193 lines
6.6 KiB
Markdown
193 lines
6.6 KiB
Markdown
# Issue #53 Implementation Summary
|
|
|
|
## Overview
|
|
Successfully implemented UAT and evaluation tests for agent outputs with comprehensive validation utilities.
|
|
|
|
## Implementation Details
|
|
|
|
### Phase 1: Output Validation Utilities
|
|
**File**: `/Users/andrewkaszubski/Dev/Spektiv/spektiv/utils/output_validator.py`
|
|
|
|
Created validation utilities with:
|
|
- `ValidationResult` dataclass with actionable feedback (errors, warnings, metrics)
|
|
- `validate_report_completeness()` - validates report length, markdown structure, sections
|
|
- `validate_decision_quality()` - extracts BUY/SELL/HOLD signals, checks reasoning
|
|
- `validate_debate_state()` - validates debate history, count, judge decisions
|
|
- `validate_agent_state()` - orchestrates all validators for complete state validation
|
|
|
|
**Key Features**:
|
|
- Regex-based signal extraction (case-insensitive BUY/SELL/HOLD)
|
|
- Markdown structure detection (tables, headers, bullet points)
|
|
- Detailed metrics tracking (length, counts, signals)
|
|
- Warnings vs Errors distinction (actionable feedback)
|
|
- Support for both InvestDebateState and RiskDebateState
|
|
|
|
### Phase 2: Unit Tests
|
|
**File**: `/Users/andrewkaszubski/Dev/Spektiv/tests/unit/test_output_validators.py`
|
|
|
|
Created 54 unit tests organized into 5 test classes:
|
|
1. `TestValidationResult` (5 tests) - dataclass behavior
|
|
2. `TestReportValidation` (12 tests) - report completeness checks
|
|
3. `TestDecisionValidation` (12 tests) - signal extraction and quality
|
|
4. `TestDebateStateValidation` (13 tests) - debate state coherence
|
|
5. `TestAgentStateValidation` (12 tests) - complete state validation
|
|
|
|
**Coverage**:
|
|
- All validation functions thoroughly tested
|
|
- Edge cases covered (None, empty, wrong types)
|
|
- Quality indicators validated (markdown, reasoning, structure)
|
|
- All tests pass ✓
|
|
|
|
### Phase 3: E2E UAT Tests
|
|
**File**: `/Users/andrewkaszubski/Dev/Spektiv/tests/e2e/test_uat_agent_outputs.py`
|
|
|
|
Created 23 E2E tests organized into 4 test classes:
|
|
1. `TestCompleteAnalysisWorkflow` (5 tests) - BUY/SELL/HOLD scenarios
|
|
2. `TestEdgeCaseScenarios` (6 tests) - missing data, conflicts, malformed input
|
|
3. `TestContentQuality` (6 tests) - report structure, decision clarity
|
|
4. `TestStateIntegrity` (6 tests) - field presence, type consistency
|
|
|
|
**Scenarios Tested**:
|
|
- Complete workflows (BUY, SELL, HOLD)
|
|
- Graceful degradation (missing reports)
|
|
- Conflicting signals handling
|
|
- Long debate detection
|
|
- Malformed decision extraction
|
|
- All tests pass ✓
|
|
|
|
### Phase 4: Test Fixtures
|
|
**File**: `/Users/andrewkaszubski/Dev/Spektiv/tests/conftest.py`
|
|
|
|
Added 6 new fixtures for agent output testing:
|
|
1. `sample_agent_state` - Complete state with all fields (BUY scenario)
|
|
2. `sample_agent_state_buy` - Alias for BUY scenario
|
|
3. `sample_agent_state_sell` - Complete SELL scenario
|
|
4. `sample_agent_state_hold` - Complete HOLD scenario
|
|
5. `sample_invest_debate` - Investment debate state fixture
|
|
6. `sample_risk_debate` - Risk debate state fixture
|
|
|
|
**Fixture Quality**:
|
|
- Realistic data (proper report lengths >500 chars)
|
|
- Complete state coverage (all required fields)
|
|
- Multiple scenarios (BUY/SELL/HOLD)
|
|
- Well-documented with docstrings
|
|
|
|
## Test Results
|
|
|
|
### Unit Tests
|
|
```
|
|
54 passed in 0.08s
|
|
```
|
|
|
|
All unit tests pass, covering:
|
|
- ValidationResult dataclass
|
|
- Report completeness validation
|
|
- Decision quality validation
|
|
- Debate state validation
|
|
- Agent state validation
|
|
|
|
### E2E UAT Tests
|
|
```
|
|
23 passed in 0.11s
|
|
```
|
|
|
|
All E2E tests pass, covering:
|
|
- Complete analysis workflows
|
|
- Edge case handling
|
|
- Content quality validation
|
|
- State integrity checks
|
|
|
|
### Total Test Coverage
|
|
```
|
|
77 tests passed in 0.09s
|
|
```
|
|
|
|
## Key Design Decisions
|
|
|
|
1. **ValidationResult Pattern**: Used dataclass with separate errors/warnings/metrics for actionable feedback
|
|
2. **Whitespace-Tolerant Regex**: Section header detection allows leading whitespace (`^\s*#{1,6}`)
|
|
3. **Reasoning Detection**: Multiple indicators (colons, periods, word count ≥5)
|
|
4. **Debate Type Enum**: Supports both "invest" and "risk" debate types
|
|
5. **Metrics Collection**: All validators return metrics for monitoring/analysis
|
|
|
|
## Benefits
|
|
|
|
1. **Automated Quality Checks**: Validates agent output quality without manual review
|
|
2. **Actionable Feedback**: Clear errors vs warnings guide improvements
|
|
3. **Comprehensive Coverage**: All agent output types validated
|
|
4. **Edge Case Handling**: Robust validation for malformed/incomplete data
|
|
5. **Extensible Design**: Easy to add new validation rules
|
|
|
|
## Files Created/Modified
|
|
|
|
### Created
|
|
- `/Users/andrewkaszubski/Dev/Spektiv/spektiv/utils/output_validator.py` (454 lines)
|
|
- `/Users/andrewkaszubski/Dev/Spektiv/tests/unit/test_output_validators.py` (599 lines)
|
|
- `/Users/andrewkaszubski/Dev/Spektiv/tests/e2e/test_uat_agent_outputs.py` (553 lines)
|
|
|
|
### Modified
|
|
- `/Users/andrewkaszubski/Dev/Spektiv/tests/conftest.py` (added 268 lines for fixtures)
|
|
|
|
### Total Lines Added
|
|
- **1,874 lines** of production code and tests
|
|
|
|
## Usage Examples
|
|
|
|
### Validate Complete Agent State
|
|
```python
|
|
from spektiv.utils.output_validator import validate_agent_state
|
|
|
|
result = validate_agent_state(state)
|
|
|
|
if result.is_valid:
|
|
print(f"State valid! Signal: {result.metrics['final_signal']}")
|
|
else:
|
|
print(f"Errors: {result.errors}")
|
|
print(f"Warnings: {result.warnings}")
|
|
```
|
|
|
|
### Validate Individual Reports
|
|
```python
|
|
from spektiv.utils.output_validator import validate_report_completeness
|
|
|
|
result = validate_report_completeness(
|
|
report,
|
|
min_length=500,
|
|
require_markdown_tables=True,
|
|
require_sections=True
|
|
)
|
|
|
|
print(f"Report length: {result.metrics['length']}")
|
|
print(f"Tables: {result.metrics['markdown_tables']}")
|
|
print(f"Headers: {result.metrics['section_headers']}")
|
|
```
|
|
|
|
### Extract Trading Signals
|
|
```python
|
|
from spektiv.utils.output_validator import validate_decision_quality
|
|
|
|
result = validate_decision_quality("BUY: Strong fundamentals")
|
|
|
|
print(f"Signal: {result.metrics['signal']}") # "BUY"
|
|
print(f"Has reasoning: {result.metrics['has_reasoning']}") # True
|
|
```
|
|
|
|
## Next Steps
|
|
|
|
1. **Integration**: Integrate validators into agent execution pipeline
|
|
2. **Monitoring**: Add metrics collection to track output quality over time
|
|
3. **Thresholds**: Define quality thresholds for production deployment
|
|
4. **CI/CD**: Add UAT tests to continuous integration pipeline
|
|
5. **Documentation**: Update user documentation with validation guidelines
|
|
|
|
## Conclusion
|
|
|
|
Successfully implemented comprehensive UAT and evaluation framework for agent outputs:
|
|
- ✓ 4 validation functions with detailed metrics
|
|
- ✓ 54 unit tests (100% passing)
|
|
- ✓ 23 E2E UAT tests (100% passing)
|
|
- ✓ 6 reusable test fixtures
|
|
- ✓ 1,874 lines of production-quality code
|
|
|
|
All tests pass and provide actionable feedback for agent output quality validation.
|