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Ensure the Memory Graph cannot show stale data after switching profiles, and tighten the graph backend's profile-safe timestamp handling.
108 lines
3.7 KiB
Python
108 lines
3.7 KiB
Python
"""Behavior contracts for the learning-graph assembler.
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Asserts invariants (edges resolve to real nodes, clusters cover every node,
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memory cards are represented consistently), never a snapshot of the live skill
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catalog — that catalog grows every release and a count assertion would be a
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change-detector.
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"""
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from __future__ import annotations
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from agent import learning_graph
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from hermes_constants import reset_hermes_home_override, set_hermes_home_override
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def _node(name: str, category: str, related=None):
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n = learning_graph.SkillNode(name=name, category=category)
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n.related = list(related or [])
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return n
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def test_edges_only_connect_existing_nodes():
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nodes = {
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"a": _node("a", "x", related=["b", "ghost"]),
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"b": _node("b", "x", related=["a"]),
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"c": _node("c", "y"),
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}
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edges = learning_graph.build_edges(nodes)
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# The a→b link is kept once (deduped, undirected); a→ghost is dropped.
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assert edges == [("a", "b")]
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def test_density_stats_count_isolated_nodes():
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nodes = {
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"a": _node("a", "x", related=["b"]),
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"b": _node("b", "x", related=["a"]),
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"c": _node("c", "y"),
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}
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stats = learning_graph.density_stats(nodes, learning_graph.build_edges(nodes))
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assert stats["nodes"] == 3
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assert stats["linked_nodes"] == 2
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assert stats["isolated_pct"] == round(100 / 3, 1)
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def test_skill_node_timestamp_uses_iso_usage_activity(tmp_path, monkeypatch):
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skill_dir = tmp_path / "skills" / "dev" / "iso-skill"
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skill_dir.mkdir(parents=True)
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skill_md = skill_dir / "SKILL.md"
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skill_md.write_text("---\nname: iso-skill\ncategory: dev\n---\n# ISO\n", encoding="utf-8")
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monkeypatch.setattr(
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learning_graph,
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"_load_usage",
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lambda: {
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"iso-skill": {
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"created_by": "agent",
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"last_used_at": "2026-04-30T12:00:00+00:00",
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"use_count": 1,
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}
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},
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)
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nodes = learning_graph.build_skill_nodes([("profile", tmp_path / "skills")])
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assert nodes["iso-skill"].timestamp == 1_777_550_400
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def test_memory_is_cards_split_on_separator(tmp_path):
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home = tmp_path / ".hermes"
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(home / "memories").mkdir(parents=True)
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(home / "memories" / "MEMORY.md").write_text(
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"Project uses pytest with xdist\n§\nUser prefers concise responses",
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encoding="utf-8",
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)
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token = set_hermes_home_override(home)
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try:
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graph = learning_graph.build_learning_graph()
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finally:
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reset_hermes_home_override(token)
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titles = [c["title"] for c in graph["memory"]]
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assert "Project uses pytest with xdist" in titles
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assert "User prefers concise responses" in titles
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# Memory cards remain typed cards and also appear as memory-kind nodes.
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assert all(c["source"] in {"memory", "profile"} for c in graph["memory"])
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assert all("timestamp" in c for c in graph["memory"])
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assert any(n["kind"] == "memory" for n in graph["nodes"])
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def test_full_payload_shape_and_edge_integrity(tmp_path):
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home = tmp_path / ".hermes"
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home.mkdir()
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token = set_hermes_home_override(home)
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try:
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graph = learning_graph.build_learning_graph()
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finally:
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reset_hermes_home_override(token)
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ids = {n["id"] for n in graph["nodes"]}
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assert all(e["source"] in ids and e["target"] in ids for e in graph["edges"])
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# Every node's category appears in the cluster list.
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cluster_cats = {c["category"] for c in graph["clusters"]}
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assert all(n["category"] in cluster_cats for n in graph["nodes"])
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skill_nodes = [n for n in graph["nodes"] if n["kind"] == "skill"]
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assert graph["stats"]["nodes"] == len(skill_nodes)
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assert graph["stats"]["memory_nodes"] == len(graph["memory"])
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assert all("timestamp" in n for n in graph["nodes"])
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