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- import os
- os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False'
- import importlib
- import io
- import json
- import os
- import re
- import sys
- import time
- import traceback
- import zipfile
- from datetime import datetime
- from pathlib import Path
- import gradio as gr
- from PIL import Image
- import modules.extensions as extensions_module
- from modules import api, chat, shared, training, ui
- from modules.html_generator import chat_html_wrapper
- 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 get_available_models():
- if shared.args.flexgen:
- return sorted([re.sub('-np$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if item.name.endswith('-np')], key=str.lower)
- else:
- return sorted([re.sub('.pth$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json'))], key=str.lower)
- def get_available_presets():
- return sorted(set((k.stem for k in Path('presets').glob('*.txt'))), key=str.lower)
- def get_available_prompts():
- prompts = []
- prompts += sorted(set((k.stem for k in Path('prompts').glob('[0-9]*.txt'))), key=str.lower, reverse=True)
- prompts += sorted(set((k.stem for k in Path('prompts').glob('*.txt'))), key=str.lower)
- prompts += ['None']
- return prompts
- def get_available_characters():
- paths = (x for x in Path('characters').iterdir() if x.suffix in ('.json', '.yaml', '.yml'))
- return ['None'] + sorted(set((k.stem for k in paths if k.stem != "instruction-following")), key=str.lower)
- def get_available_instruction_templates():
- path = "characters/instruction-following"
- paths = []
- if os.path.exists(path):
- paths = (x for x in Path(path).iterdir() if x.suffix in ('.json', '.yaml', '.yml'))
- return ['None'] + sorted(set((k.stem for k in paths)), key=str.lower)
- def get_available_extensions():
- return sorted(set(map(lambda x: x.parts[1], Path('extensions').glob('*/script.py'))), key=str.lower)
- def get_available_softprompts():
- return ['None'] + sorted(set((k.stem for k in Path('softprompts').glob('*.zip'))), key=str.lower)
- 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=str.lower)
- def load_model_wrapper(selected_model):
- if selected_model != shared.model_name:
- shared.model_name = selected_model
- unload_model()
- if selected_model != '':
- shared.model, shared.tokenizer = load_model(shared.model_name)
- return selected_model
- def load_lora_wrapper(selected_lora):
- add_lora_to_model(selected_lora)
- return selected_lora
- def load_preset_values(preset_menu, state, return_dict=False):
- generate_params = {
- 'do_sample': True,
- 'temperature': 1,
- 'top_p': 1,
- 'typical_p': 1,
- 'repetition_penalty': 1,
- 'encoder_repetition_penalty': 1,
- 'top_k': 50,
- 'num_beams': 1,
- 'penalty_alpha': 0,
- 'min_length': 0,
- 'length_penalty': 1,
- 'no_repeat_ngram_size': 0,
- 'early_stopping': False,
- }
- with open(Path(f'presets/{preset_menu}.txt'), 'r') as infile:
- preset = infile.read()
- for i in preset.splitlines():
- i = i.rstrip(',').strip().split('=')
- if len(i) == 2 and i[0].strip() != 'tokens':
- generate_params[i[0].strip()] = eval(i[1].strip())
- generate_params['temperature'] = min(1.99, generate_params['temperature'])
- if return_dict:
- return generate_params
- else:
- state.update(generate_params)
- return state, *[generate_params[k] for k in ['do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']]
- def upload_soft_prompt(file):
- with zipfile.ZipFile(io.BytesIO(file)) as zf:
- zf.extract('meta.json')
- j = json.loads(open('meta.json', 'r').read())
- name = j['name']
- Path('meta.json').unlink()
- with open(Path(f'softprompts/{name}.zip'), 'wb') as f:
- f.write(file)
- return name
- def save_prompt(text):
- fname = f"{datetime.now().strftime('%Y-%m-%d-%H%M%S')}.txt"
- with open(Path(f'prompts/{fname}'), 'w', encoding='utf-8') as f:
- f.write(text)
- return f"Saved to prompts/{fname}"
- def load_prompt(fname):
- if fname in ['None', '']:
- return ''
- else:
- with open(Path(f'prompts/{fname}.txt'), 'r', encoding='utf-8') as f:
- text = f.read()
- if text[-1] == '\n':
- text = text[:-1]
- return text
- def create_prompt_menus():
- 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():
- with gr.Column():
- shared.gradio['save_prompt'] = gr.Button('Save prompt')
- shared.gradio['status'] = gr.Markdown('Ready')
- 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)
- def download_model_wrapper(repo_id):
- try:
- downloader = importlib.import_module("download-model")
- model = repo_id
- branch = "main"
- check = False
- yield ("Cleaning up the model/branch names")
- model, branch = downloader.sanitize_model_and_branch_names(model, branch)
- yield ("Getting the download links from Hugging Face")
- links, sha256, is_lora = downloader.get_download_links_from_huggingface(model, branch, text_only=False)
- yield ("Getting the output folder")
- output_folder = downloader.get_output_folder(model, branch, is_lora)
- if check:
- yield ("Checking previously downloaded files")
- downloader.check_model_files(model, branch, links, sha256, output_folder)
- else:
- yield (f"Downloading files to {output_folder}")
- downloader.download_model_files(model, branch, links, sha256, output_folder, threads=1)
- yield ("Done!")
- except:
- yield traceback.format_exc()
- def create_model_menus():
- with gr.Row():
- with gr.Column():
- with gr.Row():
- shared.gradio['model_menu'] = gr.Dropdown(choices=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')
- ui.create_refresh_button(shared.gradio['lora_menu'], lambda: None, lambda: {'choices': get_available_loras()}, 'refresh-button')
- with gr.Row():
- with gr.Column():
- with gr.Row():
- with gr.Column():
- shared.gradio['custom_model_menu'] = gr.Textbox(label="Download custom model or LoRA",
- info="Enter Hugging Face username/model path, e.g: facebook/galactica-125m")
- with gr.Column():
- shared.gradio['download_button'] = gr.Button("Download")
- shared.gradio['download_status'] = gr.Markdown()
- with gr.Column():
- pass
- shared.gradio['model_menu'].change(load_model_wrapper, shared.gradio['model_menu'], shared.gradio['model_menu'], show_progress=True)
- shared.gradio['lora_menu'].change(load_lora_wrapper, shared.gradio['lora_menu'], shared.gradio['lora_menu'], show_progress=True)
- shared.gradio['download_button'].click(download_model_wrapper, shared.gradio['custom_model_menu'], shared.gradio['download_status'], show_progress=False)
- def create_settings_menus(default_preset):
- generate_params = load_preset_values(default_preset if not shared.args.flexgen else 'Naive', {}, return_dict=True)
- 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')
- 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)')
- with gr.Row():
- with gr.Column():
- with gr.Box():
- gr.Markdown('Custom generation parameters ([click here to view technical documentation](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.GenerationConfig))')
- with gr.Row():
- with gr.Column():
- shared.gradio['temperature'] = gr.Slider(0.01, 1.99, value=generate_params['temperature'], step=0.01, label='temperature', info='Primary factor to control randomness of outputs. 0 = deterministic (only the most likely token is used). Higher value = more randomness.')
- shared.gradio['top_p'] = gr.Slider(0.0, 1.0, value=generate_params['top_p'], step=0.01, label='top_p', info='If not set to 1, select tokens with probabilities adding up to less than this number. Higher value = higher range of possible random results.')
- shared.gradio['top_k'] = gr.Slider(0, 200, value=generate_params['top_k'], step=1, label='top_k', info='Similar to top_p, but select instead only the top_k most likely tokens. Higher value = higher range of possible random results.')
- shared.gradio['typical_p'] = gr.Slider(0.0, 1.0, value=generate_params['typical_p'], step=0.01, label='typical_p', info='If not set to 1, select only tokens that are at least this much more likely to appear than random tokens, given the prior text.')
- with gr.Column():
- shared.gradio['repetition_penalty'] = gr.Slider(1.0, 1.5, value=generate_params['repetition_penalty'], step=0.01, label='repetition_penalty', info='Exponential penalty factor for repeating prior tokens. 1 means no penalty, higher value = less repetition, lower value = more repetition.')
- shared.gradio['encoder_repetition_penalty'] = gr.Slider(0.8, 1.5, value=generate_params['encoder_repetition_penalty'], step=0.01, label='encoder_repetition_penalty', info='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.')
- shared.gradio['no_repeat_ngram_size'] = gr.Slider(0, 20, step=1, value=generate_params['no_repeat_ngram_size'], label='no_repeat_ngram_size', info='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.')
- shared.gradio['min_length'] = gr.Slider(0, 2000, step=1, value=generate_params['min_length'], label='min_length', info='Minimum generation length in tokens.')
- shared.gradio['do_sample'] = gr.Checkbox(value=generate_params['do_sample'], label='do_sample')
- with gr.Column():
- with gr.Box():
- gr.Markdown('Contrastive search')
- shared.gradio['penalty_alpha'] = gr.Slider(0, 5, value=generate_params['penalty_alpha'], label='penalty_alpha')
- gr.Markdown('Beam search (uses a lot of VRAM)')
- with gr.Row():
- with gr.Column():
- shared.gradio['num_beams'] = gr.Slider(1, 20, step=1, value=generate_params['num_beams'], label='num_beams')
- with gr.Column():
- 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')
- with gr.Group():
- with gr.Row():
- 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['ban_eos_token'] = gr.Checkbox(value=shared.settings['ban_eos_token'], label='Ban the eos token', info='This forces the model to never end the generation prematurely.')
- shared.gradio['truncation_length'] = gr.Slider(value=shared.settings['truncation_length'], minimum=shared.settings['truncation_length_min'], maximum=shared.settings['truncation_length_max'], step=1, 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['custom_stopping_strings'] = gr.Textbox(lines=1, value=shared.settings["custom_stopping_strings"] or None, label='Custom stopping strings', info='In addition to the defaults. Written between "" and separated by commas. For instance: "\\nYour Assistant:", "\\nThe assistant:"')
- with gr.Accordion('Soft prompt', open=False):
- with gr.Row():
- shared.gradio['softprompts_menu'] = gr.Dropdown(choices=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):')
- with gr.Row():
- shared.gradio['upload_softprompt'] = gr.File(type='binary', file_types=['.zip'])
- shared.gradio['preset_menu'].change(load_preset_values, [shared.gradio[k] for k in ['preset_menu', 'interface_state']], [shared.gradio[k] for k in ['interface_state', 'do_sample', 'temperature', 'top_p', 'typical_p', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']])
- shared.gradio['softprompts_menu'].change(load_soft_prompt, shared.gradio['softprompts_menu'], shared.gradio['softprompts_menu'], show_progress=True)
- shared.gradio['upload_softprompt'].upload(upload_soft_prompt, shared.gradio['upload_softprompt'], shared.gradio['softprompts_menu'])
- def set_interface_arguments(interface_mode, extensions, bool_active):
- modes = ["default", "notebook", "chat", "cai_chat"]
- 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]
- shared.args.extensions = extensions
- for k in modes[1:]:
- exec(f"shared.args.{k} = False")
- if interface_mode != "default":
- exec(f"shared.args.{interface_mode} = True")
- for k in bool_list:
- exec(f"shared.args.{k} = False")
- for k in bool_active:
- exec(f"shared.args.{k} = True")
- 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)
- # Default model
- if shared.args.model is not None:
- shared.model_name = shared.args.model
- else:
- if len(available_models) == 0:
- print('No models are available! Please download at least one.')
- sys.exit(0)
- elif len(available_models) == 1:
- i = 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]
- 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 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']
- return elements
- 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 create_interface():
- gen_events = []
- 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():
- shared.input_elements = 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()
- with gr.Tab("Text generation", elem_id="main"):
- shared.gradio['display'] = gr.HTML(value=chat_html_wrapper(shared.history['visible'], shared.settings['name1'], shared.settings['name2'], 'cai-chat'))
- shared.gradio['textbox'] = gr.Textbox(label='Input')
- 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['Copy last reply'] = gr.Button('Copy last reply')
- shared.gradio['Replace last reply'] = gr.Button('Replace last reply')
- shared.gradio['Remove last'] = gr.Button('Remove last')
- shared.gradio['Clear history'] = gr.Button('Clear history')
- shared.gradio['Clear history-confirm'] = gr.Button('Confirm', variant="stop", visible=False)
- shared.gradio['Clear history-cancel'] = gr.Button('Cancel', visible=False)
- shared.gradio["mode"] = gr.Radio(choices=["cai-chat", "chat", "instruct"], value="cai-chat", 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.")
- with gr.Tab("Character", elem_id="chat-settings"):
- with gr.Row():
- with gr.Column(scale=8):
- shared.gradio['name1'] = gr.Textbox(value=shared.settings['name1'], lines=1, label='Your name')
- shared.gradio['name2'] = gr.Textbox(value=shared.settings['name2'], lines=1, label='Character\'s name')
- 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')
- ui.create_refresh_button(shared.gradio['character_menu'], lambda: None, lambda: {'choices': get_available_characters()}, 'refresh-button')
- with gr.Row():
- with gr.Tab('Chat history'):
- with gr.Row():
- 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')
- gr.Markdown("# TavernAI PNG format")
- shared.gradio['upload_img_tavern'] = gr.File(type='binary', file_types=['image'])
- with gr.Tab("Parameters", elem_id="parameters"):
- with gr.Box():
- gr.Markdown("Chat parameters")
- with gr.Row():
- 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)
- 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']]
- gen_events.append(shared.gradio['Generate'].click(
- gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
- lambda x: (x, ''), shared.gradio['textbox'], [shared.gradio['Chat input'], shared.gradio['textbox']], show_progress=False).then(
- chat.cai_chatbot_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream).then(
- chat.save_history, shared.gradio['mode'], None, show_progress=False)
- )
- gen_events.append(shared.gradio['textbox'].submit(
- gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
- lambda x: (x, ''), shared.gradio['textbox'], [shared.gradio['Chat input'], shared.gradio['textbox']], show_progress=False).then(
- chat.cai_chatbot_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream).then(
- chat.save_history, shared.gradio['mode'], None, show_progress=False)
- )
- gen_events.append(shared.gradio['Regenerate'].click(
- gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
- chat.regenerate_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream).then(
- chat.save_history, shared.gradio['mode'], None, show_progress=False)
- )
- gen_events.append(shared.gradio['Continue'].click(
- gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
- chat.continue_wrapper, shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream).then(
- chat.save_history, shared.gradio['mode'], None, show_progress=False)
- )
- gen_events.append(shared.gradio['Impersonate'].click(
- gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
- chat.impersonate_wrapper, shared.input_params, shared.gradio['textbox'], show_progress=shared.args.no_stream)
- )
- shared.gradio['Replace last reply'].click(
- chat.replace_last_reply, [shared.gradio[k] for k in ['textbox', 'name1', 'name2', 'mode']], shared.gradio['display'], show_progress=shared.args.no_stream).then(
- lambda x: '', shared.gradio['textbox'], shared.gradio['textbox'], show_progress=False).then(
- chat.save_history, shared.gradio['mode'], None, show_progress=False)
- shared.gradio['Clear history-confirm'].click(
- lambda: [gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, clear_arr).then(
- chat.clear_chat_log, [shared.gradio[k] for k in ['name1', 'name2', 'greeting', 'mode']], shared.gradio['display']).then(
- chat.save_history, shared.gradio['mode'], None, show_progress=False)
- shared.gradio['Stop'].click(
- stop_everything_event, None, None, queue=False, cancels=gen_events if shared.args.no_stream else None).then(
- 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(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(
- chat.redraw_html, reload_inputs, shared.gradio['display'])
- shared.gradio['upload_chat_history'].upload(
- chat.load_history, [shared.gradio[k] for k in ['upload_chat_history', 'name1', 'name2']], None).then(
- chat.redraw_html, reload_inputs, shared.gradio['display'])
- shared.gradio['Copy last reply'].click(chat.send_last_reply_to_input, None, shared.gradio['textbox'], show_progress=shared.args.no_stream)
- shared.gradio['Clear history'].click(lambda: [gr.update(visible=True), gr.update(visible=False), gr.update(visible=True)], None, clear_arr)
- shared.gradio['Clear history-cancel'].click(lambda: [gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, clear_arr)
- shared.gradio['Remove last'].click(chat.remove_last_message, [shared.gradio[k] for k in ['name1', 'name2', 'mode']], [shared.gradio['display'], shared.gradio['textbox']], show_progress=False)
- shared.gradio['download_button'].click(lambda x: chat.save_history(x, timestamp=True), shared.gradio['mode'], shared.gradio['download'])
- shared.gradio['Upload character'].click(chat.upload_character, [shared.gradio['upload_json'], shared.gradio['upload_img_bot']], [shared.gradio['character_menu']])
- shared.gradio['character_menu'].change(chat.load_character, [shared.gradio[k] for k in ['character_menu', 'name1', 'name2', 'mode']], [shared.gradio[k] for k in ['name1', 'name2', 'character_picture', 'greeting', 'context', 'end_of_turn', 'display']])
- shared.gradio['upload_img_tavern'].upload(chat.upload_tavern_character, [shared.gradio['upload_img_tavern'], shared.gradio['name1'], shared.gradio['name2']], [shared.gradio['character_menu']])
- shared.gradio['your_picture'].change(chat.upload_your_profile_picture, [shared.gradio[k] for k in ['your_picture', 'name1', 'name2', 'mode']], shared.gradio['display'])
- shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js+ui.chat_js}}}")
- 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 = 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'])
- create_prompt_menus()
- 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(
- 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)
- )
- gen_events.append(shared.gradio['textbox'].submit(
- 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)
- )
- shared.gradio['Stop'].click(stop_everything_event, None, None, queue=False, cancels=gen_events if shared.args.no_stream else None)
- shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js}}}")
- else:
- shared.input_elements = 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'])
- shared.gradio['Generate'] = gr.Button('Generate')
- with gr.Row():
- with gr.Column():
- shared.gradio['Continue'] = gr.Button('Continue')
- with gr.Column():
- shared.gradio['Stop'] = gr.Button('Stop')
- create_prompt_menus()
- 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']]
- gen_events.append(shared.gradio['Generate'].click(
- 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)
- )
- gen_events.append(shared.gradio['textbox'].submit(
- 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)
- )
- gen_events.append(shared.gradio['Continue'].click(
- 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)
- )
- shared.gradio['Stop'].click(stop_everything_event, None, None, queue=False, cancels=gen_events if shared.args.no_stream else None)
- 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]
- 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:
- shared.gradio['interface'].launch(prevent_thread_lock=True, share=shared.args.share, server_name='0.0.0.0', server_port=shared.args.listen_port, inbrowser=shared.args.auto_launch, auth=auth)
- else:
- 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()
- while True:
- time.sleep(0.5)
- if shared.need_restart:
- shared.need_restart = False
- shared.gradio['interface'].close()
- create_interface()
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