import argparse model = None tokenizer = None model_name = "None" lora_name = "None" soft_prompt_tensor = None soft_prompt = False is_RWKV = False # Chat variables history = {'internal': [], 'visible': []} character = 'None' stop_everything = False processing_message = '*Is typing...*' # UI elements (buttons, sliders, HTML, etc) gradio = {} # Generation input parameters input_params = [] # For restarting the interface need_restart = False settings = { 'max_new_tokens': 200, 'max_new_tokens_min': 1, 'max_new_tokens_max': 2000, '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.', 'stop_at_newline': False, 'chat_prompt_size': 2048, 'chat_prompt_size_min': 0, 'chat_prompt_size_max': 2048, 'chat_generation_attempts': 1, 'chat_generation_attempts_min': 1, 'chat_generation_attempts_max': 5, 'name1_pygmalion': 'You', 'name2_pygmalion': 'Kawaii', 'context_pygmalion': "Kawaii's persona: Kawaii is a cheerful person who loves to make others smile. She is an optimist who loves to spread happiness and positivity wherever she goes.\n", 'stop_at_newline_pygmalion': False, 'default_extensions': [], 'chat_default_extensions': ["gallery"], 'presets': { 'default': 'NovelAI-Sphinx Moth', 'pygmalion-*': 'Pygmalion', 'RWKV-*': 'Naive', }, 'prompts': { 'default': 'Common sense questions and answers\n\nQuestion: \nFactual answer:', '^(gpt4chan|gpt-4chan|4chan)': '-----\n--- 865467536\nInput text\n--- 865467537\n', '(rosey|chip|joi)_.*_instruct.*': 'User: \n', 'oasst-*': '<|prompter|>Write a story about future of AI development<|endoftext|><|assistant|>', 'alpaca-*': "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n### Instruction:\nWrite a poem about the transformers Python library. \nMention the word \"large language models\" in that poem.\n### Response:\n", }, 'lora_prompts': { 'default': 'Common sense questions and answers\n\nQuestion: \nFactual answer:', '(alpaca-lora-7b|alpaca-lora-13b|alpaca-lora-30b)': "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n### Instruction:\nWrite a poem about the transformers Python library. \nMention the word \"large language models\" in that poem.\n### Response:\n" } } def str2bool(v): if isinstance(v, bool): return v if v.lower() in ('yes', 'true', 't', 'y', '1'): return True elif v.lower() in ('no', 'false', 'f', 'n', '0'): return False else: raise argparse.ArgumentTypeError('Boolean value expected.') parser = argparse.ArgumentParser(formatter_class=lambda prog: argparse.HelpFormatter(prog,max_help_position=54)) parser.add_argument('--model', type=str, help='Name of the model to load by default.') parser.add_argument('--lora', type=str, help='Name of the LoRA to apply to the model by default.') 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.') parser.add_argument('--chat', action='store_true', help='Launch the web UI in chat mode.') parser.add_argument('--cai-chat', action='store_true', help='Launch the web UI in chat mode with a style similar to Character.AI\'s. If the file img_bot.png or img_bot.jpg exists in the same folder as server.py, this image will be used as the bot\'s profile picture. Similarly, img_me.png or img_me.jpg will be used as your profile picture.') parser.add_argument('--cpu', action='store_true', help='Use the CPU to generate text.') parser.add_argument('--load-in-8bit', action='store_true', help='Load the model with 8-bit precision.') 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.') parser.add_argument('--wbits', type=int, default=0, help='GPTQ: 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='GPTQ: Model type of pre-quantized model. Currently only LLaMA and OPT 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 preload.') parser.add_argument('--bf16', action='store_true', help='Load the model with bfloat16 precision. Requires NVIDIA Ampere GPU.') parser.add_argument('--auto-devices', action='store_true', help='Automatically split the model across the available GPU(s) and CPU.') 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('--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.') parser.add_argument('--cpu-memory', type=str, help='Maximum CPU memory in GiB to allocate for offloaded weights. Must be an integer number. Defaults to 99.') 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.') parser.add_argument('--flexgen', action='store_true', help='Enable the use of FlexGen offloading.') 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).') parser.add_argument("--compress-weight", action="store_true", help="FlexGen: activate weight compression.") 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%%).") 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.') 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.') parser.add_argument('--no-stream', action='store_true', help='Don\'t stream the text output in real time.') 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.') 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("--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('--verbose', action='store_true', help='Print the prompts to the terminal.') 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('--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-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) args = parser.parse_args() # Provisional, this will be deleted later deprecated_dict = {'gptq_bits': ['wbits', 0], 'gptq_model_type': ['model_type', None], 'gptq_pre_layer': ['prelayer', 0]} 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.") exec(f"args.{deprecated_dict[k][0]} = args.{k}")