FreeFoundations · 25 min · Beginner
🤖

Intro to LLM APIs

How AI models receive and respond to requests

💡

What Is Intro to LLM APIs?

Simple overview · Real-world examples included

No experience needed for this one — this is the starting point for everything. We will build the simplest possible AI-powered app: a Java Spring Boot server that receives a message from you and sends it to ChatGPT (or Claude), then returns the AI's answer. Think of your app as a "middleman" — it sits between the user and the AI. By the end of this topic, you will have a real working API endpoint you can test from any browser or tool like Postman.

🎯 What You'll Learn

→How LLMs tokenize and process input
→Request/response structure of OpenAI & Claude APIs
→Build your first AI endpoint in Spring Boot
→Handle errors, timeouts and rate limits

🌍 Real-World Use Case

A customer service portal that routes messages using AI classification

📊 How It Works — Interactive Flowchart

Hover nodes for quick tip · Click to open detail · Press "Run Data Flow" to animate

Click any box to learn what it does
🧑‍💻
You
Send message
Step 1
⚙️
Spring Boot
Your server
Step 2
🔢
Tokenizer
Text → Numbers
Step 3
🌐
API Call
To OpenAI
Step 4
🤖
AI Model
Generates text
Step 5
✅
Response
Back to you
Step 6

🛠️ Step-by-Step Implementation

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0 / 6
01
Set up Spring Boot project
▾
💡 WHY AM I DOING THIS?

Spring Boot gives you a production-ready server in minutes. Without it you'd write hundreds of lines of boilerplate.

▶ WHAT HAPPENS IN THIS STEP

We create a new project using Spring Initializr with the Spring AI dependency.

📄 FILES TO CREATE / MODIFY
+pom.xml
+src/main/java/com/example/AiApplication.java
+src/main/resources/application.properties
📁 FOLDER STRUCTURE
ai-demo/
├── src/
│   ├── main/
│   │   ├── java/com/example/
│   │   │   ├── AiApplication.java
│   │   │   └── controller/
│   │   │       └── ChatController.java
│   │   └── resources/
│   │       └── application.properties
└── pom.xml
💻 CODE EXAMPLE
<!-- pom.xml -->
<dependency>
  <groupId>org.springframework.ai</groupId>
  <artifactId>spring-ai-openai-spring-boot-starter</artifactId>
</dependency>
⚠ COMMON MISTAKES
⚠Forgetting to add spring-ai BOM to dependencyManagement
⚠Using Java 8 instead of Java 17+
▶ HOW TO TEST
Run: mvn spring-boot:run — should see "Started AiApplication" in logs
✅ EXPECTED RESULT
Server starts on http://localhost:8080 with no errors
02
Configure OpenAI API key
The API key authenticates your app with OpenAI
▾
03
Create ChatClient bean
ChatClient is Spring AI's main interface to the LLM
▾
04
Build REST controller
The controller exposes your AI as an HTTP endpoint
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05
Add error handling
LLM APIs can fail — rate limits, network issues, invalid inputs
▾
06
Test with Postman
Testing manually confirms everything works end-to-end before building a frontend
▾

✍️ How to Write the Prompt for This Topic

System: "You are a helpful assistant." User: "Classify this message: {message}" — Start simple, then layer specifics.

🎯

Job Interview Prep

8 curated questions · 0 / 8 mastered
Click answers, then rate yourself to track progress
LEVEL:

💡 Don't memorise answers word-for-word. Understand the concept, then explain it in your own words using a real example from this topic's project — that's what impresses interviewers.

⚡ Live AI Demo

LIVE AI DEMO — CLAUDE HAIKUSign up for 3 free demos/day
0/500

📦 Clone & Run the Sample Project

📦
github.com / ai-dev-academy / ai-dev-academy-projects

01-intro-to-llm-apis

Hello AI — Spring Boot REST endpoint calling OpenAI

Spring Boot 3.xOpenAI APIMavenJava 17
⚡QUICK START — RUN IN 5 STEPS
1
Clone the full repo
git clone https://github.com/ai-dev-academy/ai-dev-academy-projects.git
2
Enter the topic folder
cd ai-dev-academy-projects/01-intro-to-llm-apis
3
Set up your API key
cp .env.example .env
# Then open .env and add your API key
4
Run the project
mvn spring-boot:run
5
Test the endpoint
curl -X POST http://localhost:8080/ai/chat \
  -H "Content-Type: application/json" \
  -d '"Hello, what is Intro to LLM APIs?"'
OPEN IN YOUR IDE
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