Structured Output
Force orxhestra agents to return typed Pydantic objects instead of free-form text using output_schema.
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Reusable instructions for compatible AI agents.
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Force orxhestra agents to return typed Pydantic objects instead of free-form text using output_schema.
Add planners to orxhestra agents for structured reasoning. Covers BasePlanner, PlanReActPlanner, and TaskPlanner.
Build an LLM agent with orxhestra. Use when creating a new agent, setting up LlmAgent or ReActAgent, or wiring tools to an agent.
Build orxhestra agent trees from declarative YAML orx files. Covers full schema, models, tools, agents, runner, and server.
Compose multi-agent systems with SequentialAgent, ParallelAgent, and LoopAgent. Use when building agent pipelines, parallel workflows, or iterative loops.
Add dynamic skills to orxhestra agents. Covers Skill, InMemorySkillStore, and skill discovery/loading tools.
Stream events from orxhestra agents including token-by-token output, sub-agent events via AgentTool, and Runner streaming.
Create and use tools with orxhestra agents. Covers function_tool, AgentTool, transfer tools, exit_loop, MCP tools, and CallContext.
Expose orxhestra agents as A2A protocol endpoints or connect to remote A2A agents.
Add callbacks to orxhestra agents for logging, monitoring, and error handling. Covers model and tool callbacks.
Connect orxhestra agents to MCP tool servers using MCPClient and MCPToolAdapter.
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