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1 Parent(s): 09a0fb1

Rename emojify_text.py to ner_tool.py

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  1. emojify_text.py +0 -33
  2. ner_tool.py +23 -0
emojify_text.py DELETED
@@ -1,33 +0,0 @@
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- import emoji
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- from transformers import Tool
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-
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- class EmojifyTextTool(Tool):
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- name = "emojify_text"
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- description = "Emojifies text by adding relevant emojis to enhance expressiveness."
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- inputs = ["text"]
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- outputs = ["text"] # Explicitly specify the output component
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-
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- def __call__(self, text: str):
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- # Define a dictionary mapping keywords to emojis
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- keyword_to_emoji = {
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- "happy": "๐Ÿ˜„",
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- "sad": "๐Ÿ˜ข",
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- "love": "โค๏ธ",
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- "confused": "๐Ÿ˜•",
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- "excited": "๐ŸŽ‰",
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- # Add more keywords and corresponding emojis as needed
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- }
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-
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- # Emojify the input text based on keywords
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- emojified_text = self._emojify_keywords(text, keyword_to_emoji)
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-
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- # Print the emojified text
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- print(f"Emojified Text: {emojified_text}")
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-
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- return {"emojified_text": emojified_text} # Return a dictionary with the specified output component
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-
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- def _emojify_keywords(self, text, keyword_to_emoji):
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- # Replace keywords in the text with corresponding emojis
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- for keyword, emoji_char in keyword_to_emoji.items():
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- text = text.replace(keyword, emoji_char)
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- return text
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ner_tool.py ADDED
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+ from transformers import pipeline
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+ from transformers import Tool
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+
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+ class NamedEntityRecognitionTool(Tool):
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+ name = "ner_tool"
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+ description = "Identifies and labels entities such as persons, organizations, and locations in a given text."
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+ inputs = ["text"]
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+ outputs = ["entities"]
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+
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+ def __call__(self, text: str):
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+ # Initialize the named entity recognition pipeline
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+ ner_analyzer = pipeline("ner")
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+
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+ # Perform named entity recognition on the input text
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+ entities = ner_analyzer(text)
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+
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+ # Print the identified entities
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+ print(f"Identified Entities: {entities}")
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+
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+ # Extract entity labels and return as a list
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+ entity_labels = [entity["label"] for entity in entities]
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+
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+ return entity_labels