Senior LevelLaravel
How do you implement Hybrid Vector & Full-Text Search in Laravel Scout with Meilisearch?
❓ Interview Prompt: Explain hybrid search, combining lexical keyword search with dense vector embeddings in Meilisearch, and Scout integration.
Modern search engines combine traditional keyword matching (lexical) with AI vector embeddings (semantic) for Hybrid Search:
Architecture:
1
Generate text embeddings via OpenAI/Ollama API during model saving.
2
Store vector arrays in Meilisearch index.
3
Execute hybrid queries using Meilisearch vector search through Scout model integrations, returning highly relevant search results!
Code Implementation Example
php
<?php
// Custom Scout Meilisearch search execution with vector embeddings
$results = User::search('high performance PHP developer', function ($meilisearch, $query, $options) {
$options['vector'] = [0.012, -0.043, 0.089, ...]; // OpenAI embedding array
$options['hybrid'] = ['embedder' => 'default', 'semanticRatio' => 0.5];
return $meilisearch->search($query, $options);
})->get();💡Executing hybrid vector and lexical full-text search in Scout.
🎯 Interview Key Takeaway
Combine keyword matching and vector embeddings in Scout with Meilisearch to execute AI-driven hybrid search queries.
#Hybrid Search#Vector Embeddings#Meilisearch#Scout#Senior
Back to all Laravel Questions→