feder-cr/Jobs_Applier_AI_Agent_AIHawk · error · TypeError

Error in legal_authorization data: {e}

Error message

Error in legal_authorization data: {e}

What it means

TypeError raised from the legal_authorization block in JobApplicationProfile.__init__. Two typical sources: data['legal_authorization'] is not a mapping so **-unpacking fails with 'argument of type ... is not a mapping', or LegalAuthorization's constructor received an unexpected/positional argument ('__init__() got an unexpected keyword argument ...'). The original message is included via {e}.

Source

Thrown at src/resume_schemas/job_application_profile.py:110

            raise TypeError(f"Error in self_identification data: {e}") from e
        except AttributeError as e:
            logger.error(f"Attribute error in self_identification processing: {e}")
            raise AttributeError("Attribute error in self_identification processing.") from e
        except Exception as e:
            logger.error(f"An unexpected error occurred while processing self_identification: {e}")
            raise RuntimeError("An unexpected error occurred while processing self_identification.") from e

        # Process legal_authorization
        try:
            logger.debug("Processing legal_authorization")
            self.legal_authorization = LegalAuthorization(**data['legal_authorization'])
            logger.debug(f"legal_authorization processed: {self.legal_authorization}")
        except KeyError as e:
            logger.error(f"Required field {e} is missing in legal_authorization data.")
            raise KeyError(f"Required field {e} is missing in legal_authorization data.") from e
        except TypeError as e:
            logger.error(f"Error in legal_authorization data: {e}")
            raise TypeError(f"Error in legal_authorization data: {e}") from e
        except AttributeError as e:
            logger.error(f"Attribute error in legal_authorization processing: {e}")
            raise AttributeError("Attribute error in legal_authorization processing.") from e
        except Exception as e:
            logger.error(f"An unexpected error occurred while processing legal_authorization: {e}")
            raise RuntimeError("An unexpected error occurred while processing legal_authorization.") from e

        # Process work_preferences
        try:
            logger.debug("Processing work_preferences")
            self.work_preferences = WorkPreferences(**data['work_preferences'])
            logger.debug(f"Work_preferences processed: {self.work_preferences}")
        except KeyError as e:
            logger.error(f"Required field {e} is missing in work_preferences data.")
            raise KeyError(f"Required field {e} is missing in work_preferences data.") from e
        except TypeError as e:
            logger.error(f"Error in work_preferences data: {e}")
            raise TypeError(f"Error in work_preferences data: {e}") from e

View on GitHub (pinned to 79155b52fa)

Solutions

  1. Ensure data['legal_authorization'] is a dict; coerce or default it before construction.
  2. Remove or filter unknown keys: pass only the fields LegalAuthorization accepts.
  3. Align the data schema with the current LegalAuthorization constructor signature (version check).

Example fix

# before
self.legal_authorization = LegalAuthorization(**data['legal_authorization'])  # value is a str

# after
la = data.get('legal_authorization') or {}
if not isinstance(la, dict):
    raise TypeError('legal_authorization must be a dict')
self.legal_authorization = LegalAuthorization(**la)
Defensive patterns

Strategy: type-guard

Validate before calling

la = data.get('legal_authorization')
if not isinstance(la, dict):
    raise TypeError('legal_authorization must be a dict')

Type guard

def is_legal_authorization_dict(data: dict) -> bool:
    return isinstance(data.get('legal_authorization'), dict)

Try / catch

try:
    profile = JobApplicationProfile(**data)
except TypeError as e:
    if 'legal_authorization' in str(e):
        fix_and_retry(data)  # coerce section to dict

Prevention

When it happens

Trigger: legal_authorization given as a string/list/None in the resume data; extra keys in the legal_authorization dict that LegalAuthorization.__init__ does not accept; wrong positional layout when constructing programmatically.

Common situations: YAML where legal_authorization: is a scalar or list; schema drift after adding/removing fields from LegalAuthorization; LLM- or template-generated resumes with extra keys like 'notes'.

Understand the failure class

Background: Schema validation failed / invalid input schema: payload rejected because its shape doesn't match the expected schema — this error's family across 28 libraries.

Related errors

AI-assisted analysis of feder-cr/Jobs_Applier_AI_Agent_AIHawk@79155b52fa (2026-08-28). Data as JSON: /api/errors/aacf445d0c7b5646. Report an issue: GitHub.