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import gradio as gr
from huggingface_hub import InferenceClient
import time
# Inference client setup
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
# Global flag to handle cancellation
stop_inference = False
def respond(
message,
history: list[tuple[str, str]],
system_message,
max_tokens,
temperature,
top_p,
use_local_model,
):
global stop_inference
stop_inference = False # Reset cancellation flag
if use_local_model:
# Simulate local inference
time.sleep(2) # simulate a delay
response = "This is a response from the local model."
history.append((message, response))
yield history
else:
# API-based inference
messages = [{"role": "system", "content": system_message}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
response = ""
for message in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
if stop_inference:
history.append((message, "Inference cancelled."))
yield history
break
token = message.choices[0].delta.content
response += token
history.append((message, response))
yield history
def cancel_inference():
global stop_inference
stop_inference = True
# Custom CSS for a fancy look
custom_css = """
#main-container {
background-color: #f0f0f0;
font-family: 'Arial', sans-serif;
}
.gradio-container {
max-width: 700px;
margin: 0 auto;
padding: 20px;
background: white;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
border-radius: 10px;
}
.gr-button {
background-color: #4CAF50;
color: white;
border: none;
border-radius: 5px;
padding: 10px 20px;
cursor: pointer;
transition: background-color 0.3s ease;
}
.gr-button:hover {
background-color: #45a049;
}
.gr-slider input {
color: #4CAF50;
}
.gr-chat {
font-size: 16px;
}
#title {
text-align: center;
font-size: 2em;
margin-bottom: 20px;
color: #333;
}
"""
# Define the interface
with gr.Blocks(css=custom_css) as demo:
gr.Markdown("<h1 style='text-align: center;'>🌟 Fancy AI Chatbot 🌟</h1>")
gr.Markdown("Interact with the AI chatbot using customizable settings below.")
with gr.Row():
system_message = gr.Textbox(value="You are a friendly Chatbot.", label="System message", interactive=True)
use_local_model = gr.Checkbox(label="Use Local Model", value=False)
with gr.Row():
max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
chat_history = gr.Chatbot(label="Chat")
user_input = gr.Textbox(show_label=False, placeholder="Type your message here...")
cancel_button = gr.Button("Cancel Inference", variant="danger")
def chat_fn(message, history):
return respond(
message,
history,
system_message.value,
max_tokens.value,
temperature.value,
top_p.value,
use_local_model.value,
)
user_input.submit(chat_fn, [user_input, chat_history], chat_history)
cancel_button.click(cancel_inference)
if __name__ == "__main__":
demo.launch(share=True)
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