f1a63db6fa
Base image (docker/Dockerfile): - Install JupyterLab + notebook + ipywidgets in a separate pure-Python uv pass so the cu128 pin set cannot move; EXPOSE 8888. - Bake the prebuilt llama.cpp bundle into /opt/unsloth/llama.cpp at the runtime stage using studio/install_llama_prebuilt.py from the same UNSLOTH_REF (sha256-verified, portable CUDA bundle since the build host has no GPU; arm64 resolves the linux-arm64-cuda13 bundle). Export UNSLOTH_LLAMA_CPP_PATH so unsloth_zoo's save_pretrained_gguf finds it and never reaches the interactive install prompt or a source build. - Optional github_token BuildKit secret for the resolver's API calls on shared CI runner IPs. Entrypoint: UNSLOTH_ALLOW_CPU=1 degrades a missing GPU to a warning so Docker Desktop on macOS / Windows-without-WSL2-GPU and plain CPU hosts can run Jupyter, GGUF tooling and Studio chat; with a GPU visible the normal pre-flight still runs. Full image (docker/Dockerfile.studio): now mirrors the production service set under supervisord - Studio on 8000, JupyterLab on 8888, key-only sshd on 22 (enabled only when PUBLIC_KEY/SSH_KEY is set). Points Studio's llama.cpp dir at the baked bundle to skip a duplicate download, accepts any git ref via fetch+checkout (CI passes commit SHAs), and FROMs a digest-pinned BASE_IMAGE. Publish workflow: base image moves to the base-* tag namespace; new build-studio/merge-studio jobs publish the full image as :latest (hub parity with the previous production image, which shipped Studio + Jupyter + SSH). Studio builds FROM the exact base manifest digest published by the same run. GPU smoke job now also boots the full image and probes Studio /api/health and Jupyter /api. run.sh: UNSLOTH_GPUS=none, UNSLOTH_ALLOW_CPU forwarding, UNSLOTH_PORTS publish flags, CPU-mode and Jupyter usage examples.
58 lines
1.6 KiB
Text
58 lines
1.6 KiB
Text
# Service manager for the full Unsloth image (Dockerfile.studio).
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#
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# Mirrors the service set of the production docker.io/unsloth/unsloth image:
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# studio Unsloth Studio web UI port 8000
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# jupyter JupyterLab for the notebooks port $JUPYTER_PORT (default 8888)
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# sshd key-only SSH for cloud hosts port 22
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#
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# All three log to the container's stdout/stderr (the Docker-native pattern)
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# so `docker logs` shows everything, including Studio's first-boot password
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# and Jupyter's startup line.
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[unix_http_server]
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file=/run/supervisor.sock
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chmod=0700
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[supervisorctl]
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serverurl=unix:///run/supervisor.sock
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[rpcinterface:supervisor]
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supervisor.rpcinterface_factory = supervisor.rpcinterface:make_main_rpcinterface
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[supervisord]
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nodaemon=true
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pidfile=/run/supervisord.pid
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logfile=/dev/null
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logfile_maxbytes=0
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loglevel=info
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[program:studio]
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command=%(ENV_UNSLOTH_STUDIO_HOME)s/bin/unsloth studio -H 0.0.0.0 -p 8000
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directory=/workspace
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autostart=true
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autorestart=true
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startretries=3
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startsecs=5
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stdout_logfile=/dev/stdout
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stdout_logfile_maxbytes=0
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stderr_logfile=/dev/stderr
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stderr_logfile_maxbytes=0
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[program:jupyter]
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command=jupyter lab --no-browser --ip=0.0.0.0 --port=%(ENV_JUPYTER_PORT)s --allow-root --notebook-dir=/workspace
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directory=/workspace
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autostart=true
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autorestart=true
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stdout_logfile=/dev/stdout
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stdout_logfile_maxbytes=0
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stderr_logfile=/dev/stderr
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stderr_logfile_maxbytes=0
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[program:sshd]
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command=/usr/sbin/sshd -D -e
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autostart=%(ENV_UNSLOTH_ENABLE_SSHD)s
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autorestart=true
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stdout_logfile=/dev/stdout
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stdout_logfile_maxbytes=0
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stderr_logfile=/dev/stderr
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stderr_logfile_maxbytes=0
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