AgentBarrier 0.3.0: More Flexible Approvals and Better CrewAI Support
This release makes it easier to set up custom approval workflows, adds a payment tracking example, and fixes CrewAI compatibility on Python 3.10.
AgentBarrier now supports approval barrier profiles, which let you create different approval workflows for different scenarios without changing code. This gives teams more flexibility in how they configure agent approval processes to match their specific needs.
The update also improves how the system handles unclear or ambiguous decision outcomes, making agent decision validation more robust and predictable when situations aren't clear-cut. Alongside this, a new example has been added showing how to use agent barriers with a SQLite-backed payment ledger, giving developers a working reference for payment tracking use cases.
For CrewAI users, this release adds deterministic evaluation, meaning agents can now run repeatable tests that produce the same results every time. This release also restores CrewAI support for Python 3.10 environments, fixing a compatibility issue that had prevented it from working correctly.
Finally, compatibility evidence is now automatically generated and validated during continuous integration, helping ensure consistent support across versions before changes reach users.
Together, these changes make AgentBarrier more adaptable and dependable. Teams can configure approval processes to fit their own workflows, trust that ambiguous decisions are handled more reliably, and rely on consistent, repeatable behavior when testing with CrewAI. The Python 3.10 fix also means CrewAI users on that version can resume using AgentBarrier without workarounds.
How to use it
To take advantage of the new flexibility, set up approval barrier profiles to define different approval workflows for different scenarios. If you're working with payment tracking, refer to the new SQLite payment ledger example for a complete working reference. CrewAI users can now run deterministic evaluations to get consistent, repeatable results across test runs.