⚙️

Agent工作流

Rivet

基于 Rust · 无代码搭建完整 AI 自动化流程

英文名：rivet

⭐ 5.6k Stars 🍴 189 Forks 💻 Rust 📄 Apache-2.0 🏷 AI 8.0分

8.0AI 综合评分

actorcloudflarerust

⬇ 下载源码 ZIP ⚙️ 配置说明

📚 深度解析

Rivet 是一套完整的 AI Agent 自动化工作流方案。随着 AI 能力的不断提升，基于 Agent 的自动化工作流正在成为提升个人和团队效率的核心方式。区别于传统的 RPA 自动化（模拟鼠标键盘操作），AI Agent 工作流通过理解任务意图、动态规划执行路径，能够处理更复杂的非结构化任务。

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。

GitHub Stars

⭐ 5.6k

开发语言

Rust

支持平台

Windows / macOS / Linux

维护状态

持续维护，定期更新

开源协议

Apache-2.0

AI 综合评分

8.0 分

工具类型

Agent工作流

Forks

189

📖 中文文档

以下内容由 AI Skill Hub 根据项目信息自动整理，如需查看完整原始文档请访问底部「原始来源」。

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。

📌 核心特色

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

🎯 主要使用场景

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

以下安装命令基于项目开发语言和类型自动生成，实际以官方 README 为准。

安装命令

# 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

📋 安装步骤说明

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

以下用法示例由 AI Skill Hub 整理，涵盖最常见的使用场景。

常用命令 / 代码示例

# 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

以下配置示例基于典型使用场景生成，具体参数请参照官方文档调整。

配置示例

# 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"

📑 README 深度解析真实文档完整度 57/100 查看 GitHub 原文 →

以下内容由系统直接从 GitHub README 解析整理，保留代码块、表格与列表结构。

简介

Rivet Actors are the primitive for stateful workloads.

Built for AI agents, collaborative apps, and durable execution.

Quickstart • Documentation • Changelog • Discord • X

Features

One Actor per agent, per session, per user — state, storage, and networking included.

Rivet provides: - In-memory state — Co-located with compute for instant reads and writes. Persist with SQLite or BYO database. - Runs indefinitely, sleeps when idle — Long-lived when active, hibernates when idle. - Scales infinitely, scales to zero — Supports bursty workloads and is cost-efficient. - Global edge network — Deploy close to your users or in specific legal jurisdictions without complexity.

Actors support: - WebSockets — Real-time bidirectional streaming built in. - Workflows — Multi-step operations with automatic retries. - Queues — Durable message queues for reliable async processing. - Scheduling — Timers and cron jobs within your actor.

Deployment Options

RivetKit is a library. Connect it to Rivet Cloud or self-host when you need scaling, fault tolerance, and observability.

Getting Started

Use Cases

One primitive that adapts to agents, workflows, collaboration, and more.

AI Agent — Each agent runs as its own actor with persistent context, memory, and the ability to schedule tool calls.
Sandbox Orchestration — Coordinate sandbox sessions, queue work, and schedule cleanup in one long-lived actor per workspace.
Workflows — Multi-step operations with automatic retries, scheduling, and durable state across steps.
Collaborative Documents — Real-time collaborative editing where each document is an actor broadcasting changes to all connected users.
Per-Tenant Database — One actor per tenant with low-latency in-memory reads and durable tenant data persistence.
Chat — One actor per room or conversation with in-memory state, persistent history, and realtime delivery.

Integrations

Serverless, containers, or your own servers — Rivet Actors work with your existing infrastructure, frameworks, and tools.

Infrastructure: Vercel • Railway • AWS • Docker

Frameworks: React • Next.js • Hono • Express • Elysia • tRPC

Runtimes: Node.js • Bun • Deno

Tools: Vitest • Pino • AI SDK • OpenAPI • AsyncAPI

Request an integration →

How Actors Compare

Rivet Actors vs. Traditional Infrastructure

Metric	Rivet Actor	Kubernetes Pod	Virtual Machine
Cold start	~20ms	~6s	~30s
Memory per instance	~0.6KB	~50MB	~512MB
Idle cost	$0	~$85/mo (cluster)	~$5/mo
Horizontal scale	Infinite	~5k nodes	Manual
Multi-region	Global edge	1 region	1 region

State

Metric	Rivet Actor	Redis	Postgres
Read latency	0ms	~1ms	~5ms

<details> <summary>Benchmark details & methodology</summary>

Cold Start - Rivet Actor (~20ms): Includes durable state init, not just a process spawn. No actor key, so no cross-region locking. Measured with Node.js and FoundationDB. - Kubernetes Pod (~6s): Node.js 24 Alpine image (56MB compressed) on AWS EKS with a pre-provisioned m5.large node. Breakdown: ~1s image pull and extraction, ~3-4s scheduling and container runtime setup, ~1s container start. - Virtual Machine (~30s): AWS EC2 t3.nano from launch to SSH-ready, using an Amazon Linux 2 AMI. t3.nano is the smallest available EC2 instance (512MB RAM).

Memory Per Instance - Rivet Actor (~0.6KB): RSS delta divided by actor count, measured by spawning 10,000 actors in Node.js v24 on Linux x86. - Kubernetes Pod (~50MB): Minimum idle Node.js container on Linux x86: Node.js v24 runtime (~43MB RSS), containerd-shim (~3MB), pause container (~1MB), and kubelet per-pod tracking (~2MB). - Virtual Machine (~512MB): AWS EC2 t3.nano, the smallest available EC2 instance with 512MB allocated memory.

Read Latency - Rivet Actor (0ms): State is read from co-located SQLite/KV storage on the same machine as the actor, with no network round-trip. - Redis (~1ms): AWS ElastiCache Redis (cache.t3.micro) in the same availability zone as the application. - Postgres (~5ms): AWS RDS PostgreSQL (db.t3.micro) in the same availability zone as the application.

Idle Cost - Rivet Actor ($0): Assumes Rivet Actors running on a serverless platform. Actors scale to zero with no idle infrastructure costs. Traditional container deployments may incur idle costs. - Virtual Machine (~$5/mo): AWS EC2 t3.nano ($0.0052/hr compute + $1.60/mo for 20GB gp3 storage) running 24/7. t3.nano is the smallest available EC2 instance (512MB RAM). - Kubernetes Cluster (~$85/mo): AWS EKS control plane ($73/mo) plus a single t3.nano worker node with 20GB gp3 storage, running 24/7.

Horizontal Scale - Rivet Actors (Infinite): Scale linearly by adding nodes with no single cluster size limit. - Kubernetes (~5k nodes): Officially supports clusters of up to 5,000 nodes per the Kubernetes scalability documentation.

Multi-Region - Rivet (Global edge network): Automatically spawns actors near your users and handles routing across regions.

</details>

🎯 aiskill88 AI 点评 A 级 2026-06-05

高质量的AI工作流项目