Documentation Index
Fetch the complete documentation index at: https://docs.doclo.ai/llms.txt
Use this file to discover all available pages before exploring further.
OpenAI provides GPT-4 series models with vision capabilities for document processing.
Installation
npm install @doclo/providers-llm
Basic Setup
Via OpenRouter (Recommended)
import { createVLMProvider } from '@doclo/providers-llm';
const provider = createVLMProvider({
provider: 'openai',
model: 'openai/gpt-4.1',
apiKey: process.env.OPENROUTER_API_KEY!,
via: 'openrouter'
});
Native API
const provider = createVLMProvider({
provider: 'openai',
model: 'gpt-4.1',
apiKey: process.env.OPENAI_API_KEY!
});
Available Models
| Model | Context | Reasoning | Best For |
|---|
gpt-5.1 | 256k | Yes | Complex extraction |
gpt-4.1 | 128k | No | General extraction |
gpt-4.1-mini | 128k | No | Cost-effective extraction |
o3 | 200k | Yes | Complex reasoning |
o3-mini | 200k | Yes | Fast reasoning |
o4-mini | 200k | Yes | Latest reasoning model |
OpenRouter Model IDs
When using OpenRouter, prefix models with openai/:
// OpenRouter
model: 'openai/gpt-4.1'
// Native
model: 'gpt-4.1'
Configuration Options
createVLMProvider({
provider: 'openai',
model: string, // Model ID
apiKey: string, // API key
via?: 'openrouter', // Access method
baseUrl?: string, // Custom endpoint
limits?: {
maxFileSize?: number, // Max file size (bytes)
requestTimeout?: number, // Timeout (ms)
maxJsonDepth?: number // Max JSON nesting
}
})
Capabilities
| Feature | Support |
|---|
| Images | Yes (PNG, JPEG, WebP, GIF) |
| PDFs | Yes (up to 100 pages) |
| Structured Output | Yes (json_schema) |
| Reasoning | o3, o4-mini models |
| Streaming | Yes |
Images
// Via URL
{
images: [{
url: 'https://example.com/image.jpg',
mimeType: 'image/jpeg'
}]
}
// Via Base64
{
images: [{
base64: 'data:image/jpeg;base64,...',
mimeType: 'image/jpeg'
}]
}
PDFs
// Via Base64
{
pdfs: [{
base64: 'data:application/pdf;base64,...'
}]
}
Extended Reasoning
Enable reasoning for complex extractions:
import { createFlow, extract } from '@doclo/flows';
const flow = createFlow()
.step('extract', extract({
provider: createVLMProvider({
provider: 'openai',
model: 'openai/o3',
apiKey: process.env.OPENROUTER_API_KEY!,
via: 'openrouter'
}),
schema: complexSchema,
reasoning: {
enabled: true,
effort: 'high' // 'low' | 'medium' | 'high'
}
}))
.build();
| Option | Type | Description |
|---|
enabled | boolean | Enable reasoning |
effort | string | Reasoning depth: ‘low’, ‘medium’, ‘high’ |
exclude | boolean | Exclude reasoning tokens from response |
Production Setup
Use buildLLMProvider for retry logic and fallback:
import { buildLLMProvider } from '@doclo/providers-llm';
const provider = buildLLMProvider({
providers: [
{
provider: 'openai',
model: 'openai/gpt-4.1',
apiKey: process.env.OPENROUTER_API_KEY!,
via: 'openrouter'
}
],
maxRetries: 2,
retryDelay: 1000,
useExponentialBackoff: true,
circuitBreakerThreshold: 3
});
Pricing
Via OpenRouter (approximate):
| Model | Input (per 1k) | Output (per 1k) |
|---|
| gpt-4.1 | $0.002 | $0.008 |
| gpt-4.1-mini | $0.0004 | $0.0016 |
| o3 | $0.010 | $0.040 |
| o3-mini | $0.0011 | $0.0044 |
import { createFlow, extract } from '@doclo/flows';
import { createVLMProvider } from '@doclo/providers-llm';
const provider = createVLMProvider({
provider: 'openai',
model: 'openai/gpt-4.1',
apiKey: process.env.OPENROUTER_API_KEY!,
via: 'openrouter'
});
const invoiceSchema = {
type: 'object',
properties: {
invoiceNumber: { type: 'string' },
date: { type: 'string' },
total: { type: 'number' },
vendor: { type: 'string' }
}
};
const flow = createFlow()
.step('extract', extract({
provider,
schema: invoiceSchema
}))
.build();
const result = await flow.run({
base64: 'data:application/pdf;base64,...'
});
console.log(result.output);
// { invoiceNumber: 'INV-001', date: '2024-01-15', total: 1250, vendor: 'Acme Corp' }
Next Steps
