[Feature]: First-class "Embedding & Vector Store Providers" resource, reusable across Semantic Cache and future embedding-based policies
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Description
Please select the area the issue is related to
AI Workspace, Gateway
Please select the aspect the issue is related to
Aspect/UI (Frontend layouts, components, styling), Aspect/Configuration (Config files, settings, env vars, defaults)
Suggested Feature
Embedding provider and vector DB settings needed for Semantic Cache (embedding_provider, embedding_provider_dimension, embedding_provider_api_key, vector_db_provider, vector_db_provider_host, etc.) currently live as flat keys in the gateway's config.toml, with no Console UI to manage them. The current key structure appears to only support a single embedding provider and vector store — there's no confirmed support for configuring more than one.
Suggest adding "Embedding & Vector Store Providers" as a first-class, UI-managed resource, following the same pattern already used for "LLM Providers": configure once (endpoint, auth, model, dimension / host, port, credentials), then select from a dropdown wherever needed, instead of editing config files directly.
This would also support multiple named providers, so different use cases (e.g. a cheaper model for high-volume caching vs. a stricter one elsewhere) aren't forced to share one global config.
Semantic Cache is a confirmed consumer of this config today. A shared, reusable resource would avoid re-solving the same config problem if similar embedding-based features (e.g. semantic guardrails, semantic routing) are added later.
Related Issues
https://github.com/wso2/api-platform/issues/3417
Steps to Verify
- Design Document — A detailed design document has been created and reviewed, covering architecture, data flow, and edge cases.
- Design Mail — A design summary email has been sent to relevant stakeholders for awareness and feedback.
- Code Review — All code changes have been peer-reviewed and approved according to the project's review standards.
- Testing Complete — Adequate unit, integration, and/or end-to-end tests have been written and are passing.
- Documentation Review — User-facing and/or developer documentation has been updated to reflect the new feature and reviewed.
- Feature Complete — The feature is fully implemented, all checklist items above are done, and it is ready for release.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the gateway's config.toml embedding_provider and vector_db_provider keys, the existing LLM Providers pattern, Semantic Cache, and related issue 3417. Done requires a reviewed design covering architecture, data flow, and edge cases, followed by the listed code, testing, documentation, and release checks.
Written by the indexing model from the issue text.
Assessment
- Domain
- full-stack
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100