AIKit is a minimal TypeScript wrapper that gives you unified access to the generation APIs of OpenAI, Anthropic, and Google Gemini—complete with streaming, multimodal inputs, and tool calling. No extra runtime packages: just the
fetchthat ships with modern Node and browsers.
Use AIKit for: Generation & streaming, multimodal prompts (text + images + audio), tool/function calling, embeddings, and usage tracking.
Use the official provider SDKs for everything else (fine-tuning, file management, etc.).
| Feature | What That Means |
|---|---|
| Zero Dependencies | Uses only the built-in fetch; no freeloaders. |
| No Surprises | Every provider option is right there—no secret sauce. |
| Multimodal | Text, images, and audio get equal treatment. |
| Embeddings Included | Vectors are first-class citizens. |
| Tool-Friendly | Utilities for tool and function calls, ready to go. |
| Reasoning Support | Access model reasoning for Claude and OpenAI o-series models. |
| Usage Tracking | Monitor token consumption, costs, and timing across all providers. |
| Unified API | Same call shape for OpenAI, Anthropic & Gemini. |
| Type-Safe | Exhaustive TypeScript types for requests & responses. |
| Streaming | for await over tokens or deltas. |
| Utility Functions | Helper functions for messages, tools, and content, and stream handling |
npm install @chinmaymk/aikitimport { createProvider, userText, printStream } from '@chinmaymk/aikit';
const openai = createProvider('openai', {
apiKey: process.env.OPENAI_API_KEY!,
});
const messages = [userText('Hello!')];
// Simple approach - print directly to console
await printStream(openai(messages, { model: 'gpt-4o' }));
// Or use the classic streaming approach
for await (const chunk of openai(messages, { model: 'gpt-4o' })) {
process.stdout.write(chunk.delta);
}import { createOpenAIEmbeddings } from '@chinmaymk/aikit';
const embeddings = createOpenAIEmbeddings({
apiKey: process.env.OPENAI_API_KEY!,
});
// Turn text into vectors
const result = await embeddings(['Hello, world!', 'How are you?']);
console.log(result.embeddings[0].values); // [0.123, -0.456, ...]How does this work?
AIKit directly calls apis of underlying llm providers, and maps responses to a unified result stream and consistent types.
How does this differ from the official SDKs?
AIKit focuses only on generation features across providers. That narrow focus lets us ship a smaller, unified API surface. If you need file uploads, fine-tuning, vector stores, etc., use the vendor SDK.
Will the API change under my feet?
Vendor generation endpoints rarely break. When they occasionally do, we publish a new major AIKit version right away so you can upgrade with minimal fuss. We follow semantic versioning and document any change in the changelog.
What are the best use cases for AIKit?
When you want streaming, multimodal inputs, consistent typings across providers, tool calls, environment-agnostic execution, or when you're simply interested in the generative features of large models, AIKit makes it easy—all in just a few lines.
📚 Full docs & API reference: https://chinmaymk.github.io/aikit/
MIT © 2025