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| class config(): | |
| sample_texts_path = 'data/sample_text.csv' | |
| logo_path = 'images/tum-logo.png' | |
| main_title = 'Topic Modeling for Summarization' | |
| lecture_title = 'Machine Learning for Natural Language Processing Applications (IN2106)' | |
| input_text = 'Enter Some Text:' | |
| button_text = 'Generate new sample text' | |
| topic_modelling_title = 'Topic Modelling:' | |
| topic_modelling_answers = ('BERTopic','LDA','CTM','NMF','Top2Vec') | |
| segmenter_title = 'Segmentizer:' | |
| segmenter_answers = ('Nltk','Spacy','Stanza') | |
| summarizer_title = 'Summarizer:' | |
| summarizer_answers = ('Bart','T5-base','Prophetnet','Pegasus') | |
| generate_text = 'Generate topic based summaries' | |
| output_title = 'Select topics you want to see summaries of:' | |
| warning_len_input_text = 'The length of the input text is not enough to create topic awareness summaries! or change parameters!' | |
| filter_threshold_summaries = True | |
| threshold_error = 'X -> not possible to generate a summary due to ''threshold' | |
| # model parameters | |
| MIN_NUM_SENTENCES_FOR_SUMMARY_CREATION = 2 | |
| PATH_20_NEWS_CLUSTERID_LABEL_WORDS = 'data/_20news_df_output_clusterId_label_words.csv' | |
| PATH_20_NEWS_CLUSTERID_LABEL_WORDS_CTM = 'data/_20news_df_output_doc_topic_CTM_LIST.csv' | |
| PATH_20_NEWS_CLUSTERID_LABEL_WORDS_LDA = 'data/_20news_df_output_doc_topic_LDA_LIST.csv' | |
| PATH_20_NEWS_CLUSTERID_LABEL_WORDS_NMF = 'data/_20news_df_output_doc_topic_NMF_LIST.csv' | |
| PATH_20_NEWS_CLUSTERID_LABEL_WORDS_TOP2VEC = 'data/_20news_df_output_doc_topic_Top2Vec_LIST.csv' | |
| # model paths | |
| nltk_path = 'models/nltkUtilsObj.pkl' | |
| sent_trans_path = 'models/sentTransfModelUtilsObj.pkl' | |
| pegasus_model_path = 'models/pegasus_model' | |
| bart_model_path = 'models/bart_model' | |
| t5_model_path = 'models/t5_model' | |
| prophetnet_model_path = 'models/prophetnet_model' | |