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What is Runflow?

Runflow is a complete platform for building, deploying, and managing AI agents. It combines a powerful TypeScript SDK with a command-line interface (CLI) and a management portal, making it easy to create production-ready AI applications.

CLI

Start in minutes with the command line

Quick Start

Create your first agent with code

Core Concepts

Learn about Agents, Memory, Tools, and more

Examples

See real-world use cases

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Why Runflow?

Use the CLI to authenticate, clone an agent, and start testing in under 2 minutes. No complex setup required.
Built with TypeScript-first design. Full type safety with Zod validation ensures your agents work correctly.
Built-in observability, memory management, RAG, and connectors. Everything you need for production deployments.
Create complex systems with multiple specialized agents using the supervisor pattern.

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Your Journey with Runflow

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1. Get Started with CLI (2 minutes)

The fastest way to start is with the CLI: 
# Install
npm i -g @runflow-ai/cli

# Login
rf login --api-key YOUR_API_KEY

# List and clone an agent
rf agents list

# Test locally
cd agent-name/
rf test

CLI Guide

Learn how to use the CLI

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2. Build with Code

Once you understand the basics, dive into the SDK: 
import { Agent, openai } from '@runflow-ai/sdk';

// Create a basic agent
const agent = new Agent({
  name: 'Support Agent',
  instructions: 'You are a helpful customer support assistant.',
  model: openai('gpt-4o'),
  memory: { maxTurns: 10 },
});

// Process a message
const result = await agent.process({
  message: 'I need help with my order',
  sessionId: 'session_456',
});

Quickstart Guide

Create your first agent with code

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3. Learn Core Concepts

Understand the powerful features:
  • Agents - Intelligent AI assistants with LLM, tools, and memory
  • Memory - Persistent conversation history across sessions
  • Tools - Custom functions your agents can call
  • Connectors - Integrate with HubSpot, Twilio, Slack, and more
  • Workflows - Orchestrate complex multi-step processes
  • RAG - Semantic search in your knowledge base
  • Observability - Full tracing with cost tracking

Core Concepts

Learn about Agents, Memory, Tools, and more

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4. See Real-World Examples

Explore production-ready examples:
  • Customer Support Agent with RAG
  • Sales Automation Workflows
  • Collections Agent (WhatsApp)
  • Customer Onboarding Assistant
  • Feedback Analysis System
  • Multi-Agent Systems

Real-World Examples

See practical implementations

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Features

Intelligent Agents

Create agents with LLM, tools, memory, and RAG capabilities

Type-Safe Tools

Build custom tools with Zod schema validation

Dynamic Connectors

Connect to any API with runtime schema loading

Workflows

Orchestrate complex multi-step processes

Memory Management

Persistent conversation history with auto-summarization

Agentic RAG

LLM-driven semantic search in knowledge bases

Multi-Agent Systems

Supervisor pattern with automatic routing

Full Observability

Automatic tracing with cost tracking and metrics

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Built-in Libraries

The SDK includes these libraries out-of-the-box. No need to install separately:
LibraryDescription
axiosHTTP client for API requests
zodSchema validation and TypeScript inference
date-fnsModern date utility library
lodashJavaScript utility library
cheerioHTML/XML parsing
pinoFast JSON logger

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Community & Support

GitHub

View source code and contribute

Discord

Join our community

Support

Get help from our team

Homepage

Visit Runflow.ai
Built with ❤️ by the Runflow team