app.py

import gradio as gr
from huggingface_hub import InferenceClient

# Initialize the Inference Client
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")

def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    system_message = system_message or "You are a friendly Python code writing Chatbot. Assist with Python programming tasks, debugging, and code optimization. Provide solutions for Python-related queries, help with libraries, algorithms, and best practices, and generate clean, efficient code for various applications."
    
    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


def clear_chat():
    return [], ""

# Chatbot Interface
demo = gr.Interface(
    fn=respond,
    inputs=[
        gr.Textbox(value="You are a friendly Python code writing Chatbot. Assist with Python programming tasks, debugging, and code optimization. Provide solutions for Python-related queries, help with libraries, algorithms, and best practices, and generate clean, efficient code for various applications.", label="System message"),
        gr.Textbox(placeholder="Enter your message here...", label="User Input", 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)"),
    ],
    outputs=[
        gr.Chatbot(label="Chat History"),
        gr.Textbox(label="Current Response", placeholder="Chatbot will reply here...", interactive=False)
    ],
    live=True,
    allow_flagging="never",  # Disable flagging
    layout="vertical",
    theme="huggingface",  # Optionally, set a different theme
)

# Add additional features to the interface
with demo:
    gr.Button("Clear Chat", elem_id="clear-chat").click(clear_chat, outputs=["chatbot", "textbox"])

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