kopia lustrzana https://github.com/transitive-bullshit/chatgpt-api
194 wiersze
16 KiB
Markdown
194 wiersze
16 KiB
Markdown
<p align="center">
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<a href="https://trywalter.ai"><img alt="Agentic" src="/media/agentic-header.jpg" width="308"></a>
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</p>
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<p align="center">
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<em>AI agent stdlib that works with any TypeScript AI SDK and LLM</em>
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</p>
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<p align="center">
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<a href="https://github.com/transitive-bullshit/walter/actions/workflows/main.yml"><img alt="Build Status" src="https://github.com/transitive-bullshit/walter/actions/workflows/main.yml/badge.svg" /></a>
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<a href="https://www.npmjs.com/package/@agentic/stdlib"><img alt="NPM" src="https://img.shields.io/npm/v/@agentic/stdlib.svg" /></a>
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<a href="https://github.com/transitive-bullshit/walter/blob/main/license"><img alt="MIT License" src="https://img.shields.io/badge/license-MIT-blue" /></a>
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<a href="https://prettier.io"><img alt="Prettier Code Formatting" src="https://img.shields.io/badge/code_style-prettier-brightgreen.svg" /></a>
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</p>
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# Agentic <!-- omit from toc -->
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> [!WARNING]
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> TODO: this project is not published yet and is an active WIP.
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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 apps** and that work with all of the major AI SDKs (LangChain, LlamaIndex, Vercel AI SDK, OpenAI SDK, etc).
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For example, stdlib clients like `WeatherClient` can be used normally as a fully-typed TS client:
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```ts
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import { WeatherClient } from '@agentic/stdlib'
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const weather = new WeatherClient() // (requires `WEATHER_API_KEY` env var)
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const result = await weather.getCurrentWeather({
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q: 'San Francisco'
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})
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console.log(result)
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```
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Or you can use this same function an LLM-based tool which works across all of the major AI SDKs via adaptors.
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Here's an example using [Vercel's AI SDK](https://github.com/vercel/ai):
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```ts
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// sdk-specific imports
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import { openai } from '@ai-sdk/openai'
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import { generateText } from 'ai'
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import { createAISDKTools } from '@agentic/stdlib/ai-sdk'
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// sdk-agnostic imports
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import { WeatherClient } from '@agentic/stdlib'
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const weather = new WeatherClient()
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const result = await generateText({
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model: openai('gpt-4o'),
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// this is the key line which uses the ai-sdk adaptor
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tools: createAISDKTools(weather),
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toolChoice: 'required',
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prompt: 'What is the weather in San Francisco?'
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})
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console.log(result.toolResults[0])
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```
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You can use all of our thoroughly tested stdlib AI functions with your favorite AI SDK – without having to write any glue code!
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Here's a slightly more complex example which uses multiple clients and selects a subset of their functions using the `AIFunctionSet.pick` method:
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```ts
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// sdk-specific imports
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import { ChatModel, createAIRunner } from '@dexaai/dexter'
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import { createDexterFunctions } from '@agentic/stdlib/dexter'
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// sdk-agnostic imports
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import { PerigonClient, SerperClient } from '@agentic/stdlib'
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async function main() {
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const perigon = new PerigonClient()
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const serper = new SerperClient()
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const runner = createAIRunner({
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chatModel: new ChatModel({
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params: { model: 'gpt-4o', temperature: 0 }
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}),
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functions: createDexterFunctions(
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perigon.functions.pick('search_news_stories'),
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serper
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),
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systemMessage: `You are a helpful assistant. Be as concise as possible.`
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})
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const result = await runner(
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'Summarize the latest news stories about the upcoming US election.'
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)
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console.log(result)
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}
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```
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Here we've exposed 2 functions to the LLM, `search_news_stories` (which comes from the `PerigonClient.searchStories` method) and `serper_google_search` (which implicitly comes from the `SerperClient.search` method).
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All of the SDK adaptors like `createDexterFunctions` accept very flexible in what they accept. `AIFunctionLike` objects include:
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- `AIFunctionSet` - Sets of AI functions (like `perigon.functions.pick('search_news_stories')` or `perigon.functions` or `serper.functions`)
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- `AIFunctionsProvider` - Client classes which expose an `AIFunctionSet` via the `.functions` property (like `perigon` or `serper`)
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- `AIFunction` - Individual functions (like `perigon.functions.get('search_news_stories')` or `serper.functions.get('serper_google_search')` or AI functions created directly via the `createAIFunction` utility function)
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You can pass as many of these `AIFunctionLike` objects as you'd like and you can manipulate them as `AIFunctionSet` sets via `.pick`, `.omit`, `.get`, `.map`, etc.
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All heavy third-party imports are isolated as _optional peer dependencies_ to keep the main `@agentic/stdlib` package as lightweight as possible.
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## Services
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| Service | Client | Description |
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| ------------------------------------------------------------------------ | ---------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| [Bing](https://www.microsoft.com/en-us/bing/apis/bing-web-search-api) | `BingClient` | Bing web search. |
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| [Calculator](https://github.com/silentmatt/expr-eval) | `calculator` | Basic calculator for simple mathematical expressions. |
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| [Clearbit](https://dashboard.clearbit.com/docs) | `ClearbitClient` | Resolving and enriching people and company datae. |
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| [Dexa](https://dexa.ai) | `DexaClient` | Answers questions from the world's best podcasters. |
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| [Diffbot](https://docs.diffbot.com) | `DiffbotClient` | Web page classification and scraping; person and company data enrichment. |
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| [E2B](https://e2b.dev) | `e2b` | Hosted Python code intrepreter sandbox which is really useful for data analysis, flexible code execution, and advanced reasoning on-the-fly. |
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| [Exa](https://docs.exa.ai) | `ExaClient` | Web search tailored for LLMs. |
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| [Firecrawl](https://www.firecrawl.dev) | `FirecrawlClient` | Website scraping and sanitization. |
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| [Midjourney](https://www.imagineapi.dev) | `MidjourneyClient` | Unofficial Midjourney client for generative images. |
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| [Novu](https://novu.co) | `NovuClient` | Sending notifications (email, SMS, in-app, push, etc). |
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| [People Data Labs](https://www.peopledatalabs.com) | `PeopleDataLabsClient` | People & company data (WIP). |
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| [Perigon](https://www.goperigon.com/products/news-api) | `PerigonClient` | Real-time news API and web content data from 140,000+ sources. Structured and enriched by AI, primed for LLMs. |
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| [Polygon](https://polygon.io) | `PolygonClient` | Stock market and company financial data. |
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| [PredictLeads](https://predictleads.com) | `PredictLeadsClient` | In-depth company data including signals like fundraising events, hiring news, product launches, technologies used, etc. |
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| [Proxycurl](https://nubela.co/proxycurl) | `ProxycurlClient` | People and company data from LinkedIn & Crunchbase. |
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| Scraper | `ScraperClient` | Scrapes URLs into clean html/markdown/text content (TODO: currently closed beta). |
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| [Searxng](https://docs.searxng.org) | `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](https://docs.searxng.org/user/configured_engines.html#configured-engines). |
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| [SerpAPI](https://serpapi.com/search-api) | `SerpAPIClient` | Lightweight wrapper around SerpAPI for Google search. |
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| [Serper](https://serper.dev) | `SerperClient` | Lightweight wrapper around Serper for Google search. |
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| [Slack](https://api.slack.com/docs) | `SlackClient` | Send and receive Slack messages. |
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| [Tavily](https://tavily.com) | `TavilyClient` | Web search API tailored for LLMs. 🔥 |
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| [Twilio](https://www.twilio.com/docs/conversations/api) | `TwilioClient` | Twilio conversation API to send and receive SMS messages. |
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| [Twitter](https://developer.x.com/en/docs/twitter-api) | `TwitterClient` | Basic Twitter API methods for fetching users, tweets, and searching recent tweets. Includes support for plan-aware rate-limiting. |
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| [WeatherAPI](https://www.weatherapi.com) | `WeatherClient` | Basic access to current weather data based on location. |
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| [Wikipedia](https://www.mediawiki.org/wiki/API) | `WikipediaClient` | Wikipedia page search and summaries. |
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| [Wolfram Alpha](https://products.wolframalpha.com/llm-api/documentation) | `WolframAlphaClient` | Wolfram Alpha LLM API client for answering computational, mathematical, and scientific questions. |
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## Compound Tools
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- search and scrape
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## AI SDKs
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- OpenAI SDK
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- no need for an adaptor; use `AIFunctionSet.specs` or `AIFunctionSet.toolSpecs`
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- Vercel AI SDK
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- `import { createAISDKTools } from '@agentic/stdlib/ai-sdk'`
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- LangChain
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- `import { createLangChainTools } from '@agentic/stdlib/langchain'`
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- LlamaIndex
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- `import { createLlamaIndexTools } from '@agentic/stdlib/llamaindex'`
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- Firebase Genkit
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- `import { createGenkitTools } from '@agentic/stdlib/genkit'`
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- Dexa Dexter
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- `import { createDexterFunctions } from '@agentic/stdlib/dexter'`
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## Client Goals
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- clients should be as minimal as possible
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- clients should use `ky` and `zod` where possible
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- clients should have a strongly-typed TS DX
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- clients should expose select methods via the `@aiFunction(...)` decorator
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- clients and AIFunctions should be composable via `AIFunctionSet`
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- clients should work with all major TS AI SDKs
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- SDK adaptors should be as lightweight as possible and be optional peer dependencies of `@agentic/stdlib`
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## TODO
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- rename this repo to agentic
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- sdks
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- modelfusion
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- services
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- perplexity
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- replicate
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- huggingface
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- [skyvern](https://github.com/Skyvern-AI/skyvern)
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- pull from [langchain](https://github.com/langchain-ai/langchainjs/tree/main/langchain)
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- provide a converter for langchain `DynamicStructuredTool`
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- pull from [nango](https://docs.nango.dev/integrations/overview)
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- pull from [activepieces](https://github.com/activepieces/activepieces/tree/main/packages/pieces/community)
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- general openapi support ala [workgpt](https://github.com/team-openpm/workgpt)
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- tools / chains / flows / runnables
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- market maps
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- https://github.com/causaly/zod-validation-error
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- investigate [autotool](https://github.com/run-llama/LlamaIndexTS/tree/main/packages/autotool)
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- investigate [data connectors](https://github.com/mendableai/data-connectors)
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## License
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MIT © [Travis Fischer](https://twitter.com/transitive_bs)
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To stay up to date or learn more, follow [@transitive_bs](https://twitter.com/transitive_bs) on Twitter.
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