Atomizer/docs/08_ARCHIVE/sessions/Phase_1_2_Implementation_Plan.md

Phase 1.2: Configuration Management Overhaul - Implementation Plan

Status: In Progress Started: January 2025 Target Completion: 2 days

---

✅ Completed (January 24, 2025)

1. Configuration Inventory

• Found 4 optimization_config.json files
• Found 5 workflow_config.json files
• Analyzed bracket_V3 (old format) vs drone_gimbal (new format)

2. Schema Analysis

Documented critical inconsistencies:

• Objectives: "goal" (new) vs "type" (old)
• Design vars: "parameter" + "bounds": [min, max] (new) vs "name" + "min"/"max" (old)
• Constraints: "threshold" (new) vs "value" (old)
• Location: 1_setup/ (correct) vs root directory (incorrect)

3. JSON Schema Design

Created optimization_engine/schemas/optimization_config_schema.json:

• Based on drone_gimbal format (cleaner, matches create-study skill)
• Validates all required fields
• Supports Protocol 10 (single-objective) and Protocol 11 (multi-objective)
• Includes extraction spec validation

---

🔨 Remaining Implementation Tasks

Task 1: Implement ConfigManager Class

Priority: HIGH File: optimization_engine/config_manager.py

"""Configuration validation and management for Atomizer studies."""

import json
from pathlib import Path
from typing import Dict, List, Any, Optional
import jsonschema

class ConfigValidationError(Exception):
    """Raised when configuration validation fails."""
    pass

class ConfigManager:
    """Manages and validates optimization configuration files."""

    def __init__(self, config_path: Path):
        """
        Initialize ConfigManager with path to optimization_config.json.

        Args:
            config_path: Path to optimization_config.json file
        """
        self.config_path = Path(config_path)
        self.schema_path = Path(__file__).parent / "schemas" / "optimization_config_schema.json"
        self.config: Optional[Dict[str, Any]] = None
        self.validation_errors: List[str] = []

    def load_schema(self) -> Dict[str, Any]:
        """Load JSON schema for validation."""
        with open(self.schema_path, 'r') as f:
            return json.load(f)

    def load_config(self) -> Dict[str, Any]:
        """Load configuration file."""
        if not self.config_path.exists():
            raise FileNotFoundError(f"Config file not found: {self.config_path}")

        with open(self.config_path, 'r') as f:
            self.config = json.load(f)
        return self.config

    def validate(self) -> bool:
        """
        Validate configuration against schema.

        Returns:
            True if valid, False otherwise
        """
        if self.config is None:
            self.load_config()

        schema = self.load_schema()
        self.validation_errors = []

        try:
            jsonschema.validate(instance=self.config, schema=schema)
            # Additional custom validations
            self._validate_design_variable_bounds()
            self._validate_multi_objective_consistency()
            self._validate_file_locations()
            return True
        except jsonschema.ValidationError as e:
            self.validation_errors.append(str(e))
            return False

    def _validate_design_variable_bounds(self):
        """Ensure bounds are valid (min < max)."""
        for dv in self.config.get("design_variables", []):
            bounds = dv.get("bounds", [])
            if len(bounds) == 2 and bounds[0] >= bounds[1]:
                self.validation_errors.append(
                    f"Design variable '{dv['parameter']}': min ({bounds[0]}) must be < max ({bounds[1]})"
                )

    def _validate_multi_objective_consistency(self):
        """Validate multi-objective settings consistency."""
        n_objectives = len(self.config.get("objectives", []))
        protocol = self.config.get("optimization_settings", {}).get("protocol")
        sampler = self.config.get("optimization_settings", {}).get("sampler")

        if n_objectives > 1:
            # Multi-objective must use protocol_11 and NSGA-II
            if protocol != "protocol_11_multi_objective":
                self.validation_errors.append(
                    f"Multi-objective optimization ({n_objectives} objectives) requires protocol_11_multi_objective"
                )
            if sampler != "NSGAIISampler":
                self.validation_errors.append(
                    f"Multi-objective optimization requires NSGAIISampler (got {sampler})"
                )

    def _validate_file_locations(self):
        """Check if config is in correct location (1_setup/)."""
        if "1_setup" not in str(self.config_path.parent):
            self.validation_errors.append(
                f"Config should be in '1_setup/' directory, found in {self.config_path.parent}"
            )

    def get_validation_report(self) -> str:
        """Get human-readable validation report."""
        if not self.validation_errors:
            return "✓ Configuration is valid"

        report = "✗ Configuration validation failed:\n"
        for i, error in enumerate(self.validation_errors, 1):
            report += f"  {i}. {error}\n"
        return report

    # Type-safe accessor methods

    def get_design_variables(self) -> List[Dict[str, Any]]:
        """Get design variables with validated structure."""
        if self.config is None:
            self.load_config()
        return self.config.get("design_variables", [])

    def get_objectives(self) -> List[Dict[str, Any]]:
        """Get objectives with validated structure."""
        if self.config is None:
            self.load_config()
        return self.config.get("objectives", [])

    def get_constraints(self) -> List[Dict[str, Any]]:
        """Get constraints with validated structure."""
        if self.config is None:
            self.load_config()
        return self.config.get("constraints", [])

    def get_simulation_settings(self) -> Dict[str, Any]:
        """Get simulation settings."""
        if self.config is None:
            self.load_config()
        return self.config.get("simulation", {})


# CLI tool for validation
if __name__ == "__main__":
    import sys

    if len(sys.argv) < 2:
        print("Usage: python config_manager.py <path_to_optimization_config.json>")
        sys.exit(1)

    config_path = Path(sys.argv[1])
    manager = ConfigManager(config_path)

    try:
        manager.load_config()
        is_valid = manager.validate()
        print(manager.get_validation_report())
        sys.exit(0 if is_valid else 1)
    except Exception as e:
        print(f"Error: {e}")
        sys.exit(1)

Dependencies: Add to requirements.txt:

jsonschema>=4.17.0

---

Task 2: Create Configuration Migration Tool

Priority: MEDIUM File: optimization_engine/config_migrator.py

Tool to automatically migrate old-format configs to new format:

• Convert "type" → "goal" in objectives
• Convert "min"/"max" → "bounds": [min, max] in design variables
• Convert "name" → "parameter" in design variables
• Convert "value" → "threshold" in constraints
• Move config files to 1_setup/ if in wrong location

---

Task 3: Integration with run_optimization.py

Priority: HIGH

Add validation to optimization runners:

# At start of run_optimization.py
from optimization_engine.config_manager import ConfigManager

# Load and validate config
config_manager = ConfigManager(Path(__file__).parent / "1_setup" / "optimization_config.json")
config_manager.load_config()

if not config_manager.validate():
    print(config_manager.get_validation_report())
    sys.exit(1)

print("✓ Configuration validated successfully")

---

Task 4: Update create-study Claude Skill

Priority: HIGH File: .claude/skills/create-study.md

Update skill to reference the JSON schema:

• Add link to schema documentation
• Emphasize validation after generation
• Include validation command in "Next Steps"

---

Task 5: Create Configuration Documentation

Priority: HIGH File: docs/CONFIGURATION_GUIDE.md

Comprehensive documentation covering:

1. Standard configuration format (with drone_gimbal example)
2. Field-by-field descriptions
3. Validation rules and how to run validation
4. Common validation errors and fixes
5. Migration guide for old configs
6. Protocol selection (10 vs 11)
7. Extractor mapping table

---

Task 6: Validate All Existing Studies

Priority: MEDIUM

Run validation on all existing studies:

# Test validation tool
python optimization_engine/config_manager.py studies/drone_gimbal_arm_optimization/1_setup/optimization_config.json
python optimization_engine/config_manager.py studies/bracket_stiffness_optimization_V3/optimization_config.json

# Expected: drone passes, bracket_V3 fails with specific errors

Create migration plan for failing configs.

---

Task 7: Migrate Legacy Configs

Priority: LOW (can defer to Phase 1.3)

Migrate all legacy configs to new format:

• bracket_stiffness_optimization_V3
• bracket_stiffness_optimization_V2
• bracket_stiffness_optimization

Keep old versions in archive/ for reference.

---

Success Criteria

Phase 1.2 is complete when:

• JSON schema created and comprehensive
• ConfigManager class implemented with all validation methods
• Validation integrated into at least 1 study (drone_gimbal)
• Configuration documentation written
• create-study skill updated with schema reference
• Migration tool created (basic version)
• All tests pass on drone_gimbal study
• Phase 1.2 changes committed with clear message

---

Testing Plan

1. Schema Validation Test:

   • Valid config passes ✓
   • Invalid configs fail with clear errors ✓

2. ConfigManager Test:

   • Load valid config
   • Validate and get clean report
   • Load invalid config
   • Validate and get error details

3. Integration Test:

   • Run drone_gimbal study with validation enabled
   • Verify no performance impact
   • Check validation messages appear correctly

4. Migration Test:

   • Migrate bracket_V3 config
   • Validate migrated config
   • Compare before/after

---

Next Phase Preview

Phase 1.3: Error Handling & Logging will build on this by:

• Adding structured logging with configuration context
• Error recovery using validated configurations
• Checkpoint system that validates config before saving

The clean configuration management from Phase 1.2 enables reliable error handling in Phase 1.3.