The Agent Loop

An agent is a model in a loop: think → act → observe → repeat.

The ReAct pattern (Reason + Act):

1. Send task to model with available tools
2. Model returns a final answer or requests a tool call
3. Execute the tool, send the result back
4. Repeat until done

This is the foundation of every AI agent — from arithmetic helpers to multi-step research pipelines.

Why care? This loop scales to any number of tools. Replace add and multiply with search_web, query_database, or send_email — the loop is identical. Understanding it here means you understand every agent framework under the hood.

Task

Complete Agent.run(task). Two arithmetic tools (add, multiply) and their schemas are already defined in TOOLS and TOOL_FUNCTIONS. Loop until the model returns stop_reason == "end_turn".