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from typing import Iterator
import gradio as gr
import torch
from model import get_input_token_length, run
DEFAULT_SYSTEM_PROMPT = """\
You are a helpful, respectful and honest assistant with a deep knowledge of code and software design. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.\
"""
MAX_MAX_NEW_TOKENS = 1024
DEFAULT_MAX_NEW_TOKENS = 512
MAX_INPUT_TOKEN_LENGTH = 4000
DESCRIPTION = """
# StarCoder-base-1b-sft
This Space demonstrates model [StarCoder-base-1b-sft](https://huggingface.co./abacaj/starcoderbase-1b-sft) by anton Bacaj
"""
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 ''
def generate(
message: str,
history_with_input: list[tuple[str, str]],
system_prompt: str,
max_new_tokens: int,
temperature: float,
top_p: float,
top_k: int,
) -> Iterator[list[tuple[str, str]]]:
if max_new_tokens > MAX_MAX_NEW_TOKENS:
raise ValueError
history = history_with_input[:-1]
generator = run(message, history, system_prompt, max_new_tokens, temperature, top_p, top_k)
try:
first_response = next(generator)
yield history + [(message, first_response)]
except StopIteration:
yield history + [(message, '')]
for response in generator:
yield history + [(message, response)]
def process_example(message: str) -> tuple[str, list[tuple[str, str]]]:
generator = generate(message, [], DEFAULT_SYSTEM_PROMPT, 1024, 1, 0.95, 50)
for x in generator:
pass
return '', x
def check_input_token_length(message: str, chat_history: list[tuple[str, str]], system_prompt: str) -> None:
input_token_length = get_input_token_length(message, chat_history, system_prompt)
if input_token_length > MAX_INPUT_TOKEN_LENGTH:
raise gr.Error(f'The accumulated input is too long ({input_token_length} > {MAX_INPUT_TOKEN_LENGTH}). Clear your chat history and try again.')
with gr.Blocks(css='style.css') as demo:
gr.Markdown(DESCRIPTION)
gr.DuplicateButton(value='Duplicate Space for private use',
elem_id='duplicate-button')
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()
with gr.Accordion(label='Advanced options', open=False):
system_prompt = gr.Textbox(label='System prompt',
value=DEFAULT_SYSTEM_PROMPT,
lines=6)
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=0.2,
)
top_p = gr.Slider(
label='Top-p (nucleus sampling)',
minimum=0.05,
maximum=1.0,
step=0.05,
value=0.95,
)
top_k = gr.Slider(
label='Top-k',
minimum=1,
maximum=1000,
step=1,
value=10,
)
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,
).then(
fn=check_input_token_length,
inputs=[saved_input, chatbot, system_prompt],
api_name=False,
queue=False,
).success(
fn=generate,
inputs=[
saved_input,
chatbot,
system_prompt,
max_new_tokens,
temperature,
top_p,
top_k,
],
outputs=chatbot,
api_name=False,
)
button_event_preprocess = 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,
).then(
fn=check_input_token_length,
inputs=[saved_input, chatbot, system_prompt],
api_name=False,
queue=False,
).success(
fn=generate,
inputs=[
saved_input,
chatbot,
system_prompt,
max_new_tokens,
temperature,
top_p,
top_k,
],
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(
fn=generate,
inputs=[
saved_input,
chatbot,
system_prompt,
max_new_tokens,
temperature,
top_p,
top_k,
],
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(max_size=20).launch()
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