Drop-in replacement for OpenAI

Abso provides a unified interface for calling various LLMs while maintaining full type safety.

Features

• OpenAI-compatible API 🔁 (drop in replacement)
• Call any LLM provider (OpenAI, Anthropic, Groq, Ollama, etc.)
• Lightweight & Fast ⚡
• Embeddings support 🧮
• Unified tool calling 🛠️
• Tokenizer and cost calculation (soon) 🔢
• Smart routing (soon)

Providers

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

Installation

npm install abso-ai

Usage

import { abso } from "abso-ai"

const result = await abso.chat.completions.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 correct provider for a given model, but you can also manually select a provider.

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

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

// Helper to get the final result
const fullResult = await stream.finalChatCompletion()

console.log(fullResult)

Embeddings

const embeddings = await abso.embeddings.create({
  model: "text-embedding-3-small",
  input: ["A cat was playing with a ball on the floor"],
})

console.log(embeddings.data[0].embedding)

Tokenizers (soon)

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

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

Custom Providers

You can also configure built-in providers directly by passing a configuration object with provider names as keys when instantiating Abso:

import { Abso } from "abso-ai"

const abso = new Abso({
  openai: { apiKey: "your-openai-key" },
  anthropic: { apiKey: "your-anthropic-key" },
  // add other providers as needed
})

const result = await abso.chat.completions.create({
  model: "gpt-4o",
  messages: [{ role: "user", content: "Hello!" }],
})

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

Alternatively, you can also change the providers that are loaded by passing a custom providers array to the constructor.

Observability

You can use Abso with Lunary to get instant observability into your LLM usage.

First # to Lunary and get your public key.

Then simply set the LUNARY_PUBLIC_KEY environment variable to your public key to enable observability.

Contributing

See our Contributing Guide.

Roadmap

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