How to Build an AI Chatbot Using OpenAI and Streamlit

How to Build an AI Chatbot Using OpenAI and Streamlit — No ML Required

Have you ever wanted to build your own AI chatbot without diving deep into machine learning or writing frontend code?

Good news: In 2025, it's not only possible — it's actually fun. In this tutorial, I'll walk you through building a fully functional chatbot using OpenAI’s GPT-4-turbo and Streamlit, a Python framework that makes web apps dead simple.

Why This Guide?

AI chatbots are being used for:

24/7 customer support
Internal helpdesk tools
AI-powered learning assistants
Lead qualification bots

With the right tools, you can build your own version — even if you’re new to AI.

Tools You'll Need

Python 3.10+
OpenAI API key
streamlit for the UI
dotenv for secret management
Basic Python knowledge (if, functions, pip)

Step-by-Step Walkthrough

Step 1: Set up your environment

pip install openai streamlit python-dotenv

Create a .env file and store your OpenAI key:

OPENAI_API_KEY=your_openai_api_key_here

Step 2: Write the basic chatbot logic

import openai
import streamlit as st
from dotenv import load_dotenv
import os

load_dotenv()
openai.api_key = os.getenv("OPENAI_API_KEY")

def generate_response(prompt):
    response = openai.ChatCompletion.create(
        model="gpt-4",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": prompt}
        ]
    )
    return response["choices"][0]["message"]["content"]

Step 3: Build the chat UI with Streamlit

st.set_page_config(page_title="AI Chatbot", layout="wide")
st.title("🤖 Build Your Own AI Chatbot")

if "chat_history" not in st.session_state:
    st.session_state.chat_history = []

user_input = st.text_input("You:", "Hello, how are you?")

if st.button("Send") and user_input:
    with st.spinner("Thinking..."):
        response = generate_response(user_input)
        st.session_state.chat_history.append(("You", user_input))
        st.session_state.chat_history.append(("Bot", response))

for sender, message in st.session_state.chat_history:
    st.markdown(f"**{sender}:** {message}")

Step 4: Add extra features

Sidebar with OpenAI key input

Chat reset button

Custom system prompt to change the bot’s personality

Want More?

You can upgrade your chatbot with:

Memory using vector databases (Weaviate, ChromaDB)
LangChain for advanced flows
Authentication and multi-user logs
Deploy to Streamlit Cloud or Hugging Face Spaces

Real-World Use Cases

Customer support
Personal tutors
Internal document search
Lead qualification bots

Full Tutorial + Code

👉 I’ve written the complete, detailed version of this guide (with deployment steps, design visuals, and schema):

🔗 Read the full guide here
👋 Connect With Me

I'm the CTO of Zestminds, where we help startups and enterprises build custom AI solutions using OpenAI, LangChain, and FastAPI.

If you found this helpful, leave a 💬 or let me know what you'd build with this!

How to Build an AI Chatbot Using OpenAI and Streamlit