mirror of
https://github.com/semantica-agi/semantica.git
synced 2026-08-29 04:26:20 +00:00
KaifAhmad1
dd016744ce
- ContextGraph.get_neighbors() gains include_distance_metadata flag (backward-compat)
- get_neighbor_distances() returns neighbors sorted by hop and confidence decay
- AgentContext.retrieve/find_precedents support proximity-weighted blending
- FR-4: path enrichment (decay, similarity, coherence, bottleneck, interpretation)
- FR-6: POST /api/graph/distance-matrix (hops/weighted/semantic, upper-triangle)
- FR-3: GET /api/graph/node/{id}/semantic-neighborhood
- FR-8: GET /api/decisions/causal-distance (causal-edge-only BFS)
- FR-9: GET /api/temporal/distance-history (convergence/divergence events)
- FR-10: POST /api/export/distance-enriched (CSV/JSONL, 200-node cap)
- Explorer: PathDistanceIntelPanel, Ego Mode, Structural/Semantic overlay, Heatmap
- Fix 13 Qodo review issues: API param mismatch, O(E*L) decay, breaking change,
schema key inconsistency, datetime arithmetic, id overwrite, sweep race,
node_subset DoS, full-matrix redundancy, effect race, silent exceptions, duplication
- 57 new tests in test_distance_intelligence.py; 18 regression tests in _smoke_review_fixes.py
98 lines
3.3 KiB
Python
98 lines
3.3 KiB
Python
from semantica.context.context_graph import ContextGraph
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def test_get_neighbor_distances_tracks_path_decay_and_band():
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graph = ContextGraph(advanced_analytics=False)
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graph.add_node("A", "entity", "Anchor")
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graph.add_node("B", "entity", "Bridge")
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graph.add_node("C", "decision", "Decision")
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graph.add_edge("A", "B", "influences", weight=0.9)
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graph.add_edge("B", "C", "influences", weight=0.7)
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neighbors = graph.get_neighbor_distances("A", hops=2, min_confidence=0.5)
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c_neighbor = next(item for item in neighbors if item["id"] == "C")
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assert c_neighbor["hop"] == 2
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assert c_neighbor["distance_band"] == "near"
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assert c_neighbor["confidence_decay"] == 0.63
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assert c_neighbor["path_to_anchor"] == ["A", "B", "C"]
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def test_trace_decision_causality_returns_auditable_chain_dicts():
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graph = ContextGraph(advanced_analytics=False)
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first = graph.record_decision(
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category="risk",
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scenario="Approve initial risk policy",
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reasoning="Baseline risk controls look sound",
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outcome="approved",
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confidence=0.8,
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entities=["account_123"],
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)
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second = graph.record_decision(
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category="risk",
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scenario="Approve follow-up risk exception",
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reasoning="Prior account controls still apply",
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outcome="approved",
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confidence=0.9,
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entities=["account_123"],
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)
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graph._decisions[first]["timestamp"] = 1
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graph._decisions[second]["timestamp"] = 2
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chains = graph.trace_decision_causality(second, max_depth=2)
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assert chains
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assert chains[0]["hop_count"] == 1
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assert chains[0]["distance_band"] == "direct"
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assert chains[0]["weakest_link"]["from"] == first
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assert chains[0]["hops"][0]["to"] == second
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assert "confidence" in chains[0]["interpretation"]
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assert list(chains[0])[0]["from"] == first
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def test_analyze_decision_influence_exposes_score_breakdown():
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graph = ContextGraph(advanced_analytics=False)
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source = graph.record_decision(
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category="loan",
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scenario="Approve secured loan",
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reasoning="Collateral and income verified",
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outcome="approved",
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confidence=0.9,
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entities=["borrower_1"],
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)
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graph.record_decision(
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category="loan",
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scenario="Review related refinance",
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reasoning="Same borrower and collateral",
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outcome="review",
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confidence=0.8,
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entities=["borrower_1"],
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)
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result = graph.analyze_decision_influence(source)
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assert result["influence_scores"]
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score = result["influence_scores"][0]
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assert set(score["score_breakdown"]) == {
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"entity_overlap",
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"category_match",
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"temporal_proximity",
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}
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assert score["is_direct"] is True
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def test_cross_graph_path_traverses_link_boundary():
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left = ContextGraph(advanced_analytics=False)
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right = ContextGraph(advanced_analytics=False)
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left.add_node("A", "entity", "Left")
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right.add_node("B", "entity", "Right")
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left.link_graph(right, "A", "B")
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path = left.cross_graph_path("A", right, "B")
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assert path["reachable"] is True
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assert path["hop_count"] == 1
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assert path["cross_graph_links_used"] == 1
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assert path["distance_band"] == "direct"
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assert path["path"] == [(left.graph_id, "A"), (right.graph_id, "B")]
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