| 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.resume_parser import parse_resume |
| from src.matcher import rank_jobs |
| from src.strategy_planner import gen_strategy_package |
|
|
| for case in cases: |
| if case.get('eval_split') != 'stress': |
| continue |
| print('=== ' + case['case_id'] + ' ===') |
| print(' expected_action: ' + str(case.get('expected_action'))) |
| |
| profile = parse_resume(case['resume_text']) |
| profile['_city'] = case.get('target_city', '') |
| profile['_stage'] = case.get('stage', '') |
| profile['_target_role'] = case.get('target_role', '') |
| |
| print(' has_llm_project: ' + str(profile.get('has_llm_project'))) |
| print(' has_metrics: ' + str(profile.get('has_metrics'))) |
| print(' has_rec_project: ' + str(profile.get('has_rec_project'))) |
| |
| scored = rank_jobs( |
| resume_text=case['resume_text'], |
| profile=profile, |
| target_role=case.get('target_role', ''), |
| target_city=case.get('target_city', ''), |
| stage=case.get('stage', ''), |
| top_k=8, |
| jobs_path=Path('data/jobs.json') |
| ) |
| |
| pkg = gen_strategy_package(scored, profile) |
| top3 = pkg.get('priority_top3', []) |
| for i, t in enumerate(top3): |
| print(' Top' + str(i+1) + ': ' + t['title'] + ' | action=' + t['apply_action'] + ' | pass=' + str(t.get('pass_score')) + ' | risk=' + str(t.get('risk_score')) + ' | growth=' + str(t.get('growth_score'))) |
| |
| actual = top3[0]['apply_action'] if top3 else '?' |
| exp = case.get('expected_action', '') |
| match_str = 'OK' if actual == exp else 'MISMATCH' |
| print(' RESULT: actual=' + actual + ', expected=' + exp + ' => ' + match_str) |
| print() |
|
|
