"""
Unit tests for ATS Resume tools (LLMKeywordMatcher and LLMResumeOptimizer).
These tests verify the core functionality without requiring actual LLM API calls.
Compatible with both main branch (EvalDetail) and dev branch (ModelRes).
"""
import json
import pytest
from dingo.io.input import Data
from dingo.model.llm.llm_keyword_matcher import SYNONYM_MAP, LLMKeywordMatcher
from dingo.model.llm.llm_resume_optimizer import LLMResumeOptimizer
def _has_error(result) -> bool:
"""Check if result indicates an error (compatible with both branches)."""
# EvalDetail uses 'status', ModelRes uses 'error_status'
if hasattr(result, 'error_status'):
return result.error_status is True
if hasattr(result, 'status'):
return result.status is True
return False
def _create_data_with_context(data_id: str, content: str, prompt: str, context: str):
"""Create Data object with context if supported, otherwise without."""
try:
return Data(data_id=data_id, content=content, prompt=prompt, context=context)
except TypeError:
# Main branch Data doesn't have context field
return None
class TestLLMKeywordMatcher:
"""Tests for LLMKeywordMatcher."""
def test_build_messages_basic(self):
"""Test basic message building."""
data = Data(
data_id='test_1',
content='Python developer with 5 years experience',
prompt='Senior Python Developer required'
)
messages = LLMKeywordMatcher.build_messages(data)
assert len(messages) == 1
assert messages[0]['role'] == 'user'
assert 'Python developer' in messages[0]['content']
assert 'Senior Python Developer' in messages[0]['content']
def test_build_messages_chinese(self):
"""Test Chinese content detection - uses English prompt for JD analysis."""
data = Data(
data_id='test_2',
content='我是一名Python开发工程师，有5年工作经验',
prompt='高级Python开发工程师'
)
messages = LLMKeywordMatcher.build_messages(data)
assert len(messages) == 1
# KeywordMatcher always uses English prompt (JD analysis is language-agnostic)
assert 'ATS' in messages[0]['content']
assert '高级Python开发工程师' in messages[0]['content']
def test_synonym_map(self):
"""Test synonym normalization map exists."""
assert 'k8s' in SYNONYM_MAP
assert SYNONYM_MAP['k8s'] == 'Kubernetes'
assert 'js' in SYNONYM_MAP
assert SYNONYM_MAP['js'] == 'JavaScript'
def test_calculate_match_score(self):
"""Test match score calculation."""
keyword_analysis = [
{'keyword': 'Python', 'importance': 'required', 'match_status': 'matched'},
{'keyword': 'Docker', 'importance': 'required', 'match_status': 'missing'},
{'keyword': 'AWS', 'importance': 'nice-to-have', 'match_status': 'matched'},
]
score = LLMKeywordMatcher._calculate_match_score(keyword_analysis)
# Score should be between 0 and 1
assert 0 <= score <= 1
# With 1/2 required matched and 1/1 nice-to-have matched
# Actual calculation may vary based on weights, just verify it's reasonable
assert 0.5 <= score <= 0.75
def test_eval_missing_content(self):
"""Test eval with missing content."""
data = Data(data_id='test_3', content='', prompt='Some JD')
result = LLMKeywordMatcher.eval(data)
assert _has_error(result)
def test_eval_missing_prompt(self):
"""Test eval with missing prompt (JD)."""
data = Data(data_id='test_4', content='Some resume', prompt='')
result = LLMKeywordMatcher.eval(data)
assert _has_error(result)
class TestLLMResumeOptimizer:
"""Tests for LLMResumeOptimizer."""
def test_build_messages_general_mode(self):
"""Test general mode (no context) - skip if Data doesn't support context."""
# On main branch, Data doesn't have context field, so we test differently
data = Data(
data_id='test_1',
content='Python developer resume',
prompt='Senior Python Developer'
)
# Set context via attribute if possible (for branches that support it)
if not hasattr(data, 'context'):
pytest.skip("Data class doesn't support context field (main branch)")
messages = LLMResumeOptimizer.build_messages(data)
assert len(messages) == 1
assert messages[0]['role'] == 'user'
# General mode should not have keyword injection instructions
assert 'P1 - Force Inject' not in messages[0]['content']
def test_build_messages_targeted_mode(self):
"""Test targeted mode (with context) - skip if Data doesn't support context."""
context = json.dumps({
'match_details': {
'missing': [{'skill': 'Docker', 'importance': 'Required'}],
'negative_warnings': []
}
})
data = _create_data_with_context(
data_id='test_2',
content='Python developer resume',
prompt='Senior Python Developer',
context=context
)
if data is None:
pytest.skip("Data class doesn't support context field (main branch)")
messages = LLMResumeOptimizer.build_messages(data)
assert len(messages) == 1
# Targeted mode should include Docker in the prompt
assert 'Docker' in messages[0]['content']
def test_detect_chinese(self):
"""Test Chinese language detection."""
assert LLMResumeOptimizer._detect_chinese('我是一名开发者') is True
assert LLMResumeOptimizer._detect_chinese('I am a developer') is False
assert LLMResumeOptimizer._detect_chinese('') is False
def test_parse_match_report_plugin_format(self):
"""Test parsing Plugin format match report."""
report = {
'match_details': {
'missing': [
{'skill': 'Docker', 'importance': 'Required'},
{'skill': 'AWS', 'importance': 'Nice-to-have'}
],
'negative_warnings': [{'skill': 'PHP'}]
}
}
missing_req, missing_nice, negative, is_targeted = \
LLMResumeOptimizer._parse_match_report(report)
assert 'Docker' in missing_req
assert 'AWS' in missing_nice
assert 'PHP' in negative
assert is_targeted is True
def test_parse_match_report_list_format(self):
"""Test parsing list format match report."""
report = ['Python', 'Docker', 'Kubernetes']
missing_req, missing_nice, negative, is_targeted = \
LLMResumeOptimizer._parse_match_report(report)
assert missing_req == ['Python', 'Docker', 'Kubernetes']
assert is_targeted is True
def test_parse_match_report_empty(self):
"""Test parsing empty match report."""
missing_req, missing_nice, negative, is_targeted = \
LLMResumeOptimizer._parse_match_report('')
assert missing_req == []
assert is_targeted is False
def test_eval_missing_content(self):
"""Test eval with missing content."""
data = Data(data_id='test_3', content='', prompt='Some position')
result = LLMResumeOptimizer.eval(data)
assert _has_error(result)
if __name__ == '__main__':
pytest.main([__file__, '-v'])
