"""Run codes.""" # pylint: disable=line-too-long, broad-exception-caught, invalid-name, missing-function-docstring, too-many-instance-attributes, missing-class-docstring # ruff: noqa: E501 import os import platform import random import time from dataclasses import asdict, dataclass from pathlib import Path # from types import SimpleNamespace import gradio as gr import psutil from about_time import about_time from ctransformers import AutoModelForCausalLM from dl_hf_model import dl_hf_model from loguru import logger filename_list = [ "Wizard-Vicuna-7B-Uncensored.ggmlv3.q2_K.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q3_K_L.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q3_K_M.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q3_K_S.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_0.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_1.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_K_M.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_K_S.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q5_0.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q5_1.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q5_K_M.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q5_K_S.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q6_K.bin", "Wizard-Vicuna-7B-Uncensored.ggmlv3.q8_0.bin", ] URL = "https://huggingface.co/TheBloke/Wizard-Vicuna-7B-Uncensored-GGML/raw/main/Wizard-Vicuna-7B-Uncensored.ggmlv3.q4_K_M.bin" # 4.05G url = "https://huggingface.co/savvamadar/ggml-gpt4all-j-v1.3-groovy/blob/main/ggml-gpt4all-j-v1.3-groovy.bin" url = "https://huggingface.co/TheBloke/Llama-2-13B-GGML/blob/main/llama-2-13b.ggmlv3.q4_K_S.bin" # 7.37G # url = "https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/blob/main/llama-2-13b-chat.ggmlv3.q3_K_L.bin" url = "https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/blob/main/llama-2-13b-chat.ggmlv3.q3_K_L.bin" # 6.93G # url = "https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/blob/main/llama-2-13b-chat.ggmlv3.q3_K_L.binhttps://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/blob/main/llama-2-13b-chat.ggmlv3.q4_K_M.bin" # 7.87G url = "https://huggingface.co/localmodels/Llama-2-13B-Chat-ggml/blob/main/llama-2-13b-chat.ggmlv3.q4_K_S.bin" # 7.37G _ = ( "golay" in platform.node() or "okteto" in platform.node() or Path("/kaggle").exists() # or psutil.cpu_count(logical=False) < 4 or 1 # run 7b in hf ) if _: # url = "https://huggingface.co/TheBloke/Llama-2-13B-chat-GGML/blob/main/llama-2-13b-chat.ggmlv3.q2_K.bin" url = "https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/blob/main/llama-2-7b-chat.ggmlv3.q2_K.bin" # 2.87G url = "https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/blob/main/llama-2-7b-chat.ggmlv3.q4_K_M.bin" # 2.87G url = "https://huggingface.co/TheBloke/llama2_7b_chat_uncensored-GGML/blob/main/llama2_7b_chat_uncensored.ggmlv3.q4_K_M.bin" # 4.08G prompt_template = """### HUMAN: {question} ### RESPONSE:""" _ = [elm for elm in prompt_template.splitlines() if elm.strip()] stop_string = [elm.split(":")[0] + ":" for elm in _][-2] logger.debug(f"{stop_string=} not used") _ = psutil.cpu_count(logical=False) - 1 cpu_count: int = int(_) if _ else 1 logger.debug(f"{cpu_count=}") LLM = None try: model_loc, file_size = dl_hf_model(url) except Exception as exc_: logger.error(exc_) raise SystemExit(1) from exc_ LLM = AutoModelForCausalLM.from_pretrained( model_loc, model_type="llama", # threads=cpu_count, ) logger.info(f"done load llm {model_loc=} {file_size=}G") os.environ["TZ"] = "Asia/Shanghai" try: time.tzset() # type: ignore # pylint: disable=no-member except Exception: # Windows logger.warning("Windows, cant run time.tzset()") _ = """ ns = SimpleNamespace( response="", generator=(_ for _ in []), ) # """ @dataclass class GenerationConfig: temperature: float = 0.7 top_k: int = 50 top_p: float = 0.9 repetition_penalty: float = 1.0 max_new_tokens: int = 512 seed: int = 42 reset: bool = False stream: bool = True threads: int = cpu_count # stop: list[str] = field(default_factory=lambda: [stop_string]) def generate( question: str, llm=LLM, config: GenerationConfig = GenerationConfig(), ): """Run model inference, will return a Generator if streaming is true.""" # _ = prompt_template.format(question=question) # print(_) prompt = prompt_template.format(question=question) print("\n [PROMPT]: " ,prompt) return llm( prompt, **asdict(config), ) logger.debug(f"{asdict(GenerationConfig())=}") def user(user_message, history): # return user_message, history + [[user_message, None]] history.append([user_message, None]) return user_message, history # keep user_message def user1(user_message, history): # return user_message, history + [[user_message, None]] history.append([user_message, None]) return "", history # clear user_message def bot(history): user_message = history[-1][0] response = [] logger.debug(f"{user_message=}") with about_time() as atime: # type: ignore flag = 1 prefix = "" then = time.time() logger.debug("about to generate") config = GenerationConfig(reset=True) for elm in generate(user_message, config=config): if flag == 1: logger.debug("in the loop") prefix = f"({time.time() - then:.2f}s) " flag = 0 print(prefix, end="", flush=True) logger.debug(f"{prefix=}") print(elm, end="", flush=True) # logger.debug(f"{elm}") response.append(elm) history[-1][1] = prefix + "".join(response) yield history _ = ( f"(time elapsed: {atime.duration_human}, " # type: ignore f"{atime.duration/len(''.join(response)):.2f}s/char)" # type: ignore ) history[-1][1] = "".join(response) + f"\n{_}" yield history def predict_api(prompt): logger.debug(f"{prompt=}") try: # user_prompt = prompt config = GenerationConfig( temperature=0.2, top_k=10, top_p=0.9, repetition_penalty=1.0, max_new_tokens=512, # adjust as needed seed=42, reset=True, # reset history (cache) stream=False, # threads=cpu_count, # stop=prompt_prefix[1:2], ) response = generate( prompt, config=config, ) logger.debug(f"api: {response=}") except Exception as exc: logger.error(exc) response = f"{exc=}" # bot = {"inputs": [response]} # bot = [(prompt, response)] return response logger.info("start block") with gr.Blocks( title=f"{Path(model_loc).name}", ) as block: chatbot = gr.Chatbot(height=500) with gr.Row(): with gr.Column(scale=5): msg = gr.Textbox( label="Chat Message Box", placeholder="Ask me anything (press Shift+Enter or click Submit to send)", show_label=False, # container=False, lines=6, max_lines=30, show_copy_button=True, # ).style(container=False) ) with gr.Column(scale=1, min_width=50): with gr.Row(): submit = gr.Button("Submit", elem_classes="xsmall") stop = gr.Button("Stop", visible=True) clear = gr.Button("Clear History", visible=True) with gr.Row(visible=True): with gr.Accordion("Advanced Options:", open=False): with gr.Row(): with gr.Column(scale=2): system = gr.Textbox( label="System Prompt", placeholder=prompt_template, show_label=False, # container=False, lines=6, max_lines=30, # ).style(container=False) ) with gr.Column(): with gr.Row(): change = gr.Button("Change System Prompt") reset = gr.Button("Reset System Prompt") msg_submit_event = msg.submit( # fn=conversation.user_turn, fn=user, inputs=[msg, chatbot], outputs=[msg, chatbot], queue=True, show_progress="full", # api_name=None, ).then(bot, chatbot, chatbot, queue=True) submit_click_event = submit.click( # fn=lambda x, y: ("",) + user(x, y)[1:], # clear msg fn=user1, # clear msg inputs=[msg, chatbot], outputs=[msg, chatbot], queue=True, # queue=False, show_progress="full", # api_name=None, ).then(bot, chatbot, chatbot, queue=True) stop.click( fn=None, inputs=None, outputs=None, cancels=[msg_submit_event, submit_click_event], queue=False, ) clear.click(lambda: None, None, chatbot, queue=False) with gr.Accordion("For Chat/Translation API", open=False, visible=False): input_text = gr.Text() api_btn = gr.Button("Go", variant="primary") out_text = gr.Text() api_btn.click( predict_api, input_text, out_text, api_name="api", ) # concurrency_count=5, max_size=20 # max_size=36, concurrency_count=14 # CPU cpu_count=2 16G, model 7G # CPU UPGRADE cpu_count=8 32G, model 7G concurrency_count = 1 logger.info(f"{concurrency_count=}") block.queue(concurrency_count=concurrency_count, max_size=5).launch(debug=True)