A new plugin can enable fast runtime monitoring and control

A lot happens under the hood as an LLM acts on an incoming prompt and formulates a response. Hardly any of this generative processing, though, shows up in the text that ultimately reaches users.

You can make visible an LLM’s hidden ‘thought’ process using various tools for interpreting and steering AI model behavior, but most are incompatible with inference engines optimized for speed. In production environments where a model’s safety, tone, and accuracy matter most, these safety tools typically introduce long delays. That leaves two alternatives: training lightweight adapters to handle specific issues or retraining the model and recomputing its weights.

IBM’s new plugin library moves away from tinkering with models, and instead, targets the inference engine serving them up. Called vLLM-Hook MIA, it’s designed to let developers observe and steer a model’s evolving states at runtime, to do things like decline a malicious prompt, flag ‘hallucinated’ facts, or edit a…