Weave Code
Ai Weaviate Store Laravel Package
symfony/ai-weaviate-store
Weaviate vector store integration for Symfony AI Store, with links to the REST API, GraphQL Get, and nearVector similarity search docs. Part of the Symfony AI monorepo for reporting issues and contributions.
Symfony AI Weaviate Store plugs Weaviate into the Symfony AI Store component as a vector backend. Store and query embeddings through Weaviate's REST and GraphQL APIs while coding against Symfony AI's store abstractions, so swapping vector databases doesn't require rewriting your application.
- Similarity search powered by Weaviate's
nearVectorqueries - REST and GraphQL support for writing and retrieving documents
- Filtered queries to narrow results by metadata
- Symfony-native service configuration and dependency injection
- Interchangeable with other Symfony AI vector store implementations
Frequently asked questions about Ai Weaviate Store
- What is symfony/ai-weaviate-store and what does it do in a Laravel app?
- symfony/ai-weaviate-store is a Symfony AI Store bridge that stores and queries embeddings in Weaviate through its REST and GraphQL APIs, including nearVector similarity search. It is not a Laravel-specific package, but Laravel applications can wrap its StoreInterface behind a service provider or facade. That keeps Symfony-specific types isolated while giving Laravel code a clean vector search and count API.
- How do I install symfony/ai-weaviate-store in Laravel with Composer?
- Install it with Composer using composer require symfony/ai-weaviate-store, along with the Symfony AI and HTTP client packages your integration needs. Pin the tested minor line, such as v0.14.x, because Symfony AI packages are still pre-1.0. In Laravel, register a dedicated service provider to construct the store and expose it through a facade or bound interface.
- Which Laravel and PHP versions are supported by this Weaviate store bridge?
- The package has no Laravel-specific version constraint because it is a Symfony AI component, so Laravel support depends on your integration layer. The assessed stack is Laravel 10+ with PHP 8.1+, but you should verify the current Composer platform requirements of symfony/ai, symfony/http-client, and this bridge before upgrading. Keep the integration in a module so Laravel framework upgrades and Symfony AI upgrades can be validated independently.
- How do I configure the Weaviate connection for Symfony AI Store in Laravel?
- Configure the Weaviate endpoint and any required authentication in a Laravel service provider, then pass those settings into the Symfony AI Weaviate store. Keep the Symfony HTTP client usage inside that provider rather than leaking it into controllers or domain services. You also need an existing Weaviate collection and schema before storing or querying embeddings.
- How do I run nearVector similarity searches against Weaviate from Laravel?
- Use the Symfony AI StoreInterface query flow with a nearVector query built from your embedding vector. The bridge translates that operation into Weaviate REST and GraphQL calls and returns matching documents. Expose a small Laravel service method such as searchSimilar so controllers do not depend directly on Symfony AI or Weaviate payloads.
- Does symfony/ai-weaviate-store support count operations for search totals and dashboards?
- Yes, v0.14.0 adds count capabilities for stores, which is useful for search result totals, admin dashboards, collection health checks, quota reporting, and pagination UX. Counts avoid fetching full documents, but they are not free at scale. Cache frequently requested counts and avoid calling them on every search request unless the product experience requires it.
- What is VectorDocumentInterface and should Laravel apps adopt it?
- VectorDocumentInterface is a typed document abstraction introduced in the v0.14.0 line to formalize how documents are represented in Symfony AI Store. It is optional for simple integrations but recommended if you use custom document objects. In Laravel, have domain DTOs implement it behind an adapter rather than passing Symfony-specific types directly through controllers.
- Do I manage the Weaviate schema and collections with Laravel migrations?
- No, Weaviate schema and collection lifecycle management remains outside Laravel migrations. You need an explicit process for creating and evolving collections, including vectorizer and property definitions, before the store is used. Count support does not change this, so document the schema process alongside your deployment runbook.
- How should I test Weaviate vector store integration in a Laravel application?
- Test the Laravel service provider and adapter with a mocked HTTP client or a dedicated Weaviate test instance rather than calling production. Cover CRUD, nearVector search, count operations, and Weaviate error mapping to Laravel exceptions. Keep Symfony AI types behind your adapter so most application tests can use fake store implementations.
- Is symfony/ai-weaviate-store production-ready, and what are the alternatives?
- It is usable in production with care, but Symfony AI packages are still pre-1.0, so pin tested versions and assign an owner for upgrade validation. Alternatives include other Symfony AI store bridges, a direct Weaviate REST or GraphQL client, or a Laravel-native vector search package if you do not need Symfony AI Store abstraction. Choose this bridge when you want StoreInterface compatibility and Weaviate-specific nearVector search without building the client layer yourself.
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