Embeddings

Transform your text into powerful vector representations! Embeddings let you add semantic search, recommendation systems, and other advanced natural language features to your applications.

Quick Start

Here's how to generate embeddings with just a few lines of code:

use EchoLabs\Prism\Prism;
use EchoLabs\Prism\Enums\Provider;

$response = Prism::embeddings()
    ->using(Provider::OpenAI, 'text-embedding-3-large')
    ->fromInput('Your text goes here')
    ->generate();

// Get your embeddings vector
$embeddings = $response->embeddings;

// Check token usage
echo $response->usage->tokens;

Input Methods

You've got two convenient ways to feed text into the embeddings generator:

Direct Text Input

use EchoLabs\Prism\Prism;
use EchoLabs\Prism\Enums\Provider;

$response = Prism::embeddings()
    ->using(Provider::OpenAI, 'text-embedding-3-large')
    ->fromInput('Analyze this text')
    ->generate();

From File

Need to analyze a larger document? No problem:

use EchoLabs\Prism\Prism;
use EchoLabs\Prism\Enums\Provider;

$response = Prism::embeddings()
    ->using(Provider::OpenAI, 'text-embedding-3-large')
    ->fromFile('/path/to/your/document.txt')
    ->generate();

NOTE

Make sure your file exists and is readable. The generator will throw a helpful PrismException if there's any issue accessing the file.

Common Settings

Just like with text generation, you can fine-tune your embeddings requests:

use EchoLabs\Prism\Prism;
use EchoLabs\Prism\Enums\Provider;

$response = Prism::embeddings()
    ->using(Provider::OpenAI, 'text-embedding-3-large')
    ->fromInput('Your text here')
    ->withClientOptions(['timeout' => 30]) // Adjust request timeout
    ->withClientRetry(3, 100) // Add automatic retries
    ->generate();

Response Handling

The embeddings response gives you everything you need:

// Get the embeddings vector
$vector = $response->embeddings;

// Check token usage
$tokenCount = $response->usage->tokens;

Error Handling

Always handle potential errors gracefully:

use EchoLabs\Prism\Prism;
use EchoLabs\Prism\Enums\Provider;
use EchoLabs\Prism\Exceptions\PrismException;

try {
    $response = Prism::embeddings()
        ->using(Provider::OpenAI, 'text-embedding-3-large')
        ->fromInput('Your text here')
        ->generate();
} catch (PrismException $e) {
    Log::error('Embeddings generation failed:', [
        'error' => $e->getMessage()
    ]);
}

Pro Tips 🌟

Vector Storage: Consider using a vector database like Milvus, Qdrant, or pgvector to store and query your embeddings efficiently.

Text Preprocessing: For best results, clean and normalize your text before generating embeddings. This might include:

• Removing unnecessary whitespace
• Converting to lowercase
• Removing special characters
• Handling Unicode normalization

IMPORTANT

Different providers and models produce vectors of different dimensions. Always check your provider's documentation for specific details about the embedding model you're using.