3897bcbf24
Some checks failed
CLI Tests / test-cli (push) Failing after 4s
Deploy to Testnet / deploy-testnet (push) Successful in 1m40s
Documentation Validation / validate-docs (push) Failing after 12s
Documentation Validation / validate-policies-strict (push) Successful in 4s
Integration Tests / test-service-integration (push) Successful in 2m42s
Package Tests / Python package - aitbc-agent-sdk (push) Failing after 34s
Package Tests / Python package - aitbc-core (push) Successful in 27s
Package Tests / Python package - aitbc-crypto (push) Successful in 13s
Package Tests / Python package - aitbc-sdk (push) Successful in 16s
Package Tests / JavaScript package - aitbc-sdk-js (push) Successful in 8s
Package Tests / JavaScript package - aitbc-token (push) Successful in 18s
Python Tests / test-python (push) Failing after 50s
Security Scanning / security-scan (push) Failing after 43s
Multi-Node Stress Testing / stress-test (push) Successful in 12s
Cross-Node Transaction Testing / transaction-test (push) Successful in 9s
- Created aitbc/_version.py with centralized version definition - Updated aitbc/__init__.py to import __version__ from _version module - Updated constants.py to use __version__ for PACKAGE_VERSION - Replaced print() calls with logger in decorators.py, events.py, queue_manager.py, and state.py - Added logger initialization using get_logger(__name__) in config.py, decorators.py, events.py, queue_manager.py, and state.py - Added cli/commands
Service Tests README
Test Structure
This directory contains tests for the modularized service components:
Advanced RL Tests (test_advanced_rl/)
test_agents.py- Tests for PPO, SAC, and RainbowDQN neural network agentstest_engine.py- Tests for the AdvancedReinforcementLearningEngine
Requirements:
- PyTorch (
torch) - Full AITBC environment with domain models
- pytest-asyncio for async tests
Certification Tests (test_certification/)
test_certification_system.py- Tests for CertificationSystemtest_partnership_manager.py- Tests for PartnershipManagertest_badge_system.py- Tests for BadgeSystem
Requirements:
- Full AITBC environment with domain models
- aitbc package for logging
- pytest-asyncio for async tests
Multi-Modal Fusion Tests (test_multi_modal_fusion/)
test_neural_modules.py- Tests for CrossModalAttention, MultiModalTransformer, AdaptiveModalityWeightingtest_fusion_engine.py- Tests for MultiModalFusionEngine
Requirements:
- PyTorch (
torch) - NumPy (
numpy) - Full AITBC environment with domain models
- pytest-asyncio for async tests
Running Tests
Prerequisites
Ensure you have the full AITBC environment set up with all dependencies:
cd /opt/aitbc
source venv/bin/activate # or use your preferred environment
Install additional dependencies
pip install torch pytest-asyncio
Run tests with proper PYTHONPATH
cd /opt/aitbc/apps/coordinator-api
PYTHONPATH=/opt/aitbc/apps/coordinator-api/src:/opt/aitbc python3 -m pytest tests/services/ -v
Run specific test suites
# Advanced RL tests (requires torch)
PYTHONPATH=/opt/aitbc/apps/coordinator-api/src:/opt/aitbc python3 -m pytest tests/services/test_advanced_rl/ -v
# Certification tests
PYTHONPATH=/opt/aitbc/apps/coordinator-api/src:/opt/aitbc python3 -m pytest tests/services/test_certification/ -v
# Multi-modal fusion tests (requires torch)
PYTHONPATH=/opt/aitbc/apps/coordinator-api/src:/opt/aitbc python3 -m pytest tests/services/test_multi_modal_fusion/ -v
Test Coverage
These tests were created as part of the service modularization effort (Phase 2-3 of the refactoring plan). They provide:
- Unit tests for neural network components (advanced_rl, multi_modal_fusion)
- Integration tests for certification, partnership, and badge systems
- Coverage of key methods and initialization logic
The tests use mocking where appropriate to isolate components and test individual functionality.
Current Status
- ✅ Test files created for all modularized components
- ✅ Test structure follows pytest best practices
- ⚠️ Tests require full AITBC environment to run (expected for integration tests)
- ⚠️ PyTorch-dependent tests require torch installation
Future Improvements
- Add CI/CD integration for automated test running
- Increase test coverage to 100% as per Phase 3 goals
- Add performance benchmarks for neural network components
- Add property-based tests where applicable