diff --git a/modules/shared.py b/modules/shared.py index a47a13f1..7fc61e63 100644 --- a/modules/shared.py +++ b/modules/shared.py @@ -41,6 +41,7 @@ settings = { 'truncation_length': 2048, 'truncation_length_min': 0, 'truncation_length_max': 4096, + 'mode': 'cai-chat', 'chat_prompt_size': 2048, 'chat_prompt_size_min': 0, 'chat_prompt_size_max': 2048, @@ -115,9 +116,6 @@ parser.add_argument('--wbits', type=int, default=0, help='GPTQ: Load a pre-quant parser.add_argument('--model_type', type=str, help='GPTQ: Model type of pre-quantized model. Currently LLaMA, OPT, and GPT-J are supported.') parser.add_argument('--groupsize', type=int, default=-1, help='GPTQ: Group size.') parser.add_argument('--pre_layer', type=int, default=0, help='GPTQ: The number of layers to allocate to the GPU. Setting this parameter enables CPU offloading for 4-bit models.') -parser.add_argument('--gptq-bits', type=int, default=0, help='DEPRECATED: use --wbits instead.') -parser.add_argument('--gptq-model-type', type=str, help='DEPRECATED: use --model_type instead.') -parser.add_argument('--gptq-pre-layer', type=int, default=0, help='DEPRECATED: use --pre_layer instead.') # FlexGen parser.add_argument('--flexgen', action='store_true', help='Enable the use of FlexGen offloading.') @@ -144,7 +142,7 @@ parser.add_argument("--gradio-auth-path", type=str, help='Set the gradio authent args = parser.parse_args() # Deprecation warnings for parameters that have been renamed -deprecated_dict = {'gptq_bits': ['wbits', 0], 'gptq_model_type': ['model_type', None], 'gptq_pre_layer': ['prelayer', 0]} +deprecated_dict = {} for k in deprecated_dict: if eval(f"args.{k}") != deprecated_dict[k][1]: print(f"Warning: --{k} is deprecated and will be removed. Use --{deprecated_dict[k][0]} instead.") diff --git a/server.py b/server.py index f89cbae0..e0f2c2cb 100644 --- a/server.py +++ b/server.py @@ -5,6 +5,7 @@ os.environ['GRADIO_ANALYTICS_ENABLED'] = 'False' import importlib import io import json +import math import os import re import sys @@ -15,6 +16,8 @@ from datetime import datetime from pathlib import Path import gradio as gr +import psutil +import torch from PIL import Image import modules.extensions as extensions_module @@ -82,14 +85,16 @@ def get_available_loras(): def load_model_wrapper(selected_model): - if selected_model != shared.model_name: + try: + yield f"Loading {selected_model}..." shared.model_name = selected_model - unload_model() if selected_model != '': shared.model, shared.tokenizer = load_model(shared.model_name) - return selected_model + yield f"Successfully loaded {selected_model}" + except: + yield traceback.format_exc() def load_lora_wrapper(selected_lora): @@ -203,31 +208,117 @@ def download_model_wrapper(repo_id): yield traceback.format_exc() -def create_model_menus(): - with gr.Row(): - with gr.Column(): - with gr.Row(): - shared.gradio['model_menu'] = gr.Dropdown(choices=available_models, value=shared.model_name, label='Model') - ui.create_refresh_button(shared.gradio['model_menu'], lambda: None, lambda: {'choices': get_available_models()}, 'refresh-button') - with gr.Column(): - with gr.Row(): - shared.gradio['lora_menu'] = gr.Dropdown(choices=available_loras, value=shared.lora_name, label='LoRA') - ui.create_refresh_button(shared.gradio['lora_menu'], lambda: None, lambda: {'choices': get_available_loras()}, 'refresh-button') - with gr.Row(): - with gr.Column(): - with gr.Row(): - with gr.Column(): - shared.gradio['custom_model_menu'] = gr.Textbox(label="Download custom model or LoRA", - info="Enter Hugging Face username/model path, e.g: facebook/galactica-125m") - with gr.Column(): - shared.gradio['download_button'] = gr.Button("Download") - shared.gradio['download_status'] = gr.Markdown() - with gr.Column(): - pass +def list_model_parameters(): + return ['gpu_memory', 'cpu_memory', 'auto_devices', 'disk', 'cpu', 'bf16', 'load_in_8bit', 'wbits', 'groupsize', 'model_type', 'pre_layer'] + + +# Update the command-line arguments based on the interface values +def update_model_parameters(*args): + args = list(args) + elements = list_model_parameters() + + for i, element in enumerate(elements): + if element in ['gpu_memory', 'cpu_memory'] and args[i] == 0: + args[i] = None + if element == 'wbits' and args[i] == 'None': + args[i] = 0 + if element == 'groupsize' and args[i] == 'None': + args[i] = -1 + if element == 'model_type' and args[i] == 'None': + args[i] = None + if element in ['wbits', 'groupsize', 'pre_layer']: + args[i] = int(args[i]) + if element == 'gpu_memory' and args[i] is not None: + args[i] = [f"{args[i]}MiB"] + elif element == 'cpu_memory' and args[i] is not None: + args[i] = f"{args[i]}MiB" + + #print(element, repr(eval(f"shared.args.{element}")), repr(args[i])) + #print(f"shared.args.{element} = args[i]") + exec(f"shared.args.{element} = args[i]") + #print() + +def create_model_menus(): + + # Finding the default values for the GPU and CPU memories + total_mem = math.floor(torch.cuda.get_device_properties(0).total_memory / (1024*1024)) + total_cpu_mem = math.floor(psutil.virtual_memory().total / (1024*1024)) + if shared.args.gpu_memory is not None and len(shared.args.gpu_memory) > 0: + default_gpu_mem = re.sub('[a-zA-Z ]', '', shared.args.gpu_memory[0]) + else: + default_gpu_mem = 0 + if shared.args.cpu_memory is not None: + default_cpu_mem = re.sub('[a-zA-Z ]', '', shared.args.cpu_memory) + else: + default_cpu_mem = 0 + + components = {} + with gr.Row(): + with gr.Column(): + with gr.Row(): + with gr.Column(): + with gr.Row(): + shared.gradio['model_menu'] = gr.Dropdown(choices=available_models, value=shared.model_name, label='Model') + ui.create_refresh_button(shared.gradio['model_menu'], lambda: None, lambda: {'choices': get_available_models()}, 'refresh-button') + + with gr.Column(): + with gr.Row(): + shared.gradio['lora_menu'] = gr.Dropdown(choices=available_loras, value=shared.lora_name, label='LoRA') + ui.create_refresh_button(shared.gradio['lora_menu'], lambda: None, lambda: {'choices': get_available_loras()}, 'refresh-button') + + with gr.Column(): + unload = gr.Button("Unload the model") + reload = gr.Button("Reload the model") + + with gr.Row(): + with gr.Column(): + with gr.Box(): + with gr.Row(): + with gr.Column(): + components['gpu_memory'] = gr.Slider(label="gpu-memory in MiB", maximum=total_mem, value=default_gpu_mem) + components['cpu_memory'] = gr.Slider(label="cpu-memory in MiB", maximum=total_cpu_mem, value=default_cpu_mem) + + with gr.Column(): + components['auto_devices'] = gr.Checkbox(label="auto-devices", value=shared.args.auto_devices) + components['disk'] = gr.Checkbox(label="disk", value=shared.args.disk) + components['cpu'] = gr.Checkbox(label="cpu", value=shared.args.cpu) + components['bf16'] = gr.Checkbox(label="bf16", value=shared.args.bf16) + components['load_in_8bit'] = gr.Checkbox(label="load-in-8bit", value=shared.args.load_in_8bit) + + with gr.Column(): + with gr.Box(): + with gr.Row(): + with gr.Column(): + components['wbits'] = gr.Dropdown(label="wbits", choices=["None", 1, 2, 3, 4, 8], value=shared.args.wbits if shared.args.wbits > 0 else "None") + components['groupsize'] = gr.Dropdown(label="groupsize", choices=["None", 32, 64, 128], value=shared.args.groupsize if shared.args.groupsize > 0 else "None") + + with gr.Column(): + components['model_type'] = gr.Dropdown(label="model_type", choices=["None", "llama", "opt", "gpt-j"], value=shared.args.model_type or "None") + components['pre_layer'] = gr.Slider(label="pre_layer", minimum=0, maximum=100, value=shared.args.pre_layer) + + with gr.Row(): + with gr.Column(): + shared.gradio['custom_model_menu'] = gr.Textbox(label="Download custom model or LoRA", info="Enter Hugging Face username/model path, e.g: facebook/galactica-125m") + shared.gradio['download_button'] = gr.Button("Download") + + with gr.Column(): + shared.gradio['model_status'] = gr.Markdown('No model is loaded' if shared.model_name == 'None' else 'Ready') + + shared.gradio['model_menu'].change( + update_model_parameters, [components[k] for k in list_model_parameters()], None).then( + load_model_wrapper, shared.gradio['model_menu'], shared.gradio['model_status'], show_progress=True) + + unload.click( + unload_model, None, None).then( + lambda: "Model unloaded", None, shared.gradio['model_status']) + + reload.click( + unload_model, None, None).then( + update_model_parameters, [components[k] for k in list_model_parameters()], None).then( + load_model_wrapper, shared.gradio['model_menu'], shared.gradio['model_status'], show_progress=True) - shared.gradio['model_menu'].change(load_model_wrapper, shared.gradio['model_menu'], shared.gradio['model_menu'], show_progress=True) shared.gradio['lora_menu'].change(load_lora_wrapper, shared.gradio['lora_menu'], shared.gradio['lora_menu'], show_progress=True) - shared.gradio['download_button'].click(download_model_wrapper, shared.gradio['custom_model_menu'], shared.gradio['download_status'], show_progress=False) + shared.gradio['download_button'].click(download_model_wrapper, shared.gradio['custom_model_menu'], shared.gradio['model_status'], show_progress=False) def create_settings_menus(default_preset): @@ -333,23 +424,9 @@ else: # Default model if shared.args.model is not None: shared.model_name = shared.args.model -else: - if len(available_models) == 0: - print('No models are available! Please download at least one.') - sys.exit(0) - elif len(available_models) == 1: - i = 0 - else: - print('The following models are available:\n') - for i, model in enumerate(available_models): - print(f'{i+1}. {model}') - print(f'\nWhich one do you want to load? 1-{len(available_models)}\n') - i = int(input()) - 1 - print() - shared.model_name = available_models[i] -shared.model, shared.tokenizer = load_model(shared.model_name) -if shared.args.lora: - add_lora_to_model(shared.args.lora) + shared.model, shared.tokenizer = load_model(shared.model_name) + if shared.args.lora: + add_lora_to_model(shared.args.lora) # Default UI settings default_preset = shared.settings['presets'][next((k for k in shared.settings['presets'] if re.match(k.lower(), shared.model_name.lower())), 'default')] @@ -372,12 +449,12 @@ def create_interface(): 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"): + with gr.Tab('Text generation', elem_id='main'): shared.gradio['display'] = gr.HTML(value=chat_html_wrapper(shared.history['visible'], shared.settings['name1'], shared.settings['name2'], 'cai-chat')) shared.gradio['textbox'] = gr.Textbox(label='Input') with gr.Row(): shared.gradio['Generate'] = gr.Button('Generate', elem_id='Generate') - shared.gradio['Stop'] = gr.Button('Stop', elem_id="stop") + shared.gradio['Stop'] = gr.Button('Stop', elem_id='stop') with gr.Row(): shared.gradio['Regenerate'] = gr.Button('Regenerate') shared.gradio['Continue'] = gr.Button('Continue') @@ -389,24 +466,24 @@ def create_interface(): shared.gradio['Copy last reply'] = gr.Button('Copy last reply') with gr.Row(): shared.gradio['Clear history'] = gr.Button('Clear history') - shared.gradio['Clear history-confirm'] = gr.Button('Confirm', variant="stop", visible=False) + shared.gradio['Clear history-confirm'] = gr.Button('Confirm', variant='stop', visible=False) shared.gradio['Clear history-cancel'] = gr.Button('Cancel', visible=False) shared.gradio['Remove last'] = gr.Button('Remove last') - shared.gradio["mode"] = gr.Radio(choices=["cai-chat", "chat", "instruct"], value="cai-chat", label="Mode") - shared.gradio["Instruction templates"] = gr.Dropdown(choices=get_available_instruction_templates(), label="Instruction template", value="None", visible=False, info="Change this according to the model/LoRA that you are using.") + shared.gradio['mode'] = gr.Radio(choices=['cai-chat', 'chat', 'instruct'], value=shared.settings['mode'], label='Mode') + shared.gradio['Instruction templates'] = gr.Dropdown(choices=get_available_instruction_templates(), label='Instruction template', value='None', visible=False, info='Change this according to the model/LoRA that you are using.') - with gr.Tab("Character", elem_id="chat-settings"): + with gr.Tab('Character', elem_id='chat-settings'): with gr.Row(): with gr.Column(scale=8): shared.gradio['name1'] = gr.Textbox(value=shared.settings['name1'], lines=1, label='Your name') shared.gradio['name2'] = gr.Textbox(value=shared.settings['name2'], lines=1, label='Character\'s name') shared.gradio['greeting'] = gr.Textbox(value=shared.settings['greeting'], lines=4, label='Greeting') shared.gradio['context'] = gr.Textbox(value=shared.settings['context'], lines=4, label='Context') - shared.gradio['end_of_turn'] = gr.Textbox(value=shared.settings["end_of_turn"], lines=1, label='End of turn string') + shared.gradio['end_of_turn'] = gr.Textbox(value=shared.settings['end_of_turn'], lines=1, label='End of turn string') with gr.Column(scale=1): - shared.gradio['character_picture'] = gr.Image(label='Character picture', type="pil") - shared.gradio['your_picture'] = gr.Image(label='Your picture', type="pil", value=Image.open(Path("cache/pfp_me.png")) if Path("cache/pfp_me.png").exists() else None) + shared.gradio['character_picture'] = gr.Image(label='Character picture', type='pil') + shared.gradio['your_picture'] = gr.Image(label='Your picture', type='pil', value=Image.open(Path('cache/pfp_me.png')) if Path('cache/pfp_me.png').exists() else None) with gr.Row(): shared.gradio['character_menu'] = gr.Dropdown(choices=available_characters, value='None', label='Character', elem_id='character-menu') ui.create_refresh_button(shared.gradio['character_menu'], lambda: None, lambda: {'choices': get_available_characters()}, 'refresh-button') @@ -422,7 +499,7 @@ def create_interface(): shared.gradio['download'] = gr.File() shared.gradio['download_button'] = gr.Button(value='Click me') with gr.Tab('Upload character'): - gr.Markdown("# JSON format") + gr.Markdown('# JSON format') with gr.Row(): with gr.Column(): gr.Markdown('1. Select the JSON file') @@ -432,7 +509,7 @@ def create_interface(): 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") + gr.Markdown('# TavernAI PNG format') shared.gradio['upload_img_tavern'] = gr.File(type='binary', file_types=['image']) with gr.Tab("Parameters", elem_id="parameters"): @@ -648,7 +725,7 @@ def create_interface(): current_mode = mode break cmd_list = vars(shared.args) - bool_list = [k for k in cmd_list if type(cmd_list[k]) is bool and k not in modes] + bool_list = [k for k in cmd_list if type(cmd_list[k]) is bool and k not in modes + list_model_parameters()] bool_active = [k for k in bool_list if vars(shared.args)[k]] gr.Markdown("*Experimental*") diff --git a/settings-template.json b/settings-template.json index 896c91f8..7bd393ea 100644 --- a/settings-template.json +++ b/settings-template.json @@ -6,7 +6,7 @@ "name1": "You", "name2": "Assistant", "context": "This is a conversation with your Assistant. The Assistant is very helpful and is eager to chat with you and answer your questions.", - "greeting": "Hello there!", + "greeting": "", "end_of_turn": "", "custom_stopping_strings": "", "stop_at_newline": false, @@ -15,6 +15,7 @@ "truncation_length": 2048, "truncation_length_min": 0, "truncation_length_max": 4096, + "mode": "cai-chat", "chat_prompt_size": 2048, "chat_prompt_size_min": 0, "chat_prompt_size_max": 2048,