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import logging |
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import os |
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import requests |
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import warnings |
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import modules.logging_colors |
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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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logging.basicConfig(format='%(levelname)s:%(message)s', level=logging.INFO) |
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def my_get(url, **kwargs): |
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logging.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') |
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import importlib |
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import io |
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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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import zipfile |
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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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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 |
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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, load_soft_prompt, unload_model |
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from modules.text_generation import (encode, generate_reply, |
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stop_everything_event) |
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def get_available_models(): |
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if shared.args.flexgen: |
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return sorted([re.sub('-np$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if item.name.endswith('-np')], key=str.lower) |
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else: |
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return sorted([re.sub('.pth$', '', item.name) for item in list(Path(f'{shared.args.model_dir}/').glob('*')) if not item.name.endswith(('.txt', '-np', '.pt', '.json', '.yaml'))], key=str.lower) |
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def get_available_presets(): |
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return sorted(set((k.stem for k in Path('presets').glob('*.txt'))), key=str.lower) |
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def get_available_prompts(): |
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prompts = [] |
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prompts += sorted(set((k.stem for k in Path('prompts').glob('[0-9]*.txt'))), key=str.lower, reverse=True) |
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prompts += sorted(set((k.stem for k in Path('prompts').glob('*.txt'))), key=str.lower) |
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prompts += ['None'] |
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return prompts |
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def get_available_characters(): |
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paths = (x for x in Path('characters').iterdir() if x.suffix in ('.json', '.yaml', '.yml')) |
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return ['None'] + sorted(set((k.stem for k in paths if k.stem != "instruction-following")), key=str.lower) |
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def get_available_instruction_templates(): |
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path = "characters/instruction-following" |
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paths = [] |
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if os.path.exists(path): |
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paths = (x for x in Path(path).iterdir() if x.suffix in ('.json', '.yaml', '.yml')) |
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return ['None'] + sorted(set((k.stem for k in paths)), key=str.lower) |
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def get_available_extensions(): |
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return sorted(set(map(lambda x: x.parts[1], Path('extensions').glob('*/script.py'))), key=str.lower) |
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def get_available_softprompts(): |
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return ['None'] + sorted(set((k.stem for k in Path('softprompts').glob('*.zip'))), key=str.lower) |
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def get_available_loras(): |
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return 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) |
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def load_model_wrapper(selected_model): |
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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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'repetition_penalty': 1, |
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'encoder_repetition_penalty': 1, |
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'top_k': 50, |
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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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} |
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with open(Path(f'presets/{preset_menu}.txt'), 'r') as infile: |
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preset = infile.read() |
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for i in preset.splitlines(): |
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i = i.rstrip(',').strip().split('=') |
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if len(i) == 2 and i[0].strip() != 'tokens': |
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generate_params[i[0].strip()] = eval(i[1].strip()) |
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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', 'repetition_penalty', 'encoder_repetition_penalty', 'top_k', 'min_length', 'no_repeat_ngram_size', 'num_beams', 'penalty_alpha', 'length_penalty', 'early_stopping']] |
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def upload_soft_prompt(file): |
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with zipfile.ZipFile(io.BytesIO(file)) as zf: |
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zf.extract('meta.json') |
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j = json.loads(open('meta.json', 'r').read()) |
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name = j['name'] |
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Path('meta.json').unlink() |
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with open(Path(f'softprompts/{name}.zip'), 'wb') as f: |
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f.write(file) |
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return name |
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def save_prompt(text): |
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fname = f"{datetime.now().strftime('%Y-%m-%d-%H%M%S')}.txt" |
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with open(Path(f'prompts/{fname}'), 'w', encoding='utf-8') as f: |
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f.write(text) |
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return f"Saved to prompts/{fname}" |
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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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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 = len(encode(text)[0]) |
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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 = importlib.import_module("download-model") |
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model = repo_id |
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branch = "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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def update_model_parameters(state, initial=False): |
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elements = ui.list_model_elements() |
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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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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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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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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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if model not in user_config: |
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user_config[model] = {} |
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for k in ui.list_model_elements(): |
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user_config[model][k] = state[k] |
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with open(p, 'w') as f: |
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f.write(yaml.dump(user_config)) |
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yield (f"Settings for {model} saved to {p}") |
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def create_model_menus(): |
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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=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': 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=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': 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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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 parameters') |
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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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with gr.Column(): |
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with gr.Box(): |
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gr.Markdown('GPTQ parameters') |
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with gr.Row(): |
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with gr.Column(): |
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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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with gr.Column(): |
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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) |
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with gr.Row(): |
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with gr.Column(): |
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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") |
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shared.gradio['download_model_button'] = gr.Button("Download") |
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with gr.Column(): |
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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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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['model_menu'], shared.gradio['model_status'], show_progress=True) |
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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']) |
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reload.click( |
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unload_model, None, None).then( |
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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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load_model_wrapper, shared.gradio['model_menu'], shared.gradio['model_status'], show_progress=False) |
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save_settings.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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save_model_settings, [shared.gradio[k] for k in ['model_menu', 'interface_state']], shared.gradio['model_status'], show_progress=False) |
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shared.gradio['lora_menu_apply'].click(load_lora_wrapper, shared.gradio['lora_menu'], shared.gradio['model_status'], show_progress=False) |
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shared.gradio['download_model_button'].click(download_model_wrapper, shared.gradio['custom_model_menu'], shared.gradio['model_status'], show_progress=False) |
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def create_settings_menus(default_preset): |
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generate_params = load_preset_values(default_preset if not shared.args.flexgen else 'Naive', {}, return_dict=True) |
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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['preset_menu'] = gr.Dropdown(choices=get_available_presets(), value=default_preset if not shared.args.flexgen else 'Naive', label='Generation parameters preset') |
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ui.create_refresh_button(shared.gradio['preset_menu'], lambda: None, lambda: {'choices': get_available_presets()}, 'refresh-button') |
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with gr.Column(): |
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shared.gradio['seed'] = gr.Number(value=shared.settings['seed'], label='Seed (-1 for random)') |
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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('Custom generation parameters ([click here to view technical documentation](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.GenerationConfig))') |
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with gr.Row(): |
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with gr.Column(): |
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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.') |
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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.') |
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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.') |
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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.') |
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with gr.Column(): |
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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.') |
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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.') |
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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.') |
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shared.gradio['min_length'] = gr.Slider(0, 2000, step=1, value=generate_params['min_length'], label='min_length', info='Minimum generation length in tokens.') |
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shared.gradio['do_sample'] = gr.Checkbox(value=generate_params['do_sample'], label='do_sample') |
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with gr.Column(): |
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with gr.Box(): |
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gr.Markdown('Contrastive search') |
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shared.gradio['penalty_alpha'] = gr.Slider(0, 5, value=generate_params['penalty_alpha'], label='penalty_alpha') |
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|
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gr.Markdown('Beam search (uses a lot of VRAM)') |
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with gr.Row(): |
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with gr.Column(): |
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shared.gradio['num_beams'] = gr.Slider(1, 20, step=1, value=generate_params['num_beams'], label='num_beams') |
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shared.gradio['length_penalty'] = gr.Slider(-5, 5, value=generate_params['length_penalty'], label='length_penalty') |
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with gr.Column(): |
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shared.gradio['early_stopping'] = gr.Checkbox(value=generate_params['early_stopping'], label='early_stopping') |
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|
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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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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['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='Forces the model to never end the generation prematurely.') |
|
|
|
shared.gradio['skip_special_tokens'] = gr.Checkbox(value=shared.settings['skip_special_tokens'], label='Skip special tokens', info='Some specific models need this unset.') |
|
|
|
with gr.Accordion('Soft prompt', open=False): |
|
with gr.Row(): |
|
shared.gradio['softprompts_menu'] = gr.Dropdown(choices=get_available_softprompts(), value='None', label='Soft prompt') |
|
ui.create_refresh_button(shared.gradio['softprompts_menu'], lambda: None, lambda: {'choices': get_available_softprompts()}, 'refresh-button') |
|
|
|
gr.Markdown('Upload a soft prompt (.zip format):') |
|
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:]: |
|
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(): |
|
|
|
|
|
gen_events = [] |
|
default_preset = shared.settings['presets'][next((k for k in shared.settings['presets'] if re.match(k.lower(), shared.model_name.lower())), 'default')] |
|
if len(shared.lora_names) == 1: |
|
default_text = load_prompt(shared.settings['lora_prompts'][next((k for k in shared.settings['lora_prompts'] if re.match(k.lower(), shared.lora_names[0].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' |
|
|
|
|
|
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] |
|
|
|
|
|
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, theme=ui.theme) as shared.gradio['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() |
|
|
|
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['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['Copy last reply'] = gr.Button('Copy last reply') |
|
shared.gradio['Regenerate'] = gr.Button('Regenerate') |
|
shared.gradio['Replace last reply'] = gr.Button('Replace last reply') |
|
|
|
with gr.Row(): |
|
shared.gradio['Impersonate'] = gr.Button('Impersonate') |
|
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['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=shared.settings['mode'], label='Mode') |
|
shared.gradio['instruction_template'] = gr.Dropdown(choices=get_available_instruction_templates(), label='Instruction template', value='None', visible=shared.settings['mode'] == 'instruct', info='Change this according to the model/LoRA that you are using.') |
|
|
|
with gr.Tab('Character', elem_id='chat-settings'): |
|
with gr.Row(): |
|
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['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.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=get_available_characters(), 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) |
|
|
|
|
|
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'] = 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=get_available_prompts(), value='None', label='Prompt') |
|
ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': get_available_prompts()}, 'refresh-button') |
|
|
|
shared.gradio['save_prompt'] = gr.Button('Save prompt') |
|
shared.gradio['count_tokens'] = gr.Button('Count tokens') |
|
shared.gradio['status'] = gr.Markdown('') |
|
|
|
with gr.Tab("Parameters", elem_id="parameters"): |
|
create_settings_menus(default_preset) |
|
|
|
|
|
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['save_prompt'] = gr.Button('Save prompt', 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=get_available_prompts(), value='None', label='Prompt') |
|
ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': get_available_prompts()}, 'refresh-button') |
|
|
|
with gr.Column(): |
|
shared.gradio['status'] = gr.Markdown('') |
|
|
|
with gr.Column(): |
|
with gr.Tab('Raw'): |
|
shared.gradio['output_textbox'] = gr.Textbox(elem_classes="textbox_default_output", 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) |
|
|
|
|
|
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 getattr(shared.args, mode): |
|
current_mode = mode |
|
break |
|
cmd_list = vars(shared.args) |
|
bool_list = [k for k in cmd_list if type(cmd_list[k]) is bool and k not in modes + ui.list_model_elements()] |
|
bool_active = [k for k in bool_list if vars(shared.args)[k]] |
|
|
|
gr.Markdown("*Experimental*") |
|
shared.gradio['interface_modes_menu'] = gr.Dropdown(choices=modes, value=current_mode, label="Mode") |
|
shared.gradio['extensions_menu'] = gr.CheckboxGroup(choices=get_available_extensions(), value=shared.args.extensions, label="Available extensions") |
|
shared.gradio['bool_menu'] = gr.CheckboxGroup(choices=bool_list, value=bool_active, label="Boolean command-line flags") |
|
shared.gradio['reset_interface'] = gr.Button("Apply and restart the interface") |
|
|
|
|
|
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.is_chat(): |
|
shared.input_params = [shared.gradio[k] for k in ['Chat input', 'interface_state']] |
|
clear_arr = [shared.gradio[k] for k in ['Clear history-confirm', 'Clear history', 'Clear history-cancel']] |
|
reload_inputs = [shared.gradio[k] for k in ['name1', 'name2', 'mode']] |
|
|
|
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.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( |
|
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.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( |
|
ui.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( |
|
ui.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( |
|
ui.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['Send dummy message'].click( |
|
chat.send_dummy_message, [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['Send dummy reply'].click( |
|
chat.send_dummy_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_template']).then( |
|
lambda x: gr.update(interactive=x != 'instruct'), shared.gradio['mode'], shared.gradio['character_menu']).then( |
|
chat.redraw_html, reload_inputs, shared.gradio['display']) |
|
|
|
shared.gradio['instruction_template'].change( |
|
chat.load_character, [shared.gradio[k] for k in ['instruction_template', 'name1', 'name2', 'mode']], [shared.gradio[k] for k in ['name1', 'name2', 'character_picture', 'greeting', 'context', 'turn_template', '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', 'turn_template', '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}}}") |
|
|
|
|
|
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', 'markdown', 'html']] |
|
else: |
|
output_params = [shared.gradio[k] for k in ['output_textbox', 'markdown', '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, shared.input_params, output_params, show_progress=shared.args.no_stream) |
|
|
|
) |
|
|
|
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, shared.input_params, output_params, show_progress=shared.args.no_stream) |
|
|
|
) |
|
|
|
if shared.args.notebook: |
|
shared.gradio['Undo'].click(lambda x: x, shared.gradio['last_input'], shared.gradio['textbox'], show_progress=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, shared.input_params, output_params, show_progress=shared.args.no_stream) |
|
|
|
) |
|
else: |
|
gen_events.append(shared.gradio['Continue'].click( |
|
ui.gather_interface_values, [shared.gradio[k] for k in shared.input_elements], shared.gradio['interface_state']).then( |
|
generate_reply, [shared.gradio['output_textbox']] + shared.input_params[1:], output_params, show_progress=shared.args.no_stream) |
|
|
|
) |
|
|
|
shared.gradio['Stop'].click(stop_everything_event, None, None, queue=False, cancels=gen_events if shared.args.no_stream else None) |
|
shared.gradio['prompt_menu'].change(load_prompt, shared.gradio['prompt_menu'], shared.gradio['textbox'], show_progress=False) |
|
shared.gradio['save_prompt'].click(save_prompt, shared.gradio['textbox'], shared.gradio['status'], show_progress=False) |
|
shared.gradio['count_tokens'].click(count_tokens, shared.gradio['textbox'], shared.gradio['status'], show_progress=False) |
|
shared.gradio['interface'].load(None, None, None, _js=f"() => {{{ui.main_js}}}") |
|
|
|
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) |
|
|
|
if shared.args.extensions is not None: |
|
extensions_module.create_extensions_block() |
|
|
|
|
|
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__": |
|
|
|
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: |
|
logging.info(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] |
|
|
|
|
|
extensions_module.available_extensions = get_available_extensions() |
|
if shared.is_chat(): |
|
for extension in shared.settings['chat_default_extensions']: |
|
shared.args.extensions = shared.args.extensions or [] |
|
if extension not in shared.args.extensions: |
|
shared.args.extensions.append(extension) |
|
else: |
|
for extension in shared.settings['default_extensions']: |
|
shared.args.extensions = shared.args.extensions or [] |
|
if extension not in shared.args.extensions: |
|
shared.args.extensions.append(extension) |
|
|
|
available_models = get_available_models() |
|
|
|
|
|
if shared.args.model is not None: |
|
shared.model_name = shared.args.model |
|
|
|
|
|
elif len(available_models) == 1: |
|
shared.model_name = available_models[0] |
|
|
|
|
|
elif shared.args.model_menu: |
|
if len(available_models) == 0: |
|
logging.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 shared.model_name != 'None': |
|
model_settings = get_model_specific_settings(shared.model_name) |
|
shared.settings.update(model_settings) |
|
update_model_parameters(model_settings, initial=True) |
|
|
|
|
|
shared.model, shared.tokenizer = load_model(shared.model_name) |
|
if shared.args.lora: |
|
add_lora_to_model(shared.args.lora) |
|
|
|
|
|
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'] |
|
}) |
|
|
|
|
|
create_interface() |
|
while True: |
|
time.sleep(0.5) |
|
if shared.need_restart: |
|
shared.need_restart = False |
|
shared.gradio['interface'].close() |
|
create_interface() |
|
|