chatgpt-api/readme.md

AI agent stdlib that works with any AI SDK and LLM

Agentic

[!WARNING]
TODO: this project is not published yet and is an active WIP.

The goal of this project is to create a set of standard AI functions / tools which are optimized for both normal TS-usage as well as LLM-based usage across any popular AI SDK via simple adaptors.

For example, all of the stdlib tools like WeatherClient can be used both as normal, fully-typed TS SDKs:

import { WeatherClient } from '@agentic/stdlib'

const weather = new WeatherClient() // (requires `WEATHER_API_KEY` env var)

const result = await clearbit.getCurrentWeather({
  q: 'San Francisco'
})

console.log(result)

Or you can use them as a set of LLM-based functions / tools using adaptors specific to each LLM SDK. This example uses Vercel's AI SDK:

// sdk-specific imports
import { openai } from '@ai-sdk/openai'
import { generateText } from 'ai'
import { createAISDKTools } from '@agentic/stdlib/ai-sdk'

// sdk-agnostic imports
import { WeatherClient } from '@agentic/stdlib'

const weather = new WeatherClient()

const result = await generateText({
  model: openai('gpt-4o'),
  tools: createAISDKTools(weather),
  toolChoice: 'required',
  prompt: 'What is the weather in San Francisco?'
})

console.log(result.toolResults[0])

Let's take a slightly more complicated example which uses multiple clients and selects a subset of their functions using the pick method:

// sdk-specific imports
import { ChatModel, createAIRunner } from '@dexaai/dexter'
import { createDexterFunctions } from '@agentic/stdlib/dexter'

// sdk-agnostic imports
import { PerigonClient, SerperClient } from '@agentic/stdlib'

async function main() {
  const perigon = new PerigonClient()
  const serper = new SerperClient()

  const runner = createAIRunner({
    chatModel: new ChatModel({
      params: { model: 'gpt-4o', temperature: 0 }
    }),
    functions: createDexterFunctions(
      perigon.functions.pick('search_news_stories'),
      serper
    ),
    systemMessage:
      'You are a helpful assistant. Be as concise as possible. Respond in markdown. Always cite your sources.'
  })

  const result = await runner(
    'Summarize the latest news stories about the upcoming US election.'
  )
  console.log(result)
}

Here we've exposed 2 functions to the LLM, search_news_stories which corresponds to the PerigonClient.searchStories method and serper_google_search via the SerperClient.search method.

All of the SDK adaptors like createDexterFunctions are very flexible in what they accept. AIFunctionLike objects include:

• AIFunctionSet - Sets of AI functions (like perigon.functions.pick('search_news_stories') or perigon.functions or serper.functions)
• AIFunctionsProvider - Client classes which expose an AIFunctionSet via the .functions property (like perigon or serper)
• AIFunction - Individual functions (like perigon.functions.get('search_news_stories') or serper.functions.get('serper_google_search'))

You can pass as many or as few of these AIFunctionLike objects as you'd like and you can manipulate them as AIFunctionSet objects via .pick, .omit, .get, .map, etc.

The SDK-specific imports are all isolated to keep the main @agentic/stdlib as lightweight as possible.

Client Goals

• clients should be as minimal as possible
• clients must use ky as a lightweight native fetch wrapper
• clients must have a strongly-typed TS DX
• clients should expose select methods via the @aiFunction(...) decorator
  • @aiFunction methods must use zod for input schema validation
• it should be easy to create external clients which follow the AIFunctionsProvider superclass / @aiFunction decorator pattern
• common utility functions for LLM-based function calling should be exported for convenience
• clients and AIFunctions should be composable via AIFunctionSet
• clients must work with all major TS AI SDKs
  • SDK adaptors should be as lightweight as possible and be optional peer dependencies of @agentic/stdlib
  • SDK adatptor entrypoints should all be isolated to their own top-level imports
    • @agentic/stdlib/ai-sdk
    • @agentic/stdlib/langchain
    • @agentic/stdlib/llamaindex
    • @agentic/stdlib/dexter
    • @agentic/stdlib/genkit

Services

Service	Client	Description
Bing	BingClient	Bing web search
Clearbit	ClearbitClient	Resolving and enriching people and company data
Dexa	DexaClient	Answers questions from the world's best podcasters
Diffbot	DiffbotClient	Web page classification and scraping; person and company data enrichment
Exa	ExaClient	Web search tailored for LLMs
Firecrawl	FirecrawlClient	Website scraping and sanitization
Midjourney	MidjourneyClient	Unofficial Midjourney client for generative images
Novu	NovuClient	Sending notifications (email, SMS, in-app, push, etc)
People Data Labs	PeopleDataLabsClient	People & company data (WIP)
Perigon	PerigonClient	Real-time news API and web content data from 140,000+ sources. Structured and enriched by AI, primed for LLMs.
Polygon	PolygonClient	Stock market and company financial data
PredictLeads	PredictLeadsClient	In-depth company data including signals like fundraising events, hiring news, product launches, technologies used, etc
Proxycurl	ProxycurlClient	People and company data from LinkedIn & Crunchbase
Scraper	ScraperClient	Scrapes URLs into clean html/markdown/text content (TODO: currently closed beta)
Searxng	SearxngClient	OSS meta search engine capable of searching across many providers like Reddit, Google, Brave, Arxiv, Genius, IMDB, Rotten Tomatoes, Wikidata, Wolfram Alpha, YouTube, GitHub, etc
SerpAPI	SerpAPIClient	Lightweight wrapper around SerpAPI for Google search
Serper	SerperClient	Lightweight wrapper around Serper for Google search
Twitter	TwitterClient	Basic Twitter API methods for fetching users, tweets, and searching recent tweets. Includes support for plan-aware rate-limiting.
WeatherAPI	WeatherClient	Basic access to current weather data based on location
Wikipedia	WikipediaClient	Wikipedia page search and summaries
Wolfram Alpha	WolframAlphaClient	Wolfram Alpha LLM API client for answering computational, mathematical, and scientific questions.

Non-service Tools

• calculator
• e2b (code interpreter)
• search and scrape

AI SDKs

• OpenAI SDK
  • no need for an adaptor; use AIFunctionSet.specs or AIFunctionSet.toolSpecs
• Vercel AI SDK
  • import { createAISDKTools } from '@agentic/stdlib/ai-sdk'
• LangChain
  • import { createLangChainTools } from '@agentic/stdlib/langchain'
• LlamaIndex
  • import { createLlamaIndexTools } from '@agentic/stdlib/llamaindex'
• Firebase Genkit
  • import { createGenkitTools } from '@agentic/stdlib/genkit'
• Dexa Dexter
  • import { createDexterFunctions } from '@agentic/stdlib/dexter'

TODO

• rename this repo to agentic
• services
  • replicate
  • huggingface
  • skyvern
  • unstructured
  • pull from langchain
    • provide a converter for langchain DynamicStructuredTool
  • pull from nango
  • pull from activepieces
  • general openapi support ala workgpt
• tools / chains / flows / runnables
  • market maps
• https://github.com/causaly/zod-validation-error
• investigate autotool
• investigate data connectors

License

MIT © Travis Fischer

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