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