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
3More examples found under examples/
Read this Reddit comment before you continue:
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
}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.
Executes the AI-generated functions using node:vm exec function.
Options:
{
debug?: boolean
packageFile?: string
installPackages?: boolean
}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.