feat(deploy): add Docker Compose self-hosted deployment option
Add multi-platform Docker image build (amd64 + arm64) with GitHub Actions CI that pushes to GHCR on every merge to main. Users can self-host with a single `docker compose up -d` command. - Dockerfile: multi-stage build with Next.js standalone output (~150-200MB) - docker-compose.yml: one-command self-hosted deployment - .github/workflows/docker.yml: CI workflow with QEMU cross-compilation - next.config.ts: conditional `output: "standalone"` via BUILD_STANDALONE env - README (zh/en/ja): restructure deploy section to include Docker option Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
yuanzonghao
@@ -0,0 +1,26 @@
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node_modules
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.pnpm-store
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.next
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.open-next
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.wrangler
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.vercel
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.turbo
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.claude
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.git
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dist
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build
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out
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.env
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.env.local
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.env.*.local
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.dev.vars
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.DS_Store
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*.log
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npm-debug.log*
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pnpm-debug.log*
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repomix-output.xml
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users.md
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@@ -0,0 +1,53 @@
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name: Build and push Docker image
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on:
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push:
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branches: [main]
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env:
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REGISTRY: ghcr.io
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IMAGE_NAME: ${{ github.repository }}
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jobs:
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build-and-push:
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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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steps:
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- name: Checkout
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uses: actions/checkout@v4
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- name: Set up QEMU
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uses: docker/setup-qemu-action@v3
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- name: Set up Docker Buildx
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uses: docker/setup-buildx-action@v3
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- name: Log in to GHCR
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uses: docker/login-action@v3
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with:
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registry: ${{ env.REGISTRY }}
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username: ${{ github.actor }}
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password: ${{ secrets.GITHUB_TOKEN }}
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- name: Extract metadata
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id: meta
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uses: docker/metadata-action@v5
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with:
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images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
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tags: |
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type=raw,value=latest
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type=sha,prefix=sha-
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- name: Build and push
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uses: docker/build-push-action@v6
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with:
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context: .
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platforms: linux/amd64,linux/arm64
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push: true
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tags: ${{ steps.meta.outputs.tags }}
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labels: ${{ steps.meta.outputs.labels }}
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cache-from: type=gha
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cache-to: type=gha,mode=max
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+36
@@ -0,0 +1,36 @@
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FROM node:22-alpine AS base
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RUN corepack enable && corepack prepare pnpm@9.12.0 --activate
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# --- deps: install production + dev dependencies (cached layer) ---
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FROM base AS deps
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WORKDIR /app
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COPY package.json pnpm-lock.yaml ./
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RUN pnpm install --frozen-lockfile
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# --- builder: build Next.js standalone output ---
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FROM base AS builder
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WORKDIR /app
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COPY --from=deps /app/node_modules ./node_modules
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COPY . .
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ENV NEXT_TELEMETRY_DISABLED=1
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ENV BUILD_STANDALONE=true
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RUN pnpm build
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# --- runner: minimal production image ---
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FROM node:22-alpine AS runner
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WORKDIR /app
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ENV NODE_ENV=production
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ENV NEXT_TELEMETRY_DISABLED=1
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ENV HOSTNAME=0.0.0.0
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ENV PORT=3000
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RUN addgroup --system --gid 1001 nodejs && \
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adduser --system --uid 1001 nextjs
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COPY --from=builder --chown=nextjs:nodejs /app/public ./public
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COPY --from=builder --chown=nextjs:nodejs /app/.next/standalone ./
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COPY --from=builder --chown=nextjs:nodejs /app/.next/static ./.next/static
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USER nextjs
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EXPOSE 3000
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CMD ["node", "server.js"]
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+24
-2
@@ -37,14 +37,36 @@ Free to play, no setup required: [infiplot.com](https://infiplot.com)
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---
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## One-click deploy
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## Deploy
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InfiPlot deploys to both Vercel and Cloudflare Workers. Cloudflare deployment requires the Workers Paid Plan because the scene pipeline needs longer CPU time; for personal use, the one-click Vercel deploy is recommended.
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InfiPlot offers multiple deployment options. For personal use, we recommend the one-click Vercel deploy; to self-host on your own server or local machine, use Docker.
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### Vercel / Cloudflare (one-click)
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Cloudflare deployment requires the Workers Paid Plan because the scene pipeline needs longer CPU time.
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[](https://vercel.com/new/clone?repository-url=https://github.com/zonghaoyuan/infiplot&env=TEXT_BASE_URL,TEXT_API_KEY,TEXT_MODEL,IMAGE_BASE_URL,IMAGE_API_KEY,IMAGE_MODEL,VISION_BASE_URL,VISION_API_KEY,VISION_MODEL,TTS_BASE_URL,TTS_API_KEY,TTS_SPEECH_MODEL,MOCK_IMAGE&envDescription=Three%20required%20providers%20%2B%20optional%20TTS.%20Any%20OpenAI-compatible%20endpoint%20works%20for%20text%2Fvision.%20TTS%20uses%20MiMo%27s%20own%20protocol.&envLink=https://github.com/zonghaoyuan/infiplot/blob/main/README.en.md%23configuration-guide) [](https://deploy.workers.cloudflare.com/?url=https://github.com/zonghaoyuan/infiplot)
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After deploy, fill in the environment variables — see the [Configuration guide](#configuration-guide) below. The repo root is the app itself: Vercel needs no special root directory; on Cloudflare, just set the build command to `pnpm build:cf`.
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### Docker (self-hosted)
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For VPS, home servers, or local machines. Supports x86 and ARM (including Apple Silicon Macs).
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1. Copy `.env.example` to `.env.local` and fill in your API keys (see [Configuration guide](#configuration-guide))
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2. Start:
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```bash
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docker compose up -d
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```
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Visit `http://localhost:3000` to start playing.
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> You can also run the image directly without Compose:
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> ```bash
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> docker run -d -p 3000:3000 --env-file .env.local ghcr.io/zonghaoyuan/infiplot:latest
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> ```
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---
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## 📸 Screenshots
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+24
-2
@@ -37,14 +37,36 @@ InfiPlot は、AI がコンテンツをリアルタイムに生成するイン
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---
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## ワンクリックデプロイ
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## デプロイ
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InfiPlot は Vercel と Cloudflare Workers の両方にデプロイできます。Cloudflare へのデプロイはシーンパイプラインがより長い CPU 時間を必要とするため、Workers Paid Plan が必要です。個人利用には Vercel のワンクリックデプロイをおすすめします。
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InfiPlot は複数のデプロイ方法に対応しています。個人利用には Vercel のワンクリックデプロイをおすすめします。自分のサーバーやローカルマシンで動かしたい場合は Docker を使ってください。
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### Vercel / Cloudflare（ワンクリック）
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Cloudflare へのデプロイはシーンパイプラインがより長い CPU 時間を必要とするため、Workers Paid Plan が必要です。
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[](https://vercel.com/new/clone?repository-url=https://github.com/zonghaoyuan/infiplot&env=TEXT_BASE_URL,TEXT_API_KEY,TEXT_MODEL,IMAGE_BASE_URL,IMAGE_API_KEY,IMAGE_MODEL,VISION_BASE_URL,VISION_API_KEY,VISION_MODEL,TTS_BASE_URL,TTS_API_KEY,TTS_SPEECH_MODEL,MOCK_IMAGE&envDescription=Three%20required%20providers%20%2B%20optional%20TTS.%20Any%20OpenAI-compatible%20endpoint%20works%20for%20text%2Fvision.%20TTS%20uses%20MiMo%27s%20own%20protocol.&envLink=https://github.com/zonghaoyuan/infiplot/blob/main/README.ja.md%23%E8%A8%AD%E5%AE%9A%E3%82%AC%E3%82%A4%E3%83%89) [](https://deploy.workers.cloudflare.com/?url=https://github.com/zonghaoyuan/infiplot)
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デプロイ後、環境変数を設定してください —— 下記の[設定ガイド](#設定ガイド)を参照。リポジトリのルートがアプリ本体です：Vercel では特別なルート設定は不要です。Cloudflare ではビルドコマンドを `pnpm build:cf` に設定するだけで済みます。
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### Docker デプロイ（セルフホスト）
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VPS、ホームサーバー、ローカルマシンに対応。x86 と ARM（Apple Silicon Mac を含む）をサポート。
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1. `.env.example` を `.env.local` にコピーし、API キーを設定（[設定ガイド](#設定ガイド)を参照）
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2. 起動：
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```bash
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docker compose up -d
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```
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`http://localhost:3000` にアクセスしてゲームを開始できます。
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> Compose を使わず、直接イメージを実行することもできます：
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> ```bash
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> docker run -d -p 3000:3000 --env-file .env.local ghcr.io/zonghaoyuan/infiplot:latest
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> ```
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---
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## 📸 スクリーンショット
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@@ -37,14 +37,36 @@ InfiPlot是一款AI实时生成内容的互动剧情游戏，这里没有预设
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---
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## 一键部署
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## 部署
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InfiPlot 同时支持部署到 Vercel 与 Cloudflare Workers。Cloudflare 部署因场景流水线需要更长 CPU 时间，需要 Workers Paid Plan；个人使用推荐用 Vercel 一键部署。
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InfiPlot 支持多种部署方式。个人使用推荐 Vercel 一键部署；想部署到自己的服务器或本地运行，可以用 Docker。
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### Vercel / Cloudflare（一键部署）
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Cloudflare 部署因场景流水线需要更长 CPU 时间，需要 Workers Paid Plan。
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[](https://vercel.com/new/clone?repository-url=https://github.com/zonghaoyuan/infiplot&env=TEXT_BASE_URL,TEXT_API_KEY,TEXT_MODEL,IMAGE_BASE_URL,IMAGE_API_KEY,IMAGE_MODEL,VISION_BASE_URL,VISION_API_KEY,VISION_MODEL,TTS_BASE_URL,TTS_API_KEY,TTS_SPEECH_MODEL,MOCK_IMAGE&envDescription=Three%20required%20providers%20%2B%20optional%20TTS.%20Any%20OpenAI-compatible%20endpoint%20works%20for%20text%2Fvision.%20TTS%20uses%20MiMo%27s%20own%20protocol.&envLink=https://github.com/zonghaoyuan/infiplot%23%E9%85%8D%E7%BD%AE%E6%95%99%E7%A8%8B) [](https://deploy.workers.cloudflare.com/?url=https://github.com/zonghaoyuan/infiplot)
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部署完成后，填好环境变量 —— 详见下方的[配置教程](#配置教程)。仓库根目录就是应用本身：Vercel 无需额外设置 root directory；在 Cloudflare 上把构建命令设为 `pnpm build:cf` 即可。
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### Docker 部署（自托管）
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适用于 VPS、家庭服务器或本地电脑。支持 x86 和 ARM（含 Apple Silicon Mac）。
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1. 复制 `.env.example` 为 `.env.local`，填入你的 API Key（详见[配置教程](#配置教程)）
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2. 启动：
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```bash
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docker compose up -d
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```
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访问 `http://localhost:3000` 即可开始游戏。
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> 也可以不用 Compose，直接运行镜像：
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> ```bash
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> docker run -d -p 3000:3000 --env-file .env.local ghcr.io/zonghaoyuan/infiplot:latest
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> ```
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---
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## 📸 游戏截图
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@@ -0,0 +1,8 @@
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services:
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infiplot:
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image: ghcr.io/zonghaoyuan/infiplot:latest
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ports:
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- "3000:3000"
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env_file:
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- .env.local
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restart: unless-stopped
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@@ -1,6 +1,7 @@
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import type { NextConfig } from "next";
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const config: NextConfig = {
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output: process.env.BUILD_STANDALONE === "true" ? "standalone" : undefined,
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reactStrictMode: true,
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typedRoutes: false,
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turbopack: {
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