add mission function

.idea/.gitignore

@@ -0,0 +1,8 @@
+# Default ignored files
+/shelf/
+/workspace.xml
+# Datasource local storage ignored files
+/dataSources/
+/dataSources.local.xml
+# Editor-based HTTP Client requests
+/httpRequests/

fill_in_summary.py

@@ -0,0 +1,66 @@
+
+class FillInSummary:
+    """Organizing Summarization and Subsequent Fill-In-Task."""
+
+    def __init__(self):
+        """Initialize Class with Summarizer and NER-Model."""
+        # Refer to https://huggingface.co/docs/transformers/v4.18.0/en/main_classes/pipelines#transformers.SummarizationPipeline
+        # for further information about configuration.
+        self.summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+        # Using default model: https://huggingface.co/dbmdz/bert-large-cased-finetuned-conll03-english
+        self.ner = ner= pipeline("ner", aggregation_strategy='simple')
+
+    def summarize(self, text: str) -> str:
+        """Summarize given Text.
+
+        Parameter
+        ---------
+        text : str
+          Text to be summarized. Must not exceeds BART's maximal input length.
+
+        Returns
+        -------
+        str
+          Summary
+        """
+        # Refer to https://huggingface.co/docs/transformers/main/en/main_classes/configuration#transformers.PretrainedConfig
+        # for further configuration of of the
+        output: list = self.summarizer(
+            text,
+            max_length=400,
+            min_length=100,
+            do_sample=False)
+        return output[0]['summary_text']
+
+    def blank_ne_out(self, text: str) -> dict():
+        """Blank out named entities.
+
+        Transforms 'X did this.' to {
+          'text': '_ did this',
+          'ner': [{
+            'end': 1,
+            'entity_group': 'ORG',
+            'score': 0.73085225,
+            'start': 0,
+            'word': 'X'
+            }]}
+
+        Parameter
+        ---------
+        text : str
+          Summarized text.
+
+        Returns
+        -------
+        dict
+          Entails blanked out text and recognized named entity list.
+        """
+        ner_list: list = self.ner(text)
+        output_str: str = text
+        for start, end in map(lambda e : (e['start'], e['end']), ner_list):
+            length: int = end - start
+            output_str = output_str[0:start] + ("_" * length) + output_str[end::]
+        return {
+            'text': output_str,
+            'ner': ner_list
+        }