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Ai Voyage Platform Laravel Package
symfony/ai-voyage-platform
Symfony AI bridge for Voyage AI, providing text and multimodal embedding support so your applications can generate high-quality vector representations for search, RAG, and semantic similarity features.
Voyage platform bridge for Symfony AI
Frequently asked questions about Ai Voyage Platform
- How do I install symfony/ai-voyage-platform in a Laravel application?
- Run composer require symfony/ai-voyage-platform. Confirm symfony/ai and symfony/http-client are available, then bind the Voyage platform services in a Laravel service provider and configure your Voyage API key. Because the package is Symfony-first, you may need a small container bridge rather than a Laravel-native config file.
- Does symfony/ai-voyage-platform support Laravel out of the box?
- It is a Symfony-first AI platform bridge, not a native Laravel package. You can use it in Laravel through service provider bindings and PSR-11 container bridging. Standalone Laravel apps should evaluate whether adding Symfony AI dependencies is worth it versus a direct Voyage client.
- What Laravel versions can I use with this Voyage AI embedding bridge?
- The package does not publish Laravel-specific version constraints in the provided documentation; compatibility depends on its PHP, symfony/ai, and symfony/http-client requirements plus your Laravel container. Check composer.json constraints and test the bridge on your target Laravel release. Pin versions in composer.json to avoid surprises from Symfony AI updates.
- How do I configure Voyage AI credentials and embedding models in Laravel?
- Store the Voyage API key in environment variables or config/services and bind the Symfony AI Voyage platform or client in a service provider. The exact model and option keys follow Symfony AI and Voyage configuration, so keep model selection centralized in your own config. Avoid hard-coding keys and clear Laravel config caches after changes.
- What can I use Voyage embeddings for in a Laravel app?
- Use it for semantic search, RAG retrieval, clustering, recommendations, and similarity scoring. Generate embeddings for documents and queries, then store vectors in a vector database or search engine. For large backfills, dispatch embedding jobs to Laravel queues instead of doing everything in the request.
- Does this package support text and multimodal embeddings?
- Yes. The bridge exposes Voyage AI text embeddings and multimodal embeddings through Symfony AI platform APIs. Use text embeddings for standard documents and queries, and multimodal embeddings when your inputs combine content types. Verify supported input formats and limits in Voyage's API documentation.
- How should I test Voyage AI embedding calls in Laravel without hitting the API?
- Mock the Symfony HTTP client or bind a fake Voyage platform implementation in Laravel's container. Assert that requests include the right model and input, and simulate success, rate-limit, and error responses. Keep live API calls out of CI, or use a dedicated test key with strict quotas.
- What are the production concerns for using Voyage AI embeddings in Laravel?
- Plan for Voyage API costs, quotas, latency, and rate limits. Cache embeddings where possible, throttle outbound calls, and offload batch work to Laravel queues. Monitor failures and retries, and pin Symfony AI versions so platform changes do not break production.
- Can I swap Voyage AI for another embedding provider later?
- The Symfony AI Provider abstraction is intended to allow provider swaps and dynamic model routing, but this package still couples you to Symfony AI types. In Laravel, wrap embedding calls behind your own interface so you can change providers without touching feature code. Document fallback behavior and test with a second provider if vendor lock-in matters.
- What alternatives should I consider, and is this package maintained for production use?
- Consider Voyage's direct PHP client or SDK if you do not already use symfony/ai, plus other Symfony AI platform bridges, OpenAI embeddings, or Laravel-oriented AI packages. Treat this as an early-stage Symfony AI bridge: pin versions, watch Symfony AI releases, and be prepared to contribute fixes. If you need minimal dependencies, a lightweight direct integration can reduce Symfony-Laravel bridging friction.
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