OpenAI Provider

Setup

Set your OpenAI API key:

export OPENAI_API_KEY=sk-...

llmist will automatically discover and use OpenAI.

Available Models

Text Models

Model	Alias	Best For
gpt-5	gpt5	Complex reasoning, coding
gpt-5-mini	gpt5-mini	Fast, cost-effective tasks
gpt-4-turbo	gpt4-turbo	Balanced performance
gpt-4o	gpt4o	Multimodal tasks
o3	o3	Advanced reasoning Reasoning
o4-mini	o4-mini	Fast reasoning Reasoning
o3-mini	o3-mini	Compact reasoning

Image Models

Model	Description
dall-e-3	High-quality image generation
dall-e-2	Faster, lower cost

Speech Models

Model	Description
tts-1	Text-to-speech, standard quality
tts-1-hd	Text-to-speech, high quality

Usage Examples

Text Generation

import { LLMist } from 'llmist';

const answer = await LLMist.createAgent()
  .withModel('gpt5')
  .askAndCollect('Explain quantum computing');

Image Generation

import { LLMist } from 'llmist';

const client = new LLMist();
const result = await client.image.generate({
  prompt: 'A sunset over mountains',
  model: 'dall-e-3',
  size: '1024x1024',
});

console.log(result.url);

Speech Generation

import { LLMist } from 'llmist';
import { writeFileSync } from 'fs';

const client = new LLMist();
const result = await client.speech.generate({
  input: 'Hello, world!',
  model: 'tts-1',
  voice: 'nova',
});

writeFileSync('speech.mp3', result.audio);

Reasoning Models

OpenAI’s o-series models (o3, o4-mini) and GPT-5 family support reasoning. llmist maps ReasoningEffort to OpenAI’s native reasoning.effort parameter:

Effort	OpenAI Value
"none"	"none"
"low"	"low"
"medium"	"medium"
"high"	"high"
"maximum"	"xhigh"

const answer = await LLMist.createAgent()
  .withModel('o3')
  .withReasoning('high')
  .askAndCollect('Prove that √2 is irrational.');

Tip

Models with features.reasoning: true (like o3) auto-enable reasoning at "medium" effort. Use .withoutReasoning() to opt out.

See the Reasoning Models guide for full details.

Vision (Image Input)

GPT-4o and GPT-5 models support image input:

import { LLMist, imageFromUrl } from 'llmist';

const answer = await LLMist.createAgent()
  .withModel('gpt4o')
  .askWithImage(
    'What is in this image?',
    imageFromUrl('https://example.com/photo.jpg')
  )
  .askAndCollect();

Configuration Options

import { LLMist, OpenAIChatProvider } from 'llmist';

const client = new LLMist({
  autoDiscoverProviders: false,
  adapters: [
    new OpenAIChatProvider({
      apiKey: process.env.OPENAI_API_KEY,
      baseUrl: 'https://api.openai.com/v1', // Custom endpoint
      organization: 'org-xxx',              // Optional org ID
    }),
  ],
});

Azure OpenAI

For Azure OpenAI, set a custom baseUrl pointing to your Azure endpoint and use the deployment name as the model.

Cost Tracking

llmist automatically tracks token usage and costs:

for await (const event of agent.run()) {
  if (event.type === 'llm_call_complete') {
    console.log('Tokens:', event.usage);
    console.log('Cost:', event.cost);
  }
}

Rate Limiting

OpenAI has rate limits. Use retry configuration for resilience:

const agent = LLMist.createAgent()
  .withModel('gpt5')
  .withRetry({
    maxAttempts: 3,
    retryOn: ['rate_limit', 'server_error'],
  });