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from typing import Dict, Union
def sanitize(
input: Union[str, Dict[str, str]],
) -> Dict[str, Union[str, Dict[str, str]]]:
"""
Sanitize input string or dict of strings by replacing sensitive data with
placeholders.
It returns the sanitized input string or dict of strings and the secure
context as a dict following the format:
{
"sanitized_input": <sanitized input string or dict of strings>,
"secure_context": <secure context>
}
The secure context is a bytes object that is needed to de-sanitize the response
from the LLM.
Args:
input: Input string or dict of strings.
Returns:
Sanitized input string or dict of strings and the secure context
as a dict following the format:
{
"sanitized_input": <sanitized input string or dict of strings>,
"secure_context": <secure context>
}
The `secure_context` needs to be passed to the `desanitize` function.
Raises:
ValueError: If the input is not a string or dict of strings.
ImportError: If the `opaqueprompts` Python package is not installed.
"""
try:
import opaqueprompts as op
except ImportError:
raise ImportError(
"Could not import the `opaqueprompts` Python package, "
"please install it with `pip install opaqueprompts`."
)
if isinstance(input, str):
# the input could be a string, so we sanitize the string
sanitize_response: op.SanitizeResponse = op.sanitize([input])
return {
"sanitized_input": sanitize_response.sanitized_texts[0],
"secure_context": sanitize_response.secure_context,
}
if isinstance(input, dict):
# the input could be a dict[string, string], so we sanitize the values
values = list()
# get the values from the dict
for key in input:
values.append(input[key])
# sanitize the values
sanitize_values_response: op.SanitizeResponse = op.sanitize(values)
# reconstruct the dict with the sanitized values
sanitized_input_values = sanitize_values_response.sanitized_texts
idx = 0
sanitized_input = dict()
for key in input:
sanitized_input[key] = sanitized_input_values[idx]
idx += 1
return {
"sanitized_input": sanitized_input,
"secure_context": sanitize_values_response.secure_context,
}
raise ValueError(f"Unexpected input type {type(input)}")
def desanitize(sanitized_text: str, secure_context: bytes) -> str:
"""
Restore the original sensitive data from the sanitized text.
Args:
sanitized_text: Sanitized text.
secure_context: Secure context returned by the `sanitize` function.
Returns:
De-sanitized text.
"""
try:
import opaqueprompts as op
except ImportError:
raise ImportError(
"Could not import the `opaqueprompts` Python package, "
"please install it with `pip install opaqueprompts`."
)
desanitize_response: op.DesanitizeResponse = op.desanitize(
sanitized_text, secure_context
)
return desanitize_response.desanitized_text
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