Free LLM API for Beginners: Zero to Your First AI API Call in 10 Minutes

What Is an LLM API?

An API (Application Programming Interface) is a way for your code to talk to another service over the internet. An LLM API lets your code send text to an AI model and receive a response — programmatically, without using a web interface like ChatGPT.

Instead of typing in a chat box, you write code that sends a message and reads the reply. This lets you build apps, automate tasks, process data in bulk, and integrate AI into any software you write.

What You Need

• A free API key from FreeLLMKeys.com (takes 5 seconds — just copy it)
• Python 3.8+ or Node.js 18+ installed
• That is it

Option A — Python (Recommended for Beginners)

Install the library

pip install openai

Write your first AI call

Create a file called hello_ai.py and paste this:

from openai import OpenAI

# 1. Create the client — paste your key from FreeLLMKeys.com
client = OpenAI(
    base_url="https://aiapiv2.pekpik.com/v1",
    api_key="sk-paste-your-key-here"
)

# 2. Send a message to the AI
response = client.chat.completions.create(
    model="gpt-4o",                          # which AI model to use
    messages=[
        {"role": "user", "content": "What is Python used for?"}
    ]
)

# 3. Print the reply
print(response.choices[0].message.content)

Run it

python hello_ai.py

You should see GPT-4o's response printed in your terminal within a few seconds. That is your first AI API call.

Understanding What Just Happened

Let us break down the code line by line:

client = OpenAI(
    base_url="https://aiapiv2.pekpik.com/v1",   # WHERE to send the request
    api_key="sk-your-key"                         # PROOF that you're allowed to use it
)

response = client.chat.completions.create(
    model="gpt-4o",           # WHICH AI model to use
    messages=[                # The CONVERSATION so far
        {
            "role": "user",   # Who is speaking ("user" = you, "assistant" = AI, "system" = instructions)
            "content": "..."  # What is being said
        }
    ]
)

response.choices[0].message.content  # The AI's reply text

Option B — JavaScript / Node.js

npm install openai

// hello_ai.js
import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://aiapiv2.pekpik.com/v1",
  apiKey: "sk-paste-your-key-here"
});

const response = await client.chat.completions.create({
  model: "gpt-4o",
  messages: [
    { role: "user", content: "What is JavaScript used for?" }
  ]
});

console.log(response.choices[0].message.content);

node hello_ai.js

Option C — No Code (cURL)

If you just want to test the API without installing anything, use this terminal command:

curl https://aiapiv2.pekpik.com/v1/chat/completions   -H "Content-Type: application/json"   -H "Authorization: Bearer sk-your-key-here"   -d '{
    "model": "gpt-4o",
    "messages": [{"role": "user", "content": "Say hello!"}]
  }'

Making a Simple Conversation (Multi-Turn)

To have a back-and-forth conversation, add each message to the messages list:

messages = []  # Start with empty history

while True:
    user_input = input("You: ")
    if user_input.lower() == "quit":
        break

    messages.append({"role": "user", "content": user_input})

    response = client.chat.completions.create(
        model="gpt-4o",
        messages=messages
    )

    reply = response.choices[0].message.content
    messages.append({"role": "assistant", "content": reply})

    print(f"AI: {reply}\n")

Giving the AI a Personality (System Prompt)

response = client.chat.completions.create(
    model="gpt-4o",
    messages=[
        {
            "role": "system",     # System message sets the AI's behavior
            "content": "You are a pirate. Respond to everything in pirate speak."
        },
        {
            "role": "user",
            "content": "What time is it?"
        }
    ]
)
print(response.choices[0].message.content)
# "Arrr, I know not the exact hour, but the sun be high in the sky, matey!"

Switching Between AI Models

The only thing you change to use a different AI model is the model string:

model="gpt-4o"            # OpenAI — fast, great general purpose
model="claude-opus-4-7"   # Anthropic Claude — best writing quality
model="deepseek-chat"     # DeepSeek — best for coding
model="gemini-2.5-flash"  # Google — fastest, 1M token context
model="grok-4"            # xAI Grok — real-time knowledge

Everything else in your code stays exactly the same. That is the power of an OpenAI-compatible API — write once, run on any model.

What to Build Next

Now that you can make an API call, here are beginner-friendly projects to try:

• Text summarizer: Paste a long article, get a 3-sentence summary
• Email reply generator: Paste an email, get 3 draft reply options
• Language translator: Type in English, get output in any language
• Study quiz generator: Paste your notes, get 10 multiple choice questions
• Code explainer: Paste any code snippet, get a plain-English explanation

All of these are 20–30 lines of Python using the exact same pattern you just learned. Go build something.