Magento 2 Semantic Search
sndsabin/module-semanticsearch
Enhances Magento 2 catalog search with natural-language understanding by matching queries against product embeddings stored in OpenSearch, returning semantically relevant results rather than keyword-only matches.
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Code Quality
Tested on Magento 2.4.9
Recent Test History
Each release is tested against the latest Magento version at that time.
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README
Loaded from GitHubMagento2 Module: SemanticSearch
sndsabin/module-semanticsearch
Main Functionality
This module uses product embeddings to enhance Magento 2 default search with natural language understanding. It depends on Embedding module to generate the product embedding.
Demo (Default Luma Store)
Model used for this demo:
qllama/bge-small-en-v1.5(384-dim embeddings). Results may vary depending on the embedding model used.
Query: "exercise dress"
| Default Search | Semantic Search |
|---|---|
 |
 |
Query: "pretty dress"
| Default Search | Semantic Search |
|---|---|
 |
 |
Installation
- Install the module via composer:
composer require sndsabin/module-semanticsearch
- Enable the module:
bin/magento module:enable SNDSABIN_Embedding SNDSABIN_SemanticSearch
bin/magento setup:upgrade
Configuration
⚠️ This module requires Embedding module, configure Embedding module first. Please refer to this for configuration.
⚠️ After configuration, generate product embeddings by following the instructions here.
This process may take some time depending on your catalog size. You can monitor progress by checking the document count in the configured OpenSearch index.
Go to Stores → Configuration → Semantic Search → Settings
General
- Enable
- Set it to Yes to enable the semantic search functionality.
Tested On:
- Magento 2.4.8
- PHP 8.4
- RabbitMQ 4.1
- OpenSearch 3.3
This content is fetched directly from the module's GitHub repository. We are not the authors of this content and take no responsibility for its accuracy, completeness, or any consequences arising from its use.