Add unified interface for echo9ml.py - implement module-level create_deep_tree_echo function

DEEP_TREE_ECHO_CATALOG.md

@@ -44,9 +44,10 @@ Comprehensive catalog of all Deep Tree Echo fragments, their relationships, and
 #### 4. **Echo9ML System** - `echo9ml.py`
 - **Class**: `Echo9mlSystem`
 - **Purpose**: Machine learning persona evolution
-- **Features**: Tensor-based encoding, hypergraph memory
-- **Size**: ~533+ lines
-- **Integration**: Complementary to Deep Tree Echo
+- **Features**: Tensor-based encoding, hypergraph memory, unified API
+- **Size**: 791 lines
+- **Functions**: `create_echo9ml_system()`, `create_deep_tree_echo()`
+- **Integration**: Complementary to Deep Tree Echo with standardized interface
 
 #### 5. **Echo Evolution** - `echo_evolution.py`
 - **Class**: `EchoAgent`

ECHO9ML_README.md

@@ -45,7 +45,19 @@ Shape: (3, 7, 13, 5, 2)
 
 ## Usage
 
-### Basic Usage
+### Quick Start
+
+```python
+from echo9ml import create_echo9ml_system, create_deep_tree_echo
+
+# Create a complete Echo9ml system
+system = create_echo9ml_system()
+
+# Or create just the persona kernel
+persona = create_deep_tree_echo()
+```
+
+### Basic System Usage
 
 ```python
 from echo9ml import create_echo9ml_system
@@ -66,6 +78,20 @@ result = system.process_experience(experience)
 print(f"Confidence: {result['persona_state']['confidence']:.3f}")
 ```
 
+### Direct Persona Creation
+
+```python
+from echo9ml import create_deep_tree_echo, PersonaTraitType
+
+# Create Deep Tree Echo persona kernel
+persona = create_deep_tree_echo()
+
+# Inspect persona traits
+print(f"Persona: {persona.name}")
+for trait, value in persona.traits.items():
+    print(f"  {trait.value}: {value:.2f}")
+```
+
 ### Integration with Cognitive Architecture
 
 ```python
@@ -127,12 +153,25 @@ for trait, value in snapshot['persona_kernel']['traits'].items():
 
 ## API Reference
 
+### Factory Functions
+
+```python
+# Create complete Echo9ml system
+system = create_echo9ml_system(save_path="/path/to/save")
+
+# Create Deep Tree Echo persona kernel
+persona = create_deep_tree_echo()
+```
+
 ### PersonaKernel
 
 ```python
-# Create Deep Tree Echo persona
+# Create Deep Tree Echo persona (class method)
 persona = PersonaKernel.create_deep_tree_echo()
 
+# Or use module-level function (recommended)
+persona = create_deep_tree_echo()
+
 # Access traits
 creativity = persona.traits[PersonaTraitType.CANOPY]
 

echo9ml.py

@@ -768,14 +768,25 @@ def load_state(self):
 
         return False
 
-# Convenience function for easy instantiation
+# Convenience functions for easy instantiation
 def create_echo9ml_system(save_path: Optional[str] = None) -> Echo9mlSystem:
     """Create and initialize a new Echo9ml system"""
     return Echo9mlSystem(save_path)
 
+def create_deep_tree_echo() -> PersonaKernel:
+    """Create a Deep Tree Echo persona kernel
+
+    Module-level convenience function for creating the default Deep Tree Echo
+    persona kernel. Provides unified API for integration with other components.
+
+    Returns:
+        PersonaKernel: Initialized Deep Tree Echo persona kernel
+    """
+    return PersonaKernel.create_deep_tree_echo()
+
 # Export main classes for integration
 __all__ = [
     'PersonaKernel', 'TensorPersonaEncoding', 'HypergraphPersonaEncoder',
     'AttentionAllocationLayer', 'EvolutionEngine', 'MetaCognitiveEnhancer',
-    'Echo9mlSystem', 'PersonaTraitType', 'create_echo9ml_system'
+    'Echo9mlSystem', 'PersonaTraitType', 'create_echo9ml_system', 'create_deep_tree_echo'
 ]

test_echo9ml.py

@@ -17,7 +17,7 @@
 from echo9ml import (
     PersonaKernel, TensorPersonaEncoding, HypergraphPersonaEncoder,
     AttentionAllocationLayer, EvolutionEngine, MetaCognitiveEnhancer,
-    Echo9mlSystem, PersonaTraitType, create_echo9ml_system
+    Echo9mlSystem, PersonaTraitType, create_echo9ml_system, create_deep_tree_echo
 )
 
 class TestPersonaKernel(unittest.TestCase):
@@ -50,6 +50,21 @@ def test_persona_initialization(self):
         self.assertIsInstance(self.persona.evolution, dict)
         self.assertIn("adaptation_rate", self.persona.evolution)
         self.assertGreater(self.persona.creation_time, 0)
+
+    def test_module_level_create_function(self):
+        """Test module-level create_deep_tree_echo function"""
+        # Test that module-level function works
+        module_persona = create_deep_tree_echo()
+
+        # Should be same type and structure as class method
+        self.assertIsInstance(module_persona, PersonaKernel)
+        self.assertEqual(module_persona.name, "Deep Tree Echo")
+        self.assertEqual(len(module_persona.traits), 7)
+
+        # Should have same trait values as class method
+        class_persona = PersonaKernel.create_deep_tree_echo()
+        self.assertEqual(module_persona.traits, class_persona.traits)
+        self.assertEqual(module_persona.trait_connections, class_persona.trait_connections)
 
 class TestTensorPersonaEncoding(unittest.TestCase):
     """Test tensor encoding functionality"""