Support for alternative LLM backends (OpenAI-compatible / local vLLM)

[Emilien-Etadam]

Hi,

Thanks for open-sourcing Breeze.

Would you consider decoupling the AI Brain from Anthropic-only BYOK? Use cases:

• Self-hosted setups with local GPUs (vLLM, Ollama)
• Regulated environments where data can't leave the infra
• Experimentation with other models

Config surface could stay minimal:

• provider: anthropic (default) | openai-compatible
• endpoint URL, model name, API key

I realize this isn't a trivial swap given how the Agent SDK drives tool-use and the risk engine — a LiteLLM-style translation layer or a provider abstraction inside the Brain Connector both seem viable, you'll know better which fits.

Transparency: I'd be happy to test against a local vLLM instance, and potentially contribute a PoC behind a feature flag. Any code I'd submit would be AI-assisted (Claude Code) with me driving design and testing — flagging upfront so you know what to expect on review.

Two questions:

• Roadmap item, or explicitly out of scope?
• Is the Agent SDK's tool-use format a hard requirement for the risk engine?

Thanks!

[Emilien-Etadam]

Small correction to my message above — having looked at the code, the right names are aiGuardrails (not "risk engine") and the SDK surface is narrower than I implied.

So my real questions, more precisely:

1. Is provider-pluggability on the roadmap, or out of scope (e.g. commercial differentiation with the hosted Brain)?
2. If open: would you want the abstraction to sit above query() (replacing the call entirely per provider), or somewhere else?
3. Would a PoC behind a feature flag be welcome before any wider discussion?

Thanks.