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Vibes accepts any Vercel AI SDK LanguageModel instance as its model option. This means every provider that ships a Vercel AI SDK adapter - Anthropic, OpenAI, Google, Groq, Mistral, Ollama, and custom OpenAI-compatible endpoints - works with Vibes out of the box. The model is passed at agent construction and can be overridden per run. For installation and initial setup, see Getting Started.

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Architecture

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Provider quickstarts

Install the provider package for your chosen model, set the API key environment variable, and pass the model instance to Agent.
All provider packages follow the Vercel AI SDK spec. Install the provider package for your chosen model, set the API key env var, and pass the model instance to Agent.

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Anthropic

npm install @ai-sdk/anthropic

import { Agent } from "@vibesjs/sdk";
import { anthropic } from "@ai-sdk/anthropic";
// Requires: ANTHROPIC_API_KEY environment variable

const agent = new Agent({
  model: anthropic("claude-sonnet-4-6"),
  systemPrompt: "You are helpful.",
});

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OpenAI

npm install @ai-sdk/openai

import { Agent } from "@vibesjs/sdk";
import { openai } from "@ai-sdk/openai";
// Requires: OPENAI_API_KEY environment variable

const agent = new Agent({
  model: openai("gpt-4o"),
  systemPrompt: "You are helpful.",
});

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Google Gemini

npm install @ai-sdk/google

import { Agent } from "@vibesjs/sdk";
import { google } from "@ai-sdk/google";
// Requires: GOOGLE_GENERATIVE_AI_API_KEY environment variable

const agent = new Agent({
  model: google("gemini-2.0-flash"),
  systemPrompt: "You are helpful.",
});

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Groq

npm install @ai-sdk/groq

import { Agent } from "@vibesjs/sdk";
import { groq } from "@ai-sdk/groq";
// Requires: GROQ_API_KEY environment variable

const agent = new Agent({
  model: groq("llama-3.3-70b-versatile"),
  systemPrompt: "You are helpful.",
});

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Mistral

npm install @ai-sdk/mistral

import { Agent } from "@vibesjs/sdk";
import { mistral } from "@ai-sdk/mistral";
// Requires: MISTRAL_API_KEY environment variable

const agent = new Agent({
  model: mistral("mistral-large-latest"),
  systemPrompt: "You are helpful.",
});

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Ollama (local)

npm install ollama-ai-provider

import { Agent } from "@vibesjs/sdk";
import { ollama } from "ollama-ai-provider";
// No API key required - connects to your local Ollama server

const agent = new Agent({
  model: ollama("llama3.2"),
  systemPrompt: "You are helpful.",
});

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OpenAI-compatible (custom endpoint)

Any service that exposes an OpenAI-compatible REST API can be used via createOpenAI with a custom baseURL: 
import { Agent } from "@vibesjs/sdk";
import { createOpenAI } from "@ai-sdk/openai";

const custom = createOpenAI({
  baseURL: "https://my-provider.example.com/v1",
  apiKey: process.env.MY_API_KEY,
});

const agent = new Agent({
  model: custom("my-model"),
  systemPrompt: "You are helpful.",
});

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ModelSettings

ModelSettings lets you tune the model’s sampling behavior. Pass it at agent construction to apply to every run, or override it per run via RunOptions.
FieldTypeDescription
temperaturenumber?Sampling temperature (0–2). Lower = more deterministic
maxTokensnumber?Maximum tokens to generate
topPnumber?Nucleus sampling: only sample from top-P probability mass
topKnumber?Only sample from the top-K tokens
presencePenaltynumber?Penalises tokens regardless of frequency (presence)
frequencyPenaltynumber?Penalises tokens that have already appeared (frequency)
stopSequencesstring[]?Stop generation when any of these sequences appear
seednumber?Seed for deterministic generation (model-dependent)
const agent = new Agent({
  model: anthropic("claude-sonnet-4-6"),
  modelSettings: {
    temperature: 0.7,
    maxTokens: 2000,
  },
});

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Overriding the model per run

Use agent.override({ model }) to swap the model for a single run without modifying the agent. This is useful for routing different prompts to different models - for example, a cheaper model for classification and an expensive model for generation: 
const cheapModel = groq("llama-3.3-70b-versatile");
const richModel = anthropic("claude-sonnet-4-6");

// Use cheap model for simple classification
const label = await agent
  .override({ model: cheapModel })
  .run("Classify: is this spam? " + email);

// Use powerful model for generation
const reply = await agent
  .override({ model: richModel })
  .run("Draft a professional reply to: " + email);

Install

Set up providers and environment variables

Agents

Full Agent constructor options reference