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import os
from typing import Iterator
import gradio as gr
from src.model import run
HF_PUBLIC = os.environ.get("HF_PUBLIC", False)
DEFAULT_SYSTEM_PROMPT = "You are Phoenix AI Healthcare. You are professional, you are polite, give only truthful information and are based on the Mistral-7B model from Mistral AI about Healtcare and Wellness. You can communicate in different languages equally well."
MAX_MAX_NEW_TOKENS = 4096
DEFAULT_MAX_NEW_TOKENS = 256
MAX_INPUT_TOKEN_LENGTH = 4000
DESCRIPTION = """
# [Mistral-7B](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)
"""
def clear_and_save_textbox(message: str) -> tuple[str, str]:
"""
Clear the textbox and save the input to a state variable.
:param message: The input message.
:return: A tuple of the empty string and the input message.
"""
return "", message
def display_input(
message: str, history: list[tuple[str, str]]
) -> list[tuple[str, str]]:
"""
Display the input message in the chat history.
:param message: The input message.
:param history: The chat history.
:return: The chat history with the input message appended.
"""
history.append((message, ""))
return history
def delete_prev_fn(
history: list[tuple[str, str]]) -> tuple[list[tuple[str, str]], str]:
"""
Delete the previous message from the chat history.
:param history: The chat history.
:return: The chat history with the last message removed
and the removed message.
"""
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]]]:
"""
Generate a response to the input message.
:param message: The input message.
:param history_with_input: The chat history with
the input message appended.
:param system_prompt: The system prompt.
:param max_new_tokens: The maximum number of tokens to generate.
:param temperature: The temperature.
:param top_p: The top-p (nucleus sampling) probability.
:param top_k: The top-k probability.
:return: An iterator over the chat history with
the generated response appended.
"""
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]]]:
"""
Process an example.
:param message: The input message.
:return: A tuple of the empty string and the chat history with the \
generated response appended.
"""
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:
"""
Check that the accumulated input is not too long.
:param message: The input message.
:param chat_history: The chat history.
:param system_prompt: The system prompt.
:return: None.
"""
input_token_length = len(message) + len(chat_history)
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="./styles/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="Playground")
with gr.Row():
textbox = gr.Textbox(
container=False,
show_label=False,
placeholder="Greetings, with what Healthcare/Wellness topic can I help you with today?",
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=5,
interactive=False,
)
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=0.1,
)
top_p = gr.Slider(
label="Top-p (nucleus sampling)",
minimum=0.05,
maximum=1.0,
step=0.05,
value=0.9,
)
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=32).launch(share=HF_PUBLIC, show_api=False) |