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https://github.com/ax-llm/ax

The "official" unofficial DSPy framework. Build LLM powered agents and other workflows, based on the Stanford DSP paper.
https://github.com/ax-llm/ax

ai anthropic claude cohere gemini google google-gemini gpt-4 javascript large-language-models llm nodejs ollama openai opensource rag together-compute typescript vectordb

Last synced: 15 days ago
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The "official" unofficial DSPy framework. Build LLM powered agents and other workflows, based on the Stanford DSP paper.

Awesome Lists containing this project

README 

          
# Ax: Build Reliable AI Apps in TypeScript



Stop wrestling with prompts. Start shipping AI features.



Ax brings DSPy's approach to TypeScript – describe what you want, and let the framework handle the rest. Production-ready, type-safe, works with all major LLMs.



[![NPM Package](https://img.shields.io/npm/v/@ax-llm/ax?style=for-the-badge&color=green)](https://www.npmjs.com/package/@ax-llm/ax)

[![Twitter](https://img.shields.io/twitter/follow/dosco?style=for-the-badge&color=red)](https://twitter.com/dosco)

[![Discord Chat](https://img.shields.io/discord/1078454354849304667?style=for-the-badge&color=green)](https://discord.gg/DSHg3dU7dW)



## The Problem



Building with LLMs is painful. You write prompts, test them, they break. You switch providers, everything needs rewriting. You add validation, error handling, retries – suddenly you're maintaining infrastructure instead of shipping features.



## The Solution



Define what goes in and what comes out. Ax handles the rest.



```typescript

import { ai, ax } from "@ax-llm/ax";



const llm = ai({ name: "openai", apiKey: process.env.OPENAI_APIKEY });



const classifier = ax(

  'review:string -> sentiment:class "positive, negative, neutral"',

);



const result = await classifier.forward(llm, {

  review: "This product is amazing!",

});



console.log(result.sentiment); // "positive"

```



No prompt engineering. No trial and error. Works with GPT-4, Claude, Gemini, or any LLM.



## Why Ax



**Write once, run anywhere.** Switch between OpenAI, Anthropic, Google, or 15+ providers with one line. No rewrites.



**Ship faster.** Stop tweaking prompts. Define inputs and outputs. The framework generates optimal prompts automatically.



**Production-ready.** Built-in streaming, validation, error handling, observability. Used in production handling millions of requests.



**Gets smarter.** Train your programs with examples. Watch accuracy improve automatically. No ML expertise needed.



## Examples



### Extract structured data



```typescript

const extractor = ax(`

  customerEmail:string, currentDate:datetime -> 

  priority:class "high, normal, low",

  sentiment:class "positive, negative, neutral",

  ticketNumber?:number,

  nextSteps:string[],

  estimatedResponseTime:string

`);



const result = await extractor.forward(llm, {

  customerEmail: "Order #12345 hasn't arrived. Need this resolved immediately!",

  currentDate: new Date(),

});

```



### Complex nested objects



```typescript

import { f, ax } from "@ax-llm/ax";



const productExtractor = f()

  .input("productPage", f.string())

  .output("product", f.object({

    name: f.string(),

    price: f.number(),

    specs: f.object({

      dimensions: f.object({

        width: f.number(),

        height: f.number()

      }),

      materials: f.array(f.string())

    }),

    reviews: f.array(f.object({

      rating: f.number(),

      comment: f.string()

    }))

  }))

  .build();



const generator = ax(productExtractor);

const result = await generator.forward(llm, { productPage: "..." });



// Full TypeScript inference

console.log(result.product.specs.dimensions.width);

console.log(result.product.reviews[0].comment);

```



### Validation and constraints



```typescript

const userRegistration = f()

  .input("userData", f.string())

  .output("user", f.object({

    username: f.string().min(3).max(20),

    email: f.string().email(),

    age: f.number().min(18).max(120),

    password: f.string().min(8).regex("^(?=.*[A-Za-z])(?=.*\\d)", "Must contain letter and digit"),

    bio: f.string().max(500).optional(),

    website: f.string().url().optional(),

  }))

  .build();

```



Available constraints: `.min(n)`, `.max(n)`, `.email()`, `.url()`, `.date()`, `.datetime()`, `.regex(pattern, description)`, `.optional()`



Validation runs on both input and output. Automatic retry with corrections on validation errors.



### Agents with tools (ReAct pattern)



```typescript

const assistant = ax(

  "question:string -> answer:string",

  {

    functions: [

      { name: "getCurrentWeather", func: weatherAPI },

      { name: "searchNews", func: newsAPI },

    ],

  },

);



const result = await assistant.forward(llm, {

  question: "What's the weather in Tokyo and any news about it?",

});

```



### Multi-modal (images, audio)



```typescript

const analyzer = ax(`

  image:image, question:string ->

  description:string,

  mainColors:string[],

  category:class "electronics, clothing, food, other",

  estimatedPrice:string

`);

```



## Install



```bash

npm install @ax-llm/ax

```



Additional packages:



```bash

# AWS Bedrock provider

npm install @ax-llm/ax-ai-aws-bedrock



# Vercel AI SDK v5 integration

npm install @ax-llm/ax-ai-sdk-provider



# Tools: MCP stdio transport, JS interpreter

npm install @ax-llm/ax-tools

```



## Features



- **15+ LLM Providers** – OpenAI, Anthropic, Google, Mistral, Ollama, and more

- **Type-safe** – Full TypeScript support with auto-completion

- **Streaming** – Real-time responses with validation

- **Multi-modal** – Images, audio, text in the same signature

- **Optimization** – Automatic prompt tuning with MiPRO, ACE, GEPA

- **Observability** – OpenTelemetry tracing built-in

- **Workflows** – Compose complex pipelines with AxFlow

- **RAG** – Multi-hop retrieval with quality loops

- **Agents** – Tools and multi-agent collaboration

- **Zero dependencies** – Lightweight, fast, reliable



## Documentation



**Get Started**

- [Quick Start Guide](https://github.com/ax-llm/ax/blob/main/docs/QUICKSTART.md) – Set up in 5 minutes

- [Examples Guide](https://github.com/ax-llm/ax/blob/main/docs/EXAMPLES.md) – Comprehensive examples

- [DSPy Concepts](https://github.com/ax-llm/ax/blob/main/docs/DSPY.md) – Understanding the approach

- [Signatures Guide](https://github.com/ax-llm/ax/blob/main/docs/SIGNATURES.md) – Type-safe signature design



**Deep Dives**

- [AI Providers](https://github.com/ax-llm/ax/blob/main/docs/AI.md) – All providers, AWS Bedrock, Vercel AI SDK

- [AxFlow Workflows](https://github.com/ax-llm/ax/blob/main/docs/AXFLOW.md) – Build complex AI systems

- [Optimization (MiPRO, ACE, GEPA)](https://github.com/ax-llm/ax/blob/main/docs/OPTIMIZE.md) – Make programs smarter

- [Advanced RAG](https://github.com/ax-llm/ax/blob/main/docs/AXRAG.md) – Production search and retrieval



## Run Examples



```bash

OPENAI_APIKEY=your-key npm run tsx ./src/examples/[example-name].ts

```



Core examples: `extract.ts`, `react.ts`, `agent.ts`, `streaming1.ts`, `multi-modal.ts`



Production patterns: `customer-support.ts`, `food-search.ts`, `ace-train-inference.ts`, `ax-flow-enhanced-demo.ts`



[View all 70+ examples](src/examples/)



## Community



- [Twitter](https://twitter.com/dosco) – Updates

- [Discord](https://discord.gg/DSHg3dU7dW) – Help and discussion

- [GitHub](https://github.com/ax-llm/ax) – Star the project

- [DeepWiki](https://deepwiki.com/ax-llm/ax) – AI-powered docs



## Production Ready



- Battle-tested in production

- Stable minor versions

- Comprehensive test coverage

- OpenTelemetry built-in

- TypeScript first



## Contributors



- Author: [@dosco](https://github.com/dosco)

- GEPA and ACE optimizers: [@monotykamary](https://github.com/monotykamary)



## License



Apache 2.0



---



```bash

npm install @ax-llm/ax

```