ai-hackaton-backend/TESTING_GUIDE.md

🧪 HR-AI Backend Testing Guide

✅ System Status

Core Components: All PASS ✅

• ✅ Database (PostgreSQL) - Connected, 1 resume found
• ✅ RAG System (OpenAI) - Resume parsing works
• ✅ Redis - Connected for Celery tasks
• ✅ Interview Service - Token generation works
• ✅ AI Agent - Initialization and plan handling works

🚀 Quick Start Testing (Without Voice)

1. Start the Services

# Terminal 1: Start FastAPI server
uvicorn app.main:app --reload --port 8000

# Terminal 2: Start Celery worker  
celery -A celery_worker.celery_app worker --loglevel=info

# Terminal 3: Monitor system
python simple_test.py

2. Test Resume Upload & Processing

# Create test resume file
echo "John Doe
Python Developer
Experience: 3 years
Skills: Python, Django, FastAPI, PostgreSQL
Education: Computer Science
Email: john@example.com
Phone: +1234567890" > test_resume.txt

# Upload via API
curl -X POST "http://localhost:8000/resume/upload" \
  -H "Content-Type: multipart/form-data" \
  -F "file=@test_resume.txt" \
  -F "applicant_name=John Doe" \
  -F "applicant_email=john@example.com" \
  -F "applicant_phone=+1234567890" \
  -F "vacancy_id=1"

3. Check Processing Results

# Check resume in database
curl http://localhost:8000/resume/1

# Check interview plan generation
# Should see interview_plan field with structured questions

4. Test Interview Session Creation

# Create interview session
curl -X POST "http://localhost:8000/interview/1/start" \
  -H "Content-Type: application/json"

🎤 Full Voice Testing (Requires Additional Setup)

Prerequisites for Voice Testing

1. LiveKit Server

# Download LiveKit server
docker run --rm -p 7880:7880 -p 7881:7881 \
  livekit/livekit-server --dev

2. Voice API Keys (Optional - has fallbacks)

Add to your .env file:

# For better STT (Speech-to-Text)
DEEPGRAM_API_KEY=your-deepgram-key

# For better TTS (Text-to-Speech)  
CARTESIA_API_KEY=your-cartesia-key
# OR
ELEVENLABS_API_KEY=your-elevenlabs-key

Voice Interview Testing

1. Start Complete Stack

# All previous services PLUS:
# Terminal 4: LiveKit server (see above)

2. Create Voice Interview Session

# This will start AI agent subprocess
curl -X POST "http://localhost:8000/interview/1/token"

3. Monitor AI Processes

# Check running AI agents
curl http://localhost:8000/admin/interview-processes

# System stats
curl http://localhost:8000/admin/system-stats

📊 Monitoring & Debugging

1. Check System Health

python simple_test.py

2. Monitor Celery Tasks

• Open Celery worker terminal
• Should see task processing logs

3. Database Inspection

-- Check resumes
SELECT id, applicant_name, status, interview_plan IS NOT NULL as has_plan 
FROM resume;

-- Check interview sessions  
SELECT id, room_name, status, ai_agent_pid, ai_agent_status
FROM interview_sessions;

4. Process Management

# List active AI processes
curl http://localhost:8000/admin/interview-processes

# Stop specific process
curl -X POST http://localhost:8000/admin/interview-processes/1/stop

# Cleanup dead processes
curl -X POST http://localhost:8000/admin/interview-processes/cleanup

🔧 Troubleshooting

Common Issues

1. "Database connection error"

• Check PostgreSQL is running
• Verify DATABASE_URL in config
• Run: alembic upgrade head

2. "RAG system error"

• Check OPENAI_API_KEY is set
• Verify internet connection

3. "Redis connection error"

docker run -d -p 6379:6379 redis:alpine

4. "Import errors"

• Make sure you're in project root directory
• Check virtual environment is activated

5. "Celery tasks not processing"

• Ensure Redis is running
• Check Celery worker logs
• Restart Celery worker

Performance Testing

Test Multiple Concurrent Interviews:

# Create 5 interview sessions simultaneously
for i in {1..5}; do
  curl -X POST "http://localhost:8000/interview/$i/token" &
done
wait

# Monitor system resources
curl http://localhost:8000/admin/system-stats

🧪 Test Scenarios

Scenario 1: Basic Resume Processing

1. Upload resume → Check parsing
2. Verify interview plan generation
3. Confirm data in database

Scenario 2: Interview Session Lifecycle

1. Create session → Get token
2. Start AI agent → Monitor process
3. Stop session → Verify cleanup

Scenario 3: Multi-User Load Test

1. Upload 10 resumes simultaneously
2. Create 5 interview sessions
3. Monitor system resources
4. Check process management

Scenario 4: Error Recovery

1. Stop Redis → Resume upload should queue
2. Start Redis → Tasks should process
3. Kill AI process → Should be detected and cleaned

📈 Expected Performance

Single Interview:

• Memory: ~45MB per AI agent process
• CPU: ~5-15% during active conversation
• Startup: ~3-5 seconds per agent

System Limits:

• Recommended max: 50 concurrent interviews
• Theoretical max: ~150 interviews (on 32GB RAM)

🎯 Success Criteria

✅ Basic Functionality:

• Resume upload and parsing works
• Interview plans are generated
• Database stores all data correctly
• Celery processes tasks

✅ Interview System:

• Interview sessions can be created
• AI agent processes start successfully
• Tokens are generated correctly
• Process monitoring works

✅ Advanced Features:

• Multiple concurrent interviews
• Process cleanup works
• System monitoring provides accurate data
• Error recovery works correctly

✅ Voice Testing (Optional):

• LiveKit connection established
• STT/TTS services work (if configured)
• Real-time conversation flows
• Session termination works properly

📝 Test Results Log

Keep track of your testing:

Date: ___________
System Test: PASS/FAIL
Resume Upload: PASS/FAIL  
Interview Creation: PASS/FAIL
AI Agent Start: PASS/FAIL
Voice Test: PASS/FAIL (if attempted)

Notes:
_________________________________
_________________________________

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🎉 Ready to Test!

Start with the Quick Start Testing section above. The system is ready for basic testing without voice features. For full voice testing, set up LiveKit server and optionally add voice API keys.

Good luck! 🚀