LLM Providers

import { Agent } from 'praisonai';

const getWeather = (city: string) => `Weather in ${city}: 20C, sunny`;

const agent = new Agent({
  instructions: 'Report the weather using the tool.',
  llm: 'anthropic/claude-3-5-sonnet-latest',
  tools: [getWeather],
});

await agent.start('Weather in Paris?');

import { Agent } from 'praisonai';

// OpenAI (default)
const openaiAgent = new Agent({
  instructions: 'You are helpful.',
  llm: 'gpt-4o-mini'
});

// Anthropic Claude
const claudeAgent = new Agent({
  instructions: 'You are helpful.',
  llm: 'anthropic/claude-3-5-sonnet'
});

// Google Gemini
const geminiAgent = new Agent({
  instructions: 'You are helpful.',
  llm: 'google/gemini-2.0-flash'
});

// All work the same way
await openaiAgent.chat('Hello!');
await claudeAgent.chat('Hello!');
await geminiAgent.chat('Hello!');

import { Agent, AgentTeam } from 'praisonai';

// Fast model for quick tasks
const triageAgent = new Agent({
  name: 'Triage',
  instructions: 'Quickly categorize incoming requests.',
  llm: 'gpt-4o-mini'  // Fast and cheap
});

// Powerful model for complex reasoning
const analysisAgent = new Agent({
  name: 'Analyst',
  instructions: 'Perform deep analysis of complex problems.',
  llm: 'anthropic/claude-sonnet-4'  // Best reasoning
});

// Creative model for content
const writerAgent = new Agent({
  name: 'Writer',
  instructions: 'Write engaging content.',
  llm: 'gpt-4o'  // Good for creative tasks
});

const agents = new AgentTeam([triageAgent, analysisAgent, writerAgent]);
await agents.start();

import { Agent } from 'praisonai';

function createAgentForTask(taskType: string) {
  const modelMap: Record<string, string> = {
    'quick': 'gpt-4o-mini',
    'reasoning': 'anthropic/claude-sonnet-4',
    'creative': 'gpt-4o',
    'code': 'anthropic/claude-3-5-sonnet',
    'multimodal': 'google/gemini-2.0-flash'
  };

  return new Agent({
    instructions: `You handle ${taskType} tasks.`,
    llm: modelMap[taskType] || 'gpt-4o-mini'
  });
}

const codeAgent = createAgentForTask('code');
await codeAgent.chat('Write a function to sort an array');

import { Agent } from 'praisonai';

const agent = new Agent({
  instructions: 'You tell stories.',
  llm: 'gpt-4o',
  stream: true  // Enable streaming
});

// Response streams to console
await agent.chat('Tell me a short story about a robot');

import { Agent } from 'praisonai';

// Model from environment variable
const agent = new Agent({
  instructions: 'You are helpful.',
  llm: process.env.PRAISONAI_MODEL || 'gpt-4o-mini'
});

// Or use different models per environment
const model = process.env.NODE_ENV === 'production' 
  ? 'gpt-4o'           // Better quality in prod
  : 'gpt-4o-mini';     // Cheaper in dev

const prodAgent = new Agent({
  instructions: 'You are helpful.',
  llm: model
});

import { Agent } from 'praisonai';

const agent = new Agent({
  instructions: 'You are helpful.',
  llm: 'claude-3-5-sonnet-latest',
  apiKey: process.env.MY_ANTHROPIC_KEY,          // no ANTHROPIC_API_KEY needed
  baseURL: 'https://gateway.example.com/v1',      // optional, per-agent
});

import { Agent } from 'praisonai';

// Local LM Studio
const lmStudioAgent = new Agent({
  instructions: 'You are helpful.',
  llm: 'openai-compatible/local-model',
  llmConfig: {
    baseUrl: 'http://localhost:1234/v1',
    apiKey: 'not-needed'
  }
});

// Custom OpenAI-compatible endpoint
const customAgent = new Agent({
  instructions: 'You are helpful.',
  llm: 'openai-compatible/my-model',
  llmConfig: {
    baseUrl: process.env.CUSTOM_API_BASE,
    apiKey: process.env.CUSTOM_API_KEY
  }
});

import { Agent } from 'praisonai';

// Ollama (local)
const ollamaAgent = new Agent({
  instructions: 'You are helpful.',
  llm: 'ollama/llama3.2',
  llmConfig: {
    baseUrl: 'http://localhost:11434'
  }
});

// LM Studio
const lmStudioAgent = new Agent({
  instructions: 'You are helpful.',
  llm: 'lm-studio/local-model',
  llmConfig: {
    baseUrl: 'http://localhost:1234/v1'
  }
});

// NVIDIA NIM
const nimAgent = new Agent({
  instructions: 'You are helpful.',
  llm: 'nvidia/nemotron-super'
});

import { Agent, createProvider } from 'praisonai';

// Create custom provider with options
const customProvider = createProvider('openai/gpt-4o', {
  maxRetries: 3,
  timeout: 60000
});

// Use in Agent (advanced)
const agent = new Agent({
  instructions: 'You are helpful.',
  llm: 'gpt-4o'  // Simple string is usually sufficient
});

await agent.chat('Hello!');

import { registerProvider, BaseProvider } from 'praisonai';

class MyCustomProvider extends BaseProvider {
  async generateText(options) {
    // Your implementation
    return { text: 'response', usage: { totalTokens: 10 } };
  }
}

// Register globally
registerProvider('my-provider', MyCustomProvider);

// Use in Agent
const agent = new Agent({
  instructions: 'You are helpful.',
  llm: 'my-provider/my-model'
});

# Core providers
export OPENAI_API_KEY=sk-...
export ANTHROPIC_API_KEY=sk-ant-...
export GOOGLE_API_KEY=AIza...

# Inference providers
export XAI_API_KEY=xai-...
export GROQ_API_KEY=gsk_...
export TOGETHER_API_KEY=...
export FIREWORKS_API_KEY=...

# Local providers
export OLLAMA_BASE_URL=http://localhost:11434
export LM_STUDIO_BASE_URL=http://localhost:1234/v1

# Set default model
export PRAISONAI_MODEL=openai/gpt-4o-mini