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import gradio as gr
from huggingface_hub import InferenceClient
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
def respond(message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p, backend):
# Force the AI to generate a website with index.html and specified backend
forced_instruction = f"""
You must generate a complete website structure including at least an index.html.
Use the following backend structure: {backend}.
Only use {backend} relevant code and structure, and don't include any other type.
"""
system_message = forced_instruction + "\n\n" + system_message
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
demo = gr.ChatInterface(
fn=respond,
additional_inputs=[
gr.Textbox(value="You are a helpful assistant.", 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)"),
gr.Dropdown(choices=["Flask", "Static", "Node.js"], value="Static", label="Website Backend"),
],
title="WebGen AI",
description="Ask the AI to build a website with a specific backend (Flask, Static, or Node.js). It will always include index.html.",
)
if __name__ == "__main__":
demo.launch() |