;
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# PyMuPDF (AGPL) is NOT installed here. The base image stays docling-free.
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ARG INSTALL_DOCLING=false
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RUN if [ "$INSTALL_DOCLING" = "true" ]; then \
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pip install --no-cache-dir docling==2.8.3; \
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fi
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# Env-scrubbing kernel launcher + custom kernelspec. The launcher re-execs
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# ipykernel under a minimal allowlisted env (env -i) so NO secret in the
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# gateway's environment (*_API_KEY, *_TOKEN, POSTGRES_URI, the gateway auth
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# token, ...) ever reaches kernel code. The kernelspec ships under a DISTINCT
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# name ("docsgpt-python"), so the app selects it with SANDBOX_KERNEL_NAME and it
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# is never shadowed by the stock ipykernel "python3" spec regardless of the
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# python prefix. The stock "python3" spec is left untouched (no overwrite, no
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# kernelspec-name precedence to rely on). SECURITY: never give this image
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# `env_file: ../.env` -- the scrubber blocks exfil from the kernel, but the
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# runner image itself should stay free of app secrets it has no use for.
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COPY kernel-launch.sh /opt/docsgpt/kernel-launch.sh
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RUN chmod 0555 /opt/docsgpt/kernel-launch.sh
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COPY gateway-launch.sh /opt/docsgpt/gateway-launch.sh
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RUN chmod 0555 /opt/docsgpt/gateway-launch.sh
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COPY kernels/docsgpt-python/kernel.json /usr/local/share/jupyter/kernels/docsgpt-python/kernel.json
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# Numeric UID (not the name) so a kubelet with `runAsNonRoot: true` can verify
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# the user is non-root without resolving /etc/passwd. This uid MUST match
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# `runAsUser` in deployment/k8s/deployments/sandbox-deploy.yaml.
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USER 10001
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WORKDIR /home/sandbox
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EXPOSE 8888
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# The launcher REQUIRES SANDBOX_GATEWAY_AUTH_TOKEN and fails closed if it is
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# unset: the gateway control API is reachable from kernel code over loopback, so
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# it must never run unauthenticated (see gateway-launch.sh). The token is shared
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# with the app and is scrubbed from the kernel env by kernel-launch.sh.
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CMD ["/opt/docsgpt/gateway-launch.sh"]
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