You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Plan Mode: Added Claude Code-style Plan Mode (setup_plan / PlanToolSet), so agents can enter a design-and-approval phase before implementation. Supports model-initiated entry via enter_plan_mode and user/UI-driven entry through session state, with plan drafting (update_plan_content), clarifying questions, approval gating (exit_plan_mode), and write-tool restrictions while planning.
Tools: Added Tavily as a provider for WebSearchTool and WebFetchTool. Search can return LLM-ready answers plus optional image hits; fetch can use Tavily Extract as an alternative to direct HTTP fetching.
AG-UI: Expanded long-running tool discovery so nested ToolSet tools (including Plan Mode tools) are recognized during AG-UI runs, and tool names can be resolved from session history when the client payload only carries a tool call id.
Bug Fixes
AG-UI: Fixed session state updates from the AG-UI protocol not being persisted. State-change events are now appended as non-partial events so session services apply them correctly.
Runner: Avoided repeated string concatenation while accumulating streaming partial text. Partial chunks are kept as a list and joined only when cancellation cleanup needs the full text.
Examples: Fixed a few example agents (LangGraph and Mem0) so the full example pipeline can run more reliably.
Docs
Docs: Added English and Chinese Plan Mode guides, plus dedicated pages for TodoWrite, Task, and Goal tools.
Docs: Documented Tavily configuration and usage for web search and web fetch.
Examples: Added plan_mode and plan_mode_with_goal_and_task AG-UI examples for trying Plan Mode end to end.
Internal
CI: Added a GitHub Actions release workflow for publishing releases.
CI: Added code-review helper prompts and scripts under .github/code_review/.
CI: Added pipeline_test/run_all_examples.sh to drive the full examples pipeline more consistently.