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from abc import ABC, abstractmethod |
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from dataclasses import dataclass |
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from collections import namedtuple |
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from typing import List, Optional |
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Summary = namedtuple('Summary',['source','cluster_list','link_ext','hed','dek','date','authors','original_length','summary_text','summary_length','chunk_time', 'query_time', 'mean_query_time', 'summary_time']) |
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Summary.__doc__ = f""" |
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Summary: a namedtuple for storing Summaries and relevant metadata. |
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• Source: A Source object for the source of the summarized document. |
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• cluster_list: A list of the NER entities detected in this article's hed (headline). |
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• link_ext: The link extension of the article (on the base url, source's source_url) |
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• hed, dek: headline and subheader. These are standard industry terms. |
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Dek is None if not applicable. |
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• date: Date of publication/update listed in article. |
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• authors: list of authors, currently a string containing the byline. |
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• original_length: length of the original article |
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• cluster_num: Number of clusters the source article appears in |
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• summary_text: List of summarized chunks. |
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• summary_length: Length of summary text |
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• stats for stats |
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""" |
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@dataclass |
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class Source(ABC): |
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source_name: Optional[str] = "" |
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source_url: Optional[str] = "" |
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source_summarization_checkpoint: Optional[str] = "" |
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source_ner_checkpoint: Optional[str] = "" |
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""" |
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User must implement a source-dependent method |
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to retrieve data used to create clusters. |
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This gets called when clustering is performed. |
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""" |
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@abstractmethod |
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def retrieve_cluster_data(self) -> List[namedtuple]: |
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pass |
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""" |
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User must implement a source-dependent method |
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to retrieve texts for summarization. |
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This gets called once topics for digestion have been selected. |
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""" |
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@abstractmethod |
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def retrieve_article(self) -> List[namedtuple]: |
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pass |
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