| import json, sys, os |
| sys.path.insert(0, os.path.abspath('.')) |
| from pathlib import Path |
|
|
| cases = json.loads(Path('eval/golden_cases.json').read_text(encoding='utf-8')) |
|
|
| from src.conversion import attach_conversion_scores, calc_pass_score, calc_risk_score, calc_growth_score |
|
|
| for case in cases: |
| if case.get('eval_split') != 'stress': |
| continue |
| from src.resume_parser import parse_resume |
| profile = parse_resume(case['resume_text']) |
| profile['_city'] = case.get('target_city', '') |
| profile['_stage'] = case.get('stage', '') |
| profile['_target_role'] = case.get('target_role', '') |
| |
| |
| from src.matcher import load_jobs |
| jobs = load_jobs(Path('data/jobs.json')) |
| if not jobs: |
| continue |
| job = jobs[0] |
| |
| ps = calc_pass_score(profile, job, case['resume_text']) |
| rs = calc_risk_score(profile, job, case['resume_text']) |
| gs = calc_growth_score(profile, job) |
| |
| print(case['case_id'] + ': pass=' + str(ps) + ' risk=' + str(rs) + ' growth=' + str(gs)) |
| print(' has_llm=' + str(profile.get('has_llm_project')) + ' has_metrics=' + str(profile.get('has_metrics')) + ' has_rec=' + str(profile.get('has_rec_project'))) |
| print() |
|
|
