app.py

import gradio as gr
from huggingface_hub import InferenceClient

"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")


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


"""
System Prompt Modification for NLPToolkit Agent
"""
default_system_message = (
    "You are NLPToolkit Agent, an advanced natural language processing assistant. "
    "You specialize in tasks such as text summarization, sentiment analysis, text classification, "
    "entity recognition, and answering technical questions about NLP models and datasets. "
    "Assist users with clear, concise, and actionable outputs."
)

"""
Updated Gradio Interface
"""
demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(
            value=default_system_message, 
            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)"
        ),
    ],
)

# Run the app
demo.launch()