# Knowledge Graph create_entities Fix Summary
## Issue Resolution
**Original Problem**:
```
Neo.ClientError.Statement.TypeError: Property values can only be of primitive types or arrays thereof.
Encountered: Map{content -> String("...")}.
```
**Root Cause**:
The `create_entities` method was receiving complex observation objects like `{"content": "text"}` and attempting to store them directly in Neo4j properties, which only accepts primitive types.
## Fixes Applied
### 1. Data Cleaning & Validation
```python
# Before (causing errors)
observations: [{"content": "Complex observation"}]
# After (automatically cleaned)
observations: ["Complex observation"] # Extracted from content field
```
### 2. Robust Type Conversion
The method now handles multiple input formats:
| Input Type | Output | Example |
|------------|--------|---------|
| Simple string | Unchanged | `"Simple obs"` → `"Simple obs"` |
| Complex object with content | Extract content | `{"content": "text"}` → `"text"` |
| Other objects | Convert to string | `{"name": "test"}` → `"{'name': 'test'}"` |
| Numbers/Booleans | Convert to string | `123` → `"123"`, `true` → `"True"` |
| None values | Skip | `null` → (ignored) |
### 3. Neo4j Query Optimization
Changed from:
```cypher
# OLD - Fails with empty arrays
UNWIND entity.observations AS obs
CREATE (o:Observation {content: obs, timestamp: datetime()})
```
To:
```cypher
# NEW - Handles empty arrays gracefully
FOREACH (obs IN entity.observations |
CREATE (o:Observation {content: obs, timestamp: datetime()})
CREATE (e)-[:HAS_OBSERVATION]->(o)
)
```
### 4. Enhanced Documentation
- Clear parameter format examples
- Explicit guidance on observation structure
- Migration notes for complex data
## Test Results
✅ **All data cleaning tests passed:**
- Empty observations arrays
- Simple string observations
- Complex object observations (auto-cleaned)
- Mixed observation types (auto-cleaned)
- Objects without content key (converted to strings)
## Usage Examples
### ✅ Correct Usage (All these work now)
**Simple observations:**
```json
{
"entities": [
{
"name": "Deep Learning Models",
"entityType": "Technology",
"observations": ["Uses neural networks", "Requires large datasets"]
}
]
}
```
**Complex observations (auto-cleaned):**
```json
{
"entities": [
{
"name": "AI System",
"entityType": "Technology",
"observations": [
{"content": "Complex observation 1"},
{"content": "Complex observation 2"}
]
}
]
}
```
**Empty observations:**
```json
{
"entities": [
{
"name": "Future Concept",
"entityType": "Idea",
"observations": []
}
]
}
```
## Impact
1. **Eliminates Neo4j Type Errors**: No more "Map{content -> String(...)}" errors
2. **Backward Compatibility**: Existing simple string observations continue to work
3. **Forward Compatibility**: Complex observation objects are automatically cleaned
4. **Better User Experience**: Clear error messages and documentation
5. **AI-Friendly**: Automatic data cleaning reduces cognitive load for AI users
## Tool Updates
The Knowledge Graph incarnation now provides:
- `create_entities` (improved with data cleaning)
- `add_observations` (for complex multi-observation scenarios)
- `add_single_observation` (convenience method for simple cases)
Total tools: **10** (was 9, added convenience method)
## Verification
Run the test suite to verify fixes:
```bash
python test_data_cleaning.py # Tests cleaning logic
python test_kg_tools.py # Tests tool registration
python tool_summary.py # Shows all available tools
```
The fixes ensure reliable knowledge graph entity creation regardless of input data complexity.
