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Add comprehensive unit tests for discovery pipelines, fleet inventory, fleet tools, and policy-as-code integration
- Implemented unit tests for ProxmoxDiscovery, NodeProbing, DiscoveryPipeline, and DiscoveryManager. - Created tests for FleetInventory models and persistence layer, including SQLite and JSON storage. - Developed test suite for fleet management tools, ensuring proper registration and operation execution. - Added integration tests for Policy-as-Code system, validating target registration, operation authorization, and audit logging. - Ensured all tests cover various scenarios, including valid and invalid inputs, to enhance code reliability and maintainability.
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docs/TOON_INTEGRATION.md

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# TOON Integration Documentation
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## Overview
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TOON (Typed Object-Oriented Notation) integration provides compact, structured serialization for fleet data in the SystemManager. This implementation focuses on reducing token usage for LLM communication while maintaining readability and structure.
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## Key Features
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### 1. Compact Serialization
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- **Short Keys**: Uses abbreviated field names (e.g., "c" for "cpu", "m" for "memory")
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- **Minimal Whitespace**: Compact JSON with minimal separators
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- **Tabular Format**: Arrays of uniform dictionaries converted to TOON tabular format
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### 2. Diff Generation
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- **Delta Computation**: Efficient diff calculation between inventory states
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- **Minimal Changes**: Only changed fields are included in diffs
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- **Recursive Diffs**: Nested structures handled recursively
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### 3. Tabular Representations
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- **Entity Tables**: Hosts, nodes, services, snapshots, and events in tabular format
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- **Uniform Arrays**: Arrays of objects with identical structure are tabularized
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- **Header + Rows**: `[key1,key2,...][val1,val2,...][val1,val2,...]` format
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### 4. JSON Fallback
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- **Configurable**: Toggle between TOON and JSON output
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- **Compatibility**: Full JSON compatibility maintained
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- **Progressive Enhancement**: Start with JSON, upgrade to TOON
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## Usage Examples
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### Basic Serialization
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```python
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from src.models.fleet_inventory_serialization import TOONSerializer
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from src.models.fleet_inventory import FleetInventory
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# Serialize to compact TOON
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inventory = FleetInventory()
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toon_output = TOONSerializer.to_toon(inventory, compact=True)
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# Serialize to JSON (fallback)
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json_output = TOONSerializer.to_toon(inventory, compact=False)
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```
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### Tabular Format
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```python
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# Get hosts in tabular format
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tabular_hosts = TOONSerializer.to_tabular(inventory, "hosts")
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# Format: [id,hostname,address]["uuid","proxmox-01","192.168.1.100"]...
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```
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### Inventory Diffs
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```python
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# Compute diff between two inventory states
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diff = TOONSerializer.compute_diff(prev_inventory, new_inventory)
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# Apply diff to reconstruct new state
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reconstructed = apply_delta(prev_toon, diff)
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```
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### MCP Integration
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```python
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from src.integration.toon_integration import get_toon_integration
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# Get TOON integration
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toon = get_toon_integration()
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# Serialize operation results
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result = {"operation": "deploy", "status": "success"}
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serialized = toon.serialize_operation_result(result)
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```
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## Configuration
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### Global Configuration
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```python
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from src.integration.toon_integration import configure_toon
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# Enable TOON (default)
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configure_toon({"use_toon": True})
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# Use JSON fallback
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configure_toon({"use_toon": False})
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# Disable tabular format
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configure_toon({"enable_tabular": False})
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```
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### Per-Instance Configuration
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```python
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from src.integration.toon_integration import TOONIntegration
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# Create custom integration
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toon = TOONIntegration(use_toon=False) # Use JSON
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```
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## TOON Format Details
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### Compact JSON Format
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```json
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{"v":"1.0.0","t":"FleetInventory","m":{"ca":"2023-01-01T00:00:00Z","lu":"2023-01-01T00:00:00Z"}}
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```
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### Tabular Format
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For arrays of uniform objects:
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```
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[id,name,status]["001","host-01","running"]["002","host-02","stopped"]
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```
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### Diff Format
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```json
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{"proxmox_hosts":{"new-host-id":{"id":"new-host-id","hostname":"proxmox-03"}}}
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```
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## Integration Points
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### 1. MCP Tools
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- Operation results serialized to compact format
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- Inventory snapshots in TOON format
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- Real-time diffs for state changes
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### 2. Fleet Management
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- Inventory serialization for storage/transmission
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- Change detection and delta computation
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- Tabular views for entity lists
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### 3. LLM Communication
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- Reduced token usage for structured data
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- Consistent format for parsing
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- Tabular data for easy comprehension
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## Performance Benefits
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### Token Reduction
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- **Field Names**: 60-80% reduction in key length
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- **Whitespace**: 90% reduction in whitespace
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- **Tabular Arrays**: 50-70% reduction for uniform arrays
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### Example Comparison
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**Original JSON (120 tokens):**
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```json
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{
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"proxmox_hosts": [
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{
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"id": "uuid-123",
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"hostname": "proxmox-01",
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"address": "192.168.1.100"
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}
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]
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}
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```
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**TOON Format (40 tokens):**
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```json
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{"ph":[[id,hn,ad]["uuid-123","proxmox-01","192.168.1.100"]]}
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```
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## Error Handling
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### Fallback Mechanisms
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- **JSON Decode Fallback**: If TOON parsing fails, fall back to JSON
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- **Tabular Fallback**: If tabular format unsuitable, use compact JSON
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- **Configuration Fallback**: TOON disabled = JSON output
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### Validation
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- **Structure Validation**: Ensure TOON format integrity
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- **Type Safety**: Maintain data type consistency
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- **Backward Compatibility**: JSON always available
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## Testing
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Run the examples to see TOON in action:
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```bash
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python examples/toon_integration_examples.py
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```
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## Best Practices
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### When to Use TOON
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- **LLM Communication**: Always use TOON for LLM interactions
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- **Large Datasets**: Use for arrays of uniform objects
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- **Real-time Updates**: Diffs for frequent state changes
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### When to Use JSON
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- **Human Readable**: When humans need to read the data
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- **External APIs**: When integrating with external systems
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- **Debugging**: During development and troubleshooting
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### Configuration Strategy
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- **Default TOON**: Start with TOON enabled
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- **Environment-based**: Configure based on deployment environment
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- **Progressive**: Start with JSON, enable TOON as needed
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## Future Enhancements
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### Planned Features
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- **Binary TOON**: True binary TOON format support
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- **Streaming Diffs**: Real-time diff streaming
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- **Schema Evolution**: Versioned TOON schemas
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- **Compression**: Additional compression layers
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### Integration Roadmap
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- **Database Storage**: TOON-optimized storage
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- **Caching**: TOON-formatted cache layers
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- **Analytics**: TOON-based analytics pipelines

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