Metadata-Version: 2.1
Name: autota
Version: 0.0.3
Summary: Automatic generate QA from slides and grade marker/memo.
Home-page: https://github.com/miyuiki/autota
Author: Jay
Author-email: a121406@gmail.com
License: UNKNOWN
Description: # AutoTA
        提供BookRoll中的Marker/Memo評分功能，以及教材推薦功能
        ## 準備
        以下四個服務需要先以docker在本地端或遠端建立
        1. Question generation service(問題生成才要)
        2. BERT pre-trained model service
        3. BERT fine-tuned model service(簡答題評分才要)
        4. Google cloud translation service(問題生成才要)
        
        ## 安裝
        `pip install autota`
        
        ## 使用
        獲取Marker/Memo分數
        ```python
        from autota.grader import Grader
        
        grader = Grader(pdf_path='./test.pdf', 
        		bert_api_port=PRETRAINED_BERT_SERVICE_PORT, 
        		bert_api_url='PRETRAINED_BERT_SERVICE_HOST')
        print(grader.grade_marker('marker text')) #得到單一marker分數
        print(grader.grade_memo('memo text')) #得到單一memo分數
        ```
        獲取教材推薦頁數
        ```python
        from autota.recommender import Recommender
        
        #num_page指定要推薦多少頁
        recommender = Recommender(pdf_path='./test.pdf', num_page=2, 
        			api_port=PRETRAINED_BERT_SERVICE_PORT, 
        			api_url='PRETRAINED_BERT_SERVICE_HOST')
        
        print(recommender.guiding_from(ta_ans='要推薦的概念'))
        #輸出為[(2, 0.0778473040773201), (1, 0.08752984923065377)]
        #tuple第一項元素即為頁數，第二項為該頁與ta_ans概念間的餘弦距離
        ```
        從教材自動生成問題
        ```python
        from autota.generator import Generator
        
        #num_page指定要推薦多少頁
        generator = Generator(pdf_path='./test.pdf',, 
        			translate_api_port=TRANSLATE_SERVICE_PORT, 
        			translate_api_url='TRANSLATE_SERVICE_HOST',
        			gpt2_api_port=GPT2_SERVICE_PORT,
        			gpt2_api_url='GPT2_SERVICE_HOST')
        
        print(generator.get_qa())
        #輸出為[('What is the first thing that can be a variable name?', '變數名稱的第一個字不可為數字')]
        #list中每個tuple為一組QA pair
        ```
        
        ## 開發中
        1. 簡答題自動評分
        
        
        
        
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
