Resume Analysis MCP Server

""" Tests for resume analyzer functionality """ import json import pytest from unittest.mock import AsyncMock, patch from resume_mcp.resume_analyzer import ResumeAnalyzer # Sample resume text for testing SAMPLE_RESUME = """ John Doe Software Engineer email@example.com EDUCATION University of Technology, BS Computer Science, 2018-2022 EXPERIENCE Software Engineer, Tech Company, 2022-Present - Developed web applications using Python and JavaScript - Implemented machine learning algorithms SKILLS Python, JavaScript, Machine Learning, Git """ # Sample job description for testing SAMPLE_JOB = """ Software Engineer Position Requirements: - 2+ years of experience in web development - Python programming skills - Database knowledge """ @pytest.fixture def mock_agent(): """Create a mock ADK agent""" with patch("google.adk.agents.llm_agent.Agent") as MockAgent: mock_agent = AsyncMock() mock_response = AsyncMock() mock_response.text = json.dumps({ "personal_info": {"name": "John Doe"}, "skills": ["Python", "JavaScript", "Machine Learning", "Git"] }) mock_agent.generate_content.return_value = mock_response MockAgent.return_value = mock_agent yield mock_agent @pytest.mark.asyncio async def test_analyze_resume(mock_agent): """Test resume analysis functionality""" analyzer = ResumeAnalyzer() analyzer.agent = mock_agent result = await analyzer.analyze_resume(SAMPLE_RESUME) # Check that the agent was called with the right prompt mock_agent.generate_content.assert_called_once() # Check that the result has the expected structure assert "personal_info" in result assert "skills" in result assert "Python" in result["skills"] @pytest.mark.asyncio async def test_match_resume_to_job(mock_agent): """Test resume-job matching functionality""" analyzer = ResumeAnalyzer() analyzer.agent = mock_agent # Set up different response for this specific test mock_response = AsyncMock() mock_response.text = json.dumps({ "match_score": 85, "skill_match": { "score": 90, "matched_skills": ["Python"], "missing_skills": ["Database"] } }) mock_agent.generate_content.return_value = mock_response result = await analyzer.match_resume_to_job(SAMPLE_RESUME, SAMPLE_JOB) # Check that the agent was called mock_agent.generate_content.assert_called_once() # Check that the result has the expected structure assert "match_score" in result assert "skill_match" in result assert result["match_score"] == 85 @pytest.mark.asyncio async def test_rank_candidates(mock_agent): """Test candidate ranking functionality""" analyzer = ResumeAnalyzer() analyzer.agent = mock_agent # Set up different response for this specific test mock_response = AsyncMock() mock_response.text = json.dumps({ "rankings": [ {"id": "candidate1", "match_score": 85}, {"id": "candidate2", "match_score": 75} ] }) mock_agent.generate_content.return_value = mock_response resumes = [ {"id": "candidate1", "text": SAMPLE_RESUME}, {"id": "candidate2", "text": "Jane Doe\nDatabase Admin\n2 years experience"} ] result = await analyzer.rank_candidates(resumes, SAMPLE_JOB) # Check that the agent was called mock_agent.generate_content.assert_called_once() # Check that the result has the expected structure assert len(result) == 2 assert result[0]["id"] == "candidate1" assert result[0]["match_score"] == 85