In this post, I explore how to build the same AI-powered chat app in Python, TypeScript, and Java using LangChain, LangChain.js, and LangChain4j. If you’re deciding how to bring AI into your stack, this guide will help you understand trade-offs and developer experience across ecosystems.
Why This Matters
AI chat applications are becoming central to digital experiences. They support customer service, internal tools, and user engagement. Whether you’re a Python data scientist, a TypeScript full-stack developer, or a Java enterprise engineer, LLMs are transforming your landscape.
Fortunately, frameworks like LangChain (Python), LangChain.js (TypeScript), and LangChain4j (Java) now make it easier to integrate LLMs without starting from scratch.
One Chat App, Three Languages
I built a basic chat app in each language using their respective LangChain implementation. The goal was to compare developer experience, language fit, and production readiness.
Python (3.12) + LangChain
from langchain_openai import ChatOpenAI
chat_model = ChatOpenAI(model="gpt-4o", temperature=0.7, api_key="YOUR_OPENAI_API_KEY")
while True:
user_input = input("You: ")
if user_input.lower() in ["exit", "quit"]:
break
response = chat_model.invoke(user_input)
print(f"AI: {response.content}")
Takeaway
Python offers the most seamless and concise development experience. It is ideal for fast prototyping and experimentation.
TypeScript () + LangChain.js
import { ChatOpenAI } from "@langchain/openai";
import readline from "readline";
const chatModel = new ChatOpenAI({
openAIApiKey: process.env.OPENAI_API_KEY,
model: "gpt-4o",
temperature: 0.7,
});
const rl = readline.createInterface({ input: process.stdin, output: process.stdout });
function promptUser() {
rl.question("You: ", async (input) => {
if (input.toLowerCase() === "exit" || input.toLowerCase() === "quit") {
rl.close();
return;
}
const response = await chatModel.invoke(input);
console.log(`AI: ${response.content}`);
promptUser();
});
}
promptUser();
Takeaway
TypeScript is a great fit for web-first and full-stack developers. The async structure aligns well with modern web development, and the LangChain.js ecosystem is growing rapidly.
Java (17) + LangChain4j
import dev.langchain4j.model.chat.ChatLanguageModel;
import dev.langchain4j.model.openai.OpenAiChatModel;
import java.util.Scanner;
public class BasicChatApp {
public static void main(String[] args) {
ChatLanguageModel model = OpenAiChatModel.builder()
.apiKey(System.getenv("OPENAI_API_KEY"))
.modelName("gpt-4o")
.temperature(0.7)
.build();
Scanner scanner = new Scanner(System.in);
while (true) {
System.out.print("You: ");
String input = scanner.nextLine();
if (input.equalsIgnoreCase("exit") || input.equalsIgnoreCase("quit")) break;
String response = model.chat(input);
System.out.println("AI: " + response);
}
}
}
Takeaway
Java with LangChain4j is designed for enterprise environments. It offers strong typing and structure, making it a solid choice for scalable, production-grade systems.
Side-by-Side Comparison
| Feature | Python (LangChain) | TypeScript (LangChain.js) | Java (LangChain4j) |
|---|---|---|---|
| Ease of Setup | Easiest | Moderate | Most Complex |
| Best Use Case | Prototyping, research | Web apps, full-stack | Enterprise backends |
| Ecosystem Maturity | Most mature | Rapidly growing | Evolving |
| Code Verbosity | Concise | Concise with async | Verbose and structured |
Strategic Insights
- If you are working in a startup or a research lab, Python is the fastest way to test ideas and iterate quickly.
- For web and cross-platform products, TypeScript provides excellent alignment with frontend and serverless workflows.
- In regulated or large-scale enterprise systems, Java continues to be a reliable foundation. LangChain4j brings modern AI capabilities into that world.
All three ecosystems now offer viable paths to LLM integration. Choose the one that aligns with your team’s strengths and your system’s goals.
What Do You Think?
Which tech stack do you prefer for building AI applications?
Have you tried LangChain or LangChain4j in your projects?
I’d love to hear your thoughts or questions in the comments.
D Curious Tech 