Google Antigravity SDK 0.1.18

Changelog: Local model support with LiteRT and LocalOpenAI, standardized evaluation presets, and custom subagent models

This release announces official Antigravity SDK local model support with first-class LiteRTAgentConfig and LocalOpenAIAgentConfig configurations, introduces a standardized evaluation preset (AgentConfig.eval()) for core coding evaluations, enables custom subagent model overrides, turns on the schedule tool by default across standard tool groups, and pairs background task management with command execution.

Improvements(13)

• Antigravity SDK and local models support: Official local model support is now ready to use with first-class LiteRTAgentConfig and LocalOpenAIAgentConfig configurations. Developers can execute on-device models with automated lightweight presets or integrate with local OpenAI-compatible endpoints.
• Standardized Evaluation Preset (AgentConfig.eval()): Adds a standardized, benchmark-ready preset that configures autonomous permissions, benchmark retry behavior, daemon execution in commands, and strips image generation and subagents to focus on core coding evaluations.
• Custom subagent models: Allows developers to assign specific model targets to subagents independently of the root agent configuration.
• Built-in schedule tool: Enables the schedule tool by default across standard tool groups, permitting agents and subagents to set timers and cron-based background jobs alongside task management.
• Automatic lightweight presets for LiteRT: Instantiating LiteRTAgentConfig now automatically applies optimized lightweight presets—including reduced prompt overhead and synchronous context compaction—without requiring an explicit call to .lightweight().
• Task management pairing: Automatically enables the manage_task tool whenever run_command or schedule is active, allowing background task lifecycle management.
• LiteRT and local model examples: Added getting-started guides and end-to-end examples demonstrating on-device execution with LiteRTAgentConfig (Gemma 4 26B) and OpenAI-compatible local endpoints using LocalOpenAIAgentConfig.
• Sandbox availability warning: Added a session startup warning when enable_sandbox=True is requested on an environment or OS backend where sandbox isolation cannot be enforced.
• Extended JSON Schema normalization: Added schema normalization support for OpenAPI and JSON Schema Draft 7 / 2020-12 keywords (such as multipleOf, prefixItems, and dependentSchemas) and prevented accidental mutation of uppercase sample values.
• Optimized ToolRunner coercion: Improved type resolution for closure-scoped tools and forward-referenced ToolContext parameters, and introduced TypeAdapter caching to accelerate tool call execution.
• Top-Level ServiceTier Export: Re-exported ServiceTier at the root package namespace for easier import parity.
• Excluded ASK_QUESTION from Default Tools: Excluded BuiltinTools.ASK_QUESTION from BuiltinTools.default(). Default configurations run autonomously; agents in headless workflows will no longer attempt interactive user prompts. To re-enable interactive questions, explicitly pass BuiltinTools.ASK_QUESTION in enabled_tools.
• Single compaction threshold dial: Simplified CompactionConfig to a single token_threshold property, deprecating legacy context token limits and interval dials. To configure context compaction, specify CompactionConfig(token_threshold=...).

Fixes(1)

• Service tier ingestion: Fixed an unhandled ValueError when connecting using gateways reporting unlisted backend service tiers (such as Vertex AI PROVISIONED_THROUGHPUT) by safely ignoring unknown tier values while preserving token counts.

Patches(1)

• Removed Deprecated modified_arguments_json: Removed the legacy JSON string fallback in tool hook interception in favor of modified_args.

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