cleanup: remove outdated deployment / development dirs (#193)
Meng Zhang
GitHub
parent
2bf5bcd0cf
commit
63ca6225ba
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@ -1,91 +0,0 @@
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name: Create and publish docker image
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on:
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workflow_dispatch:
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push:
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branches: [ "main" ]
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paths:
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- 'poetry.lock'
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- 'tabby/**'
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jobs:
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build:
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runs-on: ubuntu-latest
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permissions:
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contents: read
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packages: write
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# This is used to complete the identity challenge
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# with sigstore/fulcio when running outside of PRs.
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id-token: write
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steps:
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- name: Free Disk Space (Ubuntu)
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uses: jlumbroso/free-disk-space@main
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with:
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# this might remove tools that are actually needed,
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# if set to "true" but frees about 6 GB
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tool-cache: true
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# all of these default to true, but feel free to set to
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# "false" if necessary for your workflow
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android: true
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dotnet: true
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haskell: true
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large-packages: false
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swap-storage: true
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- name: Checkout repository
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uses: actions/checkout@v3
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# Workaround: https://github.com/docker/build-push-action/issues/461
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- name: Setup Docker buildx
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uses: docker/setup-buildx-action@v2.0.0
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# Login against a Docker registry except on PR
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# https://github.com/docker/login-action
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- name: Log into GitHub Container registry
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if: github.event_name != 'pull_request'
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uses: docker/login-action@v2.0.0
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with:
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registry: ghcr.io
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username: ${{ github.actor }}
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password: ${{ secrets.GITHUB_TOKEN }}
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- name: Log into Docker Hub
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if: github.event_name != 'pull_request'
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uses: docker/login-action@v2.0.0
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with:
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username: ${{ secrets.DOCKERHUB_USERNAME }}
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password: ${{ secrets.DOCKERHUB_TOKEN }}
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- name: Generate image name
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run: |
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echo "IMAGE_NAME=${GITHUB_REPOSITORY,,}" >>${GITHUB_ENV}
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- uses: int128/docker-build-cache-config-action@v1
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id: cache
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with:
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image: ghcr.io/${{ env.IMAGE_NAME }}/cache
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# Build and push Docker image with Buildx (don't push on PR)
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# https://github.com/docker/build-push-action
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- name: Build and push Docker image
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id: build-and-push
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uses: docker/build-push-action@v3.1.1
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with:
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file: Dockerfile
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context: .
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push: ${{ github.event_name != 'pull_request' }}
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tags: |
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ghcr.io/${{ env.IMAGE_NAME }}:latest
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${{ env.IMAGE_NAME }}:latest
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cache-from: ${{ steps.cache.outputs.cache-from }}
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cache-to: ${{ steps.cache.outputs.cache-to }}
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- name: Docker Hub Description
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uses: peter-evans/dockerhub-description@v3
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with:
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username: ${{ secrets.DOCKERHUB_USERNAME }}
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password: ${{ secrets.DOCKERHUB_TOKEN }}
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repository: tabbyml/tabby
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73
Dockerfile
73
Dockerfile
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# syntax = docker/dockerfile:1.5
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FROM tabbyml/fastertransformer_backend
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RUN apt update && apt -y install build-essential libssl-dev zlib1g-dev \
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libbz2-dev libreadline-dev libsqlite3-dev curl \
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libncursesw5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev libffi-dev liblzma-dev
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RUN mkdir -p /home/app
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RUN chown 1000 /home/app
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USER 1000
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WORKDIR /home/app
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ENV HOME /home/app
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# Setup pyenv
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RUN git clone --depth=1 https://github.com/pyenv/pyenv.git .pyenv
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ENV PATH="$HOME/.pyenv/shims:/home/app/.pyenv/bin:$PATH"
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ARG PYTHON_VERSION=3.10.10
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RUN pyenv install ${PYTHON_VERSION}
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RUN pyenv global ${PYTHON_VERSION}
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ARG PYPI_INDEX_URL=https://pypi.org/simple
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ARG POETRY_VERSION=1.4.0
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RUN --mount=type=cache,target=$HOME/.cache pip install -i $PYPI_INDEX_URL "poetry==$POETRY_VERSION"
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# vector
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RUN <<EOF
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curl --proto '=https' --tlsv1.2 -sSf https://sh.vector.dev | bash -s -- -y
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EOF
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ENV PATH "$HOME/.vector/bin:$PATH"
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# Supervisord
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RUN --mount=type=cache,target=$HOME/.cache pip install -i $PYPI_INDEX_URL supervisor
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RUN mkdir -p ~/.bin
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ENV PATH "$HOME/.bin:$PATH"
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# Install dagu
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RUN <<EOF
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curl -L https://github.com/yohamta/dagu/releases/download/v1.10.2/dagu_1.10.2_Linux_x86_64.tar.gz > dagu.tar.gz
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tar zxvf dagu.tar.gz
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mv dagu ~/.bin/
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rm dagu.tar.gz LICENSE.md README.md
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EOF
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# Install tabby dependencies
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COPY poetry.lock pyproject.toml ./
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RUN poetry export --without-hashes > requirements.txt
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RUN --mount=type=cache,target=$HOME/.cache pip install -i $PYPI_INDEX_URL --no-dependencies -r requirements.txt
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COPY tabby ./tabby
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# Install caddy
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RUN <<EOF
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curl -L "https://github.com/caddyserver/caddy/releases/download/v2.6.4/caddy_2.6.4_linux_amd64.tar.gz" -o caddy.tar.gz
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tar zxvf caddy.tar.gz
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mv caddy ~/.bin/
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rm caddy.tar.gz README.md LICENSE
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EOF
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# Setup file permissions
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USER root
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RUN mkdir -p /var/lib/vector
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RUN chown 1000 /var/lib/vector
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RUN mkdir -p $HOME/.cache
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RUN chown 1000 $HOME/.cache
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USER 1000
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CMD ["./tabby/scripts/tabby.sh"]
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MODEL_NAME=TabbyML/J-350M
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# Volumes
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DATA_VOLUME="../data:/data"
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HF_VOLUME="../data/hf_cache:/home/app/.cache/huggingface"
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version: '3.3'
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services:
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tabby:
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shm_size: 1gb
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environment:
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MODEL_BACKEND: triton
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MODEL_REPLICA: ${MODEL_REPLICA:-1}
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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version: '3.3'
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services:
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init:
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image: tabbyml/tabby
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container_name: init
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user: root
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volumes:
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- ${DATA_VOLUME}
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- ${HF_VOLUME}
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command: chown -R 1000 /data
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tabby:
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image: tabbyml/tabby
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container_name: tabby
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environment:
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MODEL_NAME: ${MODEL_NAME}
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ports:
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- "5000:5000"
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volumes:
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- ${DATA_VOLUME}
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- ${HF_VOLUME}
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:5000"]
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interval: 2s
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timeout: 2s
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start_period: 1200s
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depends_on:
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- init
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# Run Tabby server on any cloud with one click
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## Background
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[**SkyPilot**](https://github.com/skypilot-org/skypilot) is an open-source framework for seamlessly running machine learning on any cloud. With a simple CLI, users can easily launch many clusters and jobs, while substantially lowering their cloud bills. Currently, [Lambda Labs](https://skypilot.readthedocs.io/en/latest/getting-started/installation.html#lambda-cloud) (low-cost GPU cloud), [AWS](https://skypilot.readthedocs.io/en/latest/getting-started/installation.html#aws), [GCP](https://skypilot.readthedocs.io/en/latest/getting-started/installation.html#gcp), and [Azure](https://skypilot.readthedocs.io/en/latest/getting-started/installation.html#azure) are supported. See [docs](https://skypilot.readthedocs.io/en/latest/) to learn more.
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## Steps
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1. Install SkyPilot and [check that cloud credentials exist](https://skypilot.readthedocs.io/en/latest/getting-started/installation.html#cloud-account-setup):
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```bash
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pip install "skypilot[aws,gcp,azure,lambda]" # pick your clouds
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sky check
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```
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<img src="https://i.imgur.com/7BUci5n.png" width="485" alt="`sky check` output showing enabled clouds for SkyPilot"/>
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2. Get the [deployment folder](./):
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```bash
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git clone https://github.com/TabbyML/tabby
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cd tabby/deployment/skypilot
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```
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3. run:
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```bash
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sky launch -c tabby default.yml
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```
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4. Open another terminal and run:
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```bash
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ssh -L 5000:localhost:5000 tabby
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```
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5. Open http://localhost:5000 in your browser and start coding!
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## Cleaning up
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When you are done, you can stop or tear down the cluster:
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- **To stop the cluster**, run
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```bash
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sky stop tabby # or pass your custom name if you used "-c <other name>"
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```
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You can restart a stopped cluster and relaunch the chatbot (the `run` section in YAML) with
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```bash
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sky launch default.yml -c tabby --no-setup
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```
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Note the `--no-setup` flag: a stopped cluster preserves its disk contents so we can skip redoing the setup.
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- **To tear down the cluster** (non-restartable), run
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```bash
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sky down tabby # or pass your custom name if you used "-c <other name>"
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```
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resources:
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accelerators: A100:1
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disk_size: 1024
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setup: |
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set -ex
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# On some cloud providers, docker-compose is not installed by default.
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sudo curl -L https://github.com/docker/compose/releases/download/v2.17.2/docker-compose-linux-x86_64 -o /usr/local/bin/docker-compose
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sudo chmod a+x /usr/local/bin/docker-compose
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# Pull tabby images.
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git clone https://github.com/TabbyML/tabby.git || true
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cd tabby/deployment
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# On certain cloud providers (e.g lambda cloud), the default user is not added to docker group, so we need sudo here
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sudo docker-compose pull
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# Add current user to docker group, it won't take effect immediately as skypilot job is started by a long-running daemon.
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sudo usermod -aG docker $USER
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run: |
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cd tabby/deployment
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sudo MODEL_REPLICA=${MODEL_REPLICA:-8} docker-compose -f docker-compose.yml -f docker-compose.triton.yml up
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data
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FROM tabbyml/tabby
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ARG PYPI_INDEX_URL=https://pypi.org/simple
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DEFAULT :=
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UP_FLAGS := up --remove-orphans
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build:
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docker-compose -f ../deployment/docker-compose.yml -f docker-compose.dev.yml build
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dev:
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docker-compose -f ../deployment/docker-compose.yml -f docker-compose.dev.yml $(UP_FLAGS)
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dev-triton:
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docker-compose -f ../deployment/docker-compose.yml -f ../deployment/docker-compose.triton.yml -f docker-compose.dev.yml $(UP_FLAGS)
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version: '3.3'
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services:
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tabby:
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image: tabbyml/tabby:dev
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build:
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context: ..
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dockerfile: ./development/Dockerfile
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args:
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PYPI_INDEX_URL: https://mirrors.aliyun.com/pypi/simple
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environment:
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UVICORN_RELOAD: true
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VECTOR_WATCH_CONFIG: true
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STREAMLIT_RUN_ON_SAVE: true
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CADDY_WATCH_CONFIG: true
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STREAMLIT_HIDE_MENU: false
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volumes:
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- ../tabby:/home/app/tabby
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ports:
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- 8083:8083
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- 8084:8084
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Loading…
Reference in New Issue