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import copy
from pathlib import Path
import gradio as gr
import torch
import yaml
from transformers import is_torch_xpu_available
from modules import shared
with open(Path(__file__).resolve().parent / '../css/NotoSans/stylesheet.css', 'r') as f:
css = f.read()
with open(Path(__file__).resolve().parent / '../css/main.css', 'r') as f:
css += f.read()
with open(Path(__file__).resolve().parent / '../js/main.js', 'r') as f:
js = f.read()
with open(Path(__file__).resolve().parent / '../js/save_files.js', 'r') as f:
save_files_js = f.read()
with open(Path(__file__).resolve().parent / '../js/switch_tabs.js', 'r') as f:
switch_tabs_js = f.read()
with open(Path(__file__).resolve().parent / '../js/show_controls.js', 'r') as f:
show_controls_js = f.read()
refresh_symbol = '🔄'
delete_symbol = '🗑️'
save_symbol = '💾'
theme = gr.themes.Default(
font=['Noto Sans', 'Helvetica', 'ui-sans-serif', 'system-ui', 'sans-serif'],
font_mono=['IBM Plex Mono', 'ui-monospace', 'Consolas', 'monospace'],
).set(
border_color_primary='#c5c5d2',
button_large_padding='6px 12px',
body_text_color_subdued='#484848',
background_fill_secondary='#eaeaea'
)
if Path("notification.mp3").exists():
audio_notification_js = "document.querySelector('#audio_notification audio')?.play();"
else:
audio_notification_js = ""
def list_model_elements():
elements = [
'loader',
'filter_by_loader',
'cpu_memory',
'auto_devices',
'disk',
'cpu',
'bf16',
'load_in_8bit',
'trust_remote_code',
'use_fast',
'use_flash_attention_2',
'load_in_4bit',
'compute_dtype',
'quant_type',
'use_double_quant',
'wbits',
'groupsize',
'model_type',
'pre_layer',
'triton',
'desc_act',
'no_inject_fused_attention',
'no_inject_fused_mlp',
'no_use_cuda_fp16',
'disable_exllama',
'cfg_cache',
'no_flash_attn',
'cache_8bit',
'threads',
'threads_batch',
'n_batch',
'no_mmap',
'mlock',
'no_mul_mat_q',
'n_gpu_layers',
'tensor_split',
'n_ctx',
'llama_cpp_seed',
'gpu_split',
'max_seq_len',
'compress_pos_emb',
'alpha_value',
'rope_freq_base',
'numa',
'logits_all',
]
if is_torch_xpu_available():
for i in range(torch.xpu.device_count()):
elements.append(f'gpu_memory_{i}')
else:
for i in range(torch.cuda.device_count()):
elements.append(f'gpu_memory_{i}')
return elements
def list_interface_input_elements():
elements = [
'max_new_tokens',
'auto_max_new_tokens',
'max_tokens_second',
'seed',
'temperature',
'temperature_last',
'top_p',
'min_p',
'top_k',
'typical_p',
'epsilon_cutoff',
'eta_cutoff',
'repetition_penalty',
'presence_penalty',
'frequency_penalty',
'repetition_penalty_range',
'encoder_repetition_penalty',
'no_repeat_ngram_size',
'min_length',
'do_sample',
'penalty_alpha',
'num_beams',
'length_penalty',
'early_stopping',
'mirostat_mode',
'mirostat_tau',
'mirostat_eta',
'grammar_string',
'negative_prompt',
'guidance_scale',
'add_bos_token',
'ban_eos_token',
'custom_token_bans',
'truncation_length',
'custom_stopping_strings',
'skip_special_tokens',
'stream',
'tfs',
'top_a',
]
# Chat elements
elements += [
'textbox',
'start_with',
'character_menu',
'history',
'name1',
'name2',
'greeting',
'context',
'mode',
'instruction_template',
'name1_instruct',
'name2_instruct',
'context_instruct',
'system_message',
'custom_system_message',
'turn_template',
'chat_style',
'chat-instruct_command',
]
# Notebook/default elements
elements += [
'textbox-notebook',
'textbox-default',
'output_textbox',
'prompt_menu-default',
'prompt_menu-notebook',
]
# Model elements
elements += list_model_elements()
return elements
def gather_interface_values(*args):
output = {}
for i, element in enumerate(list_interface_input_elements()):
output[element] = args[i]
if not shared.args.multi_user:
shared.persistent_interface_state = output
return output
def apply_interface_values(state, use_persistent=False):
if use_persistent:
state = shared.persistent_interface_state
elements = list_interface_input_elements()
if len(state) == 0:
return [gr.update() for k in elements] # Dummy, do nothing
else:
return [state[k] if k in state else gr.update() for k in elements]
def save_settings(state, preset, instruction_template, extensions, show_controls):
output = copy.deepcopy(shared.settings)
exclude = ['name2', 'greeting', 'context', 'turn_template']
for k in state:
if k in shared.settings and k not in exclude:
output[k] = state[k]
output['preset'] = preset
output['prompt-default'] = state['prompt_menu-default']
output['prompt-notebook'] = state['prompt_menu-notebook']
output['character'] = state['character_menu']
output['instruction_template'] = instruction_template
output['default_extensions'] = extensions
output['seed'] = int(output['seed'])
output['show_controls'] = show_controls
return yaml.dump(output, sort_keys=False, width=float("inf"))
def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_class, interactive=True):
"""
Copied from https://github.com/AUTOMATIC1111/stable-diffusion-webui
"""
def refresh():
refresh_method()
args = refreshed_args() if callable(refreshed_args) else refreshed_args
for k, v in args.items():
setattr(refresh_component, k, v)
return gr.update(**(args or {}))
refresh_button = gr.Button(refresh_symbol, elem_classes=elem_class, interactive=interactive)
refresh_button.click(
fn=refresh,
inputs=[],
outputs=[refresh_component]
)
return refresh_button
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