Shared Embedding & Retrieval Infrastructure for Joplin AI Features ( Questions)

On your questions: For inter-plugin data access - have you tried using Joplin's command system? Commands can return structured data (objects, arrays) across plugins, which would avoid the shared-file approach. The gap is load ordering - what happens if the infra plugin hasn't loaded when a consumer calls?

On the API - put(note) / query(text) / getNoteEmbedding() / findSimilarNotes() covers the basics. Where do retrieval features like reranking and query decomposition live - in the shared query() or in individual consumers? That also defines the project scope: what's the infra layer, and what's the demo consumer that proves it works?

As @adamoutler noted, there's a question about whether this lives as a plugin or in core. @laurent thoughts?

If you're planning to submit this as a GSoC proposal, the submission template has the required structure.