deep-agents-orchestration

Orchestrate subagents, plan multi-step tasks, and require human approval for sensitive operations. All three are automatically included in create_deep_agent() . Default subagent : "general-purpose" - automatically available with same tools/config as main agent. @tool def search_papers(query: str) -> str: """Search academic papers.""" return f"Found 10 papers about {query}" agent = create_deep_agent( subagents=[ { "name": "researcher", "description": "Conduct web research and compile findings", "system_prompt": "Search thoroughly, return concise summary", "tools": [search_papers], } ] ) agent = create_deep_agent( subagents=[ { "name": "code-deployer", "description": "Deploy code to production", "system_prompt": "You deploy code after tests pass.", "tools": [run_tests, deploy_to_prod], "interrupt_on": {"deploy_to_prod": True}, # Require approval } ], checkpointer=MemorySaver() # Required for interrupts ) // CORRECT: Complete instructions upfront // task research: Find data on AI, save to /research/, return summary Each todo item has: agent = create_deep_agent() # TodoListMiddleware included by default result = agent.invoke({ "messages": [{"role": "user", "content": "Create a REST API: design models, implement CRUD, add auth, write tests"}] }, config={"configurable": {"thread_id": "session-1"}}) todos = result.get("todos", []) for todo in todos: print(f"[{todo['status']}]...