from pathlib import Path import gradio as gr import torch from modules import shared with open(Path(__file__).resolve().parent / '../css/main.css', 'r') as f: css = f.read() with open(Path(__file__).resolve().parent / '../css/chat.css', 'r') as f: chat_css = f.read() with open(Path(__file__).resolve().parent / '../css/main.js', 'r') as f: main_js = f.read() with open(Path(__file__).resolve().parent / '../css/chat.js', 'r') as f: chat_js = f.read() refresh_symbol = '\U0001f504' # 🔄 delete_symbol = '🗑️' save_symbol = '💾' theme = gr.themes.Default( font=['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' ) def list_model_elements(): elements = ['cpu_memory', 'auto_devices', 'disk', 'cpu', 'bf16', 'load_in_8bit', 'trust_remote_code', 'load_in_4bit', 'compute_dtype', 'quant_type', 'use_double_quant', 'wbits', 'groupsize', 'model_type', 'pre_layer', 'autogptq', 'threads', 'n_batch', 'no_mmap', 'mlock', 'n_gpu_layers', 'n_ctx', 'llama_cpp_seed'] for i in range(torch.cuda.device_count()): elements.append(f'gpu_memory_{i}') return elements def list_interface_input_elements(chat=False): elements = ['max_new_tokens', 'seed', 'temperature', 'top_p', 'top_k', 'typical_p', 'epsilon_cutoff', 'eta_cutoff', 'repetition_penalty', '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', 'add_bos_token', 'ban_eos_token', 'truncation_length', 'custom_stopping_strings', 'skip_special_tokens', 'preset_menu', 'stream'] if chat: elements += ['name1', 'name2', 'greeting', 'context', 'chat_prompt_size', 'chat_generation_attempts', 'stop_at_newline', 'mode', 'instruction_template', 'character_menu', 'name1_instruct', 'name2_instruct', 'context_instruct', 'turn_template', 'chat_style', 'chat-instruct_command'] elements += list_model_elements() return elements def gather_interface_values(*args): output = {} for i, element in enumerate(shared.input_elements): output[element] = args[i] 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(chat=shared.is_chat()) 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] class ToolButton(gr.Button, gr.components.FormComponent): """Small button with single emoji as text, fits inside gradio forms""" def __init__(self, **kwargs): super().__init__(variant="tool", **kwargs) def get_block_name(self): return "button" def create_refresh_button(refresh_component, refresh_method, refreshed_args, elem_id): 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 = ToolButton(value=refresh_symbol, elem_id=elem_id) refresh_button.click( fn=refresh, inputs=[], outputs=[refresh_component] ) return refresh_button def create_delete_button(**kwargs): return ToolButton(value=delete_symbol, **kwargs) def create_save_button(**kwargs): return ToolButton(value=save_symbol, **kwargs)