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The EmbeddingsBuilder provides a fluent interface for generating vector embeddings from text input. Embeddings can be used for semantic search, similarity comparison, and other vector-based operations.

​
Configuration Methods

​
model

Set the embedding model to use. 
$builder->model('text-embedding-3-small')
$builder->model(new OpenAIEmbeddings('text-embedding-3-large'))
​
model
string|EmbeddingModel
required
The embedding model identifier string or EmbeddingModel instance
​
return
static
Returns the builder instance for method chaining

​
input

Set the text input to generate embeddings for. 
$builder->input('The quick brown fox jumps over the lazy dog')
$builder->input(fn() => $article->content)
​
input
Closure|string
required
The text to embed, or a closure that returns the text
​
return
static
Returns the builder instance for method chaining

​
Callback Methods

​
onTokenStats

Set a callback for token usage statistics. 
$builder->onTokenStats(function(TokenStats $stats) {
    echo "Tokens used: {$stats->total}";
})
​
onTokenStats
Closure(TokenStats): void|null
required
Closure that receives TokenStats with usage information
​
return
static
Returns the builder instance for method chaining

​
Execution Methods

​
get

Generate the embeddings for the configured input. 
$embedded = $builder->get()
​
return
EmbeddedData
EmbeddedData instance containing the vector embeddings and metadata
​
throws
InvalidArgumentException
Thrown if input or model is not set before calling get()

​
Usage Example

use Mateffy\Magic;

// Simple usage with facade
$embedded = Magic::embeddings(
    input: 'Hello world',
    model: new OpenAIEmbeddings('text-embedding-3-small')
)->get();

// Advanced usage with builder
$embedded = Magic::embeddings()
    ->model('text-embedding-3-large')
    ->input(fn() => $document->content)
    ->onTokenStats(function($stats) {
        Log::info('Embedding tokens', ['total' => $stats->total]);
    })
    ->get();

// Access the embedding vector
$vector = $embedded->vector; // array of floats

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