ai-fun

ai-fun is an experimental LLM-powered function library. It lets you define the function purpose, the parameters and the output schema and generates and executes the code for you in the background. Think Cursor/GitHub Copilot but as a pluggable library.

npm i ai-fun

Complete example:

example.ts

import { z } from 'zod'
import AIFunctionBuilder from 'ai-fun'
import NodeExec from 'ai-fun/src/backends/node'
import { anthropic } from '@ai-sdk/anthropic'

// Provide a LLM model
const llm = anthropic.chat('claude-3-5-sonnet-20240620')

// Create a new AI Function Builder using Node/exec backend
const backend = new NodeExec()
const ai = new AIFunctionBuilder(llm, backend)

// Define the input parameters and output parameters of the function
const parameters = z.object({ a: z.number(), b: z.number() })
const output = z.number()

// Generate the function
const f = await ai.function('add values provided', parameters, output)

// Call the function and log the result
const result = await f({ a: 1, b: 2 })
console.log(result)

Output:

> bun example.ts
3

More examples found under examples/

DANGER ZONE

Read this Reddit comment before you continue:

Caching

Function caching is enabled by default for cost-saving measures. By default, the functions are stored in a file named .ai-fun.json.

Options you can provide to AIFunctionBuilder:

{
  debug?: boolean
  esModules?: boolean
  cache?: boolean
  cacheFile?: string
}

Backends

You can create your own backends by implementing the AIFunctionBackend class:

export abstract class AIFunctionBackend {
  abstract init(codeContent: CodeContent): Promise<void>
  abstract exec(params: any): Promise<any>
}

See src/backends/node for example.

Node (exec) backend

Executes the AI-generated functions using node:vm exec function.

Options:

{
  debug?: boolean
  packageFile?: string
  installPackages?: boolean
}

Contribute

As an open-source project, we welcome contributions from the community. If you are experiencing any bugs or want to add some improvements, please feel free to open an issue or pull request.