⭐ Introduction

AI chatbots are everywhere — in websites, customer support, personal assistants, and automation tools.

The good news?
You can build your own chatbot in just a few minutes, even if you are a beginner.

This guide will show you step-by-step how to create a very simple AI chatbot using:
✔ Python
✔ Groq API (free & super fast)
✔ LangChain

You don’t need advanced coding skills.
Just basic Python is enough.

Prerequisites 

Before building your chatbot, make sure you have:

✔ Python installed

✔ Basic understanding of running .py files

✔ Groq API key (free)

✔ Any code editor (VS Code recommended)

That’s all you need.

🤖 What Is AI? 

AI (Artificial Intelligence) means teaching computers to think or respond like humans.
For example:

• You ask a question → AI understands

• It finds patterns from data

• It replies back intelligently

Chatbots are one of the most common and easiest forms of AI.

Lets get started 

Step 1: Get Your Groq API Key

Groq provides free, extremely fast  AI models.

Steps:

1. Go to groq.com

1. Create account  (Signup with Google)

       You will see this Home Page 

1. Click Developers 

2. Click Free API Key

Now you will See a Button Create API Key 

1. Click “Create Key”

2. Copy the key

You will paste it inside your Python file.

Now Open VS Code or Any Other IDE you have

Step 2: Install Required Packages

pip install langchain-groq langchain

🔍 What this does:

• langchain-groq → allows LangChain to communicate with Groq

• langchain → framework to handle chat messages and models

No extra configuration needed.

Stage 1 — Build the Most Simple Chatbot 

Now we build a very basic chatbot.

Step 3: Import Required Libraries

from langchain_groq import ChatGroq

🔍 Explanation:

• ChatGroq → connects Python to Groq’s AI models

Step 4: Add Your API Key

groq_api_key = "YOUR_API_KEY_HERE"

🔍 Why we do this:

The API key tells Groq who you are.
Without it, you cannot access the model.

You can store it in .env later, but for beginners, this is fine.

Step 5: Create the LLM Client

llm = ChatGroq(
    model="llama-3.1-8b-instant",
    api_key=groq_api_key
)

🔍 Explanation:

• llama-3.1-8b-instant → a fast and powerful model

• It gives very good results for simple chatbots

• This line creates the actual AI “brain” of your chatbot

• You can now call .invoke() to generate answers

Step 6: Send a User Question

user_input = "What is AI?"

🔍 Explanation:

• user_input stores the user question 

Step 7: Get Response From the Model

response = llm.invoke(user_input)
print("Bot:", response.content)

🔍 Explanation:

• .invoke(user_input) sends your messages to the Groq model

• Groq generates the response

• response.content contains the text reply

• print() shows it on the screen

• you will see output ("Hi How can i Assist You")

🎉 Your simple chatbot is ready!
You can ask anything and get instant answers.

That Was Super Easy Right ?

Now we Create A New Chat bot With System Prompt So it can Answer According to Your Need

Lets Go!

Stage 2 — Build a Personalized Chatbot - With System Prompt

System prompts tell the AI “how to behave”.

A system message can:
✔ make the bot friendly
✔ give it a personality
✔ turn it into your personal brand assistant
✔ restrict answers
✔ improve quality

We now add a custom system message representing Awais Shakeel ToolsMaverick.cloud

Step 1: Import SystemMessage

from langchain.schema import SystemMessage, HumanMessage

🔍 Why?

• SystemMessage defines bot behavior

• HumanMessage defines user messages

Both are required for personalized chatbots.

Step 2: Define the System Prompt

system_msg = SystemMessage(
    content=(
        """You are ToolsMaverick AI, an assistant representing **Awais Shakeel**, 
        an AI and Software Engineer and founder of ToolsMaverick.cloud. 
        Answer all queries using his background, experience, and work.
        Always be helpful, polite, and provide clear information with proper links. 
        Provide not so   long answer,  keep in short and clear."""
    )
)

🔍 Explanation:

• This defines the identity and tone of your chatbot

• The bot now behaves like a branded assistant

• It answers using your experience

Step 3: Add a User Question

user_input = "Who is Awais?"

Your Question That will Bot Response

Step 4: Combine System + User Messages

messages = [
    system_msg,
    HumanMessage(content=user_input)
]

🔍 Explanation:
The order is important:

System message (bot’s identity)

User message (question)

The AI reads them in sequence to generate a better reply.

Step 5: Get Response

response = llm.invoke(messages)

print("Bot:", response.content)

🔍 Explanation:

Same as before, but now the model uses the system message too.

The result will be a personalized answer, representing ToolsMaverick.cloud

🎉 Now you have a fully branded personal chatbot.

Where You Can Use This Chatbot 

⭐ Websites

• Customer support

• FAQ bot

• Personal assistant bot

⭐ Portfolio

• Make visitors chat with “AI Awais Shakeel” 

⭐ Mobile Apps

• Productivity bot

• AI learning bot

If you Want to Learn More About AI  We Have A detail RoadMap To Become AI Developer  

We Hope This Was Help Full

About ToolsMaverick.cloud

ToolsMaverick was created with a clear vision: to make essential online tools free, fast, and remarkably easy to use. In a world full of clutter and subscriptions, we believe that basic utilities should be accessible to all.

Toolsmaverick.cloud Offers 70+ Free Online Tools - AI, SEO, Developer, Generation , Convertion and Caluclation Tools.

Our goal is to empower students, professionals, and anyone who needs to perform a quick calculation or conversion without the hassle. No login. No ads. No cost. Just smart tools that work.

Visit: www.toolsmaverick.cloud