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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()
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