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Automatically set wbits/groupsize/instruct based on model name (#1167)

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oobabooga 2023-04-14 11:07:28 -03:00 committed by GitHub
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7 changed files with 377 additions and 286 deletions
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31
models/config.yaml Normal file
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@ -0,0 +1,31 @@
.*:
wbits: 'None'
model_type: 'None'
groupsize: 'None'
pre_layer: 0
mode: 'cai-chat'
llama-[0-9]*b-4bit$:
wbits: 4
groupsize: -1
model_type: 'llama'
.*-(4bit|int4)-(gr128|128g):
wbits: 4
groupsize: 128
.*-(gr128|128g)-(4bit|int4):
wbits: 4
groupsize: 128
.*-3bit-(gr128|128g):
wbits: 3
groupsize: 128
.*-(gr128|128g)-3bit:
wbits: 3
groupsize: 128
.*oasst-sft-1-pythia-12b:
mode: 'instruct'
instruction_template: 'Open Assistant'
.*vicuna:
mode: 'instruct'
instruction_template: 'Vicuna'
.*alpaca:
mode: 'instruct'
instruction_template: 'Alpaca'

2
modules/chat.py
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@ -79,7 +79,7 @@ def get_stopping_strings(state):
stopping_strings = [f"\n{state['name1']}", f"\n{state['name2']}"]
else:
stopping_strings = [f"\n{state['name1']}:", f"\n{state['name2']}:"]
stopping_strings += state['custom_stopping_strings']
stopping_strings += eval(f"[{state['custom_stopping_strings']}]")
return stopping_strings

22
modules/shared.py
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@ -1,4 +1,7 @@
import argparse
from pathlib import Path
import yaml
model = None
tokenizer = None
@ -42,6 +45,7 @@ settings = {
'truncation_length_min': 0,
'truncation_length_max': 4096,
'mode': 'cai-chat',
'instruction_template': 'None',
'chat_prompt_size': 2048,
'chat_prompt_size_min': 0,
'chat_prompt_size_max': 2048,
@ -159,3 +163,21 @@ if args.cai_chat:
def is_chat():
return args.chat
# Loading model-specific settings (default)
with Path(f'{args.model_dir}/config.yaml') as p:
if p.exists():
model_config = yaml.safe_load(open(p, 'r').read())
else:
model_config = {}
# Applying user-defined model settings
with Path(f'{args.model_dir}/config-user.yaml') as p:
if p.exists():
user_config = yaml.safe_load(open(p, 'r').read())
for k in user_config:
if k in model_config:
model_config[k].update(user_config[k])
else:
model_config[k] = user_config[k]

2
modules/text_generation.py
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@ -192,7 +192,7 @@ def generate_reply(question, state, eos_token=None, stopping_strings=[]):
# Handling the stopping strings
stopping_criteria_list = transformers.StoppingCriteriaList()
for st in [stopping_strings, state['custom_stopping_strings']]:
for st in [stopping_strings, eval(f"[{state['custom_stopping_strings']}]")]:
if type(st) is list and len(st) > 0:
sentinel_token_ids = [encode(string, add_special_tokens=False) for string in st]
stopping_criteria_list.append(_SentinelTokenStoppingCriteria(sentinel_token_ids=sentinel_token_ids, starting_idx=len(input_ids[0])))

16
modules/ui.py
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@ -1,6 +1,7 @@
from pathlib import Path
import gradio as gr
import torch
from modules import shared
@ -16,10 +17,18 @@ with open(Path(__file__).resolve().parent / '../css/chat.js', 'r') as f:
chat_js = f.read()
def list_model_elements():
elements = ['cpu_memory', 'auto_devices', 'disk', 'cpu', 'bf16', 'load_in_8bit', 'wbits', 'groupsize', 'model_type', 'pre_layer']
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', 'repetition_penalty', 'encoder_repetition_penalty', 'no_repeat_ngram_size', 'min_length', 'do_sample', 'penalty_alpha', 'num_beams', 'length_penalty', 'early_stopping', 'add_bos_token', 'ban_eos_token', 'truncation_length', 'custom_stopping_strings']
if chat:
elements += ['name1', 'name2', 'greeting', 'context', 'end_of_turn', 'chat_prompt_size', 'chat_generation_attempts', 'stop_at_newline', 'mode']
elements += ['name1', 'name2', 'greeting', 'context', 'end_of_turn', 'chat_prompt_size', 'chat_generation_attempts', 'stop_at_newline', 'mode', 'instruction_template']
elements += list_model_elements()
return elements
@ -27,10 +36,13 @@ def gather_interface_values(*args):
output = {}
for i, element in enumerate(shared.input_elements):
output[element] = args[i]
output['custom_stopping_strings'] = eval(f"[{output['custom_stopping_strings']}]")
return output
def apply_interface_values(state):
return [state[i] for i in list_interface_input_elements(chat=shared.is_chat())]
class ToolButton(gr.Button, gr.components.FormComponent):
"""Small button with single emoji as text, fits inside gradio forms"""

589
server.py
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@ -30,31 +30,12 @@ from modules.LoRA import add_lora_to_model
from modules.models import load_model, load_soft_prompt, unload_model
from modules.text_generation import generate_reply, stop_everything_event
# Loading custom settings
settings_file = None
if shared.args.settings is not None and Path(shared.args.settings).exists():
settings_file = Path(shared.args.settings)
elif Path('settings.json').exists():
settings_file = Path('settings.json')
if settings_file is not None:
print(f"Loading settings from {settings_file}...")
new_settings = json.loads(open(settings_file, 'r').read())
for item in new_settings:
shared.settings[item] = new_settings[item]
def special_sort(model_name):
if '_' in model_name:
return ('_'.join(model_name.split('_')[1:])).lower()
else:
return model_name.lower()
def get_available_models():
if shared.args.flexgen:
return sorted([re.sub('-np$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if item.name.endswith('-np')], key=special_sort)
return sorted([re.sub('-np$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if item.name.endswith('-np')], key=str.lower)
else:
return sorted([re.sub('.pth$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=special_sort)
return sorted([re.sub('.pth$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)
def get_available_presets():
@ -91,7 +72,7 @@ def get_available_softprompts():
def get_available_loras():
return ['None'] + sorted([item.name for item in list(Path(shared.args.lora_dir).glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=special_sort)
return ['None'] + sorted([item.name for item in list(Path(shared.args.lora_dir).glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)
def load_model_wrapper(selected_model):
@ -202,42 +183,36 @@ def download_model_wrapper(repo_id):
yield traceback.format_exc()
# Model parameters: list the relevant interface elements
def list_model_parameters():
parameters = ['cpu_memory', 'auto_devices', 'disk', 'cpu', 'bf16', 'load_in_8bit', 'wbits', 'groupsize', 'model_type', 'pre_layer']
for i in range(torch.cuda.device_count()):
parameters.append(f'gpu_memory_{i}')
return parameters
# Model parameters: update the command-line arguments based on the interface values
def update_model_parameters(*args):
args = list(args) # the values of the parameters
elements = list_model_parameters() # the names of the parameters
# Update the command-line arguments based on the interface values
def update_model_parameters(state):
elements = ui.list_model_elements() # the names of the parameters
gpu_memories = []
for i, element in enumerate(elements):
if element.startswith('gpu_memory'):
gpu_memories.append(args[i])
if element not in state:
continue
if element == 'cpu_memory' and args[i] == 0:
args[i] = None
if element == 'wbits' and args[i] == 'None':
args[i] = 0
if element == 'groupsize' and args[i] == 'None':
args[i] = -1
if element == 'model_type' and args[i] == 'None':
args[i] = None
if element in ['wbits', 'groupsize', 'pre_layer']:
args[i] = int(args[i])
elif element == 'cpu_memory' and args[i] is not None:
args[i] = f"{args[i]}MiB"
value = state[element]
# print(element, repr(eval(f"shared.args.{element}")), repr(args[i]))
# print(f"shared.args.{element} = args[i]")
exec(f"shared.args.{element} = args[i]")
if element.startswith('gpu_memory'):
gpu_memories.append(value)
continue
if element == 'cpu_memory' and value == 0:
value = None
if element == 'wbits' and value == 'None':
value = 0
if element == 'groupsize' and value == 'None':
value = -1
if element == 'model_type' and value == 'None':
value = None
if element in ['wbits', 'groupsize', 'pre_layer']:
value = int(value)
elif element == 'cpu_memory' and value is not None:
value = f"{value}MiB"
exec(f"shared.args.{element} = value")
found_positive = False
for i in gpu_memories:
@ -250,6 +225,27 @@ def update_model_parameters(*args):
shared.args.gpu_memory = None
def get_model_specific_settings(model):
settings = shared.model_config
model_settings = {}
for pat in settings:
if re.match(pat, model.lower()):
for k in settings[pat]:
model_settings[k] = settings[pat][k]
return model_settings
def load_model_specific_settings(model, state, return_dict=False):
model_settings = get_model_specific_settings(model)
for k in model_settings:
if k in state:
state[k] = model_settings[k]
return state
def create_model_menus():
# Finding the default values for the GPU and CPU memories
total_mem = []
@ -272,18 +268,17 @@ def create_model_menus():
else:
default_cpu_mem = 0
components = {}
with gr.Row():
with gr.Column():
with gr.Row():
with gr.Column():
with gr.Row():
shared.gradio['model_menu'] = gr.Dropdown(choices=available_models, value=shared.model_name, label='Model')
shared.gradio['model_menu'] = gr.Dropdown(choices=get_available_models(), value=shared.model_name, label='Model')
ui.create_refresh_button(shared.gradio['model_menu'], lambda: None, lambda: {'choices': get_available_models()}, 'refresh-button')
with gr.Column():
with gr.Row():
shared.gradio['lora_menu'] = gr.Dropdown(choices=available_loras, value=shared.lora_name, label='LoRA')
shared.gradio['lora_menu'] = gr.Dropdown(choices=get_available_loras(), value=shared.lora_name, label='LoRA')
ui.create_refresh_button(shared.gradio['lora_menu'], lambda: None, lambda: {'choices': get_available_loras()}, 'refresh-button')
with gr.Column():
@ -297,27 +292,27 @@ def create_model_menus():
with gr.Row():
with gr.Column():
for i in range(len(total_mem)):
components[f'gpu_memory_{i}'] = gr.Slider(label=f"gpu-memory in MiB for device :{i}", maximum=total_mem[i], value=default_gpu_mem[i])
components['cpu_memory'] = gr.Slider(label="cpu-memory in MiB", maximum=total_cpu_mem, value=default_cpu_mem)
shared.gradio[f'gpu_memory_{i}'] = gr.Slider(label=f"gpu-memory in MiB for device :{i}", maximum=total_mem[i], value=default_gpu_mem[i])
shared.gradio['cpu_memory'] = gr.Slider(label="cpu-memory in MiB", maximum=total_cpu_mem, value=default_cpu_mem)
with gr.Column():
components['auto_devices'] = gr.Checkbox(label="auto-devices", value=shared.args.auto_devices)
components['disk'] = gr.Checkbox(label="disk", value=shared.args.disk)
components['cpu'] = gr.Checkbox(label="cpu", value=shared.args.cpu)
components['bf16'] = gr.Checkbox(label="bf16", value=shared.args.bf16)
components['load_in_8bit'] = gr.Checkbox(label="load-in-8bit", value=shared.args.load_in_8bit)
shared.gradio['auto_devices'] = gr.Checkbox(label="auto-devices", value=shared.args.auto_devices)
shared.gradio['disk'] = gr.Checkbox(label="disk", value=shared.args.disk)
shared.gradio['cpu'] = gr.Checkbox(label="cpu", value=shared.args.cpu)
shared.gradio['bf16'] = gr.Checkbox(label="bf16", value=shared.args.bf16)
shared.gradio['load_in_8bit'] = gr.Checkbox(label="load-in-8bit", value=shared.args.load_in_8bit)
with gr.Column():
with gr.Box():
gr.Markdown('GPTQ parameters')
with gr.Row():
with gr.Column():
components['wbits'] = gr.Dropdown(label="wbits", choices=["None", 1, 2, 3, 4, 8], value=shared.args.wbits if shared.args.wbits > 0 else "None")
components['groupsize'] = gr.Dropdown(label="groupsize", choices=["None", 32, 64, 128], value=shared.args.groupsize if shared.args.groupsize > 0 else "None")
shared.gradio['wbits'] = gr.Dropdown(label="wbits", choices=["None", 1, 2, 3, 4, 8], value=shared.args.wbits if shared.args.wbits > 0 else "None")
shared.gradio['groupsize'] = gr.Dropdown(label="groupsize", choices=["None", 32, 64, 128], value=shared.args.groupsize if shared.args.groupsize > 0 else "None")
with gr.Column():
components['model_type'] = gr.Dropdown(label="model_type", choices=["None", "llama", "opt", "gptj"], value=shared.args.model_type or "None")
components['pre_layer'] = gr.Slider(label="pre_layer", minimum=0, maximum=100, value=shared.args.pre_layer)
shared.gradio['model_type'] = gr.Dropdown(label="model_type", choices=["None", "llama", "opt", "gptj"], value=shared.args.model_type or "None")
shared.gradio['pre_layer'] = gr.Slider(label="pre_layer", minimum=0, maximum=100, value=shared.args.pre_layer)
with gr.Row():
with gr.Column():
@ -327,8 +322,13 @@ def create_model_menus():
with gr.Column():
shared.gradio['model_status'] = gr.Markdown('No model is loaded' if shared.model_name == 'None' else 'Ready')
# In this event handler, the interface state is read and updated
# with the model defaults (if any), and then the model is loaded
shared.gradio['model_menu'].change(
update_model_parameters, [components[k] for k in list_model_parameters()], None).then(
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
load_model_specific_settings, [shared.gradio[k] for k in ['model_menu', 'interface_state']], shared.gradio['interface_state']).then(
ui.apply_interface_values, shared.gradio['interface_state'], [shared.gradio[k] for k in ui.list_interface_input_elements(chat=shared.is_chat())], show_progress=False).then(
update_model_parameters, shared.gradio['interface_state'], None).then(
load_model_wrapper, shared.gradio['model_menu'], shared.gradio['model_status'], show_progress=True)
unload.click(
@ -337,7 +337,8 @@ def create_model_menus():
reload.click(
unload_model, None, None).then(
update_model_parameters, [components[k] for k in list_model_parameters()], None).then(
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
update_model_parameters, shared.gradio['interface_state'], None).then(
load_model_wrapper, shared.gradio['model_menu'], shared.gradio['model_status'], show_progress=True)
shared.gradio['lora_menu'].change(load_lora_wrapper, shared.gradio['lora_menu'], shared.gradio['lora_menu'], show_progress=True)
@ -351,7 +352,7 @@ def create_settings_menus(default_preset):
with gr.Row():
with gr.Column():
with gr.Row():
shared.gradio['preset_menu'] = gr.Dropdown(choices=available_presets, value=default_preset if not shared.args.flexgen else 'Naive', label='Generation parameters preset')
shared.gradio['preset_menu'] = gr.Dropdown(choices=get_available_presets(), value=default_preset if not shared.args.flexgen else 'Naive', label='Generation parameters preset')
ui.create_refresh_button(shared.gradio['preset_menu'], lambda: None, lambda: {'choices': get_available_presets()}, 'refresh-button')
with gr.Column():
shared.gradio['seed'] = gr.Number(value=shared.settings['seed'], label='Seed (-1 for random)')
@ -394,7 +395,7 @@ def create_settings_menus(default_preset):
with gr.Accordion('Soft prompt', open=False):
with gr.Row():
shared.gradio['softprompts_menu'] = gr.Dropdown(choices=available_softprompts, value='None', label='Soft prompt')
shared.gradio['softprompts_menu'] = gr.Dropdown(choices=get_available_softprompts(), value='None', label='Soft prompt')
ui.create_refresh_button(shared.gradio['softprompts_menu'], lambda: None, lambda: {'choices': get_available_softprompts()}, 'refresh-button')
gr.Markdown('Upload a soft prompt (.zip format):')
@ -425,70 +426,34 @@ def set_interface_arguments(interface_mode, extensions, bool_active):
shared.need_restart = True
available_models = get_available_models()
available_presets = get_available_presets()
available_characters = get_available_characters()
available_softprompts = get_available_softprompts()
available_loras = get_available_loras()
# Default extensions
extensions_module.available_extensions = get_available_extensions()
if shared.is_chat():
for extension in shared.settings['chat_default_extensions']:
shared.args.extensions = shared.args.extensions or []
if extension not in shared.args.extensions:
shared.args.extensions.append(extension)
else:
for extension in shared.settings['default_extensions']:
shared.args.extensions = shared.args.extensions or []
if extension not in shared.args.extensions:
shared.args.extensions.append(extension)
# Model defined through --model
if shared.args.model is not None:
shared.model_name = shared.args.model
# Only one model is available
elif len(available_models) == 1:
shared.model_name = available_models[0]
# Select the model from a command-line menu
elif shared.args.model_menu:
if len(available_models) == 0:
print('No models are available! Please download at least one.')
sys.exit(0)
else:
print('The following models are available:\n')
for i, model in enumerate(available_models):
print(f'{i+1}. {model}')
print(f'\nWhich one do you want to load? 1-{len(available_models)}\n')
i = int(input()) - 1
print()
shared.model_name = available_models[i]
# If any model has been selected, load it
if shared.model_name != 'None':
shared.model, shared.tokenizer = load_model(shared.model_name)
if shared.args.lora:
add_lora_to_model(shared.args.lora)
# Default UI settings
default_preset = shared.settings['presets'][next((k for k in shared.settings['presets'] if re.match(k.lower(), shared.model_name.lower())), 'default')]
if shared.lora_name != "None":
default_text = load_prompt(shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_name.lower())), 'default')])
else:
default_text = load_prompt(shared.settings['prompts'][next((k for k in shared.settings['prompts'] if re.match(k.lower(), shared.model_name.lower())), 'default')])
title = 'Text generation web UI'
def create_interface():
# Defining some variables
gen_events = []
default_preset = shared.settings['presets'][next((k for k in shared.settings['presets'] if re.match(k.lower(), shared.model_name.lower())), 'default')]
if shared.lora_name != "None":
default_text = load_prompt(shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_name.lower())), 'default')])
else:
default_text = load_prompt(shared.settings['prompts'][next((k for k in shared.settings['prompts'] if re.match(k.lower(), shared.model_name.lower())), 'default')])
title = 'Text generation web UI'
# Authentication variables
auth = None
if shared.args.gradio_auth_path is not None:
gradio_auth_creds = []
with open(shared.args.gradio_auth_path, 'r', encoding="utf8") as file:
for line in file.readlines():
gradio_auth_creds += [x.strip() for x in line.split(',') if x.strip()]
auth = [tuple(cred.split(':')) for cred in gradio_auth_creds]
# Importing the extension files and executing their setup() functions
if shared.args.extensions is not None and len(shared.args.extensions) > 0:
extensions_module.load_extensions()
with gr.Blocks(css=ui.css if not shared.is_chat() else ui.css + ui.chat_css, analytics_enabled=False, title=title) as shared.gradio['interface']:
if shared.is_chat():
# Create chat mode interface
if shared.is_chat():
shared.input_elements = ui.list_interface_input_elements(chat=True)
shared.gradio['interface_state'] = gr.State({k: None for k in shared.input_elements})
shared.gradio['Chat input'] = gr.State()
@ -499,15 +464,18 @@ def create_interface():
with gr.Row():
shared.gradio['Generate'] = gr.Button('Generate', elem_id='Generate')
shared.gradio['Stop'] = gr.Button('Stop', elem_id='stop')
with gr.Row():
shared.gradio['Regenerate'] = gr.Button('Regenerate')
shared.gradio['Continue'] = gr.Button('Continue')
shared.gradio['Impersonate'] = gr.Button('Impersonate')
with gr.Row():
shared.gradio['Send dummy message'] = gr.Button('Send dummy message')
shared.gradio['Send dummy reply'] = gr.Button('Send dummy reply')
shared.gradio['Replace last reply'] = gr.Button('Replace last reply')
shared.gradio['Copy last reply'] = gr.Button('Copy last reply')
with gr.Row():
shared.gradio['Clear history'] = gr.Button('Clear history')
shared.gradio['Clear history-confirm'] = gr.Button('Confirm', variant='stop', visible=False)
@ -515,7 +483,7 @@ def create_interface():
shared.gradio['Remove last'] = gr.Button('Remove last')
shared.gradio['mode'] = gr.Radio(choices=['cai-chat', 'chat', 'instruct'], value=shared.settings['mode'], label='Mode')
shared.gradio['Instruction templates'] = gr.Dropdown(choices=get_available_instruction_templates(), label='Instruction template', value='None', visible=False, info='Change this according to the model/LoRA that you are using.')
shared.gradio['instruction_template'] = gr.Dropdown(choices=get_available_instruction_templates(), label='Instruction template', value=shared.settings['instruction_template'], visible=shared.settings['mode'] == 'instruct', info='Change this according to the model/LoRA that you are using.')
with gr.Tab('Character', elem_id='chat-settings'):
with gr.Row():
@ -525,11 +493,13 @@ def create_interface():
shared.gradio['greeting'] = gr.Textbox(value=shared.settings['greeting'], lines=4, label='Greeting')
shared.gradio['context'] = gr.Textbox(value=shared.settings['context'], lines=4, label='Context')
shared.gradio['end_of_turn'] = gr.Textbox(value=shared.settings['end_of_turn'], lines=1, label='End of turn string')
with gr.Column(scale=1):
shared.gradio['character_picture'] = gr.Image(label='Character picture', type='pil')
shared.gradio['your_picture'] = gr.Image(label='Your picture', type='pil', value=Image.open(Path('cache/pfp_me.png')) if Path('cache/pfp_me.png').exists() else None)
with gr.Row():
shared.gradio['character_menu'] = gr.Dropdown(choices=available_characters, value='None', label='Character', elem_id='character-menu')
shared.gradio['character_menu'] = gr.Dropdown(choices=get_available_characters(), value='None', label='Character', elem_id='character-menu')
ui.create_refresh_button(shared.gradio['character_menu'], lambda: None, lambda: {'choices': get_available_characters()}, 'refresh-button')
with gr.Row():
@ -538,21 +508,24 @@ def create_interface():
with gr.Column():
gr.Markdown('Upload')
shared.gradio['upload_chat_history'] = gr.File(type='binary', file_types=['.json', '.txt'])
with gr.Column():
gr.Markdown('Download')
shared.gradio['download'] = gr.File()
shared.gradio['download_button'] = gr.Button(value='Click me')
with gr.Tab('Upload character'):
gr.Markdown('# JSON format')
with gr.Row():
with gr.Column():
gr.Markdown('1. Select the JSON file')
shared.gradio['upload_json'] = gr.File(type='binary', file_types=['.json'])
with gr.Column():
gr.Markdown('2. Select your character\'s profile picture (optional)')
shared.gradio['upload_img_bot'] = gr.File(type='binary', file_types=['image'])
shared.gradio['Upload character'] = gr.Button(value='Submit')
shared.gradio['Upload character'] = gr.Button(value='Submit')
gr.Markdown('# TavernAI PNG format')
shared.gradio['upload_img_tavern'] = gr.File(type='binary', file_types=['image'])
@ -563,12 +536,132 @@ def create_interface():
with gr.Column():
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['chat_prompt_size'] = gr.Slider(minimum=shared.settings['chat_prompt_size_min'], maximum=shared.settings['chat_prompt_size_max'], step=1, label='Maximum prompt size in tokens', value=shared.settings['chat_prompt_size'])
with gr.Column():
shared.gradio['chat_generation_attempts'] = gr.Slider(minimum=shared.settings['chat_generation_attempts_min'], maximum=shared.settings['chat_generation_attempts_max'], value=shared.settings['chat_generation_attempts'], step=1, label='Generation attempts (for longer replies)')
shared.gradio['stop_at_newline'] = gr.Checkbox(value=shared.settings['stop_at_newline'], label='Stop generating at new line character')
create_settings_menus(default_preset)
# Create notebook mode interface
elif shared.args.notebook:
shared.input_elements = ui.list_interface_input_elements(chat=False)
shared.gradio['interface_state'] = gr.State({k: None for k in shared.input_elements})
with gr.Tab("Text generation", elem_id="main"):
with gr.Row():
with gr.Column(scale=4):
with gr.Tab('Raw'):
shared.gradio['textbox'] = gr.Textbox(value=default_text, elem_id="textbox", lines=27)
with gr.Tab('Markdown'):
shared.gradio['markdown'] = gr.Markdown()
with gr.Tab('HTML'):
shared.gradio['html'] = gr.HTML()
with gr.Row():
with gr.Column():
with gr.Row():
shared.gradio['Generate'] = gr.Button('Generate')
shared.gradio['Stop'] = gr.Button('Stop')
with gr.Column():
pass
with gr.Column(scale=1):
gr.HTML('<div style="padding-bottom: 13px"></div>')
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'])
with gr.Row():
shared.gradio['prompt_menu'] = gr.Dropdown(choices=get_available_prompts(), value='None', label='Prompt')
ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': get_available_prompts()}, 'refresh-button')
shared.gradio['save_prompt'] = gr.Button('Save prompt')
shared.gradio['status'] = gr.Markdown('')
with gr.Tab("Parameters", elem_id="parameters"):
create_settings_menus(default_preset)
# Create default mode interface
else:
shared.input_elements = ui.list_interface_input_elements(chat=False)
shared.gradio['interface_state'] = gr.State({k: None for k in shared.input_elements})
with gr.Tab("Text generation", elem_id="main"):
with gr.Row():
with gr.Column():
shared.gradio['textbox'] = gr.Textbox(value=default_text, lines=21, label='Input')
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'])
with gr.Row():
with gr.Column():
shared.gradio['Generate'] = gr.Button('Generate')
shared.gradio['Continue'] = gr.Button('Continue')
with gr.Column():
shared.gradio['Stop'] = gr.Button('Stop')
shared.gradio['save_prompt'] = gr.Button('Save prompt')
with gr.Row():
with gr.Column():
with gr.Row():
shared.gradio['prompt_menu'] = gr.Dropdown(choices=get_available_prompts(), value='None', label='Prompt')
ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': get_available_prompts()}, 'refresh-button')
with gr.Column():
shared.gradio['status'] = gr.Markdown('')
with gr.Column():
with gr.Tab('Raw'):
shared.gradio['output_textbox'] = gr.Textbox(lines=27, label='Output')
with gr.Tab('Markdown'):
shared.gradio['markdown'] = gr.Markdown()
with gr.Tab('HTML'):
shared.gradio['html'] = gr.HTML()
with gr.Tab("Parameters", elem_id="parameters"):
create_settings_menus(default_preset)
# Model tab
with gr.Tab("Model", elem_id="model-tab"):
create_model_menus()
# Training tab
with gr.Tab("Training", elem_id="training-tab"):
training.create_train_interface()
# Interface mode tab
with gr.Tab("Interface mode", elem_id="interface-mode"):
modes = ["default", "notebook", "chat", "cai_chat"]
current_mode = "default"
for mode in modes[1:]:
if eval(f"shared.args.{mode}"):
current_mode = mode
break
cmd_list = vars(shared.args)
bool_list = [k for k in cmd_list if type(cmd_list[k]) is bool and k not in modes + ui.list_model_elements()]
bool_active = [k for k in bool_list if vars(shared.args)[k]]
gr.Markdown("*Experimental*")
shared.gradio['interface_modes_menu'] = gr.Dropdown(choices=modes, value=current_mode, label="Mode")
shared.gradio['extensions_menu'] = gr.CheckboxGroup(choices=get_available_extensions(), value=shared.args.extensions, label="Available extensions")
shared.gradio['bool_menu'] = gr.CheckboxGroup(choices=bool_list, value=bool_active, label="Boolean command-line flags")
shared.gradio['reset_interface'] = gr.Button("Apply and restart the interface")
# Reset interface event
shared.gradio['reset_interface'].click(
set_interface_arguments, [shared.gradio[k] for k in ['interface_modes_menu', 'extensions_menu', 'bool_menu']], None).then(
lambda: None, None, None, _js='() => {document.body.innerHTML=\'<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>\'; setTimeout(function(){location.reload()},2500); return []}')
# Extensions block
if shared.args.extensions is not None:
extensions_module.create_extensions_block()
# Create the invisible elements that define the API
if not shared.is_chat():
api.create_apis()
# chat mode event handlers
if shared.is_chat():
shared.input_params = [shared.gradio[k] for k in ['Chat input', 'interface_state']]
clear_arr = [shared.gradio[k] for k in ['Clear history-confirm', 'Clear history', 'Clear history-cancel']]
reload_inputs = [shared.gradio[k] for k in ['name1', 'name2', 'mode']]
@ -629,12 +722,12 @@ def create_interface():
chat.redraw_html, reload_inputs, shared.gradio['display'])
shared.gradio['mode'].change(
lambda x: gr.update(visible=x == 'instruct'), shared.gradio['mode'], shared.gradio['Instruction templates']).then(
lambda x: gr.update(visible=x == 'instruct'), shared.gradio['mode'], shared.gradio['instruction_template']).then(
lambda x: gr.update(interactive=x != 'instruct'), shared.gradio['mode'], shared.gradio['character_menu']).then(
chat.redraw_html, reload_inputs, shared.gradio['display'])
shared.gradio['Instruction templates'].change(
lambda character, name1, name2, mode: chat.load_character(character, name1, name2, mode), [shared.gradio[k] for k in ['Instruction templates', 'name1', 'name2', 'mode']], [shared.gradio[k] for k in ['name1', 'name2', 'character_picture', 'greeting', 'context', 'end_of_turn', 'display']]).then(
shared.gradio['instruction_template'].change(
lambda character, name1, name2, mode: chat.load_character(character, name1, name2, mode), [shared.gradio[k] for k in ['instruction_template', 'name1', 'name2', 'mode']], [shared.gradio[k] for k in ['name1', 'name2', 'character_picture', 'greeting', 'context', 'end_of_turn', 'display']]).then(
chat.redraw_html, reload_inputs, shared.gradio['display'])
shared.gradio['upload_chat_history'].upload(
@ -655,117 +748,29 @@ def create_interface():
shared.gradio['interface'].load(chat.load_default_history, [shared.gradio[k] for k in ['name1', 'name2']], None)
shared.gradio['interface'].load(chat.redraw_html, reload_inputs, shared.gradio['display'], show_progress=True)
elif shared.args.notebook:
shared.input_elements = ui.list_interface_input_elements(chat=False)
shared.gradio['interface_state'] = gr.State({k: None for k in shared.input_elements})
with gr.Tab("Text generation", elem_id="main"):
with gr.Row():
with gr.Column(scale=4):
with gr.Tab('Raw'):
shared.gradio['textbox'] = gr.Textbox(value=default_text, elem_id="textbox", lines=27)
with gr.Tab('Markdown'):
shared.gradio['markdown'] = gr.Markdown()
with gr.Tab('HTML'):
shared.gradio['html'] = gr.HTML()
with gr.Row():
with gr.Column():
with gr.Row():
shared.gradio['Generate'] = gr.Button('Generate')
shared.gradio['Stop'] = gr.Button('Stop')
with gr.Column():
pass
with gr.Column(scale=1):
gr.HTML('<div style="padding-bottom: 13px"></div>')
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'])
with gr.Row():
shared.gradio['prompt_menu'] = gr.Dropdown(choices=get_available_prompts(), value='None', label='Prompt')
ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': get_available_prompts()}, 'refresh-button')
shared.gradio['save_prompt'] = gr.Button('Save prompt')
shared.gradio['status'] = gr.Markdown('')
with gr.Tab("Parameters", elem_id="parameters"):
create_settings_menus(default_preset)
shared.input_params = [shared.gradio[k] for k in ['textbox', 'interface_state']]
output_params = [shared.gradio[k] for k in ['textbox', 'markdown', 'html']]
gen_events.append(shared.gradio['Generate'].click(
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream) # .then(
# None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[0]; element.scrollTop = element.scrollHeight}")
)
gen_events.append(shared.gradio['textbox'].submit(
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream) # .then(
# None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[0]; element.scrollTop = element.scrollHeight}")
)
shared.gradio['Stop'].click(stop_everything_event, None, None, queue=False, cancels=gen_events if shared.args.no_stream else None)
shared.gradio['prompt_menu'].change(load_prompt, [shared.gradio['prompt_menu']], [shared.gradio['textbox']], show_progress=False)
shared.gradio['save_prompt'].click(save_prompt, [shared.gradio['textbox']], [shared.gradio['status']], show_progress=False)
shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js}}}")
# notebook/default modes event handlers
else:
shared.input_elements = ui.list_interface_input_elements(chat=False)
shared.gradio['interface_state'] = gr.State({k: None for k in shared.input_elements})
with gr.Tab("Text generation", elem_id="main"):
with gr.Row():
with gr.Column():
shared.gradio['textbox'] = gr.Textbox(value=default_text, lines=21, label='Input')
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'])
with gr.Row():
with gr.Column():
shared.gradio['Generate'] = gr.Button('Generate')
shared.gradio['Continue'] = gr.Button('Continue')
with gr.Column():
shared.gradio['Stop'] = gr.Button('Stop')
shared.gradio['save_prompt'] = gr.Button('Save prompt')
with gr.Row():
with gr.Column():
with gr.Row():
shared.gradio['prompt_menu'] = gr.Dropdown(choices=get_available_prompts(), value='None', label='Prompt')
ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': get_available_prompts()}, 'refresh-button')
with gr.Column():
shared.gradio['status'] = gr.Markdown('')
with gr.Column():
with gr.Tab('Raw'):
shared.gradio['output_textbox'] = gr.Textbox(lines=27, label='Output')
with gr.Tab('Markdown'):
shared.gradio['markdown'] = gr.Markdown()
with gr.Tab('HTML'):
shared.gradio['html'] = gr.HTML()
with gr.Tab("Parameters", elem_id="parameters"):
create_settings_menus(default_preset)
shared.input_params = [shared.gradio[k] for k in ['textbox', 'interface_state']]
output_params = [shared.gradio[k] for k in ['output_textbox', 'markdown', 'html']]
if shared.args.notebook:
output_params = [shared.gradio[k] for k in ['textbox', 'markdown', 'html']]
else:
output_params = [shared.gradio[k] for k in ['output_textbox', 'markdown', 'html']]
gen_events.append(shared.gradio['Continue'].click(
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
generate_reply, [shared.gradio['output_textbox']] + shared.input_params[1:], output_params, show_progress=shared.args.no_stream) # .then(
# None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[1]; element.scrollTop = element.scrollHeight}")
)
gen_events.append(shared.gradio['Generate'].click(
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream) # .then(
# None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[1]; element.scrollTop = element.scrollHeight}")
# None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[0]; element.scrollTop = element.scrollHeight}")
)
gen_events.append(shared.gradio['textbox'].submit(
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
generate_reply, shared.input_params, output_params, show_progress=shared.args.no_stream) # .then(
# None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[1]; element.scrollTop = element.scrollHeight}")
)
gen_events.append(shared.gradio['Continue'].click(
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
generate_reply, [shared.gradio['output_textbox']] + shared.input_params[1:], output_params, show_progress=shared.args.no_stream) # .then(
# None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[1]; element.scrollTop = element.scrollHeight}")
# None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[0]; element.scrollTop = element.scrollHeight}")
)
shared.gradio['Stop'].click(stop_everything_event, None, None, queue=False, cancels=gen_events if shared.args.no_stream else None)
@ -773,49 +778,6 @@ def create_interface():
shared.gradio['save_prompt'].click(save_prompt, [shared.gradio['textbox']], [shared.gradio['status']], show_progress=False)
shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js}}}")
with gr.Tab("Model", elem_id="model-tab"):
create_model_menus()
with gr.Tab("Training", elem_id="training-tab"):
training.create_train_interface()
with gr.Tab("Interface mode", elem_id="interface-mode"):
modes = ["default", "notebook", "chat", "cai_chat"]
current_mode = "default"
for mode in modes[1:]:
if eval(f"shared.args.{mode}"):
current_mode = mode
break
cmd_list = vars(shared.args)
bool_list = [k for k in cmd_list if type(cmd_list[k]) is bool and k not in modes + list_model_parameters()]
bool_active = [k for k in bool_list if vars(shared.args)[k]]
gr.Markdown("*Experimental*")
shared.gradio['interface_modes_menu'] = gr.Dropdown(choices=modes, value=current_mode, label="Mode")
shared.gradio['extensions_menu'] = gr.CheckboxGroup(choices=get_available_extensions(), value=shared.args.extensions, label="Available extensions")
shared.gradio['bool_menu'] = gr.CheckboxGroup(choices=bool_list, value=bool_active, label="Boolean command-line flags")
shared.gradio['reset_interface'] = gr.Button("Apply and restart the interface")
# Reset interface event
shared.gradio['reset_interface'].click(
set_interface_arguments, [shared.gradio[k] for k in ['interface_modes_menu', 'extensions_menu', 'bool_menu']], None).then(
lambda: None, None, None, _js='() => {document.body.innerHTML=\'<h1 style="font-family:monospace;margin-top:20%;color:lightgray;text-align:center;">Reloading...</h1>\'; setTimeout(function(){location.reload()},2500); return []}')
if shared.args.extensions is not None:
extensions_module.create_extensions_block()
if not shared.is_chat():
api.create_apis()
# Authentication
auth = None
if shared.args.gradio_auth_path is not None:
gradio_auth_creds = []
with open(shared.args.gradio_auth_path, 'r', encoding="utf8") as file:
for line in file.readlines():
gradio_auth_creds += [x.strip() for x in line.split(',') if x.strip()]
auth = [tuple(cred.split(':')) for cred in gradio_auth_creds]
# Launch the interface
shared.gradio['interface'].queue()
if shared.args.listen:
@ -824,11 +786,74 @@ def create_interface():
shared.gradio['interface'].launch(prevent_thread_lock=True, share=shared.args.share, server_port=shared.args.listen_port, inbrowser=shared.args.auto_launch, auth=auth)
create_interface()
if __name__ == "__main__":
while True:
time.sleep(0.5)
if shared.need_restart:
shared.need_restart = False
shared.gradio['interface'].close()
create_interface()
# Loading custom settings
settings_file = None
if shared.args.settings is not None and Path(shared.args.settings).exists():
settings_file = Path(shared.args.settings)
elif Path('settings.json').exists():
settings_file = Path('settings.json')
if settings_file is not None:
print(f"Loading settings from {settings_file}...")
new_settings = json.loads(open(settings_file, 'r').read())
for item in new_settings:
shared.settings[item] = new_settings[item]
# Default extensions
extensions_module.available_extensions = get_available_extensions()
if shared.is_chat():
for extension in shared.settings['chat_default_extensions']:
shared.args.extensions = shared.args.extensions or []
if extension not in shared.args.extensions:
shared.args.extensions.append(extension)
else:
for extension in shared.settings['default_extensions']:
shared.args.extensions = shared.args.extensions or []
if extension not in shared.args.extensions:
shared.args.extensions.append(extension)
available_models = get_available_models()
# Model defined through --model
if shared.args.model is not None:
shared.model_name = shared.args.model
# Only one model is available
elif len(available_models) == 1:
shared.model_name = available_models[0]
# Select the model from a command-line menu
elif shared.args.model_menu:
if len(available_models) == 0:
print('No models are available! Please download at least one.')
sys.exit(0)
else:
print('The following models are available:\n')
for i, model in enumerate(available_models):
print(f'{i+1}. {model}')
print(f'\nWhich one do you want to load? 1-{len(available_models)}\n')
i = int(input()) - 1
print()
shared.model_name = available_models[i]
# If any model has been selected, load it
if shared.model_name != 'None':
model_settings = get_model_specific_settings(shared.model_name)
shared.settings.update(model_settings) # hijacking the interface defaults
update_model_parameters(model_settings) # hijacking the command-line arguments
# Load the model
shared.model, shared.tokenizer = load_model(shared.model_name)
if shared.args.lora:
add_lora_to_model(shared.args.lora)
# Launch the web UI
create_interface()
while True:
time.sleep(0.5)
if shared.need_restart:
shared.need_restart = False
shared.gradio['interface'].close()
create_interface()

1
settings-template.json
View File

@ -16,6 +16,7 @@
"truncation_length_min": 0,
"truncation_length_max": 4096,
"mode": "cai-chat",
"instruction_template": "None",
"chat_prompt_size": 2048,
"chat_prompt_size_min": 0,
"chat_prompt_size_max": 2048,