# !/usr/bin/python # -*- coding: utf-8 -*- # @time : 2021/2/29 21:41 # @author : Mo # @function: 文本纠错, 使用macro-correct import os os.environ["MACRO_CORRECT_FLAG_CSC_TOKEN"] = "1" from macro_correct import correct import gradio as gr ### 默认纠错(list输入) text_list = ["真麻烦你了。希望你们好好的跳无", "少先队员因该为老人让坐", "机七学习是人工智能领遇最能体现智能的一个分知", "一只小鱼船浮在平净的河面上" ] text_csc = correct(text_list) print("默认纠错(list输入):") for res_i in text_csc: print(res_i) print("#" * 128) """ 默认纠错(list输入): {'index': 0, 'source': '真麻烦你了。希望你们好好的跳无', 'target': '真麻烦你了。希望你们好好地跳舞', 'errors': [['的', '地', 12, 0.6584], ['无', '舞', 14, 1.0]]} {'index': 1, 'source': '少先队员因该为老人让坐', 'target': '少先队员应该为老人让坐', 'errors': [['因', '应', 4, 0.995]]} {'index': 2, 'source': '机七学习是人工智能领遇最能体现智能的一个分知', 'target': '机器学习是人工智能领域最能体现智能的一个分支', 'errors': [['七', '器', 1, 0.9998], ['遇', '域', 10, 0.9999], ['知', '支', 21, 1.0]]} {'index': 3, 'source': '一只小鱼船浮在平净的河面上', 'target': '一只小鱼船浮在平静的河面上', 'errors': [['净', '静', 8, 0.9961]]} """ def respond( message, history, system_message, max_tokens, temperature, top_p, ): messages = [{"role": "system", "content": system_message}] for val in history: if val[0]: messages.append({"role": "user", "content": val[0]}) if val[1]: messages.append({"role": "assistant", "content": val[1]}) messages.append({"role": "user", "content": message}) message_csc = correct([message]) target = message_csc[0].get("target", "") errors = message_csc[0].get("errors", "") response = target + " " + str(errors) out = "" for resp in response: out += resp yield out # response = "" # # for message in client.chat_completion( # messages, # max_tokens=max_tokens, # stream=True, # temperature=temperature, # top_p=top_p, # ): # token = message.choices[0].delta.content # # response += token # yield response """ For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface """ demo = gr.ChatInterface( respond, additional_inputs=[ gr.Textbox(value="Macro-Correct", label="System message"), # gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"), # gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"), # gr.Slider( # minimum=0.1, # maximum=1.0, # value=0.95, # step=0.05, # label="Top-p (nucleus sampling)", # ), ] # title="Chinese Spelling Correction Model Macropodus/macbert4csc_v2", # description="Copy or input error Chinese text. Submit and the machine will correct text.", # article="Link to Github REPO: macro-correct", ) if __name__ == "__main__": demo.launch() # demo.launch(server_name="0.0.0.0", server_port=8087, share=False, debug=True)