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Merge pull request #2 from BinHPdev/feature/weekly-update-cicd
Add weekly auto-update (self-hosted runner)
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‎.github/prompts/weekly-update.md‎

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# Weekly Content Update Task
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You are updating an "awesome list" of AI-driven automated model training tools.
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## Your Goal
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Search for NEW tools, frameworks, and projects related to algorithm automation and model training that have been released or significantly updated in the past 1-2 weeks. Update both `README.md` (English) and `算法自动化训练.md` (Chinese) with any new findings.
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## Search Scope
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Search across these categories (use WebSearch for each):
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1. **Autonomous ML experiment / research frameworks** - new AI agent systems that run experiments autonomously
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2. **RL alignment training** (RLHF/GRPO/DPO) - new frameworks, algorithms, or significant updates
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3. **LLM fine-tuning frameworks** - new tools or major releases (Unsloth, Axolotl, LlamaFactory, etc.)
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4. **Synthetic data generation** - new tools for generating training data at scale
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5. **Inference engines** - new or updated engines relevant to RL training loops
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6. **Coding agents** - new open-source agents for writing training scripts
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7. **Model merging & quantization** - new compression techniques or tools
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8. **Multimodal training** - new vision-language or audio-language training frameworks
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9. **Evaluation & benchmarks** - new LLM/agent benchmarks
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10. **Experiment tracking & MLOps** - new tools or significant updates
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## Quality Criteria
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Only add tools that meet ALL of these:
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- **Directly usable** for automated model training workflows
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- **Open source** with active maintenance (prefer projects with 100+ GitHub stars or from reputable labs)
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- **Genuinely new** - not already listed in the existing files
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- **Significant** - not minor forks or trivial wrappers
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## Update Process
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1. Read both `README.md` and `算法自动化训练.md` to understand the current content
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2. Search for new developments using WebSearch (at least 6 targeted searches)
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3. For each new tool found, verify it meets quality criteria
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4. Add entries to BOTH files in the appropriate sections:
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- README.md: add table rows matching the existing format `| [Name](url) | Description | Key Highlight |`
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- 算法自动化训练.md: add detailed entries matching the existing format with GitHub link, description, key features, and use cases
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5. If you find new trends, update the Trends section in both files
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6. Update the date in both files to today's date
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7. If no significant new tools are found, create a file `.github/last-update-log.md` noting "No new tools found on [date]" and do NOT modify the main files
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## Important Rules
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- Do NOT remove or modify existing entries
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- Do NOT change the structure or formatting conventions
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- Maintain consistent numbering in the Chinese doc
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- Keep table column counts consistent in README.md
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- Write Chinese descriptions for 算法自动化训练.md, English for README.md

‎.github/workflows/weekly-update.yml‎

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name: Weekly Content Update
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on:
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schedule:
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# 每周五中午 12:00 北京时间 (UTC+8) = 04:00 UTC
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- cron: '0 4 * * 5'
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workflow_dispatch:
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# 支持手动触发
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jobs:
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update:
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# 在本地 Mac 执行（复用 ClaudeNotice 的 self-hosted runner）
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runs-on: self-hosted
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permissions:
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contents: write
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timeout-minutes: 30
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steps:
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- name: 检出代码
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uses: actions/checkout@v4
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with:
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token: ${{ secrets.GITHUB_TOKEN }}
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- name: 拉取最新代码
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run: git pull origin main --rebase
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- name: 检查 Claude CLI
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run: |
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command -v claude || { echo "❌ claude CLI not found"; exit 1; }
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echo "✅ Claude CLI ready"
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- name: 运行 Claude Code 搜索更新
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timeout-minutes: 20
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run: |
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# 防止 Mac 休眠
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caffeinate -s -w $$ &
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PROMPT="Today is $(date +%Y-%m-%d). $(cat .github/prompts/weekly-update.md)"
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echo "🔍 开始搜索最新算法自动化工具..."
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claude -p "$PROMPT" \
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--max-turns 30 \
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--allowedTools "WebSearch,Read,Edit,Write,Glob,Grep,Bash(git diff*),Bash(git status*),Bash(wc *),Bash(date*)" \
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2>&1 | tee /tmp/awesome-algo-update.log
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echo "✅ Claude 搜索完成"
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- name: 提交并推送
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run: |
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git config user.name "AlgoTools Bot"
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git config user.email "bot@awesome-algo-tools.local"
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# 暂存主文件
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git add README.md "算法自动化训练.md"
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# 检查是否有实际变更
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if git diff --cached --quiet; then
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echo "📭 本周无新工具，跳过提交"
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exit 0
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fi
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echo "📝 检测到变更："
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git diff --cached --stat
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git commit -m "chore: weekly update $(date +%Y-%m-%d)
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Automated scan for new algorithm automation tools.
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Co-Authored-By: Claude <noreply@anthropic.com>"
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git push origin main
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echo "✅ 已推送到 main"

‎.gitignore‎

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# Update script logs
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scripts/*.log
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scripts/last-run-*.log
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.github/last-update-log.md

‎CLAUDE.md‎

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# Project: Awesome Algorithm Auto Tools
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A curated "awesome list" of AI-driven automated model training tools and frameworks.
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## Files
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- `README.md` — English version, uses markdown tables (`| Project | Description | Key Highlight |`)
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- `算法自动化训练.md` — Chinese version, detailed report format with numbered sections (e.g., `### 4.10 ToolName ⭐⭐⭐⭐ 🆕`)
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## Conventions
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- Both files must stay in sync: any new tool added to one must be added to the other
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- README.md tables always have 3 columns
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- Chinese doc uses sequential numbering within each section (no gaps/duplicates)
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- New entries get a 🆕 tag in the Chinese doc
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- Star ratings in Chinese doc: ⭐⭐⭐ (useful) to ⭐⭐⭐⭐⭐ (essential)
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- Update the date at the top of both files when making changes
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- Chinese doc footer date must match header date
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## Categories
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1. Autonomous Experiment / Research Frameworks
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2. Agent-Driven Training Skills (HuggingFace Ecosystem)
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3. LLM Fine-Tuning Frameworks
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4. RL Alignment Training (RLHF / GRPO)
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5. Automated Hyperparameter Optimization / AutoML
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6. Self-Evolving / Self-Play Training
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7. Synthetic Data Generation & Curation
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8. Knowledge Distillation
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9. Model Merging & Quantization
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10. Lightweight Pretraining & Distributed Training
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11. Inference Engines (for RL Training Loops)
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12. Multimodal Training Frameworks
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13. Experiment Tracking & Orchestration
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14. Benchmarks & Evaluation
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15. Coding Agents
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## Quality Criteria for Inclusion
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- Must be directly usable for automated model training workflows
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- Prefer open-source projects with active maintenance
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- Focus on tools that leverage AI/LLMs to automate the training process

‎scripts/setup_runner.sh‎

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#!/bin/bash
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# ============================================================
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# awesome-algorithm-auto-tools — 自托管 Runner 安装
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#
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# 如果你已经在 ClaudeNotice 项目配置过 self-hosted runner，
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# 有两种方式复用：
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#
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# 方式 A（推荐）：组织级 Runner
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# 将已有 runner 改为组织级，所有仓库共享
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# GitHub → Settings → Actions → Runners → 移到 Organization
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#
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# 方式 B：为本仓库单独注册一个 Runner
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# 运行本脚本：./scripts/setup_runner.sh
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#
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# 使用前：
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# 1. 打开 https://github.com/BinHPdev/awesome-algorithm-auto-tools
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# 2. Settings → Actions → Runners → New self-hosted runner
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# 3. 复制 token，粘贴到下面
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# ============================================================
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set -e
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GITHUB_REPO="https://github.com/BinHPdev/awesome-algorithm-auto-tools"
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RUNNER_TOKEN="${1:-$RUNNER_TOKEN}"
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RUNNER_NAME="algo-tools-runner"
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if [ -z "$RUNNER_TOKEN" ] || [ "$RUNNER_TOKEN" = "YOUR_RUNNER_TOKEN_FROM_GITHUB" ]; then
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echo "❌ 请提供 Runner Token："
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echo " 用法: ./scripts/setup_runner.sh <YOUR_TOKEN>"
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echo " 或: RUNNER_TOKEN=xxx ./scripts/setup_runner.sh"
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exit 1
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fi
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RUNNER_DIR="$HOME/actions-runner-algo"
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echo "======================================"
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echo " Awesome Algorithm Auto Tools Runner"
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echo "======================================"
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command -v claude >/dev/null || { echo "❌ 需要安装 Claude Code"; exit 1; }
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command -v git >/dev/null || { echo "❌ 需要安装 git"; exit 1; }
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mkdir -p "$RUNNER_DIR"
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cd "$RUNNER_DIR"
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RUNNER_VERSION=$(curl -s https://api.github.com/repos/actions/runner/releases/latest | grep '"tag_name"' | sed 's/.*"v\([^"]*\)".*/\1/')
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ARCH=$(uname -m)
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if [ "$ARCH" = "x86_64" ]; then
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PKG="actions-runner-osx-x64-${RUNNER_VERSION}.tar.gz"
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else
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PKG="actions-runner-osx-arm64-${RUNNER_VERSION}.tar.gz"
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fi
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if [ ! -f "run.sh" ]; then
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echo "📦 下载 Runner v${RUNNER_VERSION}..."
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curl -sOL "https://github.com/actions/runner/releases/download/v${RUNNER_VERSION}/${PKG}"
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tar xzf "$PKG"
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rm "$PKG"
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fi
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echo "⚙️ 配置..."
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./config.sh \
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--url "$GITHUB_REPO" \
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--token "$RUNNER_TOKEN" \
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--name "$RUNNER_NAME" \
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--labels "self-hosted,macos" \
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--work "_work" \
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--unattended \
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--replace
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echo "🚀 安装为系统服务..."
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./svc.sh install
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./svc.sh start
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echo ""
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echo "======================================"
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echo " ✅ Runner 安装完成！"
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echo " 状态: cd $RUNNER_DIR && ./svc.sh status"
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echo " 每周五中午会自动运行更新"
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echo "======================================"

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