AI Agent News/stories/pydantic-ai-2-67-0-adds-keenablesearch-and-moves-native-tool-settings.md

Frameworks

Pydantic AI 2.67.0 adds KeenableSearch and moves native-tool settings

Pydantic AI released version 2.67.0, which adds a KeenableSearch capability for keyless web research and support for several newer models. The release also includes compatibility changes, including moving provider-specific native-tool fields into provider_settings.

Source: github.com/pydantic/pydantic-ai/releases/tag/v2.67.0

The release starts with compatibility notes. Provider-specific native-tool fields now live under provider_settings, and RepoContext loads one instruction file per directory by default. Inlined nested instructions are capped at 32,000 characters per conversation unless RepoContext(nested_max_chars=...) changes the limit.

New features include the KeenableSearch capability, dequeue and set_enqueue_priority for changing a queued message before delivery, and a client option on ModalSandbox and E2BSandbox. Model support now covers Claude Fable 5.2 and Claude Mythos 5.2, Gemini 4 Carbon on GoogleModel, and OpenAI's gpt-image-2.6-flare and gpt-image-2.6-sunburst image models.

Durable execution coverage grows as well, with SubAgents(dynamic_agents=...) supported under durable execution and tool calls runnable as DBOS child workflows. Bug fixes cover Shell job handling, Gemini quota errors and streamed Mistral tool-call deltas.

Why it matters if you build agents

Code that sets native-tool options directly on agents needs to move those fields into provider_settings. Teams using RepoContext should check the new one-file-per-directory loading and the 32,000-character cap on nested instructions. Agents built on durable execution can now use dynamic subagents, which may change how their runs replay.

Get stories like this every weekday

One short email with the day's agent tooling news.

Subscribe