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import os |
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import warnings |
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from modules.logging_colors import logger |
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from modules.block_requests import OpenMonkeyPatch, RequestBlocker |
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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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with RequestBlocker(): |
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import gradio as gr |
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import matplotlib |
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matplotlib.use('Agg') |
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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 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, loaders, presets, shared, training, ui, utils |
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from modules.extensions import apply_extensions |
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from modules.github import clone_or_pull_repository |
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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.models_settings import ( |
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apply_model_settings_to_state, |
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get_model_settings_from_yamls, |
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save_model_settings, |
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update_model_parameters |
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) |
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from modules.text_generation import ( |
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generate_reply_wrapper, |
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get_encoded_length, |
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stop_everything_event |
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) |
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from modules.utils import gradio |
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def load_model_wrapper(selected_model, loader, 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\" 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, loader) |
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if shared.model is not None: |
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yield f"Successfully loaded {selected_model}" |
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else: |
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yield f"Failed to load {selected_model}." |
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except: |
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exc = traceback.format_exc() |
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logger.error('Failed to load the model.') |
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print(exc) |
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yield exc.replace('\n', '\n\n') |
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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_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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file_path = Path(f'characters/instruction-following/{fname}.yaml') |
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if not file_path.exists(): |
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return '' |
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with open(file_path, '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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file_path = Path(f'prompts/{fname}.txt') |
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if not file_path.exists(): |
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return '' |
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with open(file_path, '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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try: |
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tokens = get_encoded_length(text) |
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return f'{tokens} tokens in the input.' |
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except: |
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return 'Couldn\'t count the number of tokens. Is a tokenizer loaded?' |
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def download_model_wrapper(repo_id, progress=gr.Progress()): |
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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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progress(0.0) |
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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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base_folder = shared.args.lora_dir if is_lora else shared.args.model_dir |
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output_folder = downloader.get_output_folder(model, branch, is_lora, base_folder=base_folder) |
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if check: |
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progress(0.5) |
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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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progress(1.0) |
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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, progress_bar=progress, threads=1) |
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yield ("Done!") |
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except: |
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progress(1.0) |
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yield traceback.format_exc().replace('\n', '\n\n') |
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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=utils.get_available_models(), value=shared.model_name, label='Model', elem_classes='slim-dropdown') |
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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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load = gr.Button("Load", visible=not shared.settings['autoload_model'], elem_classes='refresh-button') |
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unload = gr.Button("Unload", elem_classes='refresh-button') |
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reload = gr.Button("Reload", elem_classes='refresh-button') |
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save_settings = gr.Button("Save settings", elem_classes='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)', elem_classes='slim-dropdown') |
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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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shared.gradio['lora_menu_apply'] = gr.Button(value='Apply LoRAs', elem_classes='refresh-button') |
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with gr.Row(): |
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with gr.Column(): |
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shared.gradio['loader'] = gr.Dropdown(label="Model loader", choices=["Transformers", "ExLlama_HF", "ExLlama", "AutoGPTQ", "GPTQ-for-LLaMa", "llama.cpp", "llamacpp_HF"], value=None) |
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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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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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shared.gradio['transformers_info'] = gr.Markdown('load-in-4bit params:') |
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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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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=16384, step=256, label="n_ctx", value=shared.args.n_ctx) |
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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_gqa'] = gr.Slider(minimum=0, maximum=16, step=1, label="n_gqa", value=shared.args.n_gqa, info='grouped-query attention. Must be 8 for llama-2 70b.') |
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shared.gradio['rms_norm_eps'] = gr.Slider(minimum=0, maximum=1e-5, step=1e-6, label="rms_norm_eps", value=shared.args.n_gqa, info='5e-6 is a good value for llama-2 models.') |
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shared.gradio['wbits'] = gr.Dropdown(label="wbits", choices=["None", 1, 2, 3, 4, 8], value=str(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=str(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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shared.gradio['autogptq_info'] = gr.Markdown('* ExLlama_HF is recommended over AutoGPTQ for models derived from LLaMA.') |
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shared.gradio['gpu_split'] = gr.Textbox(label='gpu-split', info='Comma-separated list of VRAM (in GB) to use per GPU. Example: 20,7,7') |
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shared.gradio['max_seq_len'] = gr.Slider(label='max_seq_len', minimum=2048, maximum=16384, step=256, info='Maximum sequence length.', value=shared.args.max_seq_len) |
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shared.gradio['compress_pos_emb'] = gr.Slider(label='compress_pos_emb', minimum=1, maximum=8, step=1, info='Positional embeddings compression factor. Should typically be set to max_seq_len / 2048.', value=shared.args.compress_pos_emb) |
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shared.gradio['alpha_value'] = gr.Slider(label='alpha_value', minimum=1, maximum=32, step=1, info='Positional embeddings alpha factor for NTK RoPE scaling. Scaling is not identical to embedding compression. Use either this or compress_pos_emb, not both.', value=shared.args.alpha_value) |
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with gr.Column(): |
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shared.gradio['triton'] = gr.Checkbox(label="triton", value=shared.args.triton) |
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shared.gradio['no_inject_fused_attention'] = gr.Checkbox(label="no_inject_fused_attention", value=shared.args.no_inject_fused_attention, info='Disable fused attention. Fused attention improves inference performance but uses more VRAM. Disable if running low on VRAM.') |
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shared.gradio['no_inject_fused_mlp'] = gr.Checkbox(label="no_inject_fused_mlp", value=shared.args.no_inject_fused_mlp, info='Affects Triton only. Disable fused MLP. Fused MLP improves performance but uses more VRAM. Disable if running low on VRAM.') |
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shared.gradio['no_use_cuda_fp16'] = gr.Checkbox(label="no_use_cuda_fp16", value=shared.args.no_use_cuda_fp16, info='This can make models faster on some systems.') |
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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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shared.gradio['cpu'] = gr.Checkbox(label="cpu", value=shared.args.cpu) |
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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['bf16'] = gr.Checkbox(label="bf16", value=shared.args.bf16) |
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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['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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shared.gradio['no_mmap'] = gr.Checkbox(label="no-mmap", value=shared.args.no_mmap) |
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shared.gradio['low_vram'] = gr.Checkbox(label="low-vram", value=shared.args.low_vram) |
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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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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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shared.gradio['gptq_for_llama_info'] = gr.Markdown('GPTQ-for-LLaMa is currently 2x faster than AutoGPTQ on some systems. It is installed by default with the one-click installers. Otherwise, it has to be installed manually following the instructions here: [instructions](https://github.com/oobabooga/text-generation-webui/blob/main/docs/GPTQ-models-(4-bit-mode).md#installation-1).') |
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shared.gradio['exllama_info'] = gr.Markdown('For more information, consult the [docs](https://github.com/oobabooga/text-generation-webui/blob/main/docs/ExLlama.md).') |
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shared.gradio['exllama_HF_info'] = gr.Markdown('ExLlama_HF is a wrapper that lets you use ExLlama like a Transformers model, which means it can use the Transformers samplers. It\'s a bit slower than the regular ExLlama.') |
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shared.gradio['llamacpp_HF_info'] = gr.Markdown('llamacpp_HF is a wrapper that lets you use llama.cpp like a Transformers model, which means it can use the Transformers samplers. To use it, make sure to first download oobabooga/llama-tokenizer under "Download custom model or LoRA".') |
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with gr.Column(): |
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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.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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shared.gradio['loader'].change(loaders.make_loader_params_visible, gradio('loader'), gradio(loaders.get_all_params())) |
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shared.gradio['model_menu'].change( |
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ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
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apply_model_settings_to_state, gradio('model_menu', 'interface_state'), gradio('interface_state')).then( |
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ui.apply_interface_values, gradio('interface_state'), gradio(ui.list_interface_input_elements()), show_progress=False).then( |
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update_model_parameters, gradio('interface_state'), None).then( |
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load_model_wrapper, gradio('model_menu', 'loader', 'autoload_model'), gradio('model_status'), show_progress=False) |
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load.click( |
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ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
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update_model_parameters, gradio('interface_state'), None).then( |
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partial(load_model_wrapper, autoload=True), gradio('model_menu', 'loader'), 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, 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, gradio(shared.input_elements), gradio('interface_state')).then( |
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update_model_parameters, gradio('interface_state'), None).then( |
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partial(load_model_wrapper, autoload=True), gradio('model_menu', 'loader'), gradio('model_status'), show_progress=False) |
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save_settings.click( |
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ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
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save_model_settings, gradio('model_menu', 'interface_state'), gradio('model_status'), show_progress=False) |
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shared.gradio['lora_menu_apply'].click(load_lora_wrapper, gradio('lora_menu'), gradio('model_status'), show_progress=False) |
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shared.gradio['download_model_button'].click(download_model_wrapper, gradio('custom_model_menu'), gradio('model_status'), show_progress=True) |
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shared.gradio['autoload_model'].change(lambda x: gr.update(visible=not x), gradio('autoload_model'), load) |
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def create_chat_settings_menus(): |
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if not shared.is_chat(): |
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return |
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with gr.Box(): |
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gr.Markdown("Chat parameters") |
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with gr.Row(): |
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with gr.Column(): |
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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']) |
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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.') |
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with gr.Column(): |
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shared.gradio['stop_at_newline'] = gr.Checkbox(value=shared.settings['stop_at_newline'], label='Stop generating at new line character') |
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def create_settings_menus(default_preset): |
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generate_params = presets.load_preset(default_preset) |
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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=utils.get_available_presets(), value=default_preset, label='Generation parameters preset', elem_classes='slim-dropdown') |
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ui.create_refresh_button(shared.gradio['preset_menu'], lambda: None, lambda: {'choices': utils.get_available_presets()}, 'refresh-button') |
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shared.gradio['save_preset'] = gr.Button('💾', elem_classes='refresh-button') |
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shared.gradio['delete_preset'] = gr.Button('🗑️', elem_classes='refresh-button') |
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|
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with gr.Column(): |
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filter_by_loader = gr.Dropdown(label="Filter by loader", choices=["All", "Transformers", "ExLlama_HF", "ExLlama", "AutoGPTQ", "GPTQ-for-LLaMa", "llama.cpp", "llamacpp_HF"], value="All", elem_classes='slim-dropdown') |
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|
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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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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') |
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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') |
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shared.gradio['top_k'] = gr.Slider(0, 200, value=generate_params['top_k'], step=1, label='top_k') |
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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') |
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shared.gradio['epsilon_cutoff'] = gr.Slider(0, 9, value=generate_params['epsilon_cutoff'], step=0.01, label='epsilon_cutoff') |
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shared.gradio['eta_cutoff'] = gr.Slider(0, 20, value=generate_params['eta_cutoff'], step=0.01, label='eta_cutoff') |
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shared.gradio['tfs'] = gr.Slider(0.0, 1.0, value=generate_params['tfs'], step=0.01, label='tfs') |
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shared.gradio['top_a'] = gr.Slider(0.0, 1.0, value=generate_params['top_a'], step=0.01, label='top_a') |
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|
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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') |
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shared.gradio['repetition_penalty_range'] = gr.Slider(0, 4096, step=64, value=generate_params['repetition_penalty_range'], label='repetition_penalty_range') |
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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') |
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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') |
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shared.gradio['min_length'] = gr.Slider(0, 2000, step=1, value=generate_params['min_length'], label='min_length') |
|
shared.gradio['seed'] = gr.Number(value=shared.settings['seed'], label='Seed (-1 for random)') |
|
shared.gradio['do_sample'] = gr.Checkbox(value=generate_params['do_sample'], label='do_sample') |
|
|
|
with gr.Accordion("Learn more", open=False): |
|
gr.Markdown(""" |
|
|
|
For a technical description of the parameters, the [transformers documentation](https://huggingface.co/docs/transformers/main_classes/text_generation#transformers.GenerationConfig) is a good reference. |
|
|
|
The best presets, according to the [Preset Arena](https://github.com/oobabooga/oobabooga.github.io/blob/main/arena/results.md) experiment, are: |
|
|
|
* Instruction following: |
|
1) Divine Intellect |
|
2) Big O |
|
3) simple-1 |
|
4) Space Alien |
|
5) StarChat |
|
6) Titanic |
|
7) tfs-with-top-a |
|
8) Asterism |
|
9) Contrastive Search |
|
|
|
* Chat: |
|
1) Midnight Enigma |
|
2) Yara |
|
3) Shortwave |
|
|
|
### Temperature |
|
Primary factor to control randomness of outputs. 0 = deterministic (only the most likely token is used). Higher value = more randomness. |
|
### top_p |
|
If not set to 1, select tokens with probabilities adding up to less than this number. Higher value = higher range of possible random results. |
|
### top_k |
|
Similar to top_p, but select instead only the top_k most likely tokens. Higher value = higher range of possible random results. |
|
### typical_p |
|
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. |
|
### epsilon_cutoff |
|
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. |
|
### eta_cutoff |
|
In units of 1e-4; a reasonable value is 3. Should be used with top_p, top_k, and epsilon_cutoff set to 0. |
|
### repetition_penalty |
|
Exponential penalty factor for repeating prior tokens. 1 means no penalty, higher value = less repetition, lower value = more repetition. |
|
### repetition_penalty_range |
|
The number of most recent tokens to consider for repetition penalty. 0 makes all tokens be used. |
|
### encoder_repetition_penalty |
|
Also known as the "Hallucinations filter". Used to penalize tokens that are *not* in the prior text. Higher value = more likely to stay in context, lower value = more likely to diverge. |
|
### no_repeat_ngram_size |
|
If not set to 0, specifies the length of token sets that are completely blocked from repeating at all. Higher values = blocks larger phrases, lower values = blocks words or letters from repeating. Only 0 or high values are a good idea in most cases. |
|
### min_length |
|
Minimum generation length in tokens. |
|
### penalty_alpha |
|
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. |
|
|
|
""", elem_classes="markdown") |
|
|
|
with gr.Column(): |
|
create_chat_settings_menus() |
|
with gr.Box(): |
|
with gr.Row(): |
|
with gr.Column(): |
|
shared.gradio['mirostat_mode'] = gr.Slider(0, 2, step=1, value=generate_params['mirostat_mode'], label='mirostat_mode', info='mode=1 is for llama.cpp only.') |
|
shared.gradio['mirostat_tau'] = gr.Slider(0, 10, step=0.01, value=generate_params['mirostat_tau'], label='mirostat_tau') |
|
shared.gradio['mirostat_eta'] = gr.Slider(0, 1, step=0.01, value=generate_params['mirostat_eta'], label='mirostat_eta') |
|
|
|
with gr.Column(): |
|
shared.gradio['penalty_alpha'] = gr.Slider(0, 5, value=generate_params['penalty_alpha'], label='penalty_alpha', info='For Contrastive Search. do_sample must be unchecked.') |
|
|
|
shared.gradio['num_beams'] = gr.Slider(1, 20, step=1, value=generate_params['num_beams'], label='num_beams', info='For Beam Search, along with length_penalty and early_stopping.') |
|
shared.gradio['length_penalty'] = gr.Slider(-5, 5, value=generate_params['length_penalty'], label='length_penalty') |
|
shared.gradio['early_stopping'] = gr.Checkbox(value=generate_params['early_stopping'], label='early_stopping') |
|
|
|
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=256, label='Truncate the prompt up to this length', info='The leftmost tokens are removed if the prompt exceeds this length. Most models require this to be at most 2048.') |
|
shared.gradio['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['auto_max_new_tokens'] = gr.Checkbox(value=shared.settings['auto_max_new_tokens'], label='auto_max_new_tokens', info='Expand max_new_tokens to the available context length.') |
|
shared.gradio['ban_eos_token'] = gr.Checkbox(value=shared.settings['ban_eos_token'], label='Ban the eos_token', info='Forces the model to never end the generation prematurely.') |
|
shared.gradio['add_bos_token'] = gr.Checkbox(value=shared.settings['add_bos_token'], label='Add the bos_token to the beginning of prompts', info='Disabling this can make the replies more creative.') |
|
|
|
shared.gradio['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') |
|
|
|
filter_by_loader.change(loaders.blacklist_samplers, filter_by_loader, gradio(loaders.list_all_samplers()), show_progress=False) |
|
shared.gradio['preset_menu'].change(presets.load_preset_for_ui, gradio('preset_menu', 'interface_state'), gradio('interface_state', 'do_sample', 'temperature', 'top_p', 'typical_p', 'epsilon_cutoff', 'eta_cutoff', 'repetition_penalty', 'repetition_penalty_range', '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 create_file_saving_menus(): |
|
|
|
|
|
with gr.Box(visible=False, elem_classes='file-saver') as shared.gradio['file_saver']: |
|
shared.gradio['save_filename'] = gr.Textbox(lines=1, label='File name') |
|
shared.gradio['save_root'] = gr.Textbox(lines=1, label='File folder', info='For reference. Unchangeable.', interactive=False) |
|
shared.gradio['save_contents'] = gr.Textbox(lines=10, label='File contents') |
|
with gr.Row(): |
|
shared.gradio['save_confirm'] = gr.Button('Save', elem_classes="small-button") |
|
shared.gradio['save_cancel'] = gr.Button('Cancel', elem_classes="small-button") |
|
|
|
|
|
with gr.Box(visible=False, elem_classes='file-saver') as shared.gradio['file_deleter']: |
|
shared.gradio['delete_filename'] = gr.Textbox(lines=1, label='File name') |
|
shared.gradio['delete_root'] = gr.Textbox(lines=1, label='File folder', info='For reference. Unchangeable.', interactive=False) |
|
with gr.Row(): |
|
shared.gradio['delete_confirm'] = gr.Button('Delete', elem_classes="small-button", variant='stop') |
|
shared.gradio['delete_cancel'] = gr.Button('Cancel', elem_classes="small-button") |
|
|
|
|
|
if shared.is_chat(): |
|
with gr.Box(visible=False, elem_classes='file-saver') as shared.gradio['character_saver']: |
|
shared.gradio['save_character_filename'] = gr.Textbox(lines=1, label='File name', info='The character will be saved to your characters/ folder with this base filename.') |
|
with gr.Row(): |
|
shared.gradio['save_character_confirm'] = gr.Button('Save', elem_classes="small-button") |
|
shared.gradio['save_character_cancel'] = gr.Button('Cancel', elem_classes="small-button") |
|
|
|
with gr.Box(visible=False, elem_classes='file-saver') as shared.gradio['character_deleter']: |
|
gr.Markdown('Confirm the character deletion?') |
|
with gr.Row(): |
|
shared.gradio['delete_character_confirm'] = gr.Button('Delete', elem_classes="small-button", variant='stop') |
|
shared.gradio['delete_character_cancel'] = gr.Button('Cancel', elem_classes="small-button") |
|
|
|
|
|
def create_file_saving_event_handlers(): |
|
shared.gradio['save_confirm'].click( |
|
lambda x, y, z: utils.save_file(x + y, z), gradio('save_root', 'save_filename', 'save_contents'), None).then( |
|
lambda: gr.update(visible=False), None, gradio('file_saver')) |
|
|
|
shared.gradio['delete_confirm'].click( |
|
lambda x, y: utils.delete_file(x + y), gradio('delete_root', 'delete_filename'), None).then( |
|
lambda: gr.update(visible=False), None, gradio('file_deleter')) |
|
|
|
shared.gradio['delete_cancel'].click(lambda: gr.update(visible=False), None, gradio('file_deleter')) |
|
shared.gradio['save_cancel'].click(lambda: gr.update(visible=False), None, gradio('file_saver')) |
|
if shared.is_chat(): |
|
shared.gradio['save_character_confirm'].click( |
|
chat.save_character, gradio('name2', 'greeting', 'context', 'character_picture', 'save_character_filename'), None).then( |
|
lambda: gr.update(visible=False), None, gradio('character_saver')) |
|
|
|
shared.gradio['delete_character_confirm'].click( |
|
chat.delete_character, gradio('character_menu'), None).then( |
|
lambda: gr.update(visible=False), None, gradio('character_deleter')).then( |
|
lambda: gr.update(choices=utils.get_available_characters()), None, gradio('character_menu')) |
|
|
|
shared.gradio['save_character_cancel'].click(lambda: gr.update(visible=False), None, gradio('character_saver')) |
|
shared.gradio['delete_character_cancel'].click(lambda: gr.update(visible=False), None, gradio('character_deleter')) |
|
|
|
shared.gradio['save_preset'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
presets.generate_preset_yaml, gradio('interface_state'), gradio('save_contents')).then( |
|
lambda: 'presets/', None, gradio('save_root')).then( |
|
lambda: 'My Preset.yaml', None, gradio('save_filename')).then( |
|
lambda: gr.update(visible=True), None, gradio('file_saver')) |
|
|
|
shared.gradio['delete_preset'].click( |
|
lambda x: f'{x}.yaml', gradio('preset_menu'), gradio('delete_filename')).then( |
|
lambda: 'presets/', None, gradio('delete_root')).then( |
|
lambda: gr.update(visible=True), None, gradio('file_deleter')) |
|
|
|
if not shared.args.multi_user: |
|
|
|
def load_session(file, state): |
|
decoded_file = file if type(file) == str else file.decode('utf-8') |
|
data = json.loads(decoded_file) |
|
|
|
if shared.is_chat() and 'character_menu' in data and state.get('character_menu') != data.get('character_menu'): |
|
shared.session_is_loading = True |
|
|
|
state.update(data) |
|
return state |
|
|
|
shared.gradio['save_session'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
lambda x: json.dumps(x, indent=4), gradio('interface_state'), gradio('temporary_text')).then( |
|
None, gradio('temporary_text'), None, _js=f"(contents) => {{{ui.save_files_js}; saveSession(contents, \"{shared.get_mode()}\")}}") |
|
|
|
if shared.is_chat(): |
|
shared.gradio['load_session'].upload( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
load_session, gradio('load_session', 'interface_state'), gradio('interface_state')).then( |
|
ui.apply_interface_values, gradio('interface_state'), gradio(ui.list_interface_input_elements()), show_progress=False).then( |
|
chat.redraw_html, shared.reload_inputs, gradio('display')).then( |
|
None, None, None, _js='() => {alert("The session has been loaded.")}') |
|
else: |
|
shared.gradio['load_session'].upload( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
load_session, gradio('load_session', 'interface_state'), gradio('interface_state')).then( |
|
ui.apply_interface_values, gradio('interface_state'), gradio(ui.list_interface_input_elements()), show_progress=False).then( |
|
None, None, None, _js='() => {alert("The session has been loaded.")}') |
|
|
|
|
|
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['preset'] |
|
default_text = load_prompt(shared.settings['prompt']) |
|
title = 'Text generation web UI' |
|
|
|
|
|
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] |
|
|
|
|
|
if shared.args.extensions is not None and len(shared.args.extensions) > 0: |
|
extensions_module.load_extensions() |
|
|
|
|
|
shared.persistent_interface_state.update({ |
|
'loader': shared.args.loader or 'Transformers', |
|
}) |
|
|
|
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'] |
|
}) |
|
|
|
if Path("cache/pfp_character.png").exists(): |
|
Path("cache/pfp_character.png").unlink() |
|
|
|
|
|
css = ui.css if not shared.is_chat() else ui.css + ui.chat_css |
|
js = ui.main_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_file_saving_menus() |
|
|
|
|
|
shared.gradio['temporary_text'] = gr.Textbox(visible=False) |
|
|
|
|
|
if shared.is_chat(): |
|
shared.input_elements = ui.list_interface_input_elements() |
|
|
|
shared.gradio.update({ |
|
'interface_state': gr.State({k: None for k in shared.input_elements}), |
|
'Chat input': gr.State(), |
|
'dummy': gr.State(), |
|
'history': gr.State({'internal': [], 'visible': []}), |
|
}) |
|
|
|
with gr.Tab('Text generation', elem_id='main'): |
|
shared.gradio['display'] = gr.HTML(value=chat_html_wrapper({'internal': [], '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', elem_classes=['button_nowrap']) |
|
|
|
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.Tab("Character"): |
|
with gr.Row(): |
|
with gr.Column(scale=8): |
|
with gr.Row(): |
|
shared.gradio['character_menu'] = gr.Dropdown(value='None', choices=utils.get_available_characters(), label='Character', elem_id='character-menu', info='Used in chat and chat-instruct modes.', elem_classes='slim-dropdown') |
|
ui.create_refresh_button(shared.gradio['character_menu'], lambda: None, lambda: {'choices': utils.get_available_characters()}, 'refresh-button') |
|
shared.gradio['save_character'] = gr.Button('💾', elem_classes='refresh-button') |
|
shared.gradio['delete_character'] = gr.Button('🗑️', elem_classes='refresh-button') |
|
|
|
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', elem_classes=['add_scrollbar']) |
|
shared.gradio['greeting'] = gr.Textbox(value=shared.settings['greeting'], lines=4, label='Greeting', elem_classes=['add_scrollbar']) |
|
|
|
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.Tab("Instruction template"): |
|
with gr.Row(): |
|
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.', elem_classes='slim-dropdown') |
|
ui.create_refresh_button(shared.gradio['instruction_template'], lambda: None, lambda: {'choices': utils.get_available_instruction_templates()}, 'refresh-button') |
|
shared.gradio['save_template'] = gr.Button('💾', elem_classes='refresh-button') |
|
shared.gradio['delete_template'] = gr.Button('🗑️ ', elem_classes='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.', elem_classes=['add_scrollbar']) |
|
|
|
with gr.Tab('Chat history'): |
|
with gr.Row(): |
|
with gr.Column(): |
|
shared.gradio['save_chat_history'] = gr.Button(value='Save history') |
|
|
|
with gr.Column(): |
|
shared.gradio['load_chat_history'] = gr.File(type='binary', file_types=['.json', '.txt'], label="Upload History JSON") |
|
|
|
with gr.Tab('Upload character'): |
|
with gr.Tab('YAML or JSON'): |
|
with gr.Row(): |
|
shared.gradio['upload_json'] = gr.File(type='binary', file_types=['.json', '.yaml'], label='JSON or YAML File') |
|
shared.gradio['upload_img_bot'] = gr.Image(type='pil', label='Profile Picture (optional)') |
|
|
|
shared.gradio['Submit character'] = gr.Button(value='Submit', interactive=False) |
|
|
|
with gr.Tab('TavernAI PNG'): |
|
with gr.Row(): |
|
with gr.Column(): |
|
shared.gradio['upload_img_tavern'] = gr.Image(type='pil', label='TavernAI PNG File', elem_id="upload_img_tavern") |
|
shared.gradio['tavern_json'] = gr.State() |
|
with gr.Column(): |
|
shared.gradio['tavern_name'] = gr.Textbox(value='', lines=1, label='Name', interactive=False) |
|
shared.gradio['tavern_desc'] = gr.Textbox(value='', lines=4, max_lines=4, label='Description', interactive=False) |
|
|
|
shared.gradio['Submit tavern character'] = gr.Button(value='Submit', interactive=False) |
|
|
|
with gr.Tab("Parameters", elem_id="parameters"): |
|
create_settings_menus(default_preset) |
|
|
|
|
|
elif shared.args.notebook: |
|
shared.input_elements = ui.list_interface_input_elements() |
|
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', 'add_scrollbar'], 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", elem_id='stop') |
|
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', elem_classes='slim-dropdown') |
|
ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': utils.get_available_prompts()}, ['refresh-button', 'refresh-button-small']) |
|
shared.gradio['save_prompt'] = gr.Button('💾', elem_classes=['refresh-button', 'refresh-button-small']) |
|
shared.gradio['delete_prompt'] = gr.Button('🗑️', elem_classes=['refresh-button', 'refresh-button-small']) |
|
|
|
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() |
|
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', 'add_scrollbar'], 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') |
|
shared.gradio['Stop'] = gr.Button('Stop', elem_id='stop') |
|
shared.gradio['Continue'] = gr.Button('Continue') |
|
shared.gradio['count_tokens'] = gr.Button('Count tokens') |
|
|
|
with gr.Row(): |
|
shared.gradio['prompt_menu'] = gr.Dropdown(choices=utils.get_available_prompts(), value='None', label='Prompt', elem_classes='slim-dropdown') |
|
ui.create_refresh_button(shared.gradio['prompt_menu'], lambda: None, lambda: {'choices': utils.get_available_prompts()}, 'refresh-button') |
|
shared.gradio['save_prompt'] = gr.Button('💾', elem_classes='refresh-button') |
|
shared.gradio['delete_prompt'] = gr.Button('🗑️', elem_classes='refresh-button') |
|
|
|
shared.gradio['status'] = gr.Markdown('') |
|
|
|
with gr.Column(): |
|
with gr.Tab('Raw'): |
|
shared.gradio['output_textbox'] = gr.Textbox(lines=27, label='Output', elem_classes=['textbox_default_output', 'add_scrollbar']) |
|
|
|
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) |
|
|
|
|
|
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("Session", elem_id="session-tab"): |
|
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(): |
|
|
|
with gr.Column(): |
|
with gr.Row(): |
|
shared.gradio['interface_modes_menu'] = gr.Dropdown(choices=modes, value=current_mode, label="Mode", elem_classes='slim-dropdown') |
|
shared.gradio['reset_interface'] = gr.Button("Apply and restart", elem_classes="small-button", variant="primary") |
|
shared.gradio['toggle_dark_mode'] = gr.Button('Toggle 💡', elem_classes="small-button") |
|
|
|
with gr.Row(): |
|
with gr.Column(): |
|
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', elem_classes='checkboxgroup-table') |
|
|
|
with gr.Column(): |
|
shared.gradio['bool_menu'] = gr.CheckboxGroup(choices=bool_list, value=bool_active, label="Boolean command-line flags", elem_classes='checkboxgroup-table') |
|
|
|
with gr.Column(): |
|
if not shared.args.multi_user: |
|
shared.gradio['save_session'] = gr.Button('Save session', elem_id="save_session") |
|
shared.gradio['load_session'] = gr.File(type='binary', file_types=['.json'], label="Upload Session JSON") |
|
|
|
extension_name = gr.Textbox(lines=1, label='Install or update an extension', info='Enter the GitHub URL below and press Enter. For a list of extensions, see: https://github.com/oobabooga/text-generation-webui-extensions ⚠️ WARNING ⚠️ : extensions can execute arbitrary code. Make sure to inspect their source code before activating them.') |
|
extension_status = gr.Markdown() |
|
|
|
extension_name.submit( |
|
clone_or_pull_repository, extension_name, extension_status, show_progress=False).then( |
|
lambda: gr.update(choices=utils.get_available_extensions(), value=shared.args.extensions), None, gradio('extensions_menu')) |
|
|
|
|
|
shared.gradio['reset_interface'].click( |
|
set_interface_arguments, gradio('interface_modes_menu', 'extensions_menu', 'bool_menu'), None).then( |
|
lambda: None, None, None, _js='() => {document.body.innerHTML=\'<h1 style="font-family:monospace;padding-top:20%;margin:0;height:100vh;color:lightgray;text-align:center;background:var(--body-background-fill)">Reloading...</h1>\'; setTimeout(function(){location.reload()},2500); return []}') |
|
|
|
shared.gradio['toggle_dark_mode'].click(lambda: None, None, None, _js='() => {document.getElementsByTagName("body")[0].classList.toggle("dark")}') |
|
|
|
|
|
if shared.is_chat(): |
|
shared.input_params = gradio('Chat input', 'start_with', 'interface_state') |
|
clear_arr = gradio('Clear history-confirm', 'Clear history', 'Clear history-cancel') |
|
shared.reload_inputs = gradio('history', 'name1', 'name2', 'mode', 'chat_style') |
|
|
|
gen_events.append(shared.gradio['Generate'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
lambda x: (x, ''), gradio('textbox'), gradio('Chat input', 'textbox'), show_progress=False).then( |
|
chat.generate_chat_reply_wrapper, shared.input_params, gradio('display', 'history'), show_progress=False).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
chat.save_persistent_history, gradio('history', 'character_menu', 'mode'), None).then( |
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}") |
|
) |
|
|
|
gen_events.append(shared.gradio['textbox'].submit( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
lambda x: (x, ''), gradio('textbox'), gradio('Chat input', 'textbox'), show_progress=False).then( |
|
chat.generate_chat_reply_wrapper, shared.input_params, gradio('display', 'history'), show_progress=False).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
chat.save_persistent_history, gradio('history', 'character_menu', 'mode'), None).then( |
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}") |
|
) |
|
|
|
gen_events.append(shared.gradio['Regenerate'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
partial(chat.generate_chat_reply_wrapper, regenerate=True), shared.input_params, gradio('display', 'history'), show_progress=False).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
chat.save_persistent_history, gradio('history', 'character_menu', 'mode'), None).then( |
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}") |
|
) |
|
|
|
gen_events.append(shared.gradio['Continue'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
partial(chat.generate_chat_reply_wrapper, _continue=True), shared.input_params, gradio('display', 'history'), show_progress=False).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
chat.save_persistent_history, gradio('history', 'character_menu', 'mode'), None).then( |
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}") |
|
) |
|
|
|
gen_events.append(shared.gradio['Impersonate'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
lambda x: x, gradio('textbox'), gradio('Chat input'), show_progress=False).then( |
|
chat.impersonate_wrapper, shared.input_params, gradio('textbox'), show_progress=False).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}") |
|
) |
|
|
|
shared.gradio['Replace last reply'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
chat.replace_last_reply, gradio('textbox', 'interface_state'), gradio('history')).then( |
|
lambda: '', None, gradio('textbox'), show_progress=False).then( |
|
chat.redraw_html, shared.reload_inputs, gradio('display')).then( |
|
chat.save_persistent_history, gradio('history', 'character_menu', 'mode'), None) |
|
|
|
shared.gradio['Send dummy message'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
chat.send_dummy_message, gradio('textbox', 'interface_state'), gradio('history')).then( |
|
lambda: '', None, gradio('textbox'), show_progress=False).then( |
|
chat.redraw_html, shared.reload_inputs, gradio('display')).then( |
|
chat.save_persistent_history, gradio('history', 'character_menu', 'mode'), None) |
|
|
|
shared.gradio['Send dummy reply'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
chat.send_dummy_reply, gradio('textbox', 'interface_state'), gradio('history')).then( |
|
lambda: '', None, gradio('textbox'), show_progress=False).then( |
|
chat.redraw_html, shared.reload_inputs, gradio('display')).then( |
|
chat.save_persistent_history, gradio('history', 'character_menu', 'mode'), None) |
|
|
|
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['Clear history-confirm'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
lambda: [gr.update(visible=False), gr.update(visible=True), gr.update(visible=False)], None, clear_arr).then( |
|
chat.clear_chat_log, gradio('interface_state'), gradio('history')).then( |
|
chat.redraw_html, shared.reload_inputs, gradio('display')).then( |
|
chat.save_persistent_history, gradio('history', 'character_menu', 'mode'), None) |
|
|
|
shared.gradio['Remove last'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
chat.remove_last_message, gradio('history'), gradio('textbox', 'history'), show_progress=False).then( |
|
chat.redraw_html, shared.reload_inputs, gradio('display')).then( |
|
chat.save_persistent_history, gradio('history', 'character_menu', 'mode'), None) |
|
|
|
shared.gradio['character_menu'].change( |
|
partial(chat.load_character, instruct=False), gradio('character_menu', 'name1', 'name2'), gradio('name1', 'name2', 'character_picture', 'greeting', 'context', 'dummy')).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
chat.load_persistent_history, gradio('interface_state'), gradio('history')).then( |
|
chat.redraw_html, shared.reload_inputs, 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, gradio('display')) |
|
|
|
shared.gradio['mode'].change( |
|
lambda x: gr.update(visible=x != 'instruct'), gradio('mode'), gradio('chat_style'), show_progress=False).then( |
|
chat.redraw_html, shared.reload_inputs, gradio('display')) |
|
|
|
shared.gradio['chat_style'].change(chat.redraw_html, shared.reload_inputs, gradio('display')) |
|
shared.gradio['instruction_template'].change( |
|
partial(chat.load_character, instruct=True), gradio('instruction_template', 'name1_instruct', 'name2_instruct'), gradio('name1_instruct', 'name2_instruct', 'dummy', 'dummy', 'context_instruct', 'turn_template')) |
|
|
|
shared.gradio['load_chat_history'].upload( |
|
chat.load_history, gradio('load_chat_history', 'history'), gradio('history')).then( |
|
chat.redraw_html, shared.reload_inputs, gradio('display')).then( |
|
None, None, None, _js='() => {alert("The history has been loaded.")}') |
|
|
|
shared.gradio['Copy last reply'].click(chat.send_last_reply_to_input, gradio('history'), gradio('textbox'), show_progress=False) |
|
|
|
|
|
shared.gradio['save_character'].click( |
|
lambda x: x, gradio('name2'), gradio('save_character_filename')).then( |
|
lambda: gr.update(visible=True), None, gradio('character_saver')) |
|
|
|
shared.gradio['delete_character'].click(lambda: gr.update(visible=True), None, gradio('character_deleter')) |
|
|
|
shared.gradio['save_template'].click( |
|
lambda: 'My Template.yaml', None, gradio('save_filename')).then( |
|
lambda: 'characters/instruction-following/', None, gradio('save_root')).then( |
|
chat.generate_instruction_template_yaml, gradio('name1_instruct', 'name2_instruct', 'context_instruct', 'turn_template'), gradio('save_contents')).then( |
|
lambda: gr.update(visible=True), None, gradio('file_saver')) |
|
|
|
shared.gradio['delete_template'].click( |
|
lambda x: f'{x}.yaml', gradio('instruction_template'), gradio('delete_filename')).then( |
|
lambda: 'characters/instruction-following/', None, gradio('delete_root')).then( |
|
lambda: gr.update(visible=True), None, gradio('file_deleter')) |
|
|
|
shared.gradio['save_chat_history'].click( |
|
lambda x: json.dumps(x, indent=4), gradio('history'), gradio('temporary_text')).then( |
|
None, gradio('temporary_text', 'character_menu', 'mode'), None, _js=f"(hist, char, mode) => {{{ui.save_files_js}; saveHistory(hist, char, mode)}}") |
|
|
|
shared.gradio['Submit character'].click( |
|
chat.upload_character, gradio('upload_json', 'upload_img_bot'), gradio('character_menu')).then( |
|
None, None, None, _js='() => {alert("The character has been loaded.")}') |
|
|
|
shared.gradio['Submit tavern character'].click( |
|
chat.upload_tavern_character, gradio('upload_img_tavern', 'tavern_json'), gradio('character_menu')).then( |
|
None, None, None, _js='() => {alert("The character has been loaded.")}') |
|
|
|
shared.gradio['upload_json'].upload(lambda: gr.update(interactive=True), None, gradio('Submit character')) |
|
shared.gradio['upload_json'].clear(lambda: gr.update(interactive=False), None, gradio('Submit character')) |
|
shared.gradio['upload_img_tavern'].upload(chat.check_tavern_character, gradio('upload_img_tavern'), gradio('tavern_name', 'tavern_desc', 'tavern_json', 'Submit tavern character'), show_progress=False) |
|
shared.gradio['upload_img_tavern'].clear(lambda: (None, None, None, gr.update(interactive=False)), None, gradio('tavern_name', 'tavern_desc', 'tavern_json', 'Submit tavern character'), show_progress=False) |
|
shared.gradio['your_picture'].change( |
|
chat.upload_your_profile_picture, gradio('your_picture'), None).then( |
|
partial(chat.redraw_html, reset_cache=True), shared.reload_inputs, gradio('display')) |
|
|
|
|
|
else: |
|
shared.input_params = gradio('textbox', 'interface_state') |
|
if shared.args.notebook: |
|
output_params = gradio('textbox', 'html') |
|
else: |
|
output_params = gradio('output_textbox', 'html') |
|
|
|
gen_events.append(shared.gradio['Generate'].click( |
|
lambda x: x, gradio('textbox'), gradio('last_input')).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
generate_reply_wrapper, shared.input_params, output_params, show_progress=False).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}") |
|
|
|
) |
|
|
|
gen_events.append(shared.gradio['textbox'].submit( |
|
lambda x: x, gradio('textbox'), gradio('last_input')).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
generate_reply_wrapper, shared.input_params, output_params, show_progress=False).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}") |
|
|
|
) |
|
|
|
if shared.args.notebook: |
|
shared.gradio['Undo'].click(lambda x: x, gradio('last_input'), gradio('textbox'), show_progress=False) |
|
shared.gradio['markdown_render'].click(lambda x: x, gradio('textbox'), gradio('markdown'), queue=False) |
|
gen_events.append(shared.gradio['Regenerate'].click( |
|
lambda x: x, gradio('last_input'), gradio('textbox'), show_progress=False).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
generate_reply_wrapper, shared.input_params, output_params, show_progress=False).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}") |
|
|
|
) |
|
else: |
|
shared.gradio['markdown_render'].click(lambda x: x, gradio('output_textbox'), gradio('markdown'), queue=False) |
|
gen_events.append(shared.gradio['Continue'].click( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
generate_reply_wrapper, [shared.gradio['output_textbox']] + shared.input_params[1:], output_params, show_progress=False).then( |
|
ui.gather_interface_values, gradio(shared.input_elements), gradio('interface_state')).then( |
|
lambda: None, None, None, _js=f"() => {{{audio_notification_js}}}") |
|
|
|
) |
|
|
|
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, gradio('prompt_menu'), gradio('textbox'), show_progress=False) |
|
shared.gradio['save_prompt'].click( |
|
lambda x: x, gradio('textbox'), gradio('save_contents')).then( |
|
lambda: 'prompts/', None, gradio('save_root')).then( |
|
lambda: utils.current_time() + '.txt', None, gradio('save_filename')).then( |
|
lambda: gr.update(visible=True), None, gradio('file_saver')) |
|
|
|
shared.gradio['delete_prompt'].click( |
|
lambda: 'prompts/', None, gradio('delete_root')).then( |
|
lambda x: x + '.txt', gradio('prompt_menu'), gradio('delete_filename')).then( |
|
lambda: gr.update(visible=True), None, gradio('file_deleter')) |
|
|
|
shared.gradio['count_tokens'].click(count_tokens, gradio('textbox'), gradio('status'), show_progress=False) |
|
|
|
create_file_saving_event_handlers() |
|
|
|
if shared.settings['dark_theme']: |
|
shared.gradio['interface'].load(lambda: None, None, None, _js="() => document.getElementsByTagName('body')[0].classList.add('dark')") |
|
|
|
shared.gradio['interface'].load(lambda: None, None, None, _js=f"() => {{{js}}}") |
|
shared.gradio['interface'].load(partial(ui.apply_interface_values, {}, use_persistent=True), None, gradio(ui.list_interface_input_elements()), show_progress=False) |
|
if shared.is_chat(): |
|
shared.gradio['interface'].load(chat.redraw_html, shared.reload_inputs, gradio('display')) |
|
|
|
|
|
extensions_module.create_extensions_tabs() |
|
|
|
|
|
extensions_module.create_extensions_block() |
|
|
|
|
|
shared.gradio['interface'].queue() |
|
with OpenMonkeyPatch(): |
|
shared.gradio['interface'].launch( |
|
prevent_thread_lock=True, |
|
share=shared.args.share, |
|
server_name = None if not shared.args.listen else (shared.args.listen_host or '0.0.0.0'), |
|
server_port=shared.args.listen_port, |
|
inbrowser=shared.args.auto_launch, |
|
auth=auth, |
|
ssl_verify=False if (shared.args.ssl_keyfile or shared.args.ssl_certfile) else True, |
|
ssl_keyfile=shared.args.ssl_keyfile, |
|
ssl_certfile=shared.args.ssl_certfile |
|
) |
|
|
|
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.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] |
|
|
|
|
|
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'], |
|
'n_gqa': 0, |
|
'rms_norm_eps': 0, |
|
} |
|
|
|
shared.model_config.move_to_end('.*', last=False) |
|
|
|
|
|
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() |
|
|
|
|
|
if shared.args.model is not None: |
|
shared.model_name = shared.args.model |
|
|
|
|
|
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 shared.model_name != 'None': |
|
model_settings = get_model_settings_from_yamls(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) |
|
|
|
shared.generation_lock = Lock() |
|
|
|
|
|
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() |
|
|