Merge pull request #5772 from oobabooga/dev

Merge dev branch
This commit is contained in:
oobabooga 2024-03-29 15:09:53 -03:00 committed by GitHub
commit 1a7c027386
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34 changed files with 193 additions and 146 deletions

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@ -89,6 +89,11 @@ div.svelte-15lo0d8 > *, div.svelte-15lo0d8 > .form > * {
flex-wrap: nowrap;
}
gradio-app > :first-child {
padding-left: var(--size-4) !important;
padding-right: var(--size-4) !important;
}
.header_bar {
background-color: #f7f7f7;
box-shadow: 0 2px 3px rgba(22 22 22 / 35%);
@ -522,6 +527,7 @@ div.svelte-362y77>*, div.svelte-362y77>.form>* {
position: absolute;
background-color: transparent;
left: -2px;
top: 4px;
padding: var(--block-padding);
}

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@ -2,8 +2,6 @@
# however for me to work i had to specify the exact version for my card ( 2060 ) it was 7.5
# https://developer.nvidia.com/cuda-gpus you can find the version for your card here
TORCH_CUDA_ARCH_LIST=7.5
# your command-line flags go here:
CLI_ARGS=--listen
# the port the webui binds to on the host
HOST_PORT=7860
# the port the webui binds to inside the container

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@ -61,10 +61,6 @@ For more information about the parameters, the [transformers documentation](http
* **Seed**: Set the Pytorch seed to this number. Note that some loaders do not use Pytorch (notably llama.cpp), and others are not deterministic (ExLlamaV2). For these loaders, the seed has no effect.
* **encoder_repetition_penalty**: Also known as the "Hallucinations filter". Used to penalize tokens that are *not* in the prior text. Higher value = more likely to stay in context, lower value = more likely to diverge.
* **no_repeat_ngram_size**: If not set to 0, specifies the length of token sets that are completely blocked from repeating at all. Higher values = blocks larger phrases, lower values = blocks words or letters from repeating. Only 0 or high values are a good idea in most cases.
* **min_length**: Minimum generation length in tokens. This is a built-in parameter in the transformers library that has never been very useful. Typically you want to check "Ban the eos_token" instead.
* **num_beams**: Number of beams for beam search. 1 means no beam search.
* **length_penalty**: Used by beam search only. `length_penalty > 0.0` promotes longer sequences, while `length_penalty < 0.0` encourages shorter sequences.
* **early_stopping**: Used by beam search only. When checked, the generation stops as soon as there are "num_beams" complete candidates; otherwise, a heuristic is applied and the generation stops when is it very unlikely to find better candidates (I just copied this from the transformers documentation and have never gotten beam search to generate good results).
To the right (or below if you are on mobile), the following parameters are present:

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@ -119,7 +119,7 @@ def ui():
samples_per_page=settings["gallery-items_per_page"]
)
filter_box.change(lambda: None, None, None, _js=f'() => {{{custom_js()}; gotoFirstPage()}}').success(
filter_box.change(lambda: None, None, None, js=f'() => {{{custom_js()}; gotoFirstPage()}}').success(
filter_cards, filter_box, gallery).then(
lambda x: gr.update(elem_classes='highlighted-border' if x != '' else ''), filter_box, filter_box, show_progress=False)

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@ -261,6 +261,7 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False) -
name2 = body['bot_name'] or name2
context = body['context'] or context
greeting = body['greeting'] or greeting
user_bio = body['user_bio'] or ''
# History
user_input, custom_system_message, history = convert_history(messages)
@ -271,6 +272,7 @@ def chat_completions_common(body: dict, is_legacy: bool = False, stream=False) -
'name2': name2,
'context': context,
'greeting': greeting,
'user_bio': user_bio,
'instruction_template_str': instruction_template_str,
'custom_system_message': custom_system_message,
'chat_template_str': chat_template_str,

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@ -33,10 +33,6 @@ class GenerationOptions(BaseModel):
seed: int = -1
encoder_repetition_penalty: float = 1
no_repeat_ngram_size: int = 0
min_length: int = 0
num_beams: int = 1
length_penalty: float = 1
early_stopping: bool = False
truncation_length: int = 0
max_tokens_second: int = 0
prompt_lookup_num_tokens: int = 0

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@ -64,7 +64,7 @@ def ui():
audio.change(
auto_transcribe, [audio, auto_submit, whipser_model, whipser_language], [shared.gradio['textbox'], audio]).then(
None, auto_submit, None, _js="(check) => {if (check) { document.getElementById('Generate').click() }}")
None, auto_submit, None, js="(check) => {if (check) { document.getElementById('Generate').click() }}")
whipser_model.change(lambda x: params.update({"whipser_model": x}), whipser_model, None)
whipser_language.change(lambda x: params.update({"whipser_language": x}), whipser_language, None)

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@ -32,27 +32,27 @@ function switch_to_chat() {
}
function switch_to_default() {
let default_tab_button = main_parent.childNodes[0].childNodes[4];
let default_tab_button = main_parent.childNodes[0].childNodes[5];
default_tab_button.click();
scrollToTop();
}
function switch_to_notebook() {
let notebook_tab_button = main_parent.childNodes[0].childNodes[7];
let notebook_tab_button = main_parent.childNodes[0].childNodes[9];
notebook_tab_button.click();
findButtonsByText("Raw")[1].click();
scrollToTop();
}
function switch_to_generation_parameters() {
let parameters_tab_button = main_parent.childNodes[0].childNodes[10];
let parameters_tab_button = main_parent.childNodes[0].childNodes[13];
parameters_tab_button.click();
findButtonsByText("Generation")[0].click();
scrollToTop();
}
function switch_to_character() {
let parameters_tab_button = main_parent.childNodes[0].childNodes[10];
let parameters_tab_button = main_parent.childNodes[0].childNodes[13];
parameters_tab_button.click();
findButtonsByText("Character")[0].click();
scrollToTop();

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@ -190,3 +190,5 @@
instruction_template: 'ChatML'
.*synthia:
instruction_template: 'Synthia'
.*(hercules|hyperion):
instruction_template: 'ChatML'

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@ -43,8 +43,9 @@ def my_open(*args, **kwargs):
with original_open(*args, **kwargs) as f:
file_contents = f.read()
file_contents = file_contents.replace(b'\t\t<script\n\t\t\tsrc="https://cdnjs.cloudflare.com/ajax/libs/iframe-resizer/4.3.7/iframeResizer.contentWindow.min.js"\n\t\t\tasync\n\t\t></script>', b'')
file_contents = file_contents.replace(b'\t\t<script\n\t\t\tsrc="https://cdnjs.cloudflare.com/ajax/libs/iframe-resizer/4.3.9/iframeResizer.contentWindow.min.js"\n\t\t\tasync\n\t\t></script>', b'')
file_contents = file_contents.replace(b'cdnjs.cloudflare.com', b'127.0.0.1')
return io.BytesIO(file_contents)
else:
return original_open(*args, **kwargs)

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@ -161,12 +161,14 @@ def generate_chat_prompt(user_input, state, **kwargs):
prompt = instruction_template.render(messages=outer_messages)
suffix = get_generation_prompt(instruct_renderer, impersonate=False)[1]
prompt = prompt[:-len(suffix)]
if len(suffix) > 0:
prompt = prompt[:-len(suffix)]
else:
if _continue:
suffix = get_generation_prompt(renderer, impersonate=impersonate)[1]
prompt = prompt[:-len(suffix)]
if len(suffix) > 0:
prompt = prompt[:-len(suffix)]
else:
prefix = get_generation_prompt(renderer, impersonate=impersonate)[0]
if state['mode'] == 'chat' and not impersonate:

72
modules/gradio_hijack.py Normal file
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@ -0,0 +1,72 @@
'''
Copied from: https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/14184
'''
import inspect
import warnings
from functools import wraps
import gradio as gr
class GradioDeprecationWarning(DeprecationWarning):
pass
def repair(grclass):
if not getattr(grclass, 'EVENTS', None):
return
@wraps(grclass.__init__)
def __repaired_init__(self, *args, tooltip=None, source=None, original=grclass.__init__, **kwargs):
if source:
kwargs["sources"] = [source]
allowed_kwargs = inspect.signature(original).parameters
fixed_kwargs = {}
for k, v in kwargs.items():
if k in allowed_kwargs:
fixed_kwargs[k] = v
else:
warnings.warn(f"unexpected argument for {grclass.__name__}: {k}", GradioDeprecationWarning, stacklevel=2)
original(self, *args, **fixed_kwargs)
self.webui_tooltip = tooltip
for event in self.EVENTS:
replaced_event = getattr(self, str(event))
def fun(*xargs, _js=None, replaced_event=replaced_event, **xkwargs):
if _js:
xkwargs['js'] = _js
return replaced_event(*xargs, **xkwargs)
setattr(self, str(event), fun)
grclass.__init__ = __repaired_init__
grclass.update = gr.update
for component in set(gr.components.__all__ + gr.layouts.__all__):
repair(getattr(gr, component, None))
class Dependency(gr.events.Dependency):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
def then(*xargs, _js=None, **xkwargs):
if _js:
xkwargs['js'] = _js
return original_then(*xargs, **xkwargs)
original_then = self.then
self.then = then
gr.events.Dependency = Dependency
gr.Box = gr.Group

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@ -185,13 +185,9 @@ def transformers_samplers():
'repetition_penalty_range',
'encoder_repetition_penalty',
'no_repeat_ngram_size',
'min_length',
'seed',
'do_sample',
'penalty_alpha',
'num_beams',
'length_penalty',
'early_stopping',
'mirostat_mode',
'mirostat_tau',
'mirostat_eta',
@ -262,7 +258,6 @@ loaders_samplers = {
'repetition_penalty_range',
'encoder_repetition_penalty',
'no_repeat_ngram_size',
'min_length',
'seed',
'do_sample',
'mirostat_mode',
@ -321,7 +316,6 @@ loaders_samplers = {
'repetition_penalty_range',
'encoder_repetition_penalty',
'no_repeat_ngram_size',
'min_length',
'seed',
'do_sample',
'mirostat_mode',

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@ -40,10 +40,6 @@ def default_preset():
'do_sample': True,
'encoder_repetition_penalty': 1,
'no_repeat_ngram_size': 0,
'min_length': 0,
'num_beams': 1,
'length_penalty': 1,
'early_stopping': False,
'sampler_priority': 'temperature\ndynamic_temperature\nquadratic_sampling\ntop_k\ntop_p\ntypical_p\nepsilon_cutoff\neta_cutoff\ntfs\ntop_a\nmin_p\nmirostat'
}
@ -52,7 +48,7 @@ def presets_params():
return [k for k in default_preset()]
def load_preset(name):
def load_preset(name, verbose=False):
generate_params = default_preset()
if name not in ['None', None, '']:
path = Path(f'presets/{name}.yaml')
@ -65,6 +61,10 @@ def load_preset(name):
else:
logger.error(f"The preset \"{name}\" does not exist under \"{path}\". Using the default parameters.")
if verbose:
logger.info(f"\"{name}\" preset:")
pprint.PrettyPrinter(indent=4, width=1, sort_dicts=False).pprint(remove_defaults(generate_params))
return generate_params
@ -74,7 +74,7 @@ def load_preset_memoized(name):
def load_preset_for_ui(name, state):
generate_params = load_preset(name)
generate_params = load_preset(name, verbose=True)
state.update(generate_params)
return state, *[generate_params[k] for k in presets_params()]

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@ -46,7 +46,6 @@ settings = {
'truncation_length_min': 0,
'truncation_length_max': 200000,
'max_tokens_second': 0,
'max_updates_second': 0,
'prompt_lookup_num_tokens': 0,
'custom_stopping_strings': '',
'custom_token_bans': '',

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@ -81,19 +81,16 @@ def _generate_reply(question, state, stopping_strings=None, is_chat=False, escap
state = copy.deepcopy(state)
state['stream'] = True
min_update_interval = 0
if state.get('max_updates_second', 0) > 0:
min_update_interval = 1 / state['max_updates_second']
# Generate
for reply in generate_func(question, original_question, seed, state, stopping_strings, is_chat=is_chat):
reply, stop_found = apply_stopping_strings(reply, all_stop_strings)
if escape_html:
reply = html.escape(reply)
if is_stream:
cur_time = time.time()
# Maximum number of tokens/second
# Limit number of tokens/second to make text readable in real time
if state['max_tokens_second'] > 0:
diff = 1 / state['max_tokens_second'] - (cur_time - last_update)
if diff > 0:
@ -101,13 +98,8 @@ def _generate_reply(question, state, stopping_strings=None, is_chat=False, escap
last_update = time.time()
yield reply
# Limit updates to avoid lag in the Gradio UI
# API updates are not limited
else:
if cur_time - last_update > min_update_interval:
last_update = cur_time
yield reply
yield reply
if stop_found or (state['max_tokens_second'] > 0 and shared.stop_everything):
break
@ -287,7 +279,7 @@ def get_reply_from_output_ids(output_ids, state=None, starting_from=0):
def generate_reply_HF(question, original_question, seed, state, stopping_strings=None, is_chat=False):
generate_params = {}
for k in ['max_new_tokens', 'temperature', 'temperature_last', 'dynamic_temperature', 'dynatemp_low', 'dynatemp_high', 'dynatemp_exponent', 'smoothing_factor', 'smoothing_curve', 'top_p', 'min_p', 'top_k', 'repetition_penalty', 'presence_penalty', 'frequency_penalty', 'repetition_penalty_range', 'typical_p', 'tfs', 'top_a', 'guidance_scale', 'penalty_alpha', 'mirostat_mode', 'mirostat_tau', 'mirostat_eta', 'do_sample', 'encoder_repetition_penalty', 'no_repeat_ngram_size', 'min_length', 'num_beams', 'length_penalty', 'early_stopping']:
for k in ['max_new_tokens', 'temperature', 'temperature_last', 'dynamic_temperature', 'dynatemp_low', 'dynatemp_high', 'dynatemp_exponent', 'smoothing_factor', 'smoothing_curve', 'top_p', 'min_p', 'top_k', 'repetition_penalty', 'presence_penalty', 'frequency_penalty', 'repetition_penalty_range', 'typical_p', 'tfs', 'top_a', 'guidance_scale', 'penalty_alpha', 'mirostat_mode', 'mirostat_tau', 'mirostat_eta', 'do_sample', 'encoder_repetition_penalty', 'no_repeat_ngram_size']:
if k in state:
generate_params[k] = state[k]

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@ -117,7 +117,6 @@ def list_interface_input_elements():
'max_new_tokens',
'auto_max_new_tokens',
'max_tokens_second',
'max_updates_second',
'prompt_lookup_num_tokens',
'seed',
'temperature',
@ -140,12 +139,8 @@ def list_interface_input_elements():
'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',

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@ -181,7 +181,7 @@ def create_event_handlers():
chat.generate_chat_reply_wrapper, gradio(inputs), gradio('display', 'history'), show_progress=False).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
chat.save_history, gradio('history', 'unique_id', 'character_menu', 'mode'), None).then(
lambda: None, None, None, _js=f'() => {{{ui.audio_notification_js}}}')
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
shared.gradio['textbox'].submit(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
@ -189,28 +189,28 @@ def create_event_handlers():
chat.generate_chat_reply_wrapper, gradio(inputs), gradio('display', 'history'), show_progress=False).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
chat.save_history, gradio('history', 'unique_id', 'character_menu', 'mode'), None).then(
lambda: None, None, None, _js=f'() => {{{ui.audio_notification_js}}}')
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
shared.gradio['Regenerate'].click(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
partial(chat.generate_chat_reply_wrapper, regenerate=True), gradio(inputs), gradio('display', 'history'), show_progress=False).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
chat.save_history, gradio('history', 'unique_id', 'character_menu', 'mode'), None).then(
lambda: None, None, None, _js=f'() => {{{ui.audio_notification_js}}}')
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
shared.gradio['Continue'].click(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
partial(chat.generate_chat_reply_wrapper, _continue=True), gradio(inputs), gradio('display', 'history'), show_progress=False).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
chat.save_history, gradio('history', 'unique_id', 'character_menu', 'mode'), None).then(
lambda: None, None, None, _js=f'() => {{{ui.audio_notification_js}}}')
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
shared.gradio['Impersonate'].click(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
lambda x: x, gradio('textbox'), gradio('Chat input'), show_progress=False).then(
chat.impersonate_wrapper, gradio(inputs), gradio('textbox', 'display'), show_progress=False).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
lambda: None, None, None, _js=f'() => {{{ui.audio_notification_js}}}')
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
shared.gradio['Replace last reply'].click(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
@ -288,7 +288,7 @@ def create_event_handlers():
chat.redraw_html, gradio(reload_arr), gradio('display')).then(
lambda x: gr.update(choices=(histories := chat.find_all_histories(x)), value=histories[0]), gradio('interface_state'), gradio('unique_id')).then(
chat.save_history, gradio('history', 'unique_id', 'character_menu', 'mode'), None).then(
lambda: None, None, None, _js=f'() => {{{ui.switch_tabs_js}; switch_to_chat()}}')
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_chat()}}')
shared.gradio['character_menu'].change(
chat.load_character, gradio('character_menu', 'name1', 'name2'), gradio('name1', 'name2', 'character_picture', 'greeting', 'context')).success(
@ -296,7 +296,7 @@ def create_event_handlers():
chat.load_latest_history, gradio('interface_state'), gradio('history')).then(
chat.redraw_html, gradio(reload_arr), gradio('display')).then(
lambda x: gr.update(choices=(histories := chat.find_all_histories(x)), value=histories[0]), gradio('interface_state'), gradio('unique_id')).then(
lambda: None, None, None, _js=f'() => {{{ui.update_big_picture_js}; updateBigPicture()}}')
lambda: None, None, None, js=f'() => {{{ui.update_big_picture_js}; updateBigPicture()}}')
shared.gradio['mode'].change(
lambda x: [gr.update(visible=x != 'instruct'), gr.update(visible=x == 'chat-instruct')], gradio('mode'), gradio('chat_style', 'chat-instruct_command'), show_progress=False).then(
@ -332,15 +332,15 @@ def create_event_handlers():
shared.gradio['save_chat_history'].click(
lambda x: json.dumps(x, indent=4), gradio('history'), gradio('temporary_text')).then(
None, gradio('temporary_text', 'character_menu', 'mode'), None, _js=f'(hist, char, mode) => {{{ui.save_files_js}; saveHistory(hist, char, mode)}}')
None, gradio('temporary_text', 'character_menu', 'mode'), None, js=f'(hist, char, mode) => {{{ui.save_files_js}; saveHistory(hist, char, mode)}}')
shared.gradio['Submit character'].click(
chat.upload_character, gradio('upload_json', 'upload_img_bot'), gradio('character_menu')).then(
lambda: None, None, None, _js=f'() => {{{ui.switch_tabs_js}; switch_to_character()}}')
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_character()}}')
shared.gradio['Submit tavern character'].click(
chat.upload_tavern_character, gradio('upload_img_tavern', 'tavern_json'), gradio('character_menu')).then(
lambda: None, None, None, _js=f'() => {{{ui.switch_tabs_js}; switch_to_character()}}')
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_character()}}')
shared.gradio['upload_json'].upload(lambda: gr.update(interactive=True), None, gradio('Submit character'))
shared.gradio['upload_json'].clear(lambda: gr.update(interactive=False), None, gradio('Submit character'))
@ -354,28 +354,28 @@ def create_event_handlers():
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
lambda x: x.update({'mode': 'instruct', 'history': {'internal': [], 'visible': []}}), gradio('interface_state'), None).then(
partial(chat.generate_chat_prompt, 'Input'), gradio('interface_state'), gradio('textbox-default')).then(
lambda: None, None, None, _js=f'() => {{{ui.switch_tabs_js}; switch_to_default()}}')
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_default()}}')
shared.gradio['send_instruction_to_notebook'].click(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
lambda x: x.update({'mode': 'instruct', 'history': {'internal': [], 'visible': []}}), gradio('interface_state'), None).then(
partial(chat.generate_chat_prompt, 'Input'), gradio('interface_state'), gradio('textbox-notebook')).then(
lambda: None, None, None, _js=f'() => {{{ui.switch_tabs_js}; switch_to_notebook()}}')
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_notebook()}}')
shared.gradio['send_instruction_to_negative_prompt'].click(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
lambda x: x.update({'mode': 'instruct', 'history': {'internal': [], 'visible': []}}), gradio('interface_state'), None).then(
partial(chat.generate_chat_prompt, 'Input'), gradio('interface_state'), gradio('negative_prompt')).then(
lambda: None, None, None, _js=f'() => {{{ui.switch_tabs_js}; switch_to_generation_parameters()}}')
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_generation_parameters()}}')
shared.gradio['send-chat-to-default'].click(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
partial(chat.generate_chat_prompt, '', _continue=True), gradio('interface_state'), gradio('textbox-default')).then(
lambda: None, None, None, _js=f'() => {{{ui.switch_tabs_js}; switch_to_default()}}')
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_default()}}')
shared.gradio['send-chat-to-notebook'].click(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
partial(chat.generate_chat_prompt, '', _continue=True), gradio('interface_state'), gradio('textbox-notebook')).then(
lambda: None, None, None, _js=f'() => {{{ui.switch_tabs_js}; switch_to_notebook()}}')
lambda: None, None, None, js=f'() => {{{ui.switch_tabs_js}; switch_to_notebook()}}')
shared.gradio['show_controls'].change(None, gradio('show_controls'), None, _js=f'(x) => {{{ui.show_controls_js}; toggle_controls(x)}}')
shared.gradio['show_controls'].change(None, gradio('show_controls'), None, js=f'(x) => {{{ui.show_controls_js}; toggle_controls(x)}}')

View File

@ -67,21 +67,21 @@ def create_event_handlers():
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
generate_reply_wrapper, gradio(inputs), gradio(outputs), show_progress=False).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
lambda: None, None, None, _js=f'() => {{{ui.audio_notification_js}}}')
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
shared.gradio['textbox-default'].submit(
lambda x: x, gradio('textbox-default'), gradio('last_input-default')).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
generate_reply_wrapper, gradio(inputs), gradio(outputs), show_progress=False).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
lambda: None, None, None, _js=f'() => {{{ui.audio_notification_js}}}')
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
shared.gradio['markdown_render-default'].click(lambda x: x, gradio('output_textbox'), gradio('markdown-default'), queue=False)
shared.gradio['Continue-default'].click(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
generate_reply_wrapper, [shared.gradio['output_textbox']] + gradio(inputs)[1:], gradio(outputs), show_progress=False).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
lambda: None, None, None, _js=f'() => {{{ui.audio_notification_js}}}')
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
shared.gradio['Stop-default'].click(stop_everything_event, None, None, queue=False)
shared.gradio['prompt_menu-default'].change(load_prompt, gradio('prompt_menu-default'), gradio('textbox-default'), show_progress=False)

View File

@ -75,7 +75,7 @@ def create_ui():
with gr.Row():
with gr.Column():
shared.gradio['loader'] = gr.Dropdown(label="Model loader", choices=loaders.loaders_and_params.keys(), value=None)
with gr.Box():
with gr.Blocks():
with gr.Row():
with gr.Column():
with gr.Blocks():

View File

@ -67,14 +67,14 @@ def create_event_handlers():
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
generate_reply_wrapper, gradio(inputs), gradio(outputs), show_progress=False).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
lambda: None, None, None, _js=f'() => {{{ui.audio_notification_js}}}')
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
shared.gradio['textbox-notebook'].submit(
lambda x: x, gradio('textbox-notebook'), gradio('last_input-notebook')).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
generate_reply_wrapper, gradio(inputs), gradio(outputs), show_progress=False).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
lambda: None, None, None, _js=f'() => {{{ui.audio_notification_js}}}')
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
shared.gradio['Undo'].click(lambda x: x, gradio('last_input-notebook'), gradio('textbox-notebook'), show_progress=False)
shared.gradio['markdown_render-notebook'].click(lambda x: x, gradio('textbox-notebook'), gradio('markdown-notebook'), queue=False)
@ -83,7 +83,7 @@ def create_event_handlers():
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
generate_reply_wrapper, gradio(inputs), gradio(outputs), show_progress=False).then(
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then(
lambda: None, None, None, _js=f'() => {{{ui.audio_notification_js}}}')
lambda: None, None, None, js=f'() => {{{ui.audio_notification_js}}}')
shared.gradio['Stop-notebook'].click(stop_everything_event, None, None, queue=False)
shared.gradio['prompt_menu-notebook'].change(load_prompt, gradio('prompt_menu-notebook'), gradio('textbox-notebook'), show_progress=False)

View File

@ -30,25 +30,48 @@ def create_ui(default_preset):
shared.gradio['max_new_tokens'] = gr.Slider(minimum=shared.settings['max_new_tokens_min'], maximum=shared.settings['max_new_tokens_max'], step=1, label='max_new_tokens', value=shared.settings['max_new_tokens'])
shared.gradio['temperature'] = gr.Slider(0.01, 5, value=generate_params['temperature'], step=0.01, label='temperature')
shared.gradio['top_p'] = gr.Slider(0.0, 1.0, value=generate_params['top_p'], step=0.01, label='top_p')
shared.gradio['min_p'] = gr.Slider(0.0, 1.0, value=generate_params['min_p'], step=0.01, label='min_p')
shared.gradio['top_k'] = gr.Slider(0, 200, value=generate_params['top_k'], step=1, label='top_k')
shared.gradio['repetition_penalty'] = gr.Slider(1.0, 1.5, value=generate_params['repetition_penalty'], step=0.01, label='repetition_penalty')
shared.gradio['presence_penalty'] = gr.Slider(0, 2, value=generate_params['presence_penalty'], step=0.05, label='presence_penalty')
shared.gradio['frequency_penalty'] = gr.Slider(0, 2, value=generate_params['frequency_penalty'], step=0.05, label='frequency_penalty')
shared.gradio['repetition_penalty_range'] = gr.Slider(0, 4096, step=64, value=generate_params['repetition_penalty_range'], label='repetition_penalty_range')
shared.gradio['typical_p'] = gr.Slider(0.0, 1.0, value=generate_params['typical_p'], step=0.01, label='typical_p')
shared.gradio['tfs'] = gr.Slider(0.0, 1.0, value=generate_params['tfs'], step=0.01, label='tfs')
shared.gradio['top_a'] = gr.Slider(0.0, 1.0, value=generate_params['top_a'], step=0.01, label='top_a')
shared.gradio['epsilon_cutoff'] = gr.Slider(0, 9, value=generate_params['epsilon_cutoff'], step=0.01, label='epsilon_cutoff')
shared.gradio['eta_cutoff'] = gr.Slider(0, 20, value=generate_params['eta_cutoff'], step=0.01, label='eta_cutoff')
shared.gradio['repetition_penalty'] = gr.Slider(1.0, 1.5, value=generate_params['repetition_penalty'], step=0.01, label='repetition_penalty')
shared.gradio['frequency_penalty'] = gr.Slider(0, 2, value=generate_params['frequency_penalty'], step=0.05, label='frequency_penalty')
shared.gradio['presence_penalty'] = gr.Slider(0, 2, value=generate_params['presence_penalty'], step=0.05, label='presence_penalty')
shared.gradio['repetition_penalty_range'] = gr.Slider(0, 4096, step=64, value=generate_params['repetition_penalty_range'], label='repetition_penalty_range')
shared.gradio['do_sample'] = gr.Checkbox(value=generate_params['do_sample'], label='do_sample')
gr.Markdown("[Learn more](https://github.com/oobabooga/text-generation-webui/wiki/03-%E2%80%90-Parameters-Tab)")
with gr.Column():
with gr.Group():
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='Disabling this can make the replies more creative.')
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['penalty_alpha'] = gr.Slider(0, 5, value=generate_params['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=generate_params['guidance_scale'], label='guidance_scale', info='For CFG. 1.5 is a good value.')
shared.gradio['negative_prompt'] = gr.Textbox(value=shared.settings['negative_prompt'], label='Negative prompt', lines=3, elem_classes=['add_scrollbar'])
shared.gradio['penalty_alpha'] = gr.Slider(0, 5, value=generate_params['penalty_alpha'], label='penalty_alpha', info='For Contrastive Search. do_sample must be unchecked.')
shared.gradio['mirostat_mode'] = gr.Slider(0, 2, step=1, value=generate_params['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=generate_params['mirostat_tau'], label='mirostat_tau')
shared.gradio['mirostat_eta'] = gr.Slider(0, 1, step=0.01, value=generate_params['mirostat_eta'], label='mirostat_eta')
shared.gradio['epsilon_cutoff'] = gr.Slider(0, 9, value=generate_params['epsilon_cutoff'], step=0.01, label='epsilon_cutoff')
shared.gradio['eta_cutoff'] = gr.Slider(0, 20, value=generate_params['eta_cutoff'], step=0.01, label='eta_cutoff')
shared.gradio['encoder_repetition_penalty'] = gr.Slider(0.8, 1.5, value=generate_params['encoder_repetition_penalty'], step=0.01, label='encoder_repetition_penalty')
shared.gradio['no_repeat_ngram_size'] = gr.Slider(0, 20, step=1, value=generate_params['no_repeat_ngram_size'], label='no_repeat_ngram_size')
with gr.Column():
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='', label='Grammar', lines=16, elem_classes=['add_scrollbar', 'monospace'])
with gr.Row():
with gr.Column():
shared.gradio['min_p'] = gr.Slider(0.0, 1.0, value=generate_params['min_p'], step=0.01, label='min_p')
shared.gradio['tfs'] = gr.Slider(0.0, 1.0, value=generate_params['tfs'], step=0.01, label='tfs')
shared.gradio['top_a'] = gr.Slider(0.0, 1.0, value=generate_params['top_a'], step=0.01, label='top_a')
shared.gradio['smoothing_factor'] = gr.Slider(0.0, 10.0, value=generate_params['smoothing_factor'], step=0.01, label='smoothing_factor', info='Activates Quadratic Sampling.')
shared.gradio['smoothing_curve'] = gr.Slider(1.0, 10.0, value=generate_params['smoothing_curve'], step=0.01, label='smoothing_curve', info='Adjusts the dropoff curve of Quadratic Sampling.')
shared.gradio['dynamic_temperature'] = gr.Checkbox(value=generate_params['dynamic_temperature'], label='dynamic_temperature')
@ -56,47 +79,16 @@ def create_ui(default_preset):
shared.gradio['dynatemp_high'] = gr.Slider(0.01, 5, value=generate_params['dynatemp_high'], step=0.01, label='dynatemp_high', visible=generate_params['dynamic_temperature'])
shared.gradio['dynatemp_exponent'] = gr.Slider(0.01, 5, value=generate_params['dynatemp_exponent'], step=0.01, label='dynatemp_exponent', visible=generate_params['dynamic_temperature'])
shared.gradio['temperature_last'] = gr.Checkbox(value=generate_params['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['do_sample'] = gr.Checkbox(value=generate_params['do_sample'], label='do_sample')
shared.gradio['seed'] = gr.Number(value=shared.settings['seed'], label='Seed (-1 for random)')
with gr.Accordion('Other parameters', open=False):
shared.gradio['encoder_repetition_penalty'] = gr.Slider(0.8, 1.5, value=generate_params['encoder_repetition_penalty'], step=0.01, label='encoder_repetition_penalty')
shared.gradio['no_repeat_ngram_size'] = gr.Slider(0, 20, step=1, value=generate_params['no_repeat_ngram_size'], label='no_repeat_ngram_size')
shared.gradio['min_length'] = gr.Slider(0, 2000, step=1, value=generate_params['min_length'], label='min_length')
shared.gradio['num_beams'] = gr.Slider(1, 20, step=1, value=generate_params['num_beams'], label='num_beams', info='For Beam Search, along with length_penalty and early_stopping.')
shared.gradio['length_penalty'] = gr.Slider(-5, 5, value=generate_params['length_penalty'], label='length_penalty')
shared.gradio['early_stopping'] = gr.Checkbox(value=generate_params['early_stopping'], label='early_stopping')
shared.gradio['sampler_priority'] = gr.Textbox(value=generate_params['sampler_priority'], lines=12, label='Sampler priority', info='Parameter names separated by new lines or commas.')
gr.Markdown("[Learn more](https://github.com/oobabooga/text-generation-webui/wiki/03-%E2%80%90-Parameters-Tab)")
with gr.Column():
with gr.Row():
with gr.Column():
shared.gradio['truncation_length'] = gr.Slider(value=get_truncation_length(), minimum=shared.settings['truncation_length_min'], maximum=shared.settings['truncation_length_max'], step=256, label='Truncate the prompt up to this length', info='The leftmost tokens are removed if the prompt exceeds this length. Most models require this to be at most 2048.')
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['max_updates_second'] = gr.Slider(value=shared.settings['max_updates_second'], minimum=0, maximum=24, step=1, label='Maximum UI updates/second', info='Set this if you experience lag in the UI during streaming.')
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['custom_stopping_strings'] = gr.Textbox(lines=2, value=shared.settings["custom_stopping_strings"] or None, label='Custom stopping strings', info='In addition to the defaults. 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='Custom token bans', info='Specific token IDs to ban from generating, comma-separated. The IDs can be found in the Default or Notebook tab.')
with gr.Column():
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='Disabling this can make the replies more creative.')
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['seed'] = gr.Number(value=shared.settings['seed'], label='Seed (-1 for random)')
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')
with gr.Blocks():
shared.gradio['sampler_priority'] = gr.Textbox(value=generate_params['sampler_priority'], lines=12, label='Sampler priority', info='Parameter names separated by new lines or commas.')
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='', label='Grammar', lines=16, elem_classes=['add_scrollbar', 'monospace'])
ui_chat.create_chat_settings_ui()

View File

@ -32,10 +32,10 @@ def create_ui():
# Reset interface event
shared.gradio['reset_interface'].click(
set_interface_arguments, gradio('extensions_menu', 'bool_menu'), None).then(
lambda: None, None, None, _js='() => {document.body.innerHTML=\'<h1 style="font-family:monospace;padding-top:20%;margin:0;height:100vh;color:lightgray;text-align:center;background:var(--body-background-fill)">Reloading...</h1>\'; setTimeout(function(){location.reload()},2500); return []}')
lambda: None, None, None, js='() => {document.body.innerHTML=\'<h1 style="font-family:monospace;padding-top:20%;margin:0;height:100vh;color:lightgray;text-align:center;background:var(--body-background-fill)">Reloading...</h1>\'; setTimeout(function(){location.reload()},2500); return []}')
shared.gradio['toggle_dark_mode'].click(
lambda: None, None, None, _js='() => {document.getElementsByTagName("body")[0].classList.toggle("dark")}').then(
lambda: None, None, None, js='() => {document.getElementsByTagName("body")[0].classList.toggle("dark")}').then(
lambda x: 'dark' if x == 'light' else 'light', gradio('theme_state'), gradio('theme_state'))
shared.gradio['save_settings'].click(

View File

@ -1,10 +1,10 @@
accelerate==0.27.*
aqlm[gpu,cpu]==1.1.0; platform_system == "Linux"
aqlm[gpu,cpu]==1.1.2; platform_system == "Linux"
bitsandbytes==0.43.*
colorama
datasets
einops
gradio==3.50.*
gradio==4.23.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
@ -22,7 +22,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.38.*
transformers==4.39.*
tqdm
wandb

View File

@ -2,7 +2,7 @@ accelerate==0.27.*
colorama
datasets
einops
gradio==3.50.*
gradio==4.23.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
@ -20,7 +20,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.38.*
transformers==4.39.*
tqdm
wandb

View File

@ -2,7 +2,7 @@ accelerate==0.27.*
colorama
datasets
einops
gradio==3.50.*
gradio==4.23.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
@ -20,7 +20,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.38.*
transformers==4.39.*
tqdm
wandb

View File

@ -2,7 +2,7 @@ accelerate==0.27.*
colorama
datasets
einops
gradio==3.50.*
gradio==4.23.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
@ -20,7 +20,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.38.*
transformers==4.39.*
tqdm
wandb

View File

@ -2,7 +2,7 @@ accelerate==0.27.*
colorama
datasets
einops
gradio==3.50.*
gradio==4.23.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
@ -20,7 +20,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.38.*
transformers==4.39.*
tqdm
wandb

View File

@ -2,7 +2,7 @@ accelerate==0.27.*
colorama
datasets
einops
gradio==3.50.*
gradio==4.23.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
@ -20,7 +20,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.38.*
transformers==4.39.*
tqdm
wandb

View File

@ -2,7 +2,7 @@ accelerate==0.27.*
colorama
datasets
einops
gradio==3.50.*
gradio==4.23.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
@ -20,7 +20,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.38.*
transformers==4.39.*
tqdm
wandb

View File

@ -1,10 +1,10 @@
accelerate==0.27.*
aqlm[gpu,cpu]==1.1.0; platform_system == "Linux"
aqlm[gpu,cpu]==1.1.2; platform_system == "Linux"
bitsandbytes==0.43.*
colorama
datasets
einops
gradio==3.50.*
gradio==4.23.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
@ -22,7 +22,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.38.*
transformers==4.39.*
tqdm
wandb

View File

@ -2,7 +2,7 @@ accelerate==0.27.*
colorama
datasets
einops
gradio==3.50.*
gradio==4.23.*
hqq==0.1.5
jinja2==3.1.2
lm_eval==0.3.0
@ -20,7 +20,7 @@ safetensors==0.4.*
scipy
sentencepiece
tensorboard
transformers==4.38.*
transformers==4.39.*
tqdm
wandb

View File

@ -18,6 +18,7 @@ warnings.filterwarnings('ignore', category=UserWarning, message='The value passe
warnings.filterwarnings('ignore', category=UserWarning, message='Field "model_names" has conflict')
with RequestBlocker():
from modules import gradio_hijack
import gradio as gr
import matplotlib
@ -145,11 +146,9 @@ def create_interface():
ui_model_menu.create_event_handlers()
# Interface launch events
if shared.settings['dark_theme']:
shared.gradio['interface'].load(lambda: None, None, None, _js="() => document.getElementsByTagName('body')[0].classList.add('dark')")
shared.gradio['interface'].load(lambda: None, None, None, _js=f"() => {{{js}}}")
shared.gradio['interface'].load(None, gradio('show_controls'), None, _js=f'(x) => {{{ui.show_controls_js}; toggle_controls(x)}}')
shared.gradio['interface'].load(lambda: None, None, None, js=f"() => {{if ({str(shared.settings['dark_theme']).lower()}) {{ document.getElementsByTagName('body')[0].classList.add('dark'); }} }}")
shared.gradio['interface'].load(lambda: None, None, None, js=f"() => {{{js}}}")
shared.gradio['interface'].load(lambda x: None, gradio('show_controls'), None, js=f'(x) => {{{ui.show_controls_js}; toggle_controls(x)}}')
shared.gradio['interface'].load(partial(ui.apply_interface_values, {}, use_persistent=True), None, gradio(ui.list_interface_input_elements()), show_progress=False)
shared.gradio['interface'].load(chat.redraw_html, gradio(ui_chat.reload_arr), gradio('display'))
@ -157,9 +156,10 @@ def create_interface():
extensions_module.create_extensions_block() # Extensions block
# Launch the interface
shared.gradio['interface'].queue(concurrency_count=64)
shared.gradio['interface'].queue()
with OpenMonkeyPatch():
shared.gradio['interface'].launch(
max_threads=64,
prevent_thread_lock=True,
share=shared.args.share,
server_name=None if not shared.args.listen else (shared.args.listen_host or '0.0.0.0'),
@ -168,7 +168,8 @@ def create_interface():
auth=auth or None,
ssl_verify=False if (shared.args.ssl_keyfile or shared.args.ssl_certfile) else True,
ssl_keyfile=shared.args.ssl_keyfile,
ssl_certfile=shared.args.ssl_certfile
ssl_certfile=shared.args.ssl_certfile,
allowed_paths=["cache", "css", "extensions", "js"]
)

View File

@ -15,7 +15,6 @@ truncation_length: 2048
truncation_length_min: 0
truncation_length_max: 200000
max_tokens_second: 0
max_updates_second: 0
prompt_lookup_num_tokens: 0
custom_stopping_strings: ''
custom_token_bans: ''