Build Your First Chatbot with LangChain + OpenAI

LLMs (Large Language Models) are transforming how we build tools, services, and developer experiences. And there’s no better way to dive in than by creating your own chatbot using LangChain and OpenAI.

We’ve officially kicked off our LLM Learning Series to help developers get hands-on with AI and build useful, real-world tools. 🚀

In this post, we’ll walk you through how to:

✅ Set up a LangChain project
✅ Connect to OpenAI’s API
✅ Read keys securely
✅ Build your first AI-powered chatbot

Let’s get started! 💬

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📦 Step 1: Project Setup

First, create a new Python project:

mkdir langchain-chatbot
cd langchain-chatbot
python -m venv venv
source venv/bin/activate  # or venv\Scripts\activate on Windows

Install the necessary dependencies:

pip install langchain openai python-dotenv

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🔐 Step 2: Store & Read API Keys

You’ll need an OpenAI API key.

Create a .env file:

OPENAI_API_KEY=your_openai_key_here

Then read the key securely in your Python script:

from dotenv import load_dotenv
import os

load_dotenv()
openai_api_key = os.getenv("OPENAI_API_KEY")

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🤖 Step 3: Connect to the OpenAI Model via LangChain

LangChain makes it easy to interface with LLMs. Here’s how to connect your code to OpenAI:

from langchain.llms import OpenAI

llm = OpenAI(openai_api_key=openai_api_key)

This gives you access to the llm() function, which can now generate responses based on prompts.

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💬 Step 4: Build Your First Chatbot

Here’s a basic chatbot loop that lets you have a simple conversation in your terminal:

def chatbot():
    print("🤖 Hello! Ask me anything (type 'exit' to quit)")

    while True:
        user_input = input("You: ")
        if user_input.lower() == 'exit':
            print("Bot: Goodbye!")
            break

        response = llm(user_input)
        print(f"Bot: {response}")

chatbot()

Now run your script:

python chatbot.py

🎉 You’ve just created your first AI chatbot using LangChain + OpenAI!

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🧠 What You’ve Learned So Far

By completing this short project, you now understand:

• How to set up a basic Python AI project

• How to securely read and use API keys

• How to use LangChain to connect with OpenAI models

• How to create a chatbot with minimal code

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🔜 What’s Next in the Series?

Coming up next, we’ll explore:

➡️ Prompt engineering techniques
➡️ Memory in LangChain (so your chatbot remembers context)
➡️ Connecting LangChain with external tools, APIs, and files
➡️ Deploying your chatbot as a web app

Follow the tag #LLMLearningSeries or subscribe to stay updated!
Let’s keep learning and building with AI — the possibilities are just getting started.

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📣 Want to collaborate or have questions?
DM me on Twitter/Instagram or comment below. Let’s connect and build the future of dev tools together!