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import gradio as gr | |
from transformers import AutoModelForCausalLM, AutoTokenizer | |
# Load model and tokenizer | |
MODEL_NAME = "microsoft/phi-4" | |
model = AutoModelForCausalLM.from_pretrained(MODEL_NAME) | |
tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME) | |
def chatbot_response(user_input, chat_history=[]): | |
"""Generates a response from the chatbot model.""" | |
# Tokenize input and add chat history | |
input_ids = tokenizer.encode(user_input, return_tensors="pt") | |
# Generate response | |
output = model.generate(input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id) | |
response = tokenizer.decode(output[:, input_ids.shape[-1]:][0], skip_special_tokens=True) | |
# Update chat history | |
chat_history.append((user_input, response)) | |
return chat_history, "\n".join([f"You: {msg}\nBot: {res}" for msg, res in chat_history]) | |
# Gradio Interface | |
with gr.Blocks() as chatbot_ui: | |
gr.Markdown("## Chatbot Interface") | |
chat_history = gr.State([]) # Stores the chat history | |
with gr.Row(): | |
user_input = gr.Textbox(placeholder="Type your message here...", label="Your Input") | |
submit_button = gr.Button("Send") | |
with gr.Row(): | |
chat_display = gr.Textbox(label="Chat History", lines=20, interactive=False) | |
# Event listener | |
submit_button.click(chatbot_response, inputs=[user_input, chat_history], outputs=[chat_history, chat_display]) | |
chatbot_ui.launch() | |