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AI agents Lab

Customer Service Agent

A tool-calling support agent built with the OpenAI Python SDK, used to practice agent design, guardrails, and evaluation end to end.

Context
AI Engineering program
My role
Build and evaluation
Code
Private, walkthrough on request
  • Python
  • OpenAI SDK
  • gpt-4.1-mini
  • Tool calling
  • Jupyter

Pipeline

  1. 01 Customer message Free-text request
  2. 02 Agent Chooses a tool
  3. 03 Tools Lookup, policy, actions
  4. 04 Guarded reply Checked before sending

What it is

A support agent for a simple store, built in a Jupyter notebook with the OpenAI Python SDK and gpt-4.1-mini. It handles common requests by calling tools, such as looking up an order or checking a policy, instead of answering from memory.

What I focused on

  • Tool design: small, well-described tools with strict argument schemas, so the model picks the right one.
  • Memory: keeping the relevant parts of the conversation without resending everything.
  • Guardrails: input checks for off-topic or unsafe requests, and output checks before a reply is shown.
  • Evaluation: a fixed set of customer requests with expected tool calls and outcomes, re-run after every change.

Why it’s here

This is the lab where I try techniques before using them in Tech Horizon projects: prompt structure, retrieval, tool routing, and tracing with LangSmith.