Conduct AI released conduct-litellm-guard 0.2.5, a Python package that connects Conduct Guard to LiteLLM as a runtime guardrail for AI-agent and LLM requests. Every request routed through a configured LiteLLM proxy is checked against the active Conduct policy before it leaves the network. The guard can allow or advise on a request, forward it with a warning, block it, or hold it pending human-in-the-loop approval; blocked requests do not consume an upstream model token. Each check sends Conduct a compact request summary containing fields such as the model, call type, message count, temperature, stream setting, and the latest user message, while Conduct keeps the signed configuration and hash-chained audit log. The package supports an explicit adapter configuration across LiteLLM versions and documents a native configuration that depends on a stated upstream LiteLLM change. It tracks sessions using LiteLLM metadata, an explicit Conduct session header, an adapter-generated session identifier, or a deterministic hash of user content. The default `fail_closed` mode blocks calls when the Guard is unreachable or the policy evaluator fails; `fail_open` instead allows the call and records a warning. Version 0.2.5 renames `fail_mode` to `unreachable_fallback`, retaining the old name with a deprecation warning until its planned removal in 0.3.0. The package requires Python 3.10 or newer and is distributed under Apache 2.0.
AI News
The latest AI releases, research, products, and industry updates.
Loading...