# Q5 — Build a simple LLM agent with LangChain (on Ghaymah's GenAI services)

⏱ **Budget: ~9 minutes** · Weight: 20%

## The task

Build a small **LLM agent** using **LangChain**, and point it at **Ghaymah's GenAI services** (the ready-to-use LLM models you saw in the dashboard).

Requirements:

1. Use LangChain (Python) with an **OpenAI-compatible** client pointed at Ghaymah's inference endpoint. Get the **base URL**, **API key**, and a **model ID** from https://deploy.ghaymah.systems (see the AI / models section).
2. Give the agent **at least one tool** — e.g. a calculator, a "save note" memory tool, or a tiny retrieval tool.
3. (Optional, +bonus) Wire it to the static site from **Q4** — the page calls your agent's endpoint and shows the reply.

There's a starter `agent.py` + `requirements.txt` in this folder you may extend or replace.

## Deliverable

Fill in the template below and commit your code in this folder.

---

## ANSWER — LangChain agent

### 1. What my agent does

> _one or two lines_ 

### 2. Architecture (LangChain components)

| Component | What I used |
|---|---|
| Model (LLM) | |
| Tool(s) | |
| Prompt | |
| Executor | |

### 3. How it uses Ghaymah's GenAI services

> _base URL pattern, model ID, how you got the key (do not paste the key)_ 

### 4. Code

> _commit your code in this folder (agent.py etc.) and reference it here_ 

### 5. How to run / deploy it

```bash
# commands
```