mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-10-30 14:10:14 +01:00
271 lines
16 KiB
Python
271 lines
16 KiB
Python
import argparse
|
|
import os
|
|
import sys
|
|
from collections import OrderedDict
|
|
from pathlib import Path
|
|
|
|
import yaml
|
|
|
|
from modules.logging_colors import logger
|
|
|
|
# Model variables
|
|
model = None
|
|
tokenizer = None
|
|
model_name = 'None'
|
|
is_seq2seq = False
|
|
model_dirty_from_training = False
|
|
lora_names = []
|
|
|
|
# Generation variables
|
|
stop_everything = False
|
|
generation_lock = None
|
|
processing_message = '*Is typing...*'
|
|
|
|
# UI variables
|
|
gradio = {}
|
|
persistent_interface_state = {}
|
|
need_restart = False
|
|
|
|
# UI defaults
|
|
settings = {
|
|
'dark_theme': True,
|
|
'show_controls': True,
|
|
'start_with': '',
|
|
'mode': 'chat',
|
|
'chat_style': 'cai-chat',
|
|
'prompt-default': 'QA',
|
|
'prompt-notebook': 'QA',
|
|
'preset': 'simple-1',
|
|
'max_new_tokens': 200,
|
|
'max_new_tokens_min': 1,
|
|
'max_new_tokens_max': 4096,
|
|
'seed': -1,
|
|
'negative_prompt': '',
|
|
'truncation_length': 2048,
|
|
'truncation_length_min': 0,
|
|
'truncation_length_max': 32768,
|
|
'custom_stopping_strings': '',
|
|
'auto_max_new_tokens': False,
|
|
'max_tokens_second': 0,
|
|
'ban_eos_token': False,
|
|
'custom_token_bans': '',
|
|
'add_bos_token': True,
|
|
'skip_special_tokens': True,
|
|
'stream': True,
|
|
'name1': 'You',
|
|
'character': 'Assistant',
|
|
'instruction_template': 'Alpaca',
|
|
'chat-instruct_command': 'Continue the chat dialogue below. Write a single reply for the character "<|character|>".\n\n<|prompt|>',
|
|
'autoload_model': False,
|
|
'default_extensions': ['gallery'],
|
|
}
|
|
|
|
parser = argparse.ArgumentParser(formatter_class=lambda prog: argparse.HelpFormatter(prog, max_help_position=54))
|
|
|
|
# Basic settings
|
|
parser.add_argument('--multi-user', action='store_true', help='Multi-user mode. Chat histories are not saved or automatically loaded. Warning: this is likely not safe for sharing publicly.')
|
|
parser.add_argument('--character', type=str, help='The name of the character to load in chat mode by default.')
|
|
parser.add_argument('--model', type=str, help='Name of the model to load by default.')
|
|
parser.add_argument('--lora', type=str, nargs='+', help='The list of LoRAs to load. If you want to load more than one LoRA, write the names separated by spaces.')
|
|
parser.add_argument('--model-dir', type=str, default='models/', help='Path to directory with all the models.')
|
|
parser.add_argument('--lora-dir', type=str, default='loras/', help='Path to directory with all the loras.')
|
|
parser.add_argument('--model-menu', action='store_true', help='Show a model menu in the terminal when the web UI is first launched.')
|
|
parser.add_argument('--settings', type=str, help='Load the default interface settings from this yaml file. See settings-template.yaml for an example. If you create a file called settings.yaml, this file will be loaded by default without the need to use the --settings flag.')
|
|
parser.add_argument('--extensions', type=str, nargs='+', help='The list of extensions to load. If you want to load more than one extension, write the names separated by spaces.')
|
|
parser.add_argument('--verbose', action='store_true', help='Print the prompts to the terminal.')
|
|
parser.add_argument('--chat-buttons', action='store_true', help='Show buttons on the chat tab instead of a hover menu.')
|
|
|
|
# Model loader
|
|
parser.add_argument('--loader', type=str, help='Choose the model loader manually, otherwise, it will get autodetected. Valid options: transformers, exllama_hf, exllamav2_hf, exllama, exllamav2, autogptq, gptq-for-llama, llama.cpp, llamacpp_hf, ctransformers, autoawq.')
|
|
|
|
# Accelerate/transformers
|
|
parser.add_argument('--cpu', action='store_true', help='Use the CPU to generate text. Warning: Training on CPU is extremely slow.')
|
|
parser.add_argument('--auto-devices', action='store_true', help='Automatically split the model across the available GPU(s) and CPU.')
|
|
parser.add_argument('--gpu-memory', type=str, nargs='+', help='Maximum GPU memory in GiB to be allocated per GPU. Example: --gpu-memory 10 for a single GPU, --gpu-memory 10 5 for two GPUs. You can also set values in MiB like --gpu-memory 3500MiB.')
|
|
parser.add_argument('--cpu-memory', type=str, help='Maximum CPU memory in GiB to allocate for offloaded weights. Same as above.')
|
|
parser.add_argument('--disk', action='store_true', help='If the model is too large for your GPU(s) and CPU combined, send the remaining layers to the disk.')
|
|
parser.add_argument('--disk-cache-dir', type=str, default='cache', help='Directory to save the disk cache to. Defaults to "cache".')
|
|
parser.add_argument('--load-in-8bit', action='store_true', help='Load the model with 8-bit precision (using bitsandbytes).')
|
|
parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.')
|
|
parser.add_argument('--no-cache', action='store_true', help='Set use_cache to False while generating text. This reduces VRAM usage slightly, but it comes at a performance cost.')
|
|
parser.add_argument('--xformers', action='store_true', help='Use xformer\'s memory efficient attention. This is really old and probably doesn\'t do anything.')
|
|
parser.add_argument('--sdp-attention', action='store_true', help='Use PyTorch 2.0\'s SDP attention. Same as above.')
|
|
parser.add_argument('--trust-remote-code', action='store_true', help='Set trust_remote_code=True while loading the model. Necessary for some models.')
|
|
parser.add_argument('--use_fast', action='store_true', help='Set use_fast=True while loading the tokenizer.')
|
|
|
|
# Accelerate 4-bit
|
|
parser.add_argument('--load-in-4bit', action='store_true', help='Load the model with 4-bit precision (using bitsandbytes).')
|
|
parser.add_argument('--use_double_quant', action='store_true', help='use_double_quant for 4-bit.')
|
|
parser.add_argument('--compute_dtype', type=str, default='float16', help='compute dtype for 4-bit. Valid options: bfloat16, float16, float32.')
|
|
parser.add_argument('--quant_type', type=str, default='nf4', help='quant_type for 4-bit. Valid options: nf4, fp4.')
|
|
|
|
# llama.cpp
|
|
parser.add_argument('--n_ctx', type=int, default=2048, help='Size of the prompt context.')
|
|
parser.add_argument('--threads', type=int, default=0, help='Number of threads to use.')
|
|
parser.add_argument('--threads-batch', type=int, default=0, help='Number of threads to use for batches/prompt processing.')
|
|
parser.add_argument('--no_mul_mat_q', action='store_true', help='Disable the mulmat kernels.')
|
|
parser.add_argument('--n_batch', type=int, default=512, help='Maximum number of prompt tokens to batch together when calling llama_eval.')
|
|
parser.add_argument('--no-mmap', action='store_true', help='Prevent mmap from being used.')
|
|
parser.add_argument('--mlock', action='store_true', help='Force the system to keep the model in RAM.')
|
|
parser.add_argument('--n-gpu-layers', type=int, default=0, help='Number of layers to offload to the GPU.')
|
|
parser.add_argument('--tensor_split', type=str, default=None, help='Split the model across multiple GPUs. Comma-separated list of proportions. Example: 18,17.')
|
|
parser.add_argument('--llama_cpp_seed', type=int, default=0, help='Seed for llama-cpp models. Default is 0 (random).')
|
|
parser.add_argument('--numa', action='store_true', help='Activate NUMA task allocation for llama.cpp.')
|
|
parser.add_argument('--cache-capacity', type=str, help='Maximum cache capacity (llama-cpp-python). Examples: 2000MiB, 2GiB. When provided without units, bytes will be assumed.')
|
|
|
|
# ExLlama
|
|
parser.add_argument('--gpu-split', type=str, help='Comma-separated list of VRAM (in GB) to use per GPU device for model layers. Example: 20,7,7.')
|
|
parser.add_argument('--max_seq_len', type=int, default=2048, help='Maximum sequence length.')
|
|
parser.add_argument('--cfg-cache', action='store_true', help='ExLlama_HF: Create an additional cache for CFG negative prompts. Necessary to use CFG with that loader, but not necessary for CFG with base ExLlama.')
|
|
parser.add_argument('--no_flash_attn', action='store_true', help='Force flash-attention to not be used.')
|
|
parser.add_argument('--cache_8bit', action='store_true', help='Use 8-bit cache to save VRAM.')
|
|
|
|
# AutoGPTQ
|
|
parser.add_argument('--triton', action='store_true', help='Use triton.')
|
|
parser.add_argument('--no_inject_fused_attention', action='store_true', help='Disable the use of fused attention, which will use less VRAM at the cost of slower inference.')
|
|
parser.add_argument('--no_inject_fused_mlp', action='store_true', help='Triton mode only: disable the use of fused MLP, which will use less VRAM at the cost of slower inference.')
|
|
parser.add_argument('--no_use_cuda_fp16', action='store_true', help='This can make models faster on some systems.')
|
|
parser.add_argument('--desc_act', action='store_true', help='For models that do not have a quantize_config.json, this parameter is used to define whether to set desc_act or not in BaseQuantizeConfig.')
|
|
parser.add_argument('--disable_exllama', action='store_true', help='Disable ExLlama kernel, which can improve inference speed on some systems.')
|
|
|
|
# GPTQ-for-LLaMa
|
|
parser.add_argument('--wbits', type=int, default=0, help='Load a pre-quantized model with specified precision in bits. 2, 3, 4 and 8 are supported.')
|
|
parser.add_argument('--model_type', type=str, help='Model type of pre-quantized model. Currently LLaMA, OPT, and GPT-J are supported.')
|
|
parser.add_argument('--groupsize', type=int, default=-1, help='Group size.')
|
|
parser.add_argument('--pre_layer', type=int, nargs='+', help='The number of layers to allocate to the GPU. Setting this parameter enables CPU offloading for 4-bit models. For multi-gpu, write the numbers separated by spaces, eg --pre_layer 30 60.')
|
|
parser.add_argument('--checkpoint', type=str, help='The path to the quantized checkpoint file. If not specified, it will be automatically detected.')
|
|
parser.add_argument('--monkey-patch', action='store_true', help='Apply the monkey patch for using LoRAs with quantized models.')
|
|
|
|
# DeepSpeed
|
|
parser.add_argument('--deepspeed', action='store_true', help='Enable the use of DeepSpeed ZeRO-3 for inference via the Transformers integration.')
|
|
parser.add_argument('--nvme-offload-dir', type=str, help='DeepSpeed: Directory to use for ZeRO-3 NVME offloading.')
|
|
parser.add_argument('--local_rank', type=int, default=0, help='DeepSpeed: Optional argument for distributed setups.')
|
|
|
|
# RWKV
|
|
parser.add_argument('--rwkv-strategy', type=str, default=None, help='RWKV: The strategy to use while loading the model. Examples: "cpu fp32", "cuda fp16", "cuda fp16i8".')
|
|
parser.add_argument('--rwkv-cuda-on', action='store_true', help='RWKV: Compile the CUDA kernel for better performance.')
|
|
|
|
# RoPE
|
|
parser.add_argument('--alpha_value', type=float, default=1, help='Positional embeddings alpha factor for NTK RoPE scaling. Use either this or compress_pos_emb, not both.')
|
|
parser.add_argument('--rope_freq_base', type=int, default=0, help='If greater than 0, will be used instead of alpha_value. Those two are related by rope_freq_base = 10000 * alpha_value ^ (64 / 63).')
|
|
parser.add_argument('--compress_pos_emb', type=int, default=1, help="Positional embeddings compression factor. Should be set to (context length) / (model\'s original context length). Equal to 1/rope_freq_scale.")
|
|
|
|
# Gradio
|
|
parser.add_argument('--listen', action='store_true', help='Make the web UI reachable from your local network.')
|
|
parser.add_argument('--listen-port', type=int, help='The listening port that the server will use.')
|
|
parser.add_argument('--listen-host', type=str, help='The hostname that the server will use.')
|
|
parser.add_argument('--share', action='store_true', help='Create a public URL. This is useful for running the web UI on Google Colab or similar.')
|
|
parser.add_argument('--auto-launch', action='store_true', default=False, help='Open the web UI in the default browser upon launch.')
|
|
parser.add_argument('--gradio-auth', type=str, help='Set Gradio authentication password in the format "username:password". Multiple credentials can also be supplied with "u1:p1,u2:p2,u3:p3".', default=None)
|
|
parser.add_argument('--gradio-auth-path', type=str, help='Set the Gradio authentication file path. The file should contain one or more user:password pairs in the same format as above.', default=None)
|
|
parser.add_argument('--ssl-keyfile', type=str, help='The path to the SSL certificate key file.', default=None)
|
|
parser.add_argument('--ssl-certfile', type=str, help='The path to the SSL certificate cert file.', default=None)
|
|
|
|
# API
|
|
parser.add_argument('--api', action='store_true', help='Enable the API extension.')
|
|
parser.add_argument('--public-api', action='store_true', help='Create a public URL for the API using Cloudfare.')
|
|
parser.add_argument('--public-api-id', type=str, help='Tunnel ID for named Cloudflare Tunnel. Use together with public-api option.', default=None)
|
|
parser.add_argument('--api-blocking-port', type=int, default=5000, help='The listening port for the blocking API.')
|
|
parser.add_argument('--api-streaming-port', type=int, default=5005, help='The listening port for the streaming API.')
|
|
|
|
# Multimodal
|
|
parser.add_argument('--multimodal-pipeline', type=str, default=None, help='The multimodal pipeline to use. Examples: llava-7b, llava-13b.')
|
|
|
|
# Deprecated parameters
|
|
parser.add_argument('--notebook', action='store_true', help='DEPRECATED')
|
|
parser.add_argument('--chat', action='store_true', help='DEPRECATED')
|
|
parser.add_argument('--no-stream', action='store_true', help='DEPRECATED')
|
|
parser.add_argument('--mul_mat_q', action='store_true', help='DEPRECATED')
|
|
|
|
args = parser.parse_args()
|
|
args_defaults = parser.parse_args([])
|
|
provided_arguments = []
|
|
for arg in sys.argv[1:]:
|
|
arg = arg.lstrip('-').replace('-', '_')
|
|
if hasattr(args, arg):
|
|
provided_arguments.append(arg)
|
|
|
|
# Deprecation warnings
|
|
for k in ['chat', 'notebook', 'no_stream', 'mul_mat_q']:
|
|
if getattr(args, k):
|
|
logger.warning(f'The --{k} flag has been deprecated and will be removed soon. Please remove that flag.')
|
|
|
|
# Security warnings
|
|
if args.trust_remote_code:
|
|
logger.warning('trust_remote_code is enabled. This is dangerous.')
|
|
if 'COLAB_GPU' not in os.environ:
|
|
if args.share:
|
|
logger.warning("The gradio \"share link\" feature uses a proprietary executable to create a reverse tunnel. Use it with care.")
|
|
if any((args.listen, args.share)) and not any((args.gradio_auth, args.gradio_auth_path)):
|
|
logger.warning("\nYou are potentially exposing the web UI to the entire internet without any access password.\nYou can create one with the \"--gradio-auth\" flag like this:\n\n--gradio-auth username:password\n\nMake sure to replace username:password with your own.")
|
|
if args.multi_user:
|
|
logger.warning('\nThe multi-user mode is highly experimental and should not be shared publicly.')
|
|
|
|
|
|
def fix_loader_name(name):
|
|
if not name:
|
|
return name
|
|
|
|
name = name.lower()
|
|
if name in ['llamacpp', 'llama.cpp', 'llama-cpp', 'llama cpp']:
|
|
return 'llama.cpp'
|
|
if name in ['llamacpp_hf', 'llama.cpp_hf', 'llama-cpp-hf', 'llamacpp-hf', 'llama.cpp-hf']:
|
|
return 'llamacpp_HF'
|
|
elif name in ['transformers', 'huggingface', 'hf', 'hugging_face', 'hugging face']:
|
|
return 'Transformers'
|
|
elif name in ['autogptq', 'auto-gptq', 'auto_gptq', 'auto gptq']:
|
|
return 'AutoGPTQ'
|
|
elif name in ['gptq-for-llama', 'gptqforllama', 'gptqllama', 'gptq for llama', 'gptq_for_llama']:
|
|
return 'GPTQ-for-LLaMa'
|
|
elif name in ['exllama', 'ex-llama', 'ex_llama', 'exlama']:
|
|
return 'ExLlama'
|
|
elif name in ['exllama-hf', 'exllama_hf', 'exllama hf', 'ex-llama-hf', 'ex_llama_hf']:
|
|
return 'ExLlama_HF'
|
|
elif name in ['exllamav2', 'exllama-v2', 'ex_llama-v2', 'exlamav2', 'exlama-v2', 'exllama2', 'exllama-2']:
|
|
return 'ExLlamav2'
|
|
elif name in ['exllamav2-hf', 'exllamav2_hf', 'exllama-v2-hf', 'exllama_v2_hf', 'exllama-v2_hf', 'exllama2-hf', 'exllama2_hf', 'exllama-2-hf', 'exllama_2_hf', 'exllama-2_hf']:
|
|
return 'ExLlamav2_HF'
|
|
elif name in ['ctransformers', 'ctranforemrs', 'ctransformer']:
|
|
return 'ctransformers'
|
|
elif name in ['autoawq', 'awq', 'auto-awq']:
|
|
return 'AutoAWQ'
|
|
|
|
|
|
def add_extension(name):
|
|
if args.extensions is None:
|
|
args.extensions = [name]
|
|
elif 'api' not in args.extensions:
|
|
args.extensions.append(name)
|
|
|
|
|
|
def is_chat():
|
|
return True
|
|
|
|
|
|
args.loader = fix_loader_name(args.loader)
|
|
|
|
# Activate the API extension
|
|
if args.api or args.public_api:
|
|
add_extension('api')
|
|
|
|
# Activate the multimodal extension
|
|
if args.multimodal_pipeline is not None:
|
|
add_extension('multimodal')
|
|
|
|
# Load model-specific settings
|
|
with Path(f'{args.model_dir}/config.yaml') as p:
|
|
if p.exists():
|
|
model_config = yaml.safe_load(open(p, 'r').read())
|
|
else:
|
|
model_config = {}
|
|
|
|
# Load custom model-specific settings
|
|
with Path(f'{args.model_dir}/config-user.yaml') as p:
|
|
if p.exists():
|
|
user_config = yaml.safe_load(open(p, 'r').read())
|
|
else:
|
|
user_config = {}
|
|
|
|
model_config = OrderedDict(model_config)
|
|
user_config = OrderedDict(user_config)
|