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Custom PII Types

PIIDetector accepts a custom_types dict so you can define domain-specific PII patterns — employee IDs, internal codes, API tokens, or any regex you need.

Setup

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from llmfy import PIIDetector, PIIMaskStyle, PIIStrategy

Adding Custom Types

Pass a dict mapping a type name (str) to a regex pattern (str or compiled re.Pattern). The type name becomes the placeholder label when mask_style=TYPE_NAME, and the first two characters are used for PARTIAL.

String Pattern

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detector = PIIDetector(
    custom_types={
        "EMPLOYEE_ID": r"EMP-\d{6}",
        "PROJECT_CODE": r"PRJ-[A-Z]{3}",
    }
)
result = detector.detect(
    "Employee EMP-001234 is on project PRJ-ABC and emailed john@corp.com"
)

print(result.processed_text)
# "Employee EM* is on project PR* and emailed jo*"

Compiled Pattern

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import re

detector = PIIDetector(
    custom_types={
        "API_TOKEN": re.compile(r"tok_[a-z0-9]+"),
        "ORDER_ID": re.compile(r"ORD-\d{8}"),
    }
)
result = detector.detect("Token tok_abc123xyz for order ORD-20240315")

print(result.processed_text)
# "Token to* for order OR*"

Custom Types with TYPE_NAME Style

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detector = PIIDetector(
    mask_style=PIIMaskStyle.TYPE_NAME,
    custom_types={
        "EMPLOYEE_ID": r"EMP-\d{6}",
        "PROJECT_CODE": r"PRJ-[A-Z]{3}",
    }
)
result = detector.detect(
    "Employee EMP-001234 is on project PRJ-ABC and emailed john@corp.com"
)

print(result.processed_text)
# "Employee [EMPLOYEE_ID] is on project [PROJECT_CODE] and emailed [EMAIL]"

Custom Types with REDACT

mask_style is ignored when strategy=REDACT.

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detector = PIIDetector(
    strategy=PIIStrategy.REDACT,
    types=[],
    custom_types={"EMPLOYEE_ID": r"EMP-\d{6}"},
)
result = detector.detect(
    "ID: EMP-001234, Email: bob@example.com"
)

print(result.processed_text)
# "ID: [REDACTED], Email: bob@example.com"

Note

types=[] disables all built-in PII types. Only the custom patterns run.

Combining Custom and Built-in Types

Custom types run alongside the built-in types list.

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from llmfy import PIIDetector, PIIType

detector = PIIDetector(
    types=[PIIType.EMAIL, PIIType.PHONE_NUMBER],
    custom_types={"EMPLOYEE_ID": r"EMP-\d{6}"},
)
result = detector.detect(
    "Staff EMP-007890 reached at carol@example.com or +628987654321"
)

print(result.processed_text)
# "Staff EM* reached at ca* or +6*"

print([str(d.pii_type) for d in result.detections])
# ['EMPLOYEE_ID', 'EMAIL', 'PHONE_NUMBER']

Overriding a Built-in Type

If a custom type name matches a built-in PIIType value (e.g. "EMAIL"), the custom pattern replaces the built-in one entirely. The built-in pattern is suppressed.

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# Only matches custom-*@*.com — standard email addresses are left alone
detector = PIIDetector(
    custom_types={"EMAIL": r"custom-\w+@\w+\.com"}
)
result = detector.detect(
    "Regular john@example.com and custom-user@corp.com"
)

print(result.processed_text)
# "Regular john@example.com and cu*"

Partial Override

Override one built-in type while leaving the rest active.

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# PHONE_NUMBER now only matches +62 (Indonesian) numbers
detector = PIIDetector(
    custom_types={"PHONE_NUMBER": r"\+62\d{9,12}"}
)
result = detector.detect(
    "Call +628987654321 or (555) 123-4567, email bob@test.com"
)

print(result.processed_text)
# "Call +6* or (555) 123-4567, email bo*"

(555) 123-4567 is left untouched because the built-in PHONE_NUMBER pattern is suppressed, and the custom pattern does not match it. EMAIL continues to work normally since it was not overridden.