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Ai Pinecone Store Laravel Package
symfony/ai-pinecone-store
Pinecone vector store integration for Symfony AI Store, enabling upsert, query, and delete of vectors plus serverless index creation through the Pinecone API.
Pinecone vector store bridge for Symfony AI
Frequently asked questions about Ai Pinecone Store
- How do I install symfony/ai-pinecone-store in a Laravel app?
- Install it with Composer using composer require symfony/ai-pinecone-store. Because it is a Symfony AI bridge rather than a native Laravel package, you will also need the relevant Symfony AI dependencies and a service provider or container binding to wire the Pinecone store into your app. After installation, configure your Pinecone API key and index settings before using the store.
- Is symfony/ai-pinecone-store compatible with Laravel?
- It is not a native Laravel package; it is a Pinecone vector store bridge for Symfony AI. It can be used in Laravel by adopting Symfony AI and binding the store through Laravel's service container or a custom service provider. This works well if you already use Symfony AI components, but it adds more integration boilerplate than a Laravel-specific package.
- How do I configure Pinecone credentials and the index name in Laravel?
- Store your Pinecone API key and index settings in Laravel configuration, typically backed by environment variables, and inject those values when constructing or binding the Pinecone store. Keep credentials out of source control and use Laravel's config cache in production. You will also need to ensure the configured index exists or create it through the package's serverless index support.
- What vector operations does symfony/ai-pinecone-store support?
- The package implements Symfony AI's StoreInterface and supports upserting, querying, and deleting vectors through the Pinecone API. It also supports serverless index creation, metadata filtering, and hybrid search. As of v0.14.0 it adds count capabilities, and the VectorDocumentInterface standardizes document representation across stores.
- Can I create a Pinecone serverless index from PHP with this package?
- Yes, the bridge supports creating serverless indexes through Pinecone's control-plane API. This is useful for provisioning indexes from your Laravel deployment or setup workflow. Treat index creation as an administrative operation rather than a per-request action, and make sure your API key has the required permissions.
- Does symfony/ai-pinecone-store support metadata filtering and hybrid search?
- Yes, the Pinecone bridge supports metadata filtering and hybrid search through the Pinecone API. These features are useful for RAG pipelines, semantic search, recommendations, and enterprise use cases that need more precise retrieval. Hybrid search behavior will depend on how your Pinecone index is configured.
- What Laravel and PHP versions are supported by symfony/ai-pinecone-store?
- There is no explicit Laravel version support matrix because this is a Symfony AI package rather than a Laravel package. It should work in Laravel applications that satisfy the required PHP version and the symfony/ai Composer constraints. Check the package's composer.json before upgrading and pin versions in production because the project is still pre-1.0.
- How should I test Pinecone vector store integration without hitting the live API?
- Keep Pinecone operations behind the Symfony AI StoreInterface or your own wrapper so tests can use a fake store or mocked HTTP responses. Avoid calling the live Pinecone API in unit tests, and reserve integration tests for a dedicated Pinecone test index. This keeps tests fast and prevents accidental data changes or quota usage.
- What production concerns should I consider with symfony/ai-pinecone-store?
- The package is pre-1.0, so pin your Composer version and test minor upgrades because backward-compatibility breaks are possible. Performance and latency are governed by Pinecone's SLA, and frequent count calls add extra round-trips if you poll them often. Also consider the dependency size of symfony/ai and monitor Pinecone quotas and capacity.
- What alternatives exist to symfony/ai-pinecone-store for Laravel?
- Alternatives include Pinecone's PHP SDK, a custom wrapper around Symfony HTTP Client or Laravel's HTTP client, or another Symfony AI vector store bridge if you are not committed to Pinecone. If you already use Symfony AI, staying with the official bridge gives you consistent StoreInterface behavior. If you only need simple Pinecone calls, a lighter custom wrapper may reduce dependency overhead.
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