LLM Application Development
Advanced
4.5

Build a Tool-Using AI Agent

Turn function calling into a simple autonomous agent loop.

1h 50m
1 lesson
1.2K students

What You'll Learn

Learning objectives will be added soon.

Tutorial Content

Agent = model + tools + a loop

An agent repeatedly: thinks, optionally calls a tool, observes the result, and continues until the task is done.

def run_agent(question, tools, tool_fns, max_steps=5):
    messages = [{"role": "user", "content": question}]
    for _ in range(max_steps):
        r = client.chat.completions.create(model="gpt-4o-mini",
            messages=messages, tools=tools)
        msg = r.choices[0].message
        if not msg.tool_calls:
            return msg.content
        messages.append(msg)
        for call in msg.tool_calls:
            result = tool_fns[call.function.name](call.function.arguments)
            messages.append({"role": "tool", "tool_call_id": call.id,
                             "content": str(result)})

Guardrails

Cap the number of steps, validate tool arguments, and require confirmation before any destructive action. Autonomy without limits is how agents rack up costs or cause damage.

Your Progress

Sign in to track your progress

Tags

Agents
LLM
Python