JCai
add welcome sentence, change system prompt a little bit
844bf31
raw
history blame
8.11 kB
import gradio as gr
from huggingface_hub import InferenceClient
import torch
from transformers import pipeline
from typing import Iterable
from gradio.themes.base import Base
from gradio.themes.utils import colors, fonts, sizes
# Inference client setup
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
pipe = pipeline("text-generation", "microsoft/Phi-3-mini-4k-instruct", torch_dtype=torch.bfloat16, device_map="auto")
# Global flag to handle cancellation
stop_inference = False
def respond(
message,
history: list[tuple[str, str]],
system_message="You are a friendly and playful chatbot with a love for cats. Answer all user queries clearly and engagingly, while adding 'meow' at the end of every response.",
max_tokens=512,
temperature=0.7,
top_p=0.95,
use_local_model=False,
):
global stop_inference
stop_inference = False # Reset cancellation flag
# Initialize history if it's None
if history is None:
history = []
if use_local_model:
# local inference
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 output in pipe(
messages,
max_new_tokens=max_tokens,
temperature=temperature,
do_sample=True,
top_p=top_p,
):
if stop_inference:
response = "Inference cancelled."
yield history + [(message, response)]
return
token = output['generated_text'][-1]['content']
response += token
yield history + [(message, response)] # Yield history + new response
else:
# API-based inference
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_chunk in client.chat_completion(
messages,
max_tokens=max_tokens,
stream=True,
temperature=temperature,
top_p=top_p,
):
if stop_inference:
response = "Inference cancelled."
yield history + [(message, response)]
return
if stop_inference:
response = "Inference cancelled."
break
token = message_chunk.choices[0].delta.content
response += token
yield history + [(message, response)] # Yield history + new response
def cancel_inference():
global stop_inference
stop_inference = True
# Custom CSS for a fancy look
custom_css = """
#main-container {
background-color: url('file=image.ipg');
font-family: 'Arial', sans-serif;
}
.gradio-container {
max-width: 700px;
margin: 0 auto;
padding: 20px;
background: #FFC0CB;
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
border-radius: 10px;
}
.gr-button {
background-color: #4CAF50;
color: white;
border: none;
border-radius: 5px;
padding: 10px 20px;
cursor: pointer;
transition: background-color 0.3s ease;
}
.gr-button:hover {
background-color: #45a049;
}
.gr-slider input {
color: #4CAF50;
}
.gr-chat {
font-size: 16px;
}
#title {
text-align: center;
font-size: 2em;
margin-bottom: 20px;
color: #333;
}
"""
class UI_design(Base):
def __init__(
self,
*,
primary_hue: colors.Color | str = colors.emerald,
secondary_hue: colors.Color | str = colors.blue,
neutral_hue: colors.Color | str = colors.blue,
spacing_size: sizes.Size | str = sizes.spacing_md,
radius_size: sizes.Size | str = sizes.radius_md,
text_size: sizes.Size | str = sizes.text_lg,
font: fonts.Font
| str
| Iterable[fonts.Font | str] = (
fonts.GoogleFont("Quicksand"),
"ui-sans-serif",
"sans-serif",
),
font_mono: fonts.Font
| str
| Iterable[fonts.Font | str] = (
fonts.GoogleFont("IBM Plex Mono"),
"ui-monospace",
"monospace",
),
):
super().__init__(
primary_hue=primary_hue,
secondary_hue=secondary_hue,
neutral_hue=neutral_hue,
spacing_size=spacing_size,
radius_size=radius_size,
text_size=text_size,
font=font,
font_mono=font_mono,
)
super().set(
body_background_fill="repeating-linear-gradient(45deg, *primary_200, *primary_200 10px, *primary_50 10px, *primary_50 20px)",
body_background_fill_dark="repeating-linear-gradient(45deg, *primary_800, *primary_800 10px, *primary_900 10px, *primary_900 20px)",
button_primary_background_fill="linear-gradient(90deg, *primary_300, *secondary_400)",
button_primary_background_fill_hover="linear-gradient(90deg, *primary_200, *secondary_300)",
button_primary_text_color="white",
button_primary_background_fill_dark="linear-gradient(90deg, *primary_600, *secondary_800)",
slider_color="*secondary_300",
slider_color_dark="*secondary_600",
block_title_text_weight="600",
block_border_width="3px",
block_shadow="*shadow_drop_lg",
button_shadow="*shadow_drop_lg",
button_large_padding="32px",
)
ui_design = UI_design()
# Define the interface
# with gr.Blocks(theme=ui_design) as demo:
with gr.Blocks(css=custom_css) as demo:
gr.Markdown("<h1 style='text-align: center;'> 😸 Meowthamatical AI Chatbot 😸</h1>")
gr.Markdown(" Welcome to the Cat & Math Chatbot! Whether you're here to sharpen your math skills or just enjoy some cat-themed fun, we're excited to make learning a little more pawsome!!")
# with gr.Row():
# with gr.Column():
# with gr.Tabs() as input_tabs:
# with gr.Tab("Sketch"):
# input_sketchpad = gr.Sketchpad(type="pil", label="Sketch", layers=False)
#
# input_text = gr.Textbox(label="input your question")
#
# with gr.Row():
# # with gr.Column():
# # clear_btn = gr.ClearButton(
# # [input_sketchpad, input_text])
# with gr.Column():
# submit_btn = gr.Button("Submit", variant="primary")
with gr.Row():
# system_message = gr.Textbox(value="You are a cat and you love talking about and teaching math.", label="System message", interactive=True)
use_local_model = gr.Checkbox(label="Use Local Model", value=False)
# button_1 = gr.Button("Submit", variant="primary")
with gr.Row():
max_tokens = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
temperature = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
top_p = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
chat_history = gr.Chatbot(label="Chat")
user_input = gr.Textbox(show_label=False, placeholder="Type your message here...")
cancel_button = gr.Button("Cancel Inference", variant="danger")
# Adjusted to ensure history is maintained and passed correctly
user_input.submit(respond, [user_input, chat_history, max_tokens, temperature, top_p, use_local_model], chat_history)
cancel_button.click(cancel_inference)
if __name__ == "__main__":
demo.launch(share=False) # Remove share=True because it's not supported on HF Spaces