Clusters

This cluster focuses on fixes and enhancements related to Bedrock model support and caching mechanisms within the AI agent framework.

This cluster focuses on improvements and fixes related to image model functionalities and onboarding processes in the AI agent framework.

This cluster focuses on adding new AI provider plugins and skills to enhance the framework's capabilities.

This cluster focuses on fixes and features related to cooldown handling and fallback mechanisms for models in the AI agent framework.

This cluster addresses improvements and fixes related to model fallback mechanisms and error handling in the AI agent framework.

This cluster focuses on improvements and fixes related to the Venice models in the OpenClaw framework.

This cluster focuses on adding support and fixes for the Gemini 3.1 Pro models, including compatibility and fallback mechanisms.

This cluster focuses on enabling and improving reasoning capabilities and configurations for the Kimi AI models in the OpenClaw framework.

This cluster focuses on adding various model providers to enhance the AI agent framework's capabilities.

This cluster focuses on enabling and fixing developer role management for DashScope and Qwen models within the framework.

This cluster addresses issues related to the handling of model aliases, ensuring correct resolution and error messaging for legacy and short-name keys.

This cluster focuses on improvements and fixes for the Moonshot AI provider, particularly related to video understanding and role handling.

This cluster focuses on improving the handling and sanitization of reasoning blocks in OpenAI sessions.

This cluster focuses on improving the reliability and compliance of the Gemini batch API for embedding operations.

A collection of fixes related to the MiniMax API, including region detection, pricing constants, and tool-use repairs.

This cluster addresses issues related to context window limits and model configurations in the OpenClaw framework.