mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-12-26 14:20:40 +01:00
218 lines
11 KiB
Python
218 lines
11 KiB
Python
import argparse
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import logging
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from pathlib import Path
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import yaml
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model = None
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tokenizer = None
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model_name = "None"
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model_type = None
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lora_names = []
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soft_prompt_tensor = None
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soft_prompt = False
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# Chat variables
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history = {'internal': [], 'visible': []}
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character = 'None'
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stop_everything = False
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processing_message = '*Is typing...*'
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# UI elements (buttons, sliders, HTML, etc)
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gradio = {}
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# For keeping the values of UI elements on page reload
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persistent_interface_state = {}
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# Generation input parameters
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input_params = []
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# For restarting the interface
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need_restart = False
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settings = {
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'max_new_tokens': 200,
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'max_new_tokens_min': 1,
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'max_new_tokens_max': 2000,
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'seed': -1,
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'character': 'None',
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'name1': 'You',
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'name2': 'Assistant',
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'context': 'This is a conversation with your Assistant. The Assistant is very helpful and is eager to chat with you and answer your questions.',
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'greeting': '',
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'turn_template': '',
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'custom_stopping_strings': '',
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'stop_at_newline': False,
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'add_bos_token': True,
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'ban_eos_token': False,
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'skip_special_tokens': True,
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'truncation_length': 2048,
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'truncation_length_min': 0,
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'truncation_length_max': 8192,
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'mode': 'cai-chat',
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'instruction_template': 'None',
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'chat_prompt_size': 2048,
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'chat_prompt_size_min': 0,
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'chat_prompt_size_max': 2048,
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'chat_generation_attempts': 1,
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'chat_generation_attempts_min': 1,
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'chat_generation_attempts_max': 5,
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'default_extensions': [],
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'chat_default_extensions': ["gallery"],
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'presets': {
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'default': 'Default',
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'.*(alpaca|llama|llava)': "LLaMA-Precise",
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'.*pygmalion': 'NovelAI-Storywriter',
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'.*RWKV': 'Naive',
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'.*moss': 'MOSS',
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},
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'prompts': {
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'default': 'QA',
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'.*(gpt4chan|gpt-4chan|4chan)': 'GPT-4chan',
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'.*oasst': 'Open Assistant',
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'.*alpaca': "Alpaca",
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},
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'lora_prompts': {
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'default': 'QA',
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'.*alpaca': "Alpaca",
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}
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}
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def str2bool(v):
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if isinstance(v, bool):
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return v
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if v.lower() in ('yes', 'true', 't', 'y', '1'):
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return True
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elif v.lower() in ('no', 'false', 'f', 'n', '0'):
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return False
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else:
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raise argparse.ArgumentTypeError('Boolean value expected.')
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parser = argparse.ArgumentParser(formatter_class=lambda prog: argparse.HelpFormatter(prog, max_help_position=54))
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# Basic settings
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parser.add_argument('--notebook', action='store_true', help='Launch the web UI in notebook mode, where the output is written to the same text box as the input.')
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parser.add_argument('--chat', action='store_true', help='Launch the web UI in chat mode with a style similar to the Character.AI website.')
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parser.add_argument('--cai-chat', action='store_true', help='DEPRECATED: use --chat instead.')
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parser.add_argument('--character', type=str, help='The name of the character to load in chat mode by default.')
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parser.add_argument('--model', type=str, help='Name of the model to load by default.')
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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.')
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parser.add_argument("--model-dir", type=str, default='models/', help="Path to directory with all the models")
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parser.add_argument("--lora-dir", type=str, default='loras/', help="Path to directory with all the loras")
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parser.add_argument('--model-menu', action='store_true', help='Show a model menu in the terminal when the web UI is first launched.')
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parser.add_argument('--no-stream', action='store_true', help='Don\'t stream the text output in real time.')
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parser.add_argument('--settings', type=str, help='Load the default interface settings from this json file. See settings-template.json for an example. If you create a file called settings.json, this file will be loaded by default without the need to use the --settings flag.')
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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.')
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parser.add_argument('--verbose', action='store_true', help='Print the prompts to the terminal.')
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# Accelerate/transformers
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parser.add_argument('--cpu', action='store_true', help='Use the CPU to generate text. Warning: Training on CPU is extremely slow.')
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parser.add_argument('--auto-devices', action='store_true', help='Automatically split the model across the available GPU(s) and CPU.')
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parser.add_argument('--gpu-memory', type=str, nargs="+", help='Maxmimum 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.')
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parser.add_argument('--cpu-memory', type=str, help='Maximum CPU memory in GiB to allocate for offloaded weights. Same as above.')
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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.')
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parser.add_argument('--disk-cache-dir', type=str, default="cache", help='Directory to save the disk cache to. Defaults to "cache".')
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parser.add_argument('--load-in-8bit', action='store_true', help='Load the model with 8-bit precision.')
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parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.')
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parser.add_argument('--no-cache', action='store_true', help='Set use_cache to False while generating text. This reduces the VRAM usage a bit at a performance cost.')
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parser.add_argument('--xformers', action='store_true', help="Use xformer's memory efficient attention. This should increase your tokens/s.")
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parser.add_argument('--sdp-attention', action='store_true', help="Use torch 2.0's sdp attention.")
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parser.add_argument('--trust-remote-code', action='store_true', help="Set trust_remote_code=True while loading a model. Necessary for ChatGLM.")
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# llama.cpp
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parser.add_argument('--threads', type=int, default=0, help='Number of threads to use.')
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parser.add_argument('--n_batch', type=int, default=512, help='Maximum number of prompt tokens to batch together when calling llama_eval.')
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parser.add_argument('--no-mmap', action='store_true', help='Prevent mmap from being used.')
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parser.add_argument('--mlock', action='store_true', help='Force the system to keep the model in RAM.')
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# GPTQ
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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.')
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parser.add_argument('--model_type', type=str, help='Model type of pre-quantized model. Currently LLaMA, OPT, and GPT-J are supported.')
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parser.add_argument('--groupsize', type=int, default=-1, help='Group size.')
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parser.add_argument('--pre_layer', type=int, default=0, help='The number of layers to allocate to the GPU. Setting this parameter enables CPU offloading for 4-bit models.')
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parser.add_argument('--checkpoint', type=str, help='The path to the quantized checkpoint file. If not specified, it will be automatically detected.')
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parser.add_argument('--monkey-patch', action='store_true', help='Apply the monkey patch for using LoRAs with quantized models.')
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parser.add_argument('--quant_attn', action='store_true', help='(triton) Enable quant attention.')
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parser.add_argument('--warmup_autotune', action='store_true', help='(triton) Enable warmup autotune.')
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parser.add_argument('--fused_mlp', action='store_true', help='(triton) Enable fused mlp.')
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# FlexGen
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parser.add_argument('--flexgen', action='store_true', help='Enable the use of FlexGen offloading.')
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parser.add_argument('--percent', type=int, nargs="+", default=[0, 100, 100, 0, 100, 0], help='FlexGen: allocation percentages. Must be 6 numbers separated by spaces (default: 0, 100, 100, 0, 100, 0).')
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parser.add_argument("--compress-weight", action="store_true", help="FlexGen: activate weight compression.")
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parser.add_argument("--pin-weight", type=str2bool, nargs="?", const=True, default=True, help="FlexGen: whether to pin weights (setting this to False reduces CPU memory by 20%%).")
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# DeepSpeed
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parser.add_argument('--deepspeed', action='store_true', help='Enable the use of DeepSpeed ZeRO-3 for inference via the Transformers integration.')
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parser.add_argument('--nvme-offload-dir', type=str, help='DeepSpeed: Directory to use for ZeRO-3 NVME offloading.')
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parser.add_argument('--local_rank', type=int, default=0, help='DeepSpeed: Optional argument for distributed setups.')
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# RWKV
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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".')
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parser.add_argument('--rwkv-cuda-on', action='store_true', help='RWKV: Compile the CUDA kernel for better performance.')
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# Gradio
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parser.add_argument('--listen', action='store_true', help='Make the web UI reachable from your local network.')
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parser.add_argument('--listen-host', type=str, help='The hostname that the server will use.')
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parser.add_argument('--listen-port', type=int, help='The listening port that the server will use.')
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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.')
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parser.add_argument('--auto-launch', action='store_true', default=False, help='Open the web UI in the default browser upon launch.')
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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 this format: "u1:p1,u2:p2,u3:p3"', default=None)
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# API
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parser.add_argument('--api', action='store_true', help='Enable the API extension.')
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parser.add_argument('--public-api', action='store_true', help='Create a public URL for the API using Cloudfare.')
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args = parser.parse_args()
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args_defaults = parser.parse_args([])
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# Deprecation warnings for parameters that have been renamed
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deprecated_dict = {}
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for k in deprecated_dict:
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if getattr(args, k) != deprecated_dict[k][1]:
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logging.warning(f"--{k} is deprecated and will be removed. Use --{deprecated_dict[k][0]} instead.")
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setattr(args, deprecated_dict[k][0], getattr(args, k))
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# Deprecation warnings for parameters that have been removed
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if args.cai_chat:
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logging.warning("--cai-chat is deprecated. Use --chat instead.")
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args.chat = True
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# Security warnings
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if args.trust_remote_code:
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logging.warning("trust_remote_code is enabled. This is dangerous.")
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if args.share:
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logging.warning("The gradio \"share link\" feature downloads a proprietary and unaudited blob to create a reverse tunnel. This is potentially dangerous.")
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# Activating the API extension
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if args.api or args.public_api:
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if args.extensions is None:
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args.extensions = ['api']
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elif 'api' not in args.extensions:
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args.extensions.append('api')
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def is_chat():
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return args.chat
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# Loading model-specific settings (default)
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with Path(f'{args.model_dir}/config.yaml') as p:
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if p.exists():
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model_config = yaml.safe_load(open(p, 'r').read())
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else:
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model_config = {}
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# Applying user-defined model settings
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with Path(f'{args.model_dir}/config-user.yaml') as p:
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if p.exists():
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user_config = yaml.safe_load(open(p, 'r').read())
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for k in user_config:
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if k in model_config:
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model_config[k].update(user_config[k])
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else:
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model_config[k] = user_config[k]
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