mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-12-25 05:48:55 +01:00
1103 lines
66 KiB
Python
1103 lines
66 KiB
Python
import os
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import warnings
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import requests
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from modules.logging_colors import logger
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os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False'
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os.environ['BITSANDBYTES_NOWELCOME'] = '1'
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warnings.filterwarnings('ignore', category=UserWarning, message='TypedStorage is deprecated')
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# This is a hack to prevent Gradio from phoning home when it gets imported
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def my_get(url, **kwargs):
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logger.info('Gradio HTTP request redirected to localhost :)')
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kwargs.setdefault('allow_redirects', True)
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return requests.api.request('get', 'http://127.0.0.1/', **kwargs)
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original_get = requests.get
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requests.get = my_get
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import gradio as gr
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requests.get = original_get
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import matplotlib
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matplotlib.use('Agg') # This fixes LaTeX rendering on some systems
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import importlib
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import json
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import math
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import os
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import re
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import sys
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import time
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import traceback
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from datetime import datetime
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from functools import partial
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from pathlib import Path
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from threading import Lock
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import psutil
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import torch
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import yaml
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from PIL import Image
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import modules.extensions as extensions_module
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from modules import chat, shared, training, ui, utils
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from modules.extensions import apply_extensions
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from modules.html_generator import chat_html_wrapper
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from modules.LoRA import add_lora_to_model
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from modules.models import load_model, unload_model
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from modules.text_generation import (generate_reply_wrapper,
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get_encoded_length, stop_everything_event)
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def load_model_wrapper(selected_model, autoload=False):
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if not autoload:
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yield f"The settings for {selected_model} have been updated.\nClick on \"Load the model\" to load it."
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return
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if selected_model == 'None':
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yield "No model selected"
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else:
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try:
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yield f"Loading {selected_model}..."
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shared.model_name = selected_model
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unload_model()
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if selected_model != '':
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shared.model, shared.tokenizer = load_model(shared.model_name)
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yield f"Successfully loaded {selected_model}"
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except:
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yield traceback.format_exc()
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def load_lora_wrapper(selected_loras):
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yield ("Applying the following LoRAs to {}:\n\n{}".format(shared.model_name, '\n'.join(selected_loras)))
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add_lora_to_model(selected_loras)
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yield ("Successfuly applied the LoRAs")
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def load_preset_values(preset_menu, state, return_dict=False):
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generate_params = {
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'do_sample': True,
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'temperature': 1,
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'top_p': 1,
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'typical_p': 1,
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'epsilon_cutoff': 0,
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'eta_cutoff': 0,
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'tfs': 1,
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'top_a': 0,
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'repetition_penalty': 1,
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'encoder_repetition_penalty': 1,
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'top_k': 0,
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'num_beams': 1,
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'penalty_alpha': 0,
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'min_length': 0,
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'length_penalty': 1,
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'no_repeat_ngram_size': 0,
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'early_stopping': False,
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'mirostat_mode': 0,
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'mirostat_tau': 5.0,
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'mirostat_eta': 0.1,
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}
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with open(Path(f'presets/{preset_menu}.yaml'), 'r') as infile:
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preset = yaml.safe_load(infile)
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for k in preset:
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generate_params[k] = preset[k]
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generate_params['temperature'] = min(1.99, generate_params['temperature'])
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if return_dict:
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return generate_params
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else:
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state.update(generate_params)
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return state, *[generate_params[k] for k in ['do_sample', 'temperature', 'top_p', 'typical_p', 'epsilon_cutoff', 'eta_cutoff', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping', 'mirostat_mode', 'mirostat_tau', 'mirostat_eta', 'tfs', 'top_a']]
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def open_save_prompt():
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fname = f"{datetime.now().strftime('%Y-%m-%d-%H%M%S')}"
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return gr.update(value=fname, visible=True), gr.update(visible=False), gr.update(visible=True)
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def save_prompt(text, fname):
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if fname != "":
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with open(Path(f'prompts/{fname}.txt'), 'w', encoding='utf-8') as f:
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f.write(text)
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message = f"Saved to prompts/{fname}.txt"
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else:
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message = "Error: No prompt name given."
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return message, gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)
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def load_prompt(fname):
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if fname in ['None', '']:
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return ''
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elif fname.startswith('Instruct-'):
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fname = re.sub('^Instruct-', '', fname)
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with open(Path(f'characters/instruction-following/{fname}.yaml'), 'r', encoding='utf-8') as f:
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data = yaml.safe_load(f)
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output = ''
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if 'context' in data:
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output += data['context']
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replacements = {
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'<|user|>': data['user'],
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'<|bot|>': data['bot'],
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'<|user-message|>': 'Input',
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}
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output += utils.replace_all(data['turn_template'].split('<|bot-message|>')[0], replacements)
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return output.rstrip(' ')
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else:
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with open(Path(f'prompts/{fname}.txt'), 'r', encoding='utf-8') as f:
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text = f.read()
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if text[-1] == '\n':
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text = text[:-1]
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return text
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def count_tokens(text):
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tokens = get_encoded_length(text)
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return f'{tokens} tokens in the input.'
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def download_model_wrapper(repo_id):
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try:
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downloader_module = importlib.import_module("download-model")
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downloader = downloader_module.ModelDownloader()
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repo_id_parts = repo_id.split(":")
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model = repo_id_parts[0] if len(repo_id_parts) > 0 else repo_id
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branch = repo_id_parts[1] if len(repo_id_parts) > 1 else "main"
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check = False
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yield ("Cleaning up the model/branch names")
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model, branch = downloader.sanitize_model_and_branch_names(model, branch)
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yield ("Getting the download links from Hugging Face")
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links, sha256, is_lora = downloader.get_download_links_from_huggingface(model, branch, text_only=False)
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yield ("Getting the output folder")
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output_folder = downloader.get_output_folder(model, branch, is_lora)
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if check:
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yield ("Checking previously downloaded files")
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downloader.check_model_files(model, branch, links, sha256, output_folder)
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else:
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yield (f"Downloading files to {output_folder}")
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downloader.download_model_files(model, branch, links, sha256, output_folder, threads=1)
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yield ("Done!")
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except:
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yield traceback.format_exc()
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# Update the command-line arguments based on the interface values
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def update_model_parameters(state, initial=False):
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elements = ui.list_model_elements() # the names of the parameters
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gpu_memories = []
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for i, element in enumerate(elements):
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if element not in state:
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continue
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value = state[element]
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if element.startswith('gpu_memory'):
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gpu_memories.append(value)
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continue
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if initial and vars(shared.args)[element] != vars(shared.args_defaults)[element]:
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continue
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# Setting null defaults
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if element in ['wbits', 'groupsize', 'model_type'] and value == 'None':
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value = vars(shared.args_defaults)[element]
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elif element in ['cpu_memory'] and value == 0:
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value = vars(shared.args_defaults)[element]
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# Making some simple conversions
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if element in ['wbits', 'groupsize', 'pre_layer']:
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value = int(value)
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elif element == 'cpu_memory' and value is not None:
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value = f"{value}MiB"
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if element in ['pre_layer']:
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value = [value] if value > 0 else None
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setattr(shared.args, element, value)
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found_positive = False
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for i in gpu_memories:
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if i > 0:
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found_positive = True
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break
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if not (initial and vars(shared.args)['gpu_memory'] != vars(shared.args_defaults)['gpu_memory']):
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if found_positive:
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shared.args.gpu_memory = [f"{i}MiB" for i in gpu_memories]
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else:
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shared.args.gpu_memory = None
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def get_model_specific_settings(model):
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settings = shared.model_config
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model_settings = {}
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for pat in settings:
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if re.match(pat.lower(), model.lower()):
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for k in settings[pat]:
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model_settings[k] = settings[pat][k]
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return model_settings
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def load_model_specific_settings(model, state, return_dict=False):
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model_settings = get_model_specific_settings(model)
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for k in model_settings:
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if k in state:
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state[k] = model_settings[k]
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return state
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def save_model_settings(model, state):
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if model == 'None':
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yield ("Not saving the settings because no model is loaded.")
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return
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with Path(f'{shared.args.model_dir}/config-user.yaml') as p:
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if p.exists():
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user_config = yaml.safe_load(open(p, 'r').read())
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else:
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user_config = {}
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model_regex = model + '$' # For exact matches
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for _dict in [user_config, shared.model_config]:
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if model_regex not in _dict:
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_dict[model_regex] = {}
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if model_regex not in user_config:
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user_config[model_regex] = {}
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for k in ui.list_model_elements():
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user_config[model_regex][k] = state[k]
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shared.model_config[model_regex][k] = state[k]
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with open(p, 'w') as f:
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f.write(yaml.dump(user_config, sort_keys=False))
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yield (f"Settings for {model} saved to {p}")
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def create_model_menus():
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# Finding the default values for the GPU and CPU memories
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total_mem = []
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for i in range(torch.cuda.device_count()):
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total_mem.append(math.floor(torch.cuda.get_device_properties(i).total_memory / (1024 * 1024)))
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default_gpu_mem = []
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if shared.args.gpu_memory is not None and len(shared.args.gpu_memory) > 0:
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for i in shared.args.gpu_memory:
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if 'mib' in i.lower():
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default_gpu_mem.append(int(re.sub('[a-zA-Z ]', '', i)))
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else:
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default_gpu_mem.append(int(re.sub('[a-zA-Z ]', '', i)) * 1000)
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while len(default_gpu_mem) < len(total_mem):
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default_gpu_mem.append(0)
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total_cpu_mem = math.floor(psutil.virtual_memory().total / (1024 * 1024))
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if shared.args.cpu_memory is not None:
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default_cpu_mem = re.sub('[a-zA-Z ]', '', shared.args.cpu_memory)
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else:
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default_cpu_mem = 0
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with gr.Row():
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with gr.Column():
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with gr.Row():
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with gr.Column():
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with gr.Row():
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shared.gradio['model_menu'] = gr.Dropdown(choices=utils.get_available_models(), value=shared.model_name, label='Model')
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ui.create_refresh_button(shared.gradio['model_menu'], lambda: None, lambda: {'choices': utils.get_available_models()}, 'refresh-button')
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with gr.Column():
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with gr.Row():
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shared.gradio['lora_menu'] = gr.Dropdown(multiselect=True, choices=utils.get_available_loras(), value=shared.lora_names, label='LoRA(s)')
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ui.create_refresh_button(shared.gradio['lora_menu'], lambda: None, lambda: {'choices': utils.get_available_loras(), 'value': shared.lora_names}, 'refresh-button')
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with gr.Column():
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with gr.Row():
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shared.gradio['lora_menu_apply'] = gr.Button(value='Apply the selected LoRAs')
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with gr.Row():
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load = gr.Button("Load the model", visible=not shared.settings['autoload_model'])
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unload = gr.Button("Unload the model")
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reload = gr.Button("Reload the model")
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save_settings = gr.Button("Save settings for this model")
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with gr.Row():
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with gr.Column():
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with gr.Box():
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gr.Markdown('Transformers')
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with gr.Row():
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with gr.Column():
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for i in range(len(total_mem)):
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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])
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shared.gradio['cpu_memory'] = gr.Slider(label="cpu-memory in MiB", maximum=total_cpu_mem, value=default_cpu_mem)
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with gr.Column():
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shared.gradio['auto_devices'] = gr.Checkbox(label="auto-devices", value=shared.args.auto_devices)
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shared.gradio['disk'] = gr.Checkbox(label="disk", value=shared.args.disk)
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shared.gradio['cpu'] = gr.Checkbox(label="cpu", value=shared.args.cpu)
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shared.gradio['bf16'] = gr.Checkbox(label="bf16", value=shared.args.bf16)
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shared.gradio['load_in_8bit'] = gr.Checkbox(label="load-in-8bit", value=shared.args.load_in_8bit)
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shared.gradio['trust_remote_code'] = gr.Checkbox(label="trust-remote-code", value=shared.args.trust_remote_code, info='Make sure to inspect the .py files inside the model folder before loading it with this option enabled.')
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with gr.Box():
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gr.Markdown('Transformers 4-bit')
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with gr.Row():
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with gr.Column():
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shared.gradio['load_in_4bit'] = gr.Checkbox(label="load-in-4bit", value=shared.args.load_in_4bit)
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shared.gradio['use_double_quant'] = gr.Checkbox(label="use_double_quant", value=shared.args.use_double_quant)
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with gr.Column():
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shared.gradio['compute_dtype'] = gr.Dropdown(label="compute_dtype", choices=["bfloat16", "float16", "float32"], value=shared.args.compute_dtype)
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shared.gradio['quant_type'] = gr.Dropdown(label="quant_type", choices=["nf4", "fp4"], value=shared.args.quant_type)
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with gr.Row():
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shared.gradio['autoload_model'] = gr.Checkbox(value=shared.settings['autoload_model'], label='Autoload the model', info='Whether to load the model as soon as it is selected in the Model dropdown.')
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shared.gradio['custom_model_menu'] = gr.Textbox(label="Download custom model or LoRA", info="Enter the Hugging Face username/model path, for instance: facebook/galactica-125m. To specify a branch, add it at the end after a \":\" character like this: facebook/galactica-125m:main")
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shared.gradio['download_model_button'] = gr.Button("Download")
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with gr.Column():
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with gr.Box():
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with gr.Row():
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with gr.Column():
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gr.Markdown('AutoGPTQ')
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shared.gradio['triton'] = gr.Checkbox(label="triton", value=shared.args.triton)
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shared.gradio['desc_act'] = gr.Checkbox(label="desc_act", value=shared.args.desc_act, info='\'desc_act\', \'wbits\', and \'groupsize\' are used for old models without a quantize_config.json.')
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with gr.Column():
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gr.Markdown('GPTQ-for-LLaMa')
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shared.gradio['gptq_for_llama'] = gr.Checkbox(label="gptq-for-llama", value=shared.args.gptq_for_llama, info='Use GPTQ-for-LLaMa to load the GPTQ model instead of AutoGPTQ. pre_layer should be used for CPU offloading instead of gpu-memory.')
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with gr.Row():
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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")
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shared.gradio['groupsize'] = gr.Dropdown(label="groupsize", choices=["None", 32, 64, 128, 1024], value=shared.args.groupsize if shared.args.groupsize > 0 else "None")
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shared.gradio['model_type'] = gr.Dropdown(label="model_type", choices=["None", "llama", "opt", "gptj"], value=shared.args.model_type or "None")
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shared.gradio['pre_layer'] = gr.Slider(label="pre_layer", minimum=0, maximum=100, value=shared.args.pre_layer[0] if shared.args.pre_layer is not None else 0)
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with gr.Box():
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gr.Markdown('llama.cpp')
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with gr.Row():
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with gr.Column():
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shared.gradio['threads'] = gr.Slider(label="threads", minimum=0, step=1, maximum=32, value=shared.args.threads)
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shared.gradio['n_batch'] = gr.Slider(label="n_batch", minimum=1, maximum=2048, value=shared.args.n_batch)
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shared.gradio['n_gpu_layers'] = gr.Slider(label="n-gpu-layers", minimum=0, maximum=128, value=shared.args.n_gpu_layers)
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shared.gradio['n_ctx'] = gr.Slider(minimum=0, maximum=8192, step=1, label="n_ctx", value=shared.args.n_ctx)
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with gr.Column():
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shared.gradio['no_mmap'] = gr.Checkbox(label="no-mmap", value=shared.args.no_mmap)
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shared.gradio['mlock'] = gr.Checkbox(label="mlock", value=shared.args.mlock)
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shared.gradio['llama_cpp_seed'] = gr.Number(label='Seed (0 for random)', value=shared.args.llama_cpp_seed)
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with gr.Row():
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shared.gradio['model_status'] = gr.Markdown('No model is loaded' if shared.model_name == 'None' else 'Ready')
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# In this event handler, the interface state is read and updated
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# with the model defaults (if any), and then the model is loaded
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# unless "autoload_model" is unchecked
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shared.gradio['model_menu'].change(
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ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
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load_model_specific_settings, [shared.gradio[k] for k in ['model_menu', 'interface_state']], shared.gradio['interface_state']).then(
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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(
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update_model_parameters, shared.gradio['interface_state'], None).then(
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load_model_wrapper, [shared.gradio[k] for k in ['model_menu', 'autoload_model']], shared.gradio['model_status'], show_progress=False)
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load.click(
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ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
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update_model_parameters, shared.gradio['interface_state'], None).then(
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partial(load_model_wrapper, autoload=True), shared.gradio['model_menu'], shared.gradio['model_status'], show_progress=False)
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unload.click(
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unload_model, None, None).then(
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lambda: "Model unloaded", None, shared.gradio['model_status'])
|
|
|
|
reload.click(
|
|
unload_model, None, 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(
|
|
partial(load_model_wrapper, autoload=True), shared.gradio['model_menu'], shared.gradio['model_status'], show_progress=False)
|
|
|
|
save_settings.click(
|
|
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
|
|
save_model_settings, [shared.gradio[k] for k in ['model_menu', 'interface_state']], shared.gradio['model_status'], show_progress=False)
|
|
|
|
shared.gradio['lora_menu_apply'].click(load_lora_wrapper, shared.gradio['lora_menu'], shared.gradio['model_status'], show_progress=False)
|
|
shared.gradio['download_model_button'].click(download_model_wrapper, shared.gradio['custom_model_menu'], shared.gradio['model_status'], show_progress=False)
|
|
shared.gradio['autoload_model'].change(lambda x: gr.update(visible=not x), shared.gradio['autoload_model'], load)
|
|
|
|
|
|
def create_chat_settings_menus():
|
|
if not shared.is_chat():
|
|
return
|
|
|
|
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='chat_prompt_size', info='Set limit on prompt size by removing old messages (while retaining context and user input)', 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)', info='New generations will be called until either this number is reached or no new content is generated between two iterations.')
|
|
shared.gradio['stop_at_newline'] = gr.Checkbox(value=shared.settings['stop_at_newline'], label='Stop generating at new line character')
|
|
|
|
|
|
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():
|
|
with gr.Column():
|
|
with gr.Row():
|
|
shared.gradio['preset_menu'] = gr.Dropdown(choices=utils.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': utils.get_available_presets()}, 'refresh-button')
|
|
|
|
with gr.Column():
|
|
shared.gradio['seed'] = gr.Number(value=shared.settings['seed'], label='Seed (-1 for random)')
|
|
|
|
with gr.Box():
|
|
gr.Markdown('Main parameters')
|
|
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.')
|
|
shared.gradio['epsilon_cutoff'] = gr.Slider(0, 9, value=generate_params['epsilon_cutoff'], step=0.01, label='epsilon_cutoff', info='In units of 1e-4; a reasonable value is 3. This sets a probability floor below which tokens are excluded from being sampled. Should be used with top_p, top_k, and eta_cutoff set to 0.')
|
|
shared.gradio['eta_cutoff'] = gr.Slider(0, 20, value=generate_params['eta_cutoff'], step=0.01, label='eta_cutoff', info='In units of 1e-4; a reasonable value is 3. Should be used with top_p, top_k, and epsilon_cutoff set to 0.')
|
|
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')
|
|
|
|
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():
|
|
create_chat_settings_menus()
|
|
with gr.Box():
|
|
with gr.Row():
|
|
with gr.Column():
|
|
gr.Markdown('Contrastive search')
|
|
shared.gradio['penalty_alpha'] = gr.Slider(0, 5, value=generate_params['penalty_alpha'], label='penalty_alpha', info='Contrastive Search is enabled by setting this to greater than zero and unchecking "do_sample". It should be used with a low value of top_k, for instance, top_k = 4.')
|
|
|
|
gr.Markdown('Beam search (uses a lot of VRAM)')
|
|
shared.gradio['num_beams'] = gr.Slider(1, 20, step=1, value=generate_params['num_beams'], label='num_beams')
|
|
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.Column():
|
|
gr.Markdown('Mirostat (for llama.cpp)')
|
|
shared.gradio['mirostat_mode'] = gr.Slider(0, 2, step=1, value=generate_params['mirostat_mode'], label='mirostat_mode')
|
|
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')
|
|
|
|
with gr.Box():
|
|
with gr.Row():
|
|
with gr.Column():
|
|
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.Column():
|
|
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['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=not shared.args.no_stream, label='Activate text streaming')
|
|
|
|
gr.Markdown('[Click here for more information.](https://github.com/oobabooga/text-generation-webui/blob/main/docs/Generation-parameters.md)')
|
|
|
|
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', 'epsilon_cutoff', 'eta_cutoff', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping', 'mirostat_mode', 'mirostat_tau', 'mirostat_eta', 'tfs', 'top_a']])
|
|
|
|
|
|
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:]:
|
|
setattr(shared.args, k, False)
|
|
if interface_mode != "default":
|
|
setattr(shared.args, interface_mode, True)
|
|
|
|
for k in bool_list:
|
|
setattr(shared.args, k, False)
|
|
for k in bool_active:
|
|
setattr(shared.args, k, True)
|
|
|
|
shared.need_restart = True
|
|
|
|
|
|
def create_interface():
|
|
|
|
# Defining some variables
|
|
gen_events = []
|
|
default_preset = shared.settings['preset']
|
|
default_text = load_prompt(shared.settings['prompt'])
|
|
title = 'Text generation web UI'
|
|
|
|
# Authentication variables
|
|
auth = None
|
|
gradio_auth_creds = []
|
|
if shared.args.gradio_auth:
|
|
gradio_auth_creds += [x.strip() for x in shared.args.gradio_auth.strip('"').replace('\n', '').split(',') if x.strip()]
|
|
if shared.args.gradio_auth_path is not None:
|
|
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()]
|
|
if gradio_auth_creds:
|
|
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()
|
|
|
|
# css/js strings
|
|
css = ui.css if not shared.is_chat() else ui.css + ui.chat_css
|
|
js = ui.main_js if not shared.is_chat() else ui.main_js + ui.chat_js
|
|
css += apply_extensions('css')
|
|
js += apply_extensions('js')
|
|
|
|
with gr.Blocks(css=css, analytics_enabled=False, title=title, theme=ui.theme) as shared.gradio['interface']:
|
|
if Path("notification.mp3").exists():
|
|
shared.gradio['audio_notification'] = gr.Audio(interactive=False, value="notification.mp3", elem_id="audio_notification", visible=False)
|
|
audio_notification_js = "document.querySelector('#audio_notification audio')?.play();"
|
|
else:
|
|
audio_notification_js = ""
|
|
|
|
# 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()
|
|
shared.gradio['dummy'] = 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'], 'chat', 'cai-chat'))
|
|
shared.gradio['textbox'] = gr.Textbox(label='Input')
|
|
with gr.Row():
|
|
shared.gradio['Stop'] = gr.Button('Stop', elem_id='stop')
|
|
shared.gradio['Generate'] = gr.Button('Generate', elem_id='Generate', variant='primary')
|
|
shared.gradio['Continue'] = gr.Button('Continue')
|
|
|
|
with gr.Row():
|
|
shared.gradio['Impersonate'] = gr.Button('Impersonate')
|
|
shared.gradio['Regenerate'] = gr.Button('Regenerate')
|
|
shared.gradio['Remove last'] = gr.Button('Remove last')
|
|
|
|
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['Send dummy message'] = gr.Button('Send dummy message')
|
|
shared.gradio['Send dummy reply'] = gr.Button('Send dummy reply')
|
|
|
|
with gr.Row():
|
|
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)
|
|
|
|
with gr.Row():
|
|
shared.gradio['start_with'] = gr.Textbox(label='Start reply with', placeholder='Sure thing!', value=shared.settings['start_with'])
|
|
|
|
with gr.Row():
|
|
shared.gradio['mode'] = gr.Radio(choices=['chat', 'chat-instruct', 'instruct'], value=shared.settings['mode'] if shared.settings['mode'] in ['chat', 'instruct', 'chat-instruct'] else 'chat', label='Mode', info='Defines how the chat prompt is generated. In instruct and chat-instruct modes, the instruction template selected under "Chat settings" must match the current model.')
|
|
shared.gradio['chat_style'] = gr.Dropdown(choices=utils.get_available_chat_styles(), label='Chat style', value=shared.settings['chat_style'], visible=shared.settings['mode'] != 'instruct')
|
|
|
|
with gr.Tab('Chat settings', elem_id='chat-settings'):
|
|
with gr.Row():
|
|
with gr.Column(scale=8):
|
|
with gr.Row():
|
|
shared.gradio['character_menu'] = gr.Dropdown(choices=utils.get_available_characters(), label='Character', elem_id='character-menu', info='Used in chat and chat-instruct modes.')
|
|
ui.create_refresh_button(shared.gradio['character_menu'], lambda: None, lambda: {'choices': utils.get_available_characters()}, 'refresh-button')
|
|
shared.gradio['save_character'] = ui.create_save_button(elem_id='refresh-button')
|
|
shared.gradio['delete_character'] = ui.create_delete_button(elem_id='refresh-button')
|
|
|
|
shared.gradio['save_character-filename'] = gr.Textbox(lines=1, label='File name:', interactive=True, visible=False)
|
|
shared.gradio['save_character-confirm'] = gr.Button('Confirm save character', elem_classes="small-button", variant='primary', visible=False)
|
|
shared.gradio['save_character-cancel'] = gr.Button('Cancel', elem_classes="small-button", visible=False)
|
|
shared.gradio['delete_character-confirm'] = gr.Button('Confirm delete character', elem_classes="small-button", variant='stop', visible=False)
|
|
shared.gradio['delete_character-cancel'] = gr.Button('Cancel', elem_classes="small-button", visible=False)
|
|
|
|
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['context'] = gr.Textbox(value=shared.settings['context'], lines=4, label='Context')
|
|
shared.gradio['greeting'] = gr.Textbox(value=shared.settings['greeting'], lines=4, label='Greeting')
|
|
|
|
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['instruction_template'] = gr.Dropdown(choices=utils.get_available_instruction_templates(), label='Instruction template', value='None', info='Change this according to the model/LoRA that you are using. Used in instruct and chat-instruct modes.')
|
|
ui.create_refresh_button(shared.gradio['instruction_template'], lambda: None, lambda: {'choices': utils.get_available_instruction_templates()}, 'refresh-button')
|
|
|
|
shared.gradio['name1_instruct'] = gr.Textbox(value='', lines=2, label='User string')
|
|
shared.gradio['name2_instruct'] = gr.Textbox(value='', lines=1, label='Bot string')
|
|
shared.gradio['context_instruct'] = gr.Textbox(value='', lines=4, label='Context')
|
|
shared.gradio['turn_template'] = gr.Textbox(value=shared.settings['turn_template'], lines=1, label='Turn template', info='Used to precisely define the placement of spaces and new line characters in instruction prompts.')
|
|
with gr.Row():
|
|
shared.gradio['chat-instruct_command'] = gr.Textbox(value=shared.settings['chat-instruct_command'], lines=4, label='Command for chat-instruct mode', info='<|character|> gets replaced by the bot name, and <|prompt|> gets replaced by the regular chat prompt.')
|
|
|
|
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"):
|
|
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})
|
|
shared.gradio['last_input'] = gr.State('')
|
|
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_classes="textbox", lines=27)
|
|
|
|
with gr.Tab('Markdown'):
|
|
shared.gradio['markdown_render'] = gr.Button('Render')
|
|
shared.gradio['markdown'] = gr.Markdown()
|
|
|
|
with gr.Tab('HTML'):
|
|
shared.gradio['html'] = gr.HTML()
|
|
|
|
with gr.Row():
|
|
shared.gradio['Generate'] = gr.Button('Generate', variant='primary', elem_classes="small-button")
|
|
shared.gradio['Stop'] = gr.Button('Stop', elem_classes="small-button")
|
|
shared.gradio['Undo'] = gr.Button('Undo', elem_classes="small-button")
|
|
shared.gradio['Regenerate'] = gr.Button('Regenerate', elem_classes="small-button")
|
|
|
|
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=utils.get_available_prompts(), value='None', label='Prompt')
|
|
ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': utils.get_available_prompts()}, 'refresh-button')
|
|
|
|
shared.gradio['open_save_prompt'] = gr.Button('Save prompt')
|
|
shared.gradio['save_prompt'] = gr.Button('Confirm save prompt', visible=False)
|
|
shared.gradio['prompt_to_save'] = gr.Textbox(elem_classes="textbox_default", lines=1, label='Prompt name:', interactive=True, visible=False)
|
|
shared.gradio['count_tokens'] = gr.Button('Count tokens')
|
|
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})
|
|
shared.gradio['last_input'] = gr.State('')
|
|
with gr.Tab("Text generation", elem_id="main"):
|
|
with gr.Row():
|
|
with gr.Column():
|
|
shared.gradio['textbox'] = gr.Textbox(value=default_text, elem_classes="textbox_default", lines=27, 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():
|
|
shared.gradio['Generate'] = gr.Button('Generate', variant='primary', elem_classes="small-button")
|
|
shared.gradio['Stop'] = gr.Button('Stop', elem_classes="small-button")
|
|
shared.gradio['Continue'] = gr.Button('Continue', elem_classes="small-button")
|
|
shared.gradio['open_save_prompt'] = gr.Button('Save prompt', elem_classes="small-button")
|
|
shared.gradio['save_prompt'] = gr.Button('Confirm save prompt', visible=False, elem_classes="small-button")
|
|
shared.gradio['count_tokens'] = gr.Button('Count tokens', elem_classes="small-button")
|
|
|
|
with gr.Row():
|
|
with gr.Column():
|
|
with gr.Row():
|
|
shared.gradio['prompt_menu'] = gr.Dropdown(choices=utils.get_available_prompts(), value='None', label='Prompt')
|
|
ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': utils.get_available_prompts()}, 'refresh-button')
|
|
|
|
with gr.Column():
|
|
shared.gradio['prompt_to_save'] = gr.Textbox(elem_classes="textbox_default", lines=1, label='Prompt name:', interactive=True, visible=False)
|
|
shared.gradio['status'] = gr.Markdown('')
|
|
|
|
with gr.Column():
|
|
with gr.Tab('Raw'):
|
|
shared.gradio['output_textbox'] = gr.Textbox(elem_classes="textbox_default_output", lines=27, label='Output')
|
|
|
|
with gr.Tab('Markdown'):
|
|
shared.gradio['markdown_render'] = gr.Button('Render')
|
|
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"]
|
|
current_mode = "default"
|
|
for mode in modes[1:]:
|
|
if getattr(shared.args, mode):
|
|
current_mode = mode
|
|
break
|
|
|
|
cmd_list = vars(shared.args)
|
|
bool_list = sorted([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]]
|
|
|
|
with gr.Row():
|
|
shared.gradio['interface_modes_menu'] = gr.Dropdown(choices=modes, value=current_mode, label="Mode")
|
|
shared.gradio['toggle_dark_mode'] = gr.Button('Toggle dark/light mode', elem_classes="small-button")
|
|
|
|
shared.gradio['extensions_menu'] = gr.CheckboxGroup(choices=utils.get_available_extensions(), value=shared.args.extensions, label="Available extensions", info='Note that some of these extensions may require manually installing Python requirements through the command: pip install -r extensions/extension_name/requirements.txt')
|
|
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 []}')
|
|
|
|
shared.gradio['toggle_dark_mode'].click(lambda: None, None, None, _js='() => {document.getElementsByTagName("body")[0].classList.toggle("dark")}')
|
|
|
|
# chat mode event handlers
|
|
if shared.is_chat():
|
|
shared.input_params = [shared.gradio[k] for k in ['Chat input', 'start_with', 'interface_state']]
|
|
clear_arr = [shared.gradio[k] for k in ['Clear history-confirm', 'Clear history', 'Clear history-cancel']]
|
|
shared.reload_inputs = [shared.gradio[k] for k in ['name1', 'name2', 'mode', 'chat_style']]
|
|
|
|
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(
|
|
lambda x: (x, ''), shared.gradio['textbox'], [shared.gradio['Chat input'], shared.gradio['textbox']], show_progress=False).then(
|
|
chat.generate_chat_reply_wrapper, shared.input_params, shared.gradio['display'], show_progress=False).then(
|
|
chat.save_history, shared.gradio['mode'], None, show_progress=False).then(
|
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}")
|
|
)
|
|
|
|
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(
|
|
lambda x: (x, ''), shared.gradio['textbox'], [shared.gradio['Chat input'], shared.gradio['textbox']], show_progress=False).then(
|
|
chat.generate_chat_reply_wrapper, shared.input_params, shared.gradio['display'], show_progress=False).then(
|
|
chat.save_history, shared.gradio['mode'], None, show_progress=False).then(
|
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}")
|
|
)
|
|
|
|
gen_events.append(shared.gradio['Regenerate'].click(
|
|
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
|
|
partial(chat.generate_chat_reply_wrapper, regenerate=True), shared.input_params, shared.gradio['display'], show_progress=False).then(
|
|
chat.save_history, shared.gradio['mode'], None, show_progress=False).then(
|
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}")
|
|
)
|
|
|
|
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(
|
|
partial(chat.generate_chat_reply_wrapper, _continue=True), shared.input_params, shared.gradio['display'], show_progress=False).then(
|
|
chat.save_history, shared.gradio['mode'], None, show_progress=False).then(
|
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}")
|
|
)
|
|
|
|
gen_events.append(shared.gradio['Impersonate'].click(
|
|
ui.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'], show_progress=False).then(
|
|
chat.impersonate_wrapper, shared.input_params, shared.gradio['textbox'], show_progress=False).then(
|
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}")
|
|
)
|
|
|
|
shared.gradio['Replace last reply'].click(
|
|
chat.replace_last_reply, shared.gradio['textbox'], None).then(
|
|
lambda: '', None, shared.gradio['textbox'], show_progress=False).then(
|
|
chat.save_history, shared.gradio['mode'], None, show_progress=False).then(
|
|
chat.redraw_html, shared.reload_inputs, shared.gradio['display'])
|
|
|
|
shared.gradio['Send dummy message'].click(
|
|
chat.send_dummy_message, shared.gradio['textbox'], None).then(
|
|
lambda: '', None, shared.gradio['textbox'], show_progress=False).then(
|
|
chat.save_history, shared.gradio['mode'], None, show_progress=False).then(
|
|
chat.redraw_html, shared.reload_inputs, shared.gradio['display'])
|
|
|
|
shared.gradio['Send dummy reply'].click(
|
|
chat.send_dummy_reply, shared.gradio['textbox'], None).then(
|
|
lambda: '', None, shared.gradio['textbox'], show_progress=False).then(
|
|
chat.save_history, shared.gradio['mode'], None, show_progress=False).then(
|
|
chat.redraw_html, shared.reload_inputs, shared.gradio['display'])
|
|
|
|
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 ['greeting', 'mode']], None).then(
|
|
chat.save_history, shared.gradio['mode'], None, show_progress=False).then(
|
|
chat.redraw_html, shared.reload_inputs, shared.gradio['display'])
|
|
|
|
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, shared.reload_inputs, shared.gradio['display'])
|
|
|
|
shared.gradio['mode'].change(
|
|
lambda x: gr.update(visible=x != 'instruct'), shared.gradio['mode'], shared.gradio['chat_style'], show_progress=False).then(
|
|
chat.redraw_html, shared.reload_inputs, shared.gradio['display'])
|
|
|
|
shared.gradio['chat_style'].change(chat.redraw_html, shared.reload_inputs, shared.gradio['display'])
|
|
shared.gradio['instruction_template'].change(
|
|
partial(chat.load_character, instruct=True), [shared.gradio[k] for k in ['instruction_template', 'name1_instruct', 'name2_instruct']], [shared.gradio[k] for k in ['name1_instruct', 'name2_instruct', 'dummy', 'dummy', 'context_instruct', 'turn_template']])
|
|
|
|
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, shared.reload_inputs, shared.gradio['display'])
|
|
|
|
shared.gradio['Copy last reply'].click(chat.send_last_reply_to_input, None, shared.gradio['textbox'], show_progress=False)
|
|
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, None, shared.gradio['textbox'], show_progress=False).then(
|
|
chat.save_history, shared.gradio['mode'], None, show_progress=False).then(
|
|
chat.redraw_html, shared.reload_inputs, shared.gradio['display'])
|
|
|
|
# Save/delete a character
|
|
shared.gradio['save_character'].click(
|
|
lambda x: x, shared.gradio['name2'], shared.gradio['save_character-filename'], show_progress=True).then(
|
|
lambda: [gr.update(visible=True)] * 3, None, [shared.gradio[k] for k in ['save_character-filename', 'save_character-confirm', 'save_character-cancel']], show_progress=False)
|
|
|
|
shared.gradio['save_character-cancel'].click(
|
|
lambda: [gr.update(visible=False)] * 3, None, [shared.gradio[k] for k in ['save_character-filename', 'save_character-confirm', 'save_character-cancel']], show_progress=False)
|
|
|
|
shared.gradio['save_character-confirm'].click(
|
|
partial(chat.save_character, instruct=False), [shared.gradio[k] for k in ['name2', 'greeting', 'context', 'character_picture', 'save_character-filename']], None).then(
|
|
lambda: [gr.update(visible=False)] * 3, None, [shared.gradio[k] for k in ['save_character-filename', 'save_character-confirm', 'save_character-cancel']], show_progress=False).then(
|
|
lambda x: x, shared.gradio['save_character-filename'], shared.gradio['character_menu'])
|
|
|
|
shared.gradio['delete_character'].click(
|
|
lambda: [gr.update(visible=True)] * 2, None, [shared.gradio[k] for k in ['delete_character-confirm', 'delete_character-cancel']], show_progress=False)
|
|
|
|
shared.gradio['delete_character-cancel'].click(
|
|
lambda: [gr.update(visible=False)] * 2, None, [shared.gradio[k] for k in ['delete_character-confirm', 'delete_character-cancel']], show_progress=False)
|
|
|
|
shared.gradio['delete_character-confirm'].click(
|
|
partial(chat.delete_character, instruct=False), shared.gradio['character_menu'], None).then(
|
|
lambda: gr.update(choices=utils.get_available_characters()), outputs=shared.gradio['character_menu']).then(
|
|
lambda: 'None', None, shared.gradio['character_menu']).then(
|
|
lambda: [gr.update(visible=False)] * 2, None, [shared.gradio[k] for k in ['delete_character-confirm', 'delete_character-cancel']], 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(
|
|
partial(chat.load_character, instruct=False), [shared.gradio[k] for k in ['character_menu', 'name1', 'name2']], [shared.gradio[k] for k in ['name1', 'name2', 'character_picture', 'greeting', 'context', 'dummy']]).then(
|
|
chat.redraw_html, shared.reload_inputs, shared.gradio['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['your_picture'], None).then(
|
|
partial(chat.redraw_html, reset_cache=True), shared.reload_inputs, shared.gradio['display'])
|
|
|
|
# notebook/default modes event handlers
|
|
else:
|
|
shared.input_params = [shared.gradio[k] for k in ['textbox', 'interface_state']]
|
|
if shared.args.notebook:
|
|
output_params = [shared.gradio[k] for k in ['textbox', 'html']]
|
|
else:
|
|
output_params = [shared.gradio[k] for k in ['output_textbox', 'html']]
|
|
|
|
gen_events.append(shared.gradio['Generate'].click(
|
|
lambda x: x, shared.gradio['textbox'], shared.gradio['last_input']).then(
|
|
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
|
|
generate_reply_wrapper, shared.input_params, output_params, show_progress=False).then(
|
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}")
|
|
# lambda: None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[0]; element.scrollTop = element.scrollHeight}")
|
|
)
|
|
|
|
gen_events.append(shared.gradio['textbox'].submit(
|
|
lambda x: x, shared.gradio['textbox'], shared.gradio['last_input']).then(
|
|
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
|
|
generate_reply_wrapper, shared.input_params, output_params, show_progress=False).then(
|
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}")
|
|
# lambda: None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[0]; element.scrollTop = element.scrollHeight}")
|
|
)
|
|
|
|
if shared.args.notebook:
|
|
shared.gradio['Undo'].click(lambda x: x, shared.gradio['last_input'], shared.gradio['textbox'], show_progress=False)
|
|
shared.gradio['markdown_render'].click(lambda x: x, shared.gradio['textbox'], shared.gradio['markdown'], queue=False)
|
|
gen_events.append(shared.gradio['Regenerate'].click(
|
|
lambda x: x, shared.gradio['last_input'], shared.gradio['textbox'], show_progress=False).then(
|
|
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then(
|
|
generate_reply_wrapper, shared.input_params, output_params, show_progress=False).then(
|
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}")
|
|
# lambda: None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[0]; element.scrollTop = element.scrollHeight}")
|
|
)
|
|
else:
|
|
shared.gradio['markdown_render'].click(lambda x: x, shared.gradio['output_textbox'], shared.gradio['markdown'], queue=False)
|
|
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_wrapper, [shared.gradio['output_textbox']] + shared.input_params[1:], output_params, show_progress=False).then(
|
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}")
|
|
# lambda: None, None, None, _js="() => {element = document.getElementsByTagName('textarea')[1]; 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['open_save_prompt'].click(open_save_prompt, None, [shared.gradio[k] for k in ['prompt_to_save', 'open_save_prompt', 'save_prompt']], show_progress=False)
|
|
shared.gradio['save_prompt'].click(save_prompt, [shared.gradio[k] for k in ['textbox', 'prompt_to_save']], [shared.gradio[k] for k in ['status', 'prompt_to_save', 'open_save_prompt', 'save_prompt']], show_progress=False)
|
|
shared.gradio['count_tokens'].click(count_tokens, shared.gradio['textbox'], shared.gradio['status'], show_progress=False)
|
|
|
|
shared.gradio['interface'].load(lambda: None, None, None, _js=f"() => {{{js}}}")
|
|
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(partial(ui.apply_interface_values, {}, use_persistent=True), None, [shared.gradio[k] for k in ui.list_interface_input_elements(chat=shared.is_chat())], show_progress=False)
|
|
|
|
# Extensions tabs
|
|
extensions_module.create_extensions_tabs()
|
|
|
|
# Extensions block
|
|
extensions_module.create_extensions_block()
|
|
|
|
# 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=shared.args.listen_host or '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)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
# 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.yaml').exists():
|
|
settings_file = Path('settings.yaml')
|
|
elif Path('settings.json').exists():
|
|
settings_file = Path('settings.json')
|
|
|
|
if settings_file is not None:
|
|
logger.info(f"Loading settings from {settings_file}...")
|
|
file_contents = open(settings_file, 'r', encoding='utf-8').read()
|
|
new_settings = json.loads(file_contents) if settings_file.suffix == "json" else yaml.safe_load(file_contents)
|
|
for item in new_settings:
|
|
shared.settings[item] = new_settings[item]
|
|
|
|
# Set default model settings based on settings file
|
|
shared.model_config['.*'] = {
|
|
'wbits': 'None',
|
|
'model_type': 'None',
|
|
'groupsize': 'None',
|
|
'pre_layer': 0,
|
|
'mode': shared.settings['mode'],
|
|
'skip_special_tokens': shared.settings['skip_special_tokens'],
|
|
'custom_stopping_strings': shared.settings['custom_stopping_strings'],
|
|
'truncation_length': shared.settings['truncation_length'],
|
|
}
|
|
|
|
shared.model_config.move_to_end('.*', last=False) # Move to the beginning
|
|
|
|
# Default extensions
|
|
extensions_module.available_extensions = utils.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 = utils.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:
|
|
logger.error('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, initial=True) # 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)
|
|
|
|
# Force a character to be loaded
|
|
if shared.is_chat():
|
|
shared.persistent_interface_state.update({
|
|
'mode': shared.settings['mode'],
|
|
'character_menu': shared.args.character or shared.settings['character'],
|
|
'instruction_template': shared.settings['instruction_template']
|
|
})
|
|
|
|
shared.generation_lock = Lock()
|
|
# Launch the web UI
|
|
create_interface()
|
|
while True:
|
|
time.sleep(0.5)
|
|
if shared.need_restart:
|
|
shared.need_restart = False
|
|
time.sleep(0.5)
|
|
shared.gradio['interface'].close()
|
|
time.sleep(0.5)
|
|
create_interface()
|