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import gradio as gr
from huggingface_hub import InferenceClient
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
def respond(message, history, system_message, max_tokens, temperature, top_p):
messages = [{"role": "system", "content": system_message}]
for user, assistant in history:
if user:
messages.append({"role": "user", "content": user})
if assistant:
messages.append({"role": "assistant", "content": assistant})
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,
):
token = message.choices[0].delta.content
response += token
yield response
# Custom CSS for improved visual appeal
custom_css = """
body {
background-color: #f0f4f8;
font-family: 'Arial', sans-serif;
}
.gradio-container {
max-width: 800px !important;
margin: auto;
padding: 20px;
border-radius: 15px;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
background-color: white;
}
.chat-window {
border-radius: 10px;
border: 1px solid #e0e0e0;
}
.chat-message {
padding: 10px 15px;
border-radius: 8px;
margin: 5px 0;
}
.user-message {
background-color: #e3f2fd;
}
.bot-message {
background-color: #f1f8e9;
}
"""
# Create the ChatInterface with custom styling
demo = gr.ChatInterface(
respond,
additional_inputs=[
gr.Textbox(value="You are a friendly Chatbot.", label="System Message", lines=2),
gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max New Tokens"),
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (Nucleus Sampling)"),
],
title="Enhanced AI Chatbot",
description="Engage in a conversation with an AI powered by the Zephyr-7b-beta model.",
theme="soft",
css=custom_css,
examples=[
["Tell me a short story about a robot learning to paint."],
["What are the main challenges in space exploration?"],
["Explain quantum computing to a 10-year-old."]
],
)
if __name__ == "__main__":
demo.launch() |