app.py

import gradio as gr
from huggingface_hub import InferenceClient

client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")

# Background effect from CodePen
background_html = """
<style>
body {
  margin: 0;
  padding: 0;
  overflow: hidden;
  background: #141414;
}

.canvas-container {
  position: absolute;
  top: 0;
  left: 0;
  right: 0;
  bottom: 0;
  z-index: -1;
  display: flex;
  justify-content: center;
  align-items: center;
}

canvas {
  display: block;
  width: 100%;
  height: 100%;
}
</style>

<div class="canvas-container">
  <canvas id="background-effect"></canvas>
</div>

<script>
const canvas = document.getElementById('background-effect');
const ctx = canvas.getContext('2d');

function resizeCanvas() {
  canvas.width = window.innerWidth;
  canvas.height = window.innerHeight;
}
window.addEventListener('resize', resizeCanvas);
resizeCanvas();

function randomInt(min, max) {
  return Math.floor(Math.random() * (max - min + 1)) + min;
}

function drawBackground() {
  ctx.clearRect(0, 0, canvas.width, canvas.height);

  for (let i = 0; i < 100; i++) {
    const x = randomInt(0, canvas.width);
    const y = randomInt(0, canvas.height);
    const radius = randomInt(1, 5);
    const r = randomInt(0, 255);
    const g = randomInt(0, 255);
    const b = randomInt(0, 255);
    const alpha = Math.random();

    ctx.beginPath();
    ctx.arc(x, y, radius, 0, Math.PI * 2, false);
    ctx.fillStyle = `rgba(${r}, ${g}, ${b}, ${alpha})`;
    ctx.fill();
  }

  requestAnimationFrame(drawBackground);
}

drawBackground();
</script>
"""

def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    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,
    ):
        token = message.choices[0].delta.content

        response += token
        yield response


with gr.Blocks() as demo:
    gr.HTML(background_html)  # Insert the background effect
    gr.ChatInterface(
        respond,
        additional_inputs=[
            gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
            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)",
            ),
        ],
    )

if __name__ == "__main__":
    demo.launch()