app.py

import deepsparse
from transformers import TextIteratorStreamer
from threading import Thread
import time
import gradio as gr
from typing import Tuple, List

deepsparse.cpu.print_hardware_capability()

MODEL_PATH = "hf:mgoin/TinyStories-1M-deepsparse"

DESCRIPTION = f"""
# {MODEL_PATH} running on DeepSparse
"""

MAX_MAX_NEW_TOKENS = 2048
DEFAULT_MAX_NEW_TOKENS = 512

# Setup the engine
pipe = deepsparse.Pipeline.create(
    task="text-generation",
    model_path=MODEL_PATH,
    sequence_length=MAX_MAX_NEW_TOKENS,
    prompt_sequence_length=16,
)


def clear_and_save_textbox(message: str) -> Tuple[str, str]:
    return "", message


def display_input(
    message: str, history: List[Tuple[str, str]]
) -> List[Tuple[str, str]]:
    history.append((message, ""))
    return history


def delete_prev_fn(history: List[Tuple[str, str]]) -> Tuple[List[Tuple[str, str]], str]:
    try:
        message, _ = history.pop()
    except IndexError:
        message = ""
    return history, message or ""


with gr.Blocks(css="style.css") as demo:
    gr.Markdown(DESCRIPTION)

    with gr.Group():
        chatbot = gr.Chatbot(label="Chatbot")
        with gr.Row():
            textbox = gr.Textbox(
                container=False,
                show_label=False,
                placeholder="Type a message...",
                scale=10,
            )
            submit_button = gr.Button("Submit", variant="primary", scale=1, min_width=0)

    with gr.Row():
        retry_button = gr.Button("🔄  Retry", variant="secondary")
        undo_button = gr.Button("↩️ Undo", variant="secondary")
        clear_button = gr.Button("🗑️  Clear", variant="secondary")

    saved_input = gr.State()

    gr.Examples(
        examples=["Once upon a time"],
        inputs=[textbox],
    )

    max_new_tokens = gr.Slider(
        label="Max new tokens",
        minimum=1,
        maximum=MAX_MAX_NEW_TOKENS,
        step=1,
        value=DEFAULT_MAX_NEW_TOKENS,
    )
    temperature = gr.Slider(
        label="Temperature",
        minimum=0.1,
        maximum=4.0,
        step=0.1,
        value=1.0,
    )

    # Generation inference
    def generate(message, history, max_new_tokens: int, temperature: float):        
        generation_config = {"max_new_tokens": max_new_tokens, "temperature": temperature}
        inference = pipe(sequences=message, streaming=True, **generation_config)
        for token in inference:
            history[-1][1] += token.generations[0].text
            yield history

        print(pipe.timer_manager)

    # Hooking up all the buttons
    textbox.submit(
        fn=clear_and_save_textbox,
        inputs=textbox,
        outputs=[textbox, saved_input],
        api_name=False,
        queue=False,
    ).then(
        fn=display_input,
        inputs=[saved_input, chatbot],
        outputs=chatbot,
        api_name=False,
        queue=False,
    ).success(
        generate,
        inputs=[saved_input, chatbot, max_new_tokens, temperature],
        outputs=[chatbot],
        api_name=False,
    )

    submit_button.click(
        fn=clear_and_save_textbox,
        inputs=textbox,
        outputs=[textbox, saved_input],
        api_name=False,
        queue=False,
    ).then(
        fn=display_input,
        inputs=[saved_input, chatbot],
        outputs=chatbot,
        api_name=False,
        queue=False,
    ).success(
        generate,
        inputs=[saved_input, chatbot, max_new_tokens, temperature],
        outputs=[chatbot],
        api_name=False,
    )

    retry_button.click(
        fn=delete_prev_fn,
        inputs=chatbot,
        outputs=[chatbot, saved_input],
        api_name=False,
        queue=False,
    ).then(
        fn=display_input,
        inputs=[saved_input, chatbot],
        outputs=chatbot,
        api_name=False,
        queue=False,
    ).then(
        generate,
        inputs=[saved_input, chatbot, max_new_tokens, temperature],
        outputs=[chatbot],
        api_name=False,
    )

    undo_button.click(
        fn=delete_prev_fn,
        inputs=chatbot,
        outputs=[chatbot, saved_input],
        api_name=False,
        queue=False,
    ).then(
        fn=lambda x: x,
        inputs=[saved_input],
        outputs=textbox,
        api_name=False,
        queue=False,
    )

    clear_button.click(
        fn=lambda: ([], ""),
        outputs=[chatbot, saved_input],
        queue=False,
        api_name=False,
    )

demo.queue().launch()