langchain-fundamentals

You can implement human-in-the-loop approval by applying middleware patterns to create_agent(), which intercepts the agent loop to pause tool execution and request manual approval before proceeding.

Wire tools into a LangChain agent by defining them with the @tool decorator in Python or the tool() function in TypeScript, passing these schema-defined tools directly to create_agent().

Middleware handles errors and persistent state by wrapping the create_agent() loop, enabling logging, error recovery, and memory persistence to maintain context across multiple agent interactions.

Yes, LangChain is required to use create_agent(). The framework provides the core orchestration loop, state management, and tool execution capabilities required to build and run production-grade agent workflows.

Yes, create_agent works with custom Python decorators. You can use the @tool decorator to define custom tools with clear input schemas, which are then automatically wired into the agent's execution loop.