feder-cr/Jobs_Applier_AI_Agent_AIHawk · error · TypeError

Invalid data for Education: {e}

Error message

Invalid data for Education: {e}

What it means

EducationDetails construction failed with a TypeError — wrong-typed or unexpected keyword arguments. Common causes: exam entries built via Exam(name=k, grade=v) where v isn't a str, a required field missing from the kwargs (Python reports missing arguments as TypeError), or extra keys passed through.

Source

Thrown at src/resume_schemas/resume.py:153

    def _process_education_details(self, data: List[Dict[str, Any]]) -> List[EducationDetails]:
        education_list = []
        for edu in data:
            try:
                exams = [Exam(name=k, grade=v) for k, v in edu.get('exam', {}).items()]
                education = EducationDetails(
                    education_level=edu.get('education_level'),
                    institution=edu.get('institution'),
                    field_of_study=edu.get('field_of_study'),
                    final_evaluation_grade=edu.get('final_evaluation_grade'),
                    start_date=edu.get('start_date'),
                    year_of_completion=edu.get('year_of_completion'),
                    exam=exams
                )
                education_list.append(education)
            except KeyError as e:
                raise KeyError(f"Missing field in education details: {e}") from e
            except TypeError as e:
                raise TypeError(f"Invalid data for Education: {e}") from e
            except AttributeError as e:
                raise AttributeError(f"AttributeError in Education: {e}") from e
            except Exception as e:
                raise Exception(f"Unexpected error in Education processing: {e}") from e
        return education_list

    def _process_experience_details(self, data: List[Dict[str, Any]]) -> List[ExperienceDetails]:
        experience_list = []
        for exp in data:
            try:
                key_responsibilities = [
                    Responsibility(description=list(resp.values())[0])
                    for resp in exp.get('key_responsibilities', [])
                ]
                skills_acquired = [str(skill) for skill in exp.get('skills_acquired', [])]
                experience = ExperienceDetails(
                    position=exp['position'],
                    company=exp['company'],

View on GitHub (pinned to 79155b52fa)

Solutions

  1. Check the TypeError text: 'missing 1 required positional argument' vs 'unexpected keyword argument' pinpoints the field.
  2. Normalize the exam structure before the loop: if isinstance(edu.get('exam'), list): convert to a dict.
  3. Add defaults (Optional[...] = None) to non-critical EducationDetails fields.
  4. Validate types of values (grade must be str/int) before constructing Exam.

Example fix

// before
exams = [Exam(name=k, grade=v) for k, v in edu.get('exam', {}).items()]

# after
exam_data = edu.get('exam') or {}
if not isinstance(exam_data, dict):
    exam_data = {e['name']: e['grade'] for e in exam_data}
exams = [Exam(name=k, grade=str(v)) for k, v in exam_data.items()]
Defensive patterns

Strategy: type-guard

Validate before calling

exam = edu.get('exam') or {}
if not isinstance(exam, dict):
    if isinstance(exam, list):
        exam = {item['name']: item['grade'] for item in exam if isinstance(item, dict)}
    else:
        exam = {}

Type guard

def is_exam_map(x: Any) -> TypeGuard[dict]:
    return isinstance(x, dict) and all(isinstance(v, (str, int, float)) for v in x.values())

Try / catch

try:
    edu_list = _process_education_details(data)
except TypeError as e:
    logger.error("education type mismatch: %s", e)
    raise

Prevention

When it happens

Trigger: edu.get('exam', {}) returning a non-dict (e.g. a list) so .items() yields malformed k/v; EducationDetails called without a required argument because a .get() returned None where the field has no default.

Common situations: LLM-generated resumes where 'exam' is sometimes a list of objects instead of a {name: grade} map; schema drift adding new required fields.

Related errors

AI-assisted analysis of feder-cr/Jobs_Applier_AI_Agent_AIHawk@79155b52fa (2026-08-28). Data as JSON: /api/errors/df748265b13a9bbc. Report an issue: GitHub.