DAY 2

Groq API 🔌🤖⚡

Create a free Groq account, get your API key, and make your first real AI call in Python.

⏱ 30 mins
⚡ +100 XP

Day 2 — Connect to Groq API

AI Agent Course — RohithBuilds

Today you will create a free Groq account, get your API key, and make your first real AI call in Python.

Step 1 — Create a Free Groq Account

  1. Go to console.groq.com
  2. Click Sign Up
  3. Sign up with Google or Email
  4. Verify your email if asked

Step 2 — Get Your API Key

  1. After logging in click API Keys on the left sidebar
Groq console showing API Keys in the left sidebar
  1. Click Create API Key
  2. Give it a name — type ai-agent-course
Groq Create API Key dialog with name ai-agent-course
  1. Copy the key and save it somewhere safe
Groq API key displayed after creation

⚠️ Important

You will not see this key again after closing the window. Copy it now.

Step 3 — Save Your API Key Safely

Create a file called .env in your project folder. Open it in VS Code and add this line — replace the value with your actual key:

GROQ_API_KEY=paste_your_key_here
.env file open in VS Code with GROQ_API_KEY set

Also create a .gitignore file and add this so your key never gets pushed to GitHub:

.env

Step 4 — Load Your API Key

Run this code:

from dotenv import load_dotenv
import os

load_dotenv()

api_key = os.getenv("GROQ_API_KEY")

if api_key:
    print("API key loaded successfully")
    print(f"Key starts with: {api_key[:8]}...")
else:
    print("API key not found. Check your .env file.")
main.py with API key loading code in VS Code

Expected Output

Terminal showing API key loaded successfully 
API key loaded successfully
Key starts with: gsk_****

Step 5 — Connect to Groq

Run this code:

from groq import Groq

client = Groq(api_key=api_key)

print("Groq client ready")
Groq client initialization code in VS Code

Expected Output

Terminal showing Groq client ready

Step 6 — Make Your First AI Call

Run this code:

response = client.chat.completions.create(
    model="llama-3.3-70b-versatile",
    messages=[
        {"role": "user", "content": "Say hello and tell me what you can do in 3 bullet points."}
    ]
)

print(response.choices[0].message.content)
First AI call code in VS Code

Expected Output

You will see an AI-generated response like:

Terminal showing AI response with hello and bullet points

Step 7 — Understand the Response Object

Run this code:

response = client.chat.completions.create(
    model="llama-3.1-70b-versatile",
    messages=[
        {"role": "user", "content": "What is 2 + 2?"}
    ]
)

print("Model used:", response.model)
print("Tokens used:", response.usage.total_tokens)
print("Response:", response.choices[0].message.content)
Response object exploration code in VS Code

Expected Output

Terminal showing model name, tokens used, and AI response

Step 8 — Try Your Own Message

Change the message below to anything you want and run it. Try a few different things to get comfortable with the API.

# Change this message to anything you want
my_message = "Write a one line motivational quote for a developer building their first AI agent."

response = client.chat.completions.create(
    model="llama3-70b-8192",
    messages=[
        {"role": "user", "content": my_message}
    ]
)

print("You asked:", my_message)
print("\nAI replied:")
print(response.choices[0].message.content)

Step 9 — Build a Simple Helper Function

Instead of writing the full API call every time, wrap it in a function. You will use this pattern throughout the rest of the course.

def ask(question):
    response = client.chat.completions.create(
        model="llama3-70b-8192",
        messages=[
            {"role": "user", "content": question}
        ]
    )
    return response.choices[0].message.content


# Test the function with 3 different questions
print("Q1:", ask("What is Python in one sentence?"))
print()
print("Q2:", ask("What is an API in one sentence?"))
print()
print("Q3:", ask("What is Groq in one sentence?"))

Expected Output

Terminal showing responses for all 3 test questions

✅ Day 2 Complete

Here is what you accomplished today:

Key Takeaways

  • Groq account created ✅
  • API key saved in .env ✅
  • API key loaded in Python ✅
  • Groq client connected ✅
  • First real AI call made ✅
  • Response structure understood ✅
  • Helper function built ✅

What is Coming Tomorrow

On Day 3 you will:

  • Give your agent a name and personality using a system prompt
  • Add memory so it remembers the full conversation
  • Build an interactive chat loop in the terminal
  • Save the conversation to a JSON file

See you there! 🚀

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