CS 335 API Assignment

Northeastern Illinois University — Introduction to Artificial Intelligence

Student: Alex Curtis API Used: Google Gemini API

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Overview

This project uses the Gemini API to make 3 different API calls using Python.

The program runs in the terminal and prints the responses directly to the screen.

The 3 API calls are:

1. What is machine learning?
2. What is supervised learning?
3. User input question for Gemini

The API key is stored safely in the env file and loaded using python-dotenv.

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Step-by-Step Setup

Step 1 — Clone the Course Repo

Clone the full course repository and navigate to this assignment's folder:

git clone https://github.com/osindy/NEIU335AI.git
cd NEIU335AI/assignments/assignment-01-api

Step 2 — Create a Virtual Environment

A virtual environment isolates this project's dependencies from your system Python.

Used: # Windows (Command Prompt)

Go to the assignment folder

cd NEIU335AI/assignments/api_assignment

Create virtual environment

python -m venv venv
venv\Scripts\activate

You should see (venv) at the start of your prompt — this confirms the environment is active.

Step 3 — Install Dependencies

pip install -r requirements.txt

Step 4 — Set Up Your API Key

Copy the example environment file and fill in your real API key:

copy .env.example .env

Open .env in any text editor and replace the placeholder:

MY_API_KEY=your_actual_api_key_here

Important: Never commit your .env file. It is covered by the repo's root .gitignore.

Step 5 — Run the Script

python starter.py

You should see formatted output in the terminal for each of the 3 API calls.

Sample Output

CALL 1

Machine learning enables computers to learn from data without explicit programming.

CALL 2

Supervised learning is a machine learning technique where an algorithm learns from labeled data.

CALL 3

User input: What day is it today?

Response: Today is Thursday.

Program finished successfully.