Creating a Generative AI Chatbot with Python

AI models have become incredibly popular in the development of chatbots. With Python, it's easy to create such a chatbot using deep learning techniques and libraries like transformers, TensorFlow, and PyTorch. In this article, we’ll guide you step by step to build a simple generative AI chatbot using Python.

Why we use a AI Chatbot with Python?
Using an AI chatbot with Python offers several advantages, particularly in the areas of simplicity, flexibility, and access to powerful machine learning frameworks.

• First step to start with ai chatbot development Install the necessary dependencies

pip install transformers torch

Install virtualenv in console if you don’t have it already:

pip install virtualenv

• Create a virtual environment

virtualenv chatbot-env

• We need Activate the environment. I use Windows

chatbot-env\Scripts\activate

• Importing Required Libraries

from transformers import GPT2LMHeadModel, GPT2Tokenizer
import torch

• Loading Pre-trained GPT model

model_name = "gpt2"
model = GPT2LMHeadModel.from_pretrained(model_name)
tokenizer = GPT2Tokenizer.from_pretrained(model_name)

model.eval()

• Creating the Chatbot’s Response Generator

def generate_response(user_input):

    inputs = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors="pt")

    outputs = model.generate(inputs, max_length=150, num_return_sequences=1, no_repeat_ngram_size=2, temperature=0.7)

    response = tokenizer.decode(outputs[0], skip_special_tokens=True)

    return response

• Building the Chatbot Interface.

Finally, we’ll create a simple loop where the user can input text, and the chatbot will generate a response.

print("Hello! I am your chatbot. Type 'quit' to exit.")

while True:
    user_input = input("You: ")

    if user_input.lower() == "quit":
        break

    response = generate_response(user_input)
    print("Chatbot: ", response)

• Finally Testing the Chatbot!!

python chatbot.py

Conclusions
We've shown you how to create a simple generative AI chatbot using Python. The chatbot uses a pre-trained model to generate responses based on user input. With some fine-tuning and improvements, you can create a more sophisticated and context-aware chatbot. Chatbots like this one can be used in a variety of applications, such as customer service, education, and entertainment.