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| """Credit to https://github.com/THUDM/ChatGLM2-6B/blob/main/web_demo.py while mistakes are mine.""" | |
| # pylint: disable=broad-exception-caught, redefined-outer-name, missing-function-docstring, missing-module-docstring, too-many-arguments, line-too-long, invalid-name, redefined-builtin, redefined-argument-from-local | |
| # import gradio as gr | |
| # model_name = "fb700/chatglm-fitness-RLHF" | |
| # gr.load(model_name).lauch() | |
| # %%writefile demo-4bit.py | |
| import os | |
| import time | |
| from textwrap import dedent | |
| import gradio as gr | |
| import mdtex2html | |
| import torch | |
| from loguru import logger | |
| from transformers import AutoModel, AutoTokenizer | |
| # fix timezone in Linux | |
| os.environ["TZ"] = "Asia/Shanghai" | |
| try: | |
| time.tzset() # type: ignore # pylint: disable=no-member | |
| except Exception: | |
| # Windows | |
| logger.warning("Windows, cant run time.tzset()") | |
| # model_name = "THUDM/chatglm2-6b" # 7x?G | |
| model_name = "fb700/chatglm-fitness-RLHF" # 3.9G | |
| RETRY_FLAG = False | |
| tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) | |
| # model = AutoModel.from_pretrained(model_name, trust_remote_code=True).cuda() | |
| # 4/8 bit | |
| # model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).quantize(4).cuda() | |
| has_cuda = torch.cuda.is_available() | |
| # has_cuda = False # force cpu | |
| if has_cuda: | |
| if model_name.endswith("int4"): | |
| model = AutoModel.from_pretrained(model_name, trust_remote_code=True).cuda() | |
| else: | |
| model = ( | |
| AutoModel.from_pretrained(model_name, trust_remote_code=True).cuda().half() | |
| ) | |
| else: | |
| model = AutoModel.from_pretrained( | |
| model_name, trust_remote_code=True | |
| ).float() # .half().float(), .float() required for CPU | |
| model = model.eval() | |
| _ = """Override Chatbot.postprocess""" | |
| def postprocess(self, y): | |
| if y is None: | |
| return [] | |
| for i, (message, response) in enumerate(y): | |
| y[i] = ( | |
| None if message is None else mdtex2html.convert((message)), | |
| None if response is None else mdtex2html.convert(response), | |
| ) | |
| return y | |
| gr.Chatbot.postprocess = postprocess | |
| def parse_text(text): | |
| """Copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT/.""" | |
| lines = text.split("\n") | |
| lines = [line for line in lines if line != ""] | |
| count = 0 | |
| for i, line in enumerate(lines): | |
| if "```" in line: | |
| count += 1 | |
| items = line.split("`") | |
| if count % 2 == 1: | |
| lines[i] = f'<pre><code class="language-{items[-1]}">' | |
| else: | |
| lines[i] = "<br></code></pre>" | |
| else: | |
| if i > 0: | |
| if count % 2 == 1: | |
| line = line.replace("`", r"\`") | |
| line = line.replace("<", "<") | |
| line = line.replace(">", ">") | |
| line = line.replace(" ", " ") | |
| line = line.replace("*", "*") | |
| line = line.replace("_", "_") | |
| line = line.replace("-", "-") | |
| line = line.replace(".", ".") | |
| line = line.replace("!", "!") | |
| line = line.replace("(", "(") | |
| line = line.replace(")", ")") | |
| line = line.replace("$", "$") | |
| lines[i] = "<br>" + line | |
| text = "".join(lines) | |
| return text | |
| def predict( | |
| RETRY_FLAG, input, chatbot, max_length, top_p, temperature, history, past_key_values | |
| ): | |
| try: | |
| chatbot.append((parse_text(input), "")) | |
| except Exception as exc: | |
| logger.error(exc) | |
| logger.debug(f"{chatbot=}") | |
| _ = """ | |
| if chatbot: | |
| chatbot[-1] = (parse_text(input), str(exc)) | |
| yield chatbot, history, past_key_values | |
| # """ | |
| yield chatbot, history, past_key_values | |
| for response, history in model.stream_chat( | |
| tokenizer, | |
| input, | |
| history, | |
| past_key_values=past_key_values, | |
| return_past_key_values=True, | |
| max_length=max_length, | |
| top_p=top_p, | |
| temperature=temperature, | |
| ): | |
| chatbot[-1] = (parse_text(input), parse_text(response)) | |
| yield chatbot, history, past_key_values | |
| def trans_api(input, max_length=40960, top_p=0.8, temperature=0.2): | |
| if max_length < 10: | |
| max_length = 4096 | |
| if top_p < 0.1 or top_p > 1: | |
| top_p = 0.85 | |
| if temperature <= 0 or temperature > 1: | |
| temperature = 0.01 | |
| try: | |
| res, _ = model.chat( | |
| tokenizer, | |
| input, | |
| history=[], | |
| past_key_values=None, | |
| max_length=max_length, | |
| top_p=top_p, | |
| temperature=temperature, | |
| ) | |
| # logger.debug(f"{res=} \n{_=}") | |
| except Exception as exc: | |
| logger.error(f"{exc=}") | |
| res = str(exc) | |
| return res | |
| def reset_user_input(): | |
| return gr.update(value="") | |
| def reset_state(): | |
| return [], [], None | |
| # Delete last turn | |
| def delete_last_turn(chat, history): | |
| if chat and history: | |
| chat.pop(-1) | |
| history.pop(-1) | |
| return chat, history | |
| # Regenerate response | |
| def retry_last_answer( | |
| user_input, chatbot, max_length, top_p, temperature, history, past_key_values | |
| ): | |
| if chatbot and history: | |
| # Removing the previous conversation from chat | |
| chatbot.pop(-1) | |
| # Setting up a flag to capture a retry | |
| RETRY_FLAG = True | |
| # Getting last message from user | |
| user_input = history[-1][0] | |
| # Removing bot response from the history | |
| history.pop(-1) | |
| yield from predict( | |
| RETRY_FLAG, # type: ignore | |
| user_input, | |
| chatbot, | |
| max_length, | |
| top_p, | |
| temperature, | |
| history, | |
| past_key_values, | |
| ) | |
| with gr.Blocks(title="ChatGLM2-6B-int4", theme=gr.themes.Soft(text_size="sm")) as demo: | |
| # gr.HTML("""<h1 align="center">ChatGLM2-6B-int4</h1>""") | |
| gr.HTML( | |
| """<center><a href="https://huggingface.co/spaces/mikeee/chatglm2-6b-4bit?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>To avoid the queue and for faster inference Duplicate this Space and upgrade to GPU</center>""" | |
| ) | |
| with gr.Accordion("🎈 Info", open=False): | |
| _ = f""" | |
| ## {model_name} | |
| Try to refresh the browser and try again when occasionally an error occurs. | |
| With a GPU, a query takes from a few seconds to a few tens of seconds, dependent on the number of words/characters | |
| the question and responses contain. The quality of the responses varies quite a bit it seems. Even the same | |
| question with the same parameters, asked at different times, can result in quite different responses. | |
| * Low temperature: responses will be more deterministic and focused; High temperature: responses more creative. | |
| * Suggested temperatures -- translation: up to 0.3; chatting: > 0.4 | |
| * Top P controls dynamic vocabulary selection based on context. | |
| For a table of example values for different scenarios, refer to [this](https://community.openai.com/t/cheat-sheet-mastering-temperature-and-top-p-in-chatgpt-api-a-few-tips-and-tricks-on-controlling-the-creativity-deterministic-output-of-prompt-responses/172683) | |
| If the instance is not on a GPU (T4), it will be very slow. You can try to run the colab notebook [chatglm2-6b-4bit colab notebook](https://colab.research.google.com/drive/1WkF7kOjVCcBBatDHjaGkuJHnPdMWNtbW?usp=sharing) for a spin. | |
| The T4 GPU is sponsored by a community GPU grant from Huggingface. Thanks a lot! | |
| """ | |
| gr.Markdown(dedent(_)) | |
| chatbot = gr.Chatbot() | |
| with gr.Row(): | |
| with gr.Column(scale=4): | |
| with gr.Column(scale=12): | |
| user_input = gr.Textbox( | |
| show_label=False, | |
| placeholder="Input...", | |
| ).style(container=False) | |
| RETRY_FLAG = gr.Checkbox(value=False, visible=False) | |
| with gr.Column(min_width=32, scale=1): | |
| with gr.Row(): | |
| submitBtn = gr.Button("Submit", variant="primary") | |
| deleteBtn = gr.Button("Delete last turn", variant="secondary") | |
| retryBtn = gr.Button("Regenerate", variant="secondary") | |
| with gr.Column(scale=1): | |
| emptyBtn = gr.Button("Clear History") | |
| max_length = gr.Slider( | |
| 0, | |
| 32768, | |
| value=8192, | |
| step=1.0, | |
| label="Maximum length", | |
| interactive=True, | |
| ) | |
| top_p = gr.Slider( | |
| 0, 1, value=0.85, step=0.01, label="Top P", interactive=True | |
| ) | |
| temperature = gr.Slider( | |
| 0.01, 1, value=0.95, step=0.01, label="Temperature", interactive=True | |
| ) | |
| history = gr.State([]) | |
| past_key_values = gr.State(None) | |
| user_input.submit( | |
| predict, | |
| [ | |
| RETRY_FLAG, | |
| user_input, | |
| chatbot, | |
| max_length, | |
| top_p, | |
| temperature, | |
| history, | |
| past_key_values, | |
| ], | |
| [chatbot, history, past_key_values], | |
| show_progress="full", | |
| ) | |
| submitBtn.click( | |
| predict, | |
| [ | |
| RETRY_FLAG, | |
| user_input, | |
| chatbot, | |
| max_length, | |
| top_p, | |
| temperature, | |
| history, | |
| past_key_values, | |
| ], | |
| [chatbot, history, past_key_values], | |
| show_progress="full", | |
| api_name="predict", | |
| ) | |
| submitBtn.click(reset_user_input, [], [user_input]) | |
| emptyBtn.click( | |
| reset_state, outputs=[chatbot, history, past_key_values], show_progress="full" | |
| ) | |
| retryBtn.click( | |
| retry_last_answer, | |
| inputs=[ | |
| user_input, | |
| chatbot, | |
| max_length, | |
| top_p, | |
| temperature, | |
| history, | |
| past_key_values, | |
| ], | |
| # outputs = [chatbot, history, last_user_message, user_message] | |
| outputs=[chatbot, history, past_key_values], | |
| ) | |
| deleteBtn.click(delete_last_turn, [chatbot, history], [chatbot, history]) | |
| with gr.Accordion("Example inputs", open=True): | |
| etext = """In America, where cars are an important part of the national psyche, a decade ago people had suddenly started to drive less, which had not happened since the oil shocks of the 1970s. """ | |
| examples = gr.Examples( | |
| examples=[ | |
| ["What NFL team won the Super Bowl in the year Justin Bieber was born? "], | |
| ["What NFL team won the Super Bowl in the year Justin Bieber was born? Think step by step."], | |
| ["Explain the plot of Cinderella in a sentence."], | |
| [ | |
| "How long does it take to become proficient in French, and what are the best methods for retaining information?" | |
| ], | |
| ["What are some common mistakes to avoid when writing code?"], | |
| ["Build a prompt to generate a beautiful portrait of a horse"], | |
| ["Suggest four metaphors to describe the benefits of AI"], | |
| ["Write a pop song about leaving home for the sandy beaches."], | |
| ["Write a summary demonstrating my ability to tame lions"], | |
| ["鲁迅和周树人什么关系"], | |
| ["从前有一头牛，这头牛后面有什么？"], | |
| ["正无穷大加一大于正无穷大吗？"], | |
| ["正无穷大加正无穷大大于正无穷大吗？"], | |
| ["-2的平方根等于什么"], | |
| ["树上有5只鸟，猎人开枪打死了一只。树上还有几只鸟？"], | |
| ["树上有11只鸟，猎人开枪打死了一只。树上还有几只鸟？提示：需考虑鸟可能受惊吓飞走。"], | |
| ["鲁迅和周树人什么关系 用英文回答"], | |
| ["以红楼梦的行文风格写一张委婉的请假条。不少于320字。"], | |
| [f"{etext} 翻成中文，列出3个版本"], | |
| [f"{etext} \n 翻成中文，保留原意，但使用文学性的语言。不要写解释。列出3个版本"], | |
| ["js 判断一个数是不是质数"], | |
| ["js 实现python 的 range(10)"], | |
| ["js 实现python 的 [*(range(10)]"], | |
| ["假定 1 + 2 = 4, 试求 7 + 8"], | |
| ["Erkläre die Handlung von Cinderella in einem Satz."], | |
| ["Erkläre die Handlung von Cinderella in einem Satz. Auf Deutsch"], | |
| ], | |
| inputs=[user_input], | |
| examples_per_page=30, | |
| ) | |
| with gr.Accordion("For Chat/Translation API", open=False, visible=False): | |
| input_text = gr.Text() | |
| tr_btn = gr.Button("Go", variant="primary") | |
| out_text = gr.Text() | |
| tr_btn.click( | |
| trans_api, | |
| [input_text, max_length, top_p, temperature], | |
| out_text, | |
| # show_progress="full", | |
| api_name="tr", | |
| ) | |
| _ = """ | |
| input_text.submit( | |
| trans_api, | |
| [input_text, max_length, top_p, temperature], | |
| out_text, | |
| show_progress="full", | |
| api_name="tr1", | |
| ) | |
| # """ | |
| # demo.queue().launch(share=False, inbrowser=True) | |
| # demo.queue().launch(share=True, inbrowser=True, debug=True) | |
| # concurrency_count > 1 requires more memory, max_size: queue size | |
| # T4 medium: 30GB, model size: ~4G concurrency_count = 6 | |
| # leave one for api access | |
| # reduce to 5 if OOM occurs to often | |
| demo.queue(concurrency_count=6, max_size=30).launch(debug=True) | |