Rivet
AI Skill Hub 强烈推荐：Rivet 是一款优质的Agent工作流。已获得 5.6k 颗 GitHub Star，AI 综合评分 8.0 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
Rivet 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 8.0 分，是同类 Agent 工作流中的精选推荐。
📋 工具概览
Rivet 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
Rivet 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：cargo install（推荐） cargo install rivet # 方式二：从源码编译 git clone https://github.com/rivet-dev/rivet cd rivet cargo build --release # 二进制在 ./target/release/rivet
- 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
# 查看帮助 rivet --help # 基本运行 rivet [options] <input> # 详细使用说明请查阅文档 # https://github.com/rivet-dev/rivet
# rivet 配置说明 # 查看配置选项 rivet --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 RIVET_CONFIG="/path/to/config.yml"
简介
Fast, high-density, scalable orchestration for agentic workloads.
Rivet Actors are durable processes for agents, workflows, and sandboxes.
12 ms cold starts, 72 KB per Actor, billions on one control plane.
Open source and self-hostable.
Quickstart • Documentation • Changelog • Discord • X
Features
Routing, scheduling, types, and telemetry, built in.
- Fault tolerance by design: A worker going down reschedules its Actors elsewhere with their state intact. No replay harness or checkpointing of your own.
- Multi-region: Place Actors near the users and data they serve, and route requests to wherever each one currently lives.
- HTTP & WebSocket networking: Address an Actor directly over HTTP or hold a live WebSocket to it. No queue or broker in between.
- End-to-end type safety: Actor definitions generate their own client types, so a signature change breaks the build rather than production.
- React SDK: First-party hooks that subscribe a component to an Actor's state and keep it live as the Actor updates.
- OpenTelemetry & observability: Traces, metrics, and structured logs emitted in OTel format, into the collector you already run.
- Single Rust binary: The control plane ships as one static binary with no external dependencies to stand up first.
- Cron & scheduling: Wake an Actor on a schedule or at a timestamp it sets for itself, without a separate scheduler.
- Sleeps when idle: Idle Actors release their resources and wake with durable state intact when the next request arrives.
- Actor-to-Actor calls: Actors address each other by key and call across the cluster as if the other one were local.
- No Kubernetes operator: One control plane behind a load balancer, speaking plain HTTP inside your VPC. No CRDs, no operator, no service mesh to keep alive.
- Open source: Apache 2.0, self-hostable in full. The managed service runs the same control plane you can run yourself.
Getting Started
Deployment Options
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