Abso makes calling various LLMs—simple, typed, and extensible. It provides a unified interface while maintaining full type safety and streaming capabilities.

Features

• 🔁 OpenAI-compatible API across multiple LLM providers
• 🚀 Lightweight & Fast: no overhead
• 🔍 TypeScript-first: strongly typed methods, requests, and responses
• 📦 Streaming support via both events and async iteration
• 🛠️ Easy extensibility: add new providers with minimal fuss
• 🧮 Embeddings support for semantic search and text analysis
• 🔢 Tokenizer support for accurate token counting and cost estimation

Providers

Provider	Chat	Streaming	Tool Calling	Embeddings	Tokenizer	Cost Calculation
OpenAI	✅	✅	✅	✅	🚧	🚧
Anthropic	✅	✅	✅	❌	🚧	🚧
xAI Grok	✅	✅	✅	❌	🚧	🚧
Mistral	✅	✅	✅	❌	🚧	🚧
Groq	✅	✅	✅	❌	❌	🚧
Ollama	✅	✅	✅	❌	❌	🚧
OpenRouter	✅	✅	✅	❌	❌	🚧
Voyage	❌	❌	❌	✅	❌	❌
Azure	🚧	🚧	🚧	🚧	❌	🚧
Bedrock	🚧	🚧	🚧	🚧	❌	🚧
Gemini	✅	✅	✅	❌	❌	❌

Installation

npm install abso-ai

Usage

import { abso } from "abso-ai";

const result = await abso.chat.create({
  messages: [{ role: "user", content: "Say this is a test" }],
  model: "gpt-4o",
});

console.log(result.choices[0].message.content);

Manually selecting a provider

Abso tries to infer the best provider for a given model, but you can also manually select a provider.

const result = await abso.chat.create({
  messages: [{ role: "user", content: "Say this is a test" }],
  model: "openai/gpt-4o",
  provider: "openrouter",
});

console.log(result.choices[0].message.content);

Streaming

const stream = await abso.chat.stream({
  messages: [{ role: "user", content: "Say this is a test" }],
  model: "gpt-4o",
});

for await (const chunk of stream) {
  console.log(chunk);
}

Tokenizers (soon)

const tokens = await abso.tokenize({
  messages: [{ role: "user", content: "Hello, world!" }],
  model: "gpt-4o",
});

console.log(`${tokens.count} tokens`);

Custom Providers

import { Abso } from "abso";
import { MyCustomProvider } from "./myCustomProvider";

const abso = new Abso([]);
abso.registerProvider(new MyCustomProvider(/* config */));

const result = await abso.chat.create({
  model: "my-custom-model",
  messages: [{ role: "user", content: "Hello!" }],
});

Ollama

import { abso } from "abso-ai";

const result = await abso.chat.create({
  messages: [{ role: "user", content: "Hi, what's up?" }],
  model: "llama3.2",
  provider: "ollama",
});

console.log(result.choices[0].message.content);

Contributing

See our Contributing Guide.

Roadmap

• More providers
• Built in caching
• Tokenizers
• Cost calculation