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Switch between any LLM provider — OpenAI, Anthropic, Google, and more — without changing your agent code.

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Quick Start

1

Simple Usage

npm install praisonai
2

With Configuration

import { Agent } from 'praisonai';

const agent = new Agent({
  instructions: 'You are a helpful assistant.',
  llm: 'openai/gpt-4o-mini'
});

const response = await agent.chat('Hello, how are you?');
console.log(response);
3

Switch Providers with One Line

import { Agent } from 'praisonai';

const agent = new Agent({
  instructions: 'You are a helpful assistant.',
  llm: 'anthropic/claude-3-5-sonnet-latest'
});

const response = await agent.chat('Explain AI in one sentence');
console.log(response);

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How It Works

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Supported Providers

ProviderModel StringExample
OpenAIopenai/modelopenai/gpt-4o, openai/gpt-4o-mini
Anthropicanthropic/modelanthropic/claude-3-5-sonnet-latest
Googlegoogle/modelgoogle/gemini-2.0-flash
Groqgroq/modelgroq/llama-3.3-70b-versatile
Mistralmistral/modelmistral/mistral-large-latest
Coherecohere/modelcohere/command-r-plus
DeepSeekdeepseek/modeldeepseek/deepseek-chat
xAIxai/modelxai/grok-2

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Common Patterns

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Agent with Tools

import { Agent } from 'praisonai';

function getWeather(city: string): string {
  return JSON.stringify({ city, temperature: 22, condition: 'sunny' });
}

const agent = new Agent({
  instructions: 'You help users check the weather.',
  llm: 'openai/gpt-4o-mini',
  tools: [getWeather]
});

const response = await agent.chat('What is the weather in Paris?');
console.log(response);

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Structured Output

import { Agent } from 'praisonai';
import { z } from 'zod';

const PersonSchema = z.object({
  name: z.string(),
  age: z.number(),
  city: z.string()
});

const agent = new Agent({
  instructions: 'Extract person information from text.',
  llm: 'openai/gpt-4o-mini',
  outputSchema: PersonSchema
});

const result = await agent.chat('John is 30 years old and lives in Paris');

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Multi-Agent Pipeline

import { Agent } from 'praisonai';

const researcher = new Agent({
  name: 'researcher',
  instructions: 'Research topics thoroughly.',
  llm: 'anthropic/claude-3-5-sonnet-latest'
});

const writer = new Agent({
  name: 'writer',
  instructions: 'Write engaging content based on research.',
  llm: 'openai/gpt-4o'
});

const research = await researcher.chat('Research the history of AI');
const article = await writer.chat(`Write an article based on: ${research}`);
console.log(article);

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Environment Variables

export OPENAI_API_KEY=sk-...
export ANTHROPIC_API_KEY=sk-ant-...
export GOOGLE_API_KEY=AIza...
export GROQ_API_KEY=gsk_...

# Override backend resolver
export PRAISONAI_BACKEND=ai-sdk   # Force AI SDK for all providers
export PRAISONAI_BACKEND=native   # Force native providers only
export PRAISONAI_BACKEND=auto     # Auto-select (default)

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Best Practices

Always use "provider/model" strings ("openai/gpt-4o-mini") rather than provider-specific config objects. Switching providers is a one-line change.
Core PraisonAI bundles OpenAI support. For other providers install @ai-sdk/anthropic, @ai-sdk/google, etc. only when you use them.
For quick tasks use openai/gpt-4o-mini or google/gemini-2.0-flash. For complex reasoning use anthropic/claude-3-5-sonnet-latest or openai/gpt-4o. Mix providers across agents in multi-agent workflows.
Never hard-code API keys. Use environment variables (OPENAI_API_KEY, ANTHROPIC_API_KEY, etc.). For production deployments use a secrets manager.

Providers

Full provider reference and configuration

Structured Output

Type-safe JSON responses