Spaces:
Runtime error
Runtime error
from __future__ import annotations | |
from typing import Iterable | |
import gradio as Gradio | |
from gradio.themes.utils import colors, fonts, sizes | |
from gradio.themes import Base | |
from llama_cpp import Llama | |
from huggingface_hub import hf_hub_download | |
hf_hub_download(repo_id="TheBloke/dolphin-2_6-phi-2-GGUF", filename="dolphin-2_6-phi-2.Q5_K_S.gguf", local_dir=".") | |
llm = Llama(model_path="./dolphin-2_6-phi-2.Q5_K_S.gguf", n_ctx=1024) | |
ins = '''<|im_start|>user | |
{question}<|im_end|> | |
<|im_start|>assistant | |
''' | |
class BlueTheme(Gradio.themes.Soft): | |
def __init__( | |
self, | |
*, | |
primary_hue: colors.Color | str = colors.purple, | |
secondary_hue: colors.Color | str = colors.blue, | |
neutral_hue: colors.Color | str = colors.neutral, | |
spacing_size: sizes.Size | str = sizes.spacing_md, | |
radius_size: sizes.Size | str = sizes.radius_md, | |
font: fonts.Font | |
| str | |
| Iterable[fonts.Font | str] = ( | |
fonts.GoogleFont("Space Grotesk"), | |
"ui-sans-serif", | |
"sans-serif", | |
), | |
font_mono: fonts.Font | |
| str | |
| Iterable[fonts.Font | str] = ( | |
fonts.GoogleFont("Space 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, | |
font=font, | |
font_mono=font_mono, | |
) | |
super().set( | |
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)", | |
block_shadow="*shadow_drop_lg", | |
button_shadow="*shadow_drop_lg", | |
input_background_fill="zinc", | |
input_border_color="*secondary_300", | |
input_shadow="*shadow_drop", | |
input_shadow_focus="*shadow_drop_lg", | |
) | |
custom_theme = BlueTheme() | |
def generate(instruction): | |
prompt = ins.format(question=instruction) | |
response = llm.create_completion(prompt, stream=True, stop=['<|im_start|>user', '<|im_end|>'], repeat_penalty=1.1) | |
result = "" | |
for output in response: | |
result += output['choices'][0]['text'] | |
yield result | |
examples = [ | |
"How do dogs bark?", | |
"Why are apples red?", | |
"How do I make a campfire?", | |
"Why do cats love to chirp at something?" | |
] | |
def process_example(args): | |
for x in generate(args): | |
pass | |
return x | |
css = ".generating {visibility: hidden}" | |
with Gradio.Blocks(theme=custom_theme, analytics_enabled=False, css=css) as demo: | |
with Gradio.Column(): | |
Gradio.Markdown( | |
""" # 𓄿 [Corvus] Dolphin-2.6 (Phi-2) | |
Type in the box below and click the button to generate answers to your most pressing questions! | |
""") | |
with Gradio.Tabs(): | |
with Gradio.Tab(label="Prompt"): | |
usr_prompt = Gradio.components.Textbox(placeholder="Why do cats meow?", label="Prompt", info="What things do you want to ask the chat assistant?"); | |
with Gradio.Tab(label="Configuration (disabled)"): | |
top_p = Gradio.components.Slider(value=0.4, maximum=1, interactive=True, label="Top-P (Nucleus sampling)", info="Represents the token diversity threshold for CogniForge."); | |
top_k = Gradio.components.Slider(value=40, maximum=100, interactive=True, label="Top-K sampling", info="Represents the token probability threshold for CogniForge."); | |
temp = Gradio.components.Slider(value=0.7, maximum=2, interactive=True, label="Temperature", info="Represents the creativity threshold for CogniForge."); | |
with Gradio.Group(): | |
output = Gradio.components.Textbox(value="", label="Output", info="Corvus' output"); | |
Gradio.Examples( | |
examples=examples, | |
inputs=[usr_prompt], | |
cache_examples=False, | |
fn=process_example, | |
outputs=[output], | |
); | |
submit = Gradio.Button("Generate", variant="primary") | |
submit.click(generate, inputs=[usr_prompt], outputs=[output], concurrency_limit=1) | |
demo.launch(debug=True) |