app_old.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,
):
    system_message = "You are a Music Advisor Chatbot specializing in English pop music. You recommend upbeat tunes for energy boosts, soothing melodies for relaxation, and nostalgic songs for reflective moments. Share your mood or preferences, and let me suggest the perfect English pop track for you!"
    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

"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value = "You are a Music Advisor Chatbot specializing in English pop music. You recommend upbeat tunes for energy boosts, soothing melodies for relaxation, and nostalgic songs for reflective moments. Share your mood or preferences, and let me suggest the perfect English pop track for you!"),
        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)",
        ),
    ],

    examples = [ 
        ["I'm in the mood for some upbeat music to energize me."],
        ["Could you recommend a relaxing English pop song to unwind?"],
        ["What's a good English pop song for when I'm feeling nostalgic?"]
    ],
    title = 'English Pop Music Advisor Chatbot 🎵'
)


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