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securityF
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qualityA bridge between AI assistants like GitHub Copilot and Supabase databases, allowing AI to understand schema, assist with query writing, and provide context-aware suggestions related to your data model.
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Enables containerized deployment of the service, with support for both standalone Docker and Docker Compose configurations.
Integrates with GitHub for version control and automated deployment through Railway, detecting repository changes for continuous deployment.
Generates vector embeddings using OpenAI's embedding models to create searchable vectors from project data that are stored in Supabase.
Provides deployment configuration for hosting the service on Railway's platform, with built-in monitoring through health check endpoints.
Synchronizes vector embeddings between Supabase tables, monitoring changes in the 'proyectos' table and updating the 'proyecto_vector' table with vector embeddings for efficient multi-tenant search capabilities.
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