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# Updated NamedEntityRecognitionTool in ner_tool.py
from transformers import pipeline
from transformers import Tool
class NamedEntityRecognitionTool(Tool):
name = "ner_tool"
description = "Identifies and labels entities such as persons, organizations, and locations in a given text."
inputs = ["text"]
outputs = ["entities"]
def __call__(self, text: str):
# Initialize the named entity recognition pipeline
ner_analyzer = pipeline("ner")
# Perform named entity recognition on the input text
entities = ner_analyzer(text)
# Extract relevant information for each identified entity
entity_info = [{"entity": entity.get("entity", "UNKNOWN"), "word": entity.get("word", ""), "start": entity.get("start", -1), "end": entity.get("end", -1)} for entity in entities]
# Extract the actual text span for each identified location entity
location_entities = [text[start:end] for entity in entity_info if entity["entity"] == "I-LOC" for start, end in [(entity["start"], entity["end"])]]
# Print the identified entities
print(f"Identified Location Entities: {location_entities}")
return {"entities": location_entities} # Return a dictionary with the specified output component
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