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https://github.com/semantica-agi/semantica.git
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KaifAhmad1
58707ff721
- Robust ID extraction in CentralityCalculator, CommunityDetector, and ConnectivityAnalyzer - Support for direct Entity objects and dictionaries as node identifiers - Improved Entity hashability in utils/types.py - Added integration test to verify fix and prevent regression
113 lines
4.0 KiB
Python
113 lines
4.0 KiB
Python
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import pytest
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from semantica.utils.types import Entity
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from semantica.kg.graph_builder import GraphBuilder
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from semantica.kg.entity_resolver import EntityResolver
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from semantica.kg.graph_analyzer import GraphAnalyzer
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def test_full_entity_pipeline():
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"""
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Tests the full pipeline using Entity objects:
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Builder -> Resolver -> Analyzer
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This specifically verifies the fix for 'unhashable type: Entity'
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and the robustness of ID extraction.
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"""
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# 1. Create Entity objects
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e1 = Entity(id="ent1", text="Entity 1", type="PERSON")
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e2 = Entity(id="ent2", text="Entity 2", type="ORG")
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e3 = Entity(id="ent3", text="Entity 3", type="LOCATION")
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# 2. Define relationships using Entity objects
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relationships = [
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{"source": e1, "target": e2, "type": "WORKS_AT"},
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{"source": e2, "target": e3, "type": "LOCATED_IN"},
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{"source": e1, "target": e3, "type": "LIVES_IN"}
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]
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# 3. Build the graph
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builder = GraphBuilder()
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# Provide both entities and relationships
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sources = {
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"entities": [e1, e2, e3],
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"relationships": relationships
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}
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graph_data = builder.build(sources=sources)
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# DEBUG: Print graph_data keys and entities count
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print(f"DEBUG: graph_data keys: {list(graph_data.keys())}")
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print(f"DEBUG: Entities count: {len(graph_data.get('entities', []))}")
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print(f"DEBUG: Relationships count: {len(graph_data.get('relationships', []))}")
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if graph_data.get('entities'):
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print(f"DEBUG: First entity: {graph_data['entities'][0]}")
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# Verify graph data contains the entities and normalized relationships
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assert len(graph_data["entities"]) >= 3
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assert len(graph_data["relationships"]) == 3
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# 4. Resolve entities
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resolver = EntityResolver()
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resolved_entities = resolver.resolve_entities(graph_data["entities"])
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resolved_graph = {
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"entities": resolved_entities,
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"relationships": graph_data["relationships"]
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}
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# 5. Analyze the graph
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# This is where the 'unhashable type: Entity' usually occurred
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analyzer = GraphAnalyzer()
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analysis_results = analyzer.analyze(resolved_graph)
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# Verify analysis results
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assert "centrality" in analysis_results
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assert "communities" in analysis_results
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assert "connectivity" in analysis_results
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# Verify specific metrics are present
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centrality = analysis_results["centrality"]
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assert "centrality_measures" in centrality
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# It seems by default it might only calculate degree
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assert "degree" in centrality["centrality_measures"]
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# Verify connectivity
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connectivity = analysis_results["connectivity"]
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assert "is_connected" in connectivity
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assert connectivity["is_connected"] is True
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assert connectivity["num_components"] == 1
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print("Full pipeline test passed successfully!")
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def test_direct_entity_objects_in_analyzer():
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"""
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Specifically tests the fix for 'unhashable type: Entity' when
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Entity objects are directly passed in the relationships to GraphAnalyzer.
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This simulates the scenario reported by users where the graph
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contains Entity objects instead of IDs.
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"""
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# 1. Create Entity objects
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e1 = Entity(id="ent1", text="Entity 1", type="PERSON")
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e2 = Entity(id="ent2", text="Entity 2", type="ORG")
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# 2. Define relationships directly using Entity objects
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# In some scenarios, the user might pass objects instead of strings
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graph = {
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"entities": [e1, e2],
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"relationships": [
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{"source": e1, "target": e2, "type": "CONNECTED_TO"}
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]
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}
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# 3. Analyze the graph
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analyzer = GraphAnalyzer()
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# This should not raise TypeError: unhashable type: 'Entity'
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analysis_results = analyzer.analyze(graph)
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assert "centrality" in analysis_results
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assert "metrics" in analysis_results
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print("Direct Entity objects test passed successfully!")
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if __name__ == "__main__":
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test_full_entity_pipeline()
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test_direct_entity_objects_in_analyzer()
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