githubmirror/text-generation-webui

modules/ui_parameters.py
142 строки15 KB
oobabooga
Make user_data configurable: add --user-data-dir flag, auto-detect ../user_data
06 мар 2026, 06:31
06 мар 2026, 06:31e2548f6
from pathlib import Path

import gradio as gr

from modules import loaders, presets, shared, ui, ui_chat, utils
from modules.utils import gradio


def create_ui():
    mu = shared.args.multi_user
    with gr.Tab("Parameters", elem_id="parameters"):
        with gr.Tab("Generation"):
            with gr.Row():
                with gr.Column():
                    with gr.Row():
                        shared.gradio['preset_menu'] = gr.Dropdown(choices=utils.get_available_presets(), value=shared.settings['preset'], label='Preset', elem_classes='slim-dropdown')
                        ui.create_refresh_button(shared.gradio['preset_menu'], lambda: None, lambda: {'choices': utils.get_available_presets()}, 'refresh-button', interactive=not mu)
                        shared.gradio['save_preset'] = gr.Button('💾', elem_classes='refresh-button', interactive=not mu)
                        shared.gradio['delete_preset'] = gr.Button('🗑️', elem_classes='refresh-button', interactive=not mu)
                        shared.gradio['reset_preset'] = gr.Button('Restore preset', elem_classes='refresh-button', interactive=True)
                        shared.gradio['neutralize_samplers'] = gr.Button('Neutralize samplers', elem_classes='refresh-button', interactive=True)

                with gr.Column():
                    shared.gradio['filter_by_loader'] = gr.Dropdown(label="Filter by loader", choices=["All"] + list(loaders.loaders_and_params.keys()) if not shared.args.portable else ['llama.cpp'], value="All", elem_classes='slim-dropdown')

            with gr.Row():
                with gr.Column():
                    with gr.Row():
                        with gr.Column():
                            gr.Markdown('## Curve shape')
                            shared.gradio['temperature'] = gr.Slider(0.01, 5, value=shared.settings['temperature'], step=0.01, label='temperature')
                            shared.gradio['dynatemp_low'] = gr.Slider(0.01, 5, value=shared.settings['dynatemp_low'], step=0.01, label='dynatemp_low', visible=shared.settings['dynamic_temperature'])
                            shared.gradio['dynatemp_high'] = gr.Slider(0.01, 5, value=shared.settings['dynatemp_high'], step=0.01, label='dynatemp_high', visible=shared.settings['dynamic_temperature'])
                            shared.gradio['dynatemp_exponent'] = gr.Slider(0.01, 5, value=shared.settings['dynatemp_exponent'], step=0.01, label='dynatemp_exponent', visible=shared.settings['dynamic_temperature'])
                            shared.gradio['smoothing_factor'] = gr.Slider(0.0, 10.0, value=shared.settings['smoothing_factor'], step=0.01, label='smoothing_factor', info='Activates Quadratic Sampling.')
                            shared.gradio['smoothing_curve'] = gr.Slider(1.0, 10.0, value=shared.settings['smoothing_curve'], step=0.01, label='smoothing_curve', info='Adjusts the dropoff curve of Quadratic Sampling.')
                            shared.gradio['dynamic_temperature'] = gr.Checkbox(value=shared.settings['dynamic_temperature'], label='dynamic_temperature')

                            gr.Markdown('## Curve cutoff')
                            shared.gradio['min_p'] = gr.Slider(0.0, 1.0, value=shared.settings['min_p'], step=0.01, label='min_p')
                            shared.gradio['top_n_sigma'] = gr.Slider(0.0, 5.0, value=shared.settings['top_n_sigma'], step=0.01, label='top_n_sigma')
                            shared.gradio['top_p'] = gr.Slider(0.0, 1.0, value=shared.settings['top_p'], step=0.01, label='top_p')
                            shared.gradio['top_k'] = gr.Slider(0, 200, value=shared.settings['top_k'], step=1, label='top_k')
                            shared.gradio['typical_p'] = gr.Slider(0.0, 1.0, value=shared.settings['typical_p'], step=0.01, label='typical_p')
                            shared.gradio['xtc_threshold'] = gr.Slider(0, 0.5, value=shared.settings['xtc_threshold'], step=0.01, label='xtc_threshold', info='If 2 or more tokens have probability above this threshold, consider removing all but the last one.')
                            shared.gradio['xtc_probability'] = gr.Slider(0, 1, value=shared.settings['xtc_probability'], step=0.01, label='xtc_probability', info='Probability that the removal will actually happen. 0 disables the sampler. 1 makes it always happen.')
                            shared.gradio['epsilon_cutoff'] = gr.Slider(0, 9, value=shared.settings['epsilon_cutoff'], step=0.01, label='epsilon_cutoff')
                            shared.gradio['eta_cutoff'] = gr.Slider(0, 20, value=shared.settings['eta_cutoff'], step=0.01, label='eta_cutoff')
                            shared.gradio['tfs'] = gr.Slider(0.0, 1.0, value=shared.settings['tfs'], step=0.01, label='tfs')
                            shared.gradio['top_a'] = gr.Slider(0.0, 1.0, value=shared.settings['top_a'], step=0.01, label='top_a')

                            gr.Markdown('## Repetition suppression')
                            shared.gradio['dry_multiplier'] = gr.Slider(0, 5, value=shared.settings['dry_multiplier'], step=0.01, label='dry_multiplier', info='Set to greater than 0 to enable DRY. Recommended value: 0.8.')
                            shared.gradio['dry_allowed_length'] = gr.Slider(1, 20, value=shared.settings['dry_allowed_length'], step=1, label='dry_allowed_length', info='Longest sequence that can be repeated without being penalized.')
                            shared.gradio['dry_base'] = gr.Slider(1, 4, value=shared.settings['dry_base'], step=0.01, label='dry_base', info='Controls how fast the penalty grows with increasing sequence length.')
                            shared.gradio['repetition_penalty'] = gr.Slider(1.0, 1.5, value=shared.settings['repetition_penalty'], step=0.01, label='repetition_penalty')
                            shared.gradio['frequency_penalty'] = gr.Slider(0, 2, value=shared.settings['frequency_penalty'], step=0.05, label='frequency_penalty')
                            shared.gradio['presence_penalty'] = gr.Slider(0, 2, value=shared.settings['presence_penalty'], step=0.05, label='presence_penalty')
                            shared.gradio['encoder_repetition_penalty'] = gr.Slider(0.8, 1.5, value=shared.settings['encoder_repetition_penalty'], step=0.01, label='encoder_repetition_penalty')
                            shared.gradio['no_repeat_ngram_size'] = gr.Slider(0, 20, step=1, value=shared.settings['no_repeat_ngram_size'], label='no_repeat_ngram_size')
                            shared.gradio['repetition_penalty_range'] = gr.Slider(0, 4096, step=64, value=shared.settings['repetition_penalty_range'], label='repetition_penalty_range')

                        with gr.Column():
                            gr.Markdown('## Alternative sampling methods')
                            shared.gradio['penalty_alpha'] = gr.Slider(0, 5, value=shared.settings['penalty_alpha'], label='penalty_alpha', info='For Contrastive Search. do_sample must be unchecked.')
                            shared.gradio['guidance_scale'] = gr.Slider(-0.5, 2.5, step=0.05, value=shared.settings['guidance_scale'], label='guidance_scale', info='For CFG. 1.5 is a good value.')
                            shared.gradio['mirostat_mode'] = gr.Slider(0, 2, step=1, value=shared.settings['mirostat_mode'], label='mirostat_mode', info='mode=1 is for llama.cpp only.')
                            shared.gradio['mirostat_tau'] = gr.Slider(0, 10, step=0.01, value=shared.settings['mirostat_tau'], label='mirostat_tau')
                            shared.gradio['mirostat_eta'] = gr.Slider(0, 1, step=0.01, value=shared.settings['mirostat_eta'], label='mirostat_eta')
                            shared.gradio['adaptive_target'] = gr.Slider(0.0, 1.0, value=shared.settings['adaptive_target'], step=0.01, label='adaptive_target', info='Target probability for adaptive-p sampling. Tokens near this probability are favored. 0 disables.')
                            shared.gradio['adaptive_decay'] = gr.Slider(0.0, 0.99, value=shared.settings['adaptive_decay'], step=0.01, label='adaptive_decay', info='EMA decay rate for adaptive-p. Controls history window (~1/(1-decay) tokens). Default: 0.9.')

                            gr.Markdown('## Other options')
                            shared.gradio['do_sample'] = gr.Checkbox(value=shared.settings['do_sample'], label='do_sample')
                            shared.gradio['temperature_last'] = gr.Checkbox(value=shared.settings['temperature_last'], label='temperature_last', info='Moves temperature/dynamic temperature/quadratic sampling to the end of the sampler stack, ignoring their positions in "Sampler priority".')
                            shared.gradio['sampler_priority'] = gr.Textbox(value=shared.settings['sampler_priority'], lines=10, label='Sampler priority', info='Parameter names separated by new lines or commas.', elem_classes=['add_scrollbar'])
                            shared.gradio['dry_sequence_breakers'] = gr.Textbox(value=shared.settings['dry_sequence_breakers'], label='dry_sequence_breakers', info='Tokens across which sequence matching is not continued. Specified as a comma-separated list of quoted strings.')

                with gr.Column():
                    with gr.Row():
                        with gr.Column():
                            with gr.Blocks():
                                shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], value=shared.settings['max_new_tokens'], step=1, label='max_new_tokens', info='⚠️ Setting this too high can cause prompt truncation.')
                                shared.gradio['prompt_lookup_num_tokens'] = gr.Slider(value=shared.settings['prompt_lookup_num_tokens'], minimum=0, maximum=10, step=1, label='prompt_lookup_num_tokens', info='Activates Prompt Lookup Decoding.')
                                shared.gradio['max_tokens_second'] = gr.Slider(value=shared.settings['max_tokens_second'], minimum=0, maximum=20, step=1, label='Maximum tokens/second', info='To make text readable in real time.')

                            shared.gradio['auto_max_new_tokens'] = gr.Checkbox(value=shared.settings['auto_max_new_tokens'], label='auto_max_new_tokens', info='Expand max_new_tokens to the available context length.')
                            shared.gradio['ban_eos_token'] = gr.Checkbox(value=shared.settings['ban_eos_token'], label='Ban the eos_token', info='Forces the model to never end the generation prematurely.')
                            shared.gradio['add_bos_token'] = gr.Checkbox(value=shared.settings['add_bos_token'], label='Add the bos_token to the beginning of prompts', info='Only applies to text completion (notebook). In chat mode, templates control BOS tokens.')
                            shared.gradio['skip_special_tokens'] = gr.Checkbox(value=shared.settings['skip_special_tokens'], label='Skip special tokens', info='Some specific models need this unset.')
                            shared.gradio['stream'] = gr.Checkbox(value=shared.settings['stream'], label='Activate text streaming')
                            shared.gradio['static_cache'] = gr.Checkbox(value=shared.settings['static_cache'], label='Static KV cache', info='Use a static cache for improved performance.')

                        with gr.Column():
                            shared.gradio['truncation_length'] = gr.Number(precision=0, step=256, value=get_truncation_length(), label='Truncate the prompt up to this length', info='The leftmost tokens are removed if the prompt exceeds this length.')
                            shared.gradio['seed'] = gr.Number(value=shared.settings['seed'], label='Seed (-1 for random)')
                            shared.gradio['custom_system_message'] = gr.Textbox(value=shared.settings['custom_system_message'], lines=2, label='Custom system message', info='If not empty, will be used instead of the default one.', elem_classes=['add_scrollbar'])
                            shared.gradio['custom_stopping_strings'] = gr.Textbox(lines=2, value=shared.settings["custom_stopping_strings"] or None, label='Custom stopping strings', info='Written between "" and separated by commas.', placeholder='"\\n", "\\nYou:"')
                            shared.gradio['custom_token_bans'] = gr.Textbox(value=shared.settings['custom_token_bans'] or None, label='Token bans', info='Token IDs to ban, separated by commas. The IDs can be found in the Default or Notebook tab.')
                            shared.gradio['negative_prompt'] = gr.Textbox(value=shared.settings['negative_prompt'], label='Negative prompt', info='For CFG. Only used when guidance_scale is different than 1.', lines=3, elem_classes=['add_scrollbar'])
                            with gr.Row() as shared.gradio['grammar_file_row']:
                                shared.gradio['grammar_file'] = gr.Dropdown(value='None', choices=utils.get_available_grammars(), label='Load grammar from file (.gbnf)', elem_classes='slim-dropdown')
                                ui.create_refresh_button(shared.gradio['grammar_file'], lambda: None, lambda: {'choices': utils.get_available_grammars()}, 'refresh-button', interactive=not mu)
                                shared.gradio['save_grammar'] = gr.Button('💾', elem_classes='refresh-button', interactive=not mu)
                                shared.gradio['delete_grammar'] = gr.Button('🗑️ ', elem_classes='refresh-button', interactive=not mu)

                            shared.gradio['grammar_string'] = gr.Textbox(value=shared.settings['grammar_string'], label='Grammar', lines=16, elem_classes=['add_scrollbar', 'monospace'])

        ui_chat.create_chat_settings_ui()


def create_event_handlers():
    shared.gradio['filter_by_loader'].change(loaders.blacklist_samplers, gradio('filter_by_loader', 'dynamic_temperature'), gradio(loaders.list_all_samplers()), show_progress=False)
    shared.gradio['preset_menu'].change(
        ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
        presets.load_preset_for_ui, gradio('preset_menu', 'interface_state'), gradio('interface_state') + gradio(presets.presets_params()), show_progress=False)

    shared.gradio['reset_preset'].click(
        ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
        presets.reset_preset_for_ui, gradio('preset_menu', 'interface_state'), gradio('interface_state') + gradio(presets.presets_params()), show_progress=False)

    shared.gradio['neutralize_samplers'].click(
        ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
        presets.neutralize_samplers_for_ui, gradio('interface_state'), gradio('interface_state') + gradio(presets.presets_params()), show_progress=False)

    shared.gradio['grammar_file'].change(load_grammar, gradio('grammar_file'), gradio('grammar_string'), show_progress=False)
    shared.gradio['dynamic_temperature'].change(lambda x: [gr.update(visible=x)] * 3, gradio('dynamic_temperature'), gradio('dynatemp_low', 'dynatemp_high', 'dynatemp_exponent'), show_progress=False)


def get_truncation_length():
    if shared.args.ctx_size > 0 and ('ctx_size' in shared.provided_arguments or shared.args.ctx_size != shared.args_defaults.ctx_size):
        return shared.args.ctx_size
    else:
        return shared.settings['truncation_length']


def load_grammar(name):
    p = shared.user_data_dir / 'grammars' / name
    if p.exists():
        return open(p, 'r', encoding='utf-8').read()
    else:
        return ''