GitHub - gensx-inc/gensx: The TypeScript framework for agents & workflows with react-like components. Lightning fast dev loop. Easy to learn. Easy to extend.

GenSX is a simple TypeScript framework for building complex LLM applications. It's a workflow engine designed for building agents, chatbots, and long-running workflows.

Why GenSX?

• 🎯 Pure Functions: Components are pure TypeScript functions that are easily testable, reusable, and sharable
• 🌴 Natural Composition: Building workflows is as simple as composing functions together
• 🔒 Type-safe: Full TypeScript support with no DSLs or special syntax - just standard language features
• 🚀 Built for Scale: Start simple and evolve to complex patterns like agents and reflection without changing your programming model
• 📊 Automatic Tracing: Real-time tracing of all component inputs/outputs, tool calls, and LLM calls making debugging and observability easy
• ☁️ One-Click Deployment: Deploy workflows as REST APIs with a single command, optimized for long-running LLM workloads up to 60 minutes
• 💾 Built-in Storage: Zero-config blob storage, SQL databases, and vector search for building stateful agents and workflows

Check out the documentation to learn more about building LLM applications with GenSX.

Building a workflow

Most LLM frameworks are graph oriented--you express your workflow with nodes, edges, and a global state object. GenSX takes a different approach--you compose your workflow with components, and GenSX handles the execution for you.

Components in GenSX look a lot like functions. You create them by passing in a function and a name to gensx.Component(), a higher order function::

import * as gensx from "@gensx/core";
import { openai } from "@ai-sdk/openai";
import { generateText } from "@gensx/vercel-ai";

// input interface
interface WriteDraftInput {
  research: string[];
  prompt: string;
}

// components are pure functions that are reusable by default
const WriteDraft = gensx.Component(
  "WriteDraft",
  async ({ prompt, research }: WriteDraftInput) => {
    const systemMessage = `You're an expert technical writer.
    Use the information when responding to users: ${research}`;

    const result = await generateText({
      messages: [
        {
          role: "system",
          content: systemMessage,
        },
        {
          role: "user",
          content: `Write a blog post about ${prompt}`,
        },
      ],
      model: openai("gpt-4.1-mini"),
    });

    return result.text;
  },
);

Components can be composed together to create more complex agents and workflows:

import * as gensx from "@gensx/core";
import { OpenAIProvider } from "gensx/openai";
import { Research, WriteDraft, EditDraft } from "./writeBlog";

interface WriteBlogInput {
  title: string;
  description: string;
}

const WriteBlog = gensx.Workflow(
  "WriteBlog",
  async ({ title, description }: WriteBlogInput) => {
    const queries = await GenerateQueries({
      title,
      description,
    });
    const research = await ResearchBlog({ queries });
    const draft = await WriteDraft({ title, context: research });
    const final = await EditDraft({ title, content: draft });
    return final;
  },
);

const result = await WriteBlog({
  title: "How AI broke modern infra",
  description: "Long-running workflows require a new approach to infra",
});

Getting Started

Check out the Quickstart Guide to build your first workflow in just a few minutes.

Examples

This repo contains a number of examples to help you get up and running with GenSX.

To run an example:

cd examples/<example-name>

pnpm install

pnpm start

Basic Examples

Full Examples

Working with this repo

This monorepo contains GenSX, its related packages, examples, and documentation. You can find more detailed instructions in CONTRIBUTING.md.

Repository Structure

• packages/ - Published packages
• examples/ - Example applications and use cases
• website/ - GenSX website

License

Apache 2.0