开源AI工作流
AI Skill Hub 推荐使用：开源AI工作流 是一款优质的Agent工作流。AI 综合评分 7.5 分，在同类工具中表现稳健。如果你正在寻找可靠的Agent工作流解决方案，这是一个值得深入了解的选择。
📚 深度解析
开源AI工作流 工作流的设计遵循"最小配置，最大复用"原则：核心逻辑已经封装好，用户只需配置自己的 API Key 和业务参数即可快速上手。工作流内置错误处理和重试机制，在网络波动或 API 限速等情况下仍能稳定运行，适合作为生产环境的自动化基础设施。
在实际部署时，建议先在测试环境中运行 3-5 次，验证各个环节的输出结果符合预期，再部署到生产环境。AI Skill Hub 评分 7.5 分，是同类 Agent 工作流中的精选推荐。
📋 工具概览
Workflow orchestration for AI coding agents, from task to merged PR，提供AI编码代理的工作流管理，提高开发效率。
开源AI工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排，将复杂的多步骤任务拆解为清晰的自动化流程，实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成，适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
📖 中文文档
Workflow orchestration for AI coding agents, from task to merged PR，提供AI编码代理的工作流管理，提高开发效率。
开源AI工作流 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排，将复杂的多步骤任务拆解为清晰的自动化流程，实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成，适合构建数据处理管线、业务自动化和 AI 辅助决策系统。
- 可视化 Agent 工作流编排，无需编写复杂代码
- 支持多步骤自动化任务链，实现全流程无人值守
- 与外部 API、数据库和第三方服务无缝集成
- 内置错误处理与自动重试机制，保障稳定运行
- 提供可复用的自动化模板，快速在同类场景部署
- 自动化日常重复性工作，将精力集中于创造性任务
- 构建数据采集 → 处理 → 输出的完整自动化管线
- 实现跨平台、跨系统的数据流转和业务协同
# 方式一：npm 全局安装 npm install -g optio # 方式二：npx 直接运行（无需安装） npx optio --help # 方式三：项目依赖安装 npm install optio # 方式四：从源码运行 git clone https://github.com/jonwiggins/optio cd optio npm install npm start
- 访问 GitHub 仓库获取工作流文件
- 在对应平台（Dify / Flowise / Make 等）中找到「导入工作流」功能
- 上传工作流文件
- 按照提示配置必要的环境变量和 API Key
- 运行测试确认流程正常后投入使用
# 命令行使用
optio --help
# 基本用法
optio [options] <input>
# Node.js 代码中使用
const optio = require('optio');
const result = await optio.run(options);
console.log(result);
# optio 配置说明 # 查看配置选项 optio --config-example > config.yml # 常见配置项 # output_dir: ./output # log_level: info # workers: 4 # 环境变量（覆盖配置文件） export OPTIO_CONFIG="/path/to/config.yml"
Optio
Self-hosted AI engineering platform — your cluster, your agents, your code.
Optio organizes agent work into three tiers, all driven by the same trigger types, prompt-template engine, log streaming, and /api/tasks HTTP surface:
- Tasks (Repo Tasks) — turn tickets into merged pull requests. Submit a task (manually, from a GitHub Issue, Linear, Jira, or Notion), and Optio provisions an isolated environment, runs an AI agent, opens a PR, monitors CI, triggers code review, auto-fixes failures, and merges when everything passes.
- Jobs (Standalone Tasks) — reusable, parameterized agent runs with no repo checkout. Generate reports, triage alerts, audit dependencies, query a database, post to Slack — anything that doesn't need to land as a PR.
- Agents (Persistent Agents) — long-lived, named, message-driven agent processes. Each has a stable slug, an inbox, and a cyclic state machine. Wake on user messages, agent messages, webhooks, cron ticks, or ticket events. Three pod lifecycle modes (
always-on/sticky/on-demand). Address each other via an inter-agent HTTP API. See the four-agent Forge demo and the Mars Mission Control example. - Connections — give your agents access to external services. Connect Notion, Slack, Linear, GitHub, PostgreSQL, Sentry, or any MCP-compatible server, and Optio injects them into agent pods at runtime.
Tasks and Jobs are the job model — one-shot runs whose identity is the run itself. Persistent Agents are the service model — a turn is an input to the long-lived process, not the unit of work. Pick the tier by what shape your work has; see examples/ for runnable starting points and docs/tasks.md for the full breakdown.
The feedback loop is what makes Tasks different. When CI fails, the agent is automatically resumed with the failure context. When a reviewer requests changes, the agent picks up the review comments and pushes a fix. When everything passes, the PR is squash-merged and the issue is closed. You describe the work; Optio drives it to completion.
Under the hood, all task and pod state changes flow through a Kubernetes-style reconciliation control plane — a pure-decision-plus-CAS-executor loop with periodic resync that keeps runs from getting stuck on lost events.
<p align="center"> <img src="docs/screenshots/overview.png" alt="Optio dashboard showing 10 running tasks, 19 completed, with Claude Max usage, active pods, and recent task activity" width="100%"/> </p> <p align="center"><em>Dashboard — real-time overview of running agents, pod status, costs, and recent activity</em></p>
<p align="center"> <img src="docs/screenshots/task-detail.png" alt="Task detail view showing live agent logs, pipeline progress through stages (queued, setup, running, PR, CI checks, review, merge, done), and cost tracking" width="100%"/> </p> <p align="center"><em>Task detail — live-streamed agent output with pipeline progress, PR tracking, and cost breakdown</em></p>
Connections — extend agent capabilities
Connections give your agents access to external tools and data at runtime. Configure a provider once, assign it to repos or agents, and Optio injects MCP servers into agent pods automatically.
Built-in providers: Notion, GitHub, Slack, Linear, PostgreSQL, Sentry, Filesystem, plus custom MCP servers and HTTP APIs.
Key Features
- Autonomous feedback loop — auto-resumes the agent on CI failures, merge conflicts, and review feedback; auto-merges when everything passes
- Three Task tiers — Tasks land code via PRs; Jobs run agents in empty pods for reports, triage, and ops; Agents are long-lived, message-driven services. All three share triggers (manual / schedule / webhook / ticket), prompt templates, the reconciler, and the unified
/api/tasksHTTP layer - Inter-agent messaging — Persistent Agents address each other via
/api/internal/persistent-agents/*for direct messages and broadcasts, enabling multi-agent teams (see the Forge demo) - Connections — plug external services (Notion, Slack, Linear, GitHub, PostgreSQL, Sentry, custom MCP servers) into agent pods with fine-grained access control per repo and agent type
- Pod-per-repo architecture — one long-lived Kubernetes pod per repo with git worktree isolation, multi-pod scaling, and idle cleanup
- Code review agent — automatically launches a review agent as a subtask, with a separate prompt and model
- Multi-agent support — run Claude Code, OpenAI Codex, GitHub Copilot, Google Gemini, or OpenCode with per-repo model and prompt configuration
- GitHub Issues, Linear, Jira, and Notion intake — assign issues to Optio from the UI or via ticket sync
- Reconciliation control plane — K8s-style pure-decision-plus-CAS-executor loop with periodic resync over four
RunKinds (repo,standalone,pr-review,persistent-agent); keeps state from getting stuck on lost events - Real-time dashboard — live log streaming, pipeline progress, cost analytics, and cluster health
Prerequisites
- Kubernetes v1.33+ — required for post-quantum TLS on the control plane. v1.33 is the first release built on Go 1.24, which enables hybrid X25519MLKEM768 key exchange automatically. Earlier versions run but do not negotiate post-quantum TLS between Optio and the Kubernetes API server.
- Docker Desktop with Kubernetes enabled (Settings → Kubernetes → Enable)
- Node.js 22+ and pnpm 10+
- Helm (
brew install helm)
Setup
git clone https://github.com/jonwiggins/optio.git && cd optio
./scripts/setup-local.shThat's it. The setup script installs dependencies, builds all Docker images (API, web, and agent presets), deploys the full stack to your local Kubernetes cluster via Helm, and installs metrics-server.
Web UI ...... http://localhost:30310
API ......... http://localhost:30400Open the web UI and the setup wizard will walk you through configuring GitHub access, agent credentials (API key or Max/Pro subscription), and adding your first repository.
GitHub App Setup
Optio can use a GitHub App instead of a Personal Access Token for GitHub operations. This provides user-scoped access (respecting CODEOWNERS, branch protection, and repository permissions), automatic token refresh, and clear attribution on PRs and commits.
Production Deployment
Optio ships with a Helm chart for production Kubernetes clusters. Three installation methods are available:
Install from Helm repository (recommended)
helm repo add optio https://jonwiggins.github.io/optio
helm repo update
helm install optio optio/optio -n optio --create-namespace \
--set encryption.key=$(openssl rand -hex 32) \
--set postgresql.enabled=false \
--set externalDatabase.url="postgres://..." \
--set redis.enabled=false \
--set externalRedis.url="redis://..." \
--set ingress.enabled=true \
--set ingress.hosts[0].host=optio.example.comInstall from OCI registry
helm install optio oci://ghcr.io/jonwiggins/optio -n optio --create-namespace \
--set encryption.key=$(openssl rand -hex 32) \
--set postgresql.enabled=false \
--set externalDatabase.url="postgres://..." \
--set redis.enabled=false \
--set externalRedis.url="redis://..." \
--set ingress.enabled=true \
--set ingress.hosts[0].host=optio.example.comInstall from source
git clone https://github.com/jonwiggins/optio.git && cd optio
helm install optio helm/optio -n optio --create-namespace \
--set encryption.key=$(openssl rand -hex 32) \
--set postgresql.enabled=false \
--set externalDatabase.url="postgres://..." \
--set redis.enabled=false \
--set externalRedis.url="redis://..." \
--set ingress.enabled=true \
--set ingress.hosts[0].host=optio.example.comSee the Helm chart values for full configuration options including OAuth providers, resource limits, and agent image settings.
Quick Start
Configuration
After creating the app and installing it on your organisation, configure Optio via Helm values:
github:
app:
id: "123456" # App ID (from app settings page)
clientId: "Iv1.abc123" # Client ID (for user OAuth login)
clientSecret: "..." # Client secret
installationId: "789" # Installation ID (from org install URL)
privateKey: | # PEM private key (for server-side tokens)
-----BEGIN RSA PRIVATE KEY-----
...
-----END RSA PRIVATE KEY-----When configured, users who log in via GitHub get a user access token that is used for all their git and API operations. Background workers (PR watcher, ticket sync) use the app's installation token. If the GitHub App is not configured, Optio falls back to the GITHUB_TOKEN PAT.
该项目提供了AI编码代理的工作流管理，提高开发效率，值得关注
- 构建多智能体协作系统的 Agent 开发者
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
- 云端托管：可放在 Vercel / Railway / Fly.io 等 PaaS 平台
⚡ 核心功能
- 可视化 Agent 工作流编排，无需编写复杂代码
- 支持多步骤自动化任务链，实现全流程无人值守
- 与外部 API、数据库和第三方服务无缝集成
- 内置错误处理与自动重试机制，保障稳定运行
- 提供可复用的自动化模板，快速在同类场景部署
- 构建多智能体协作系统的 Agent 开发者
- Agent 任务先做 dry-run 验证工具调用链，再开启自主执行
- API key 直接提交到 git 仓库（请用 .env 并加入 .gitignore）
👥 适合人群
🎯 使用场景
- 自动化日常重复性工作，将精力集中于创造性任务
- 构建数据采集 → 处理 → 输出的完整自动化管线
- 实现跨平台、跨系统的数据流转和业务协同
⚖️ 优点与不足
- +MIT 协议，可免费商用
- +大幅减少重复性人工操作
- +可视化流程，清晰直观
- +可扩展性强，支持复杂场景
- −初始配置和调试需投入一定时间
- −强依赖外部服务的稳定性
- −复杂场景需具备一定技术基础
AI Skill Hub 为第三方内容聚合平台，本页面信息基于公开数据整理，不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后，再部署至生产环境，并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一，可自由商用、修改、分发，仅需保留版权声明。
🔗 相关工具推荐
❓ 常见问题 FAQ
总体来看，开源AI工作流 是一款质量良好的Agent工作流，在同类工具中具备一定竞争力。AI Skill Hub 将持续追踪其更新动态，建议收藏备用，结合自身场景选择合适时机引入使用。
| 原始名称 | optio |
| 原始描述 | 开源AI工作流：Workflow orchestration for AI coding agents, from task to merged PR.。⭐980 · TypeScript |
| Topics | workflowagentaiclaude-codecopilottypescript |
| GitHub | https://github.com/jonwiggins/optio |
| License | MIT |
| 语言 | TypeScript |
收录时间：2026-06-11 · 更新时间：2026-06-11 · License：MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。