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"""Process an snippet to determine if it is spam or not."""
from google.protobuf.json_format import MessageToDict
import api.v1.spamcheck_pb2 as spam
from app import logger
from app.spammable import Spammable
from server.interceptors import SpamCheckContext
log = logger.logger
# Expecting a module to exist in the directory specified by the ml_classifiers config option.
# i.e {ml_classifiers}/snippet/ml
try:
from issue import classifier
except ModuleNotFoundError as exp:
log.warning("generic ML classifier not loaded", extra={"error": exp})
classifier = None # pylint: disable=invalid-name
class Generic(Spammable):
"""Analyze a generic spammable to determine if it is spam."""
def __init__(self, spammable: spam.Generic, context: SpamCheckContext) -> None:
super().__init__(spammable, context, classifier)
def to_dict(self) -> dict:
"""Return the dictionary representation of the spammable."""
spammable_dict = MessageToDict(self._spammable)
spammable_dict["correlation_id"] = str(self.context.correlation_id)
spammable_dict["title"] = ""
spammable_dict["description"] = spammable_dict.pop("text")
return spammable_dict
def type(self) -> str:
s_type = self._spammable.type
if s_type == "":
s_type = "Generic"
return s_type
Generic.set_max_verdict()
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