langchain/libs/experimental/langchain_experimental/data_anonymizer/base.py
maks-operlejn-ds 274c3dc3a8
Multilingual anonymization (#10327)
### Description

Add multiple language support to Anonymizer

PII detection in Microsoft Presidio relies on several components - in
addition to the usual pattern matching (e.g. using regex), the analyser
uses a model for Named Entity Recognition (NER) to extract entities such
as:
- `PERSON`
- `LOCATION`
- `DATE_TIME`
- `NRP`
- `ORGANIZATION`


[[Source]](https://github.com/microsoft/presidio/blob/main/presidio-analyzer/presidio_analyzer/predefined_recognizers/spacy_recognizer.py)

To handle NER in specific languages, we utilize unique models from the
`spaCy` library, recognized for its extensive selection covering
multiple languages and sizes. However, it's not restrictive, allowing
for integration of alternative frameworks such as
[Stanza](https://microsoft.github.io/presidio/analyzer/nlp_engines/spacy_stanza/)
or
[transformers](https://microsoft.github.io/presidio/analyzer/nlp_engines/transformers/)
when necessary.

### Future works

- **automatic language detection** - instead of passing the language as
a parameter in `anonymizer.anonymize`, we could detect the language/s
beforehand and then use the corresponding NER model. We have discussed
this internally and @mateusz-wosinski-ds will look into a standalone
language detection tool/chain for LangChain 😄

### Twitter handle
@deepsense_ai / @MaksOpp

### Tag maintainer
@baskaryan @hwchase17 @hinthornw
2023-09-07 14:42:24 -07:00

33 lines
905 B
Python

from abc import ABC, abstractmethod
from typing import Optional
class AnonymizerBase(ABC):
"""
Base abstract class for anonymizers.
It is public and non-virtual because it allows
wrapping the behavior for all methods in a base class.
"""
def anonymize(self, text: str, language: Optional[str] = None) -> str:
"""Anonymize text"""
return self._anonymize(text, language)
@abstractmethod
def _anonymize(self, text: str, language: Optional[str]) -> str:
"""Abstract method to anonymize text"""
class ReversibleAnonymizerBase(AnonymizerBase):
"""
Base abstract class for reversible anonymizers.
"""
def deanonymize(self, text: str) -> str:
"""Deanonymize text"""
return self._deanonymize(text)
@abstractmethod
def _deanonymize(self, text: str) -> str:
"""Abstract method to deanonymize text"""