Conversational Ai Development Tutorials, Guides & Insights

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

# Load pre-trained model and tokenizer
model_name = "microsoft/DialoGPT-small"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# Initialize chat history
chat_history_ids = None

def chat_with_bot(user_input):
    global chat_history_ids

    # Encode the new user input, add the eos_token and return a tensor in Pytorch
    new_user_input_ids = tokenizer.encode(user_input + tokenizer.eos_token, return_tensors='pt')

    # Append the new user input tokens to the chat history
    bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1) if chat_history_ids is not None else new_user_input_ids

    # Generate a response
    chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id)

    # Decode the last response
    bot_response = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True)

    return bot_response

if __name__ == "__main__":
    print("Start chatting with the AI chatbot (type 'exit' to stop)!")
    while True:
        user_input = input("You: ")
        if user_input.lower() == "exit":
            break
        bot_response = chat_with_bot(user_input)
        print(f"Bot: {bot_response}")

Run the script in your terminal or command prompt: