Import AITURK IDE 1.0.0-beta.1 from Hermes 63279301; preserve MIT license

tests/agent/test_learning_graph.py

@@ -0,0 +1,81 @@
+"""Behavior contracts for the learning-graph assembler.
+
+Asserts invariants (edges resolve to real nodes, clusters cover every node,
+memory cards are represented consistently), never a snapshot of the live skill
+catalog — that catalog grows every release and a count assertion would be a
+change-detector.
+"""
+
+from __future__ import annotations
+
+from agent import learning_graph
+from hermes_constants import reset_hermes_home_override, set_hermes_home_override
+
+
+def _node(name: str, category: str, related=None):
+    n = learning_graph.SkillNode(name=name, category=category)
+    n.related = list(related or [])
+    return n
+
+
+
+
+def test_density_stats_count_isolated_nodes():
+    nodes = {
+        "a": _node("a", "x", related=["b"]),
+        "b": _node("b", "x", related=["a"]),
+        "c": _node("c", "y"),
+    }
+    stats = learning_graph.density_stats(nodes, learning_graph.build_edges(nodes))
+
+    assert stats["nodes"] == 3
+    assert stats["linked_nodes"] == 2
+    assert stats["isolated_pct"] == round(100 / 3, 1)
+
+
+
+
+def test_memory_is_cards_split_on_separator(tmp_path):
+    home = tmp_path / ".hermes"
+    (home / "memories").mkdir(parents=True)
+    (home / "memories" / "MEMORY.md").write_text(
+        "Project uses pytest with xdist\n§\nUser prefers concise responses",
+        encoding="utf-8",
+    )
+    token = set_hermes_home_override(home)
+    try:
+        graph = learning_graph.build_learning_graph()
+    finally:
+        reset_hermes_home_override(token)
+
+    titles = [c["title"] for c in graph["memory"]]
+    assert "Project uses pytest with xdist" in titles
+    assert "User prefers concise responses" in titles
+    # Memory cards remain typed cards and also appear as memory-kind nodes.
+    assert all(c["source"] in {"memory", "profile"} for c in graph["memory"])
+    assert all("timestamp" in c for c in graph["memory"])
+    assert any(n["kind"] == "memory" for n in graph["nodes"])
+
+
+
+
+
+
+def test_full_payload_shape_and_edge_integrity(tmp_path):
+    home = tmp_path / ".hermes"
+    home.mkdir()
+    token = set_hermes_home_override(home)
+    try:
+        graph = learning_graph.build_learning_graph()
+    finally:
+        reset_hermes_home_override(token)
+
+    ids = {n["id"] for n in graph["nodes"]}
+    assert all(e["source"] in ids and e["target"] in ids for e in graph["edges"])
+    # Every node's category appears in the cluster list.
+    cluster_cats = {c["category"] for c in graph["clusters"]}
+    assert all(n["category"] in cluster_cats for n in graph["nodes"])
+    skill_nodes = [n for n in graph["nodes"] if n["kind"] == "skill"]
+    assert graph["stats"]["nodes"] == len(skill_nodes)
+    assert graph["stats"]["memory_nodes"] == len(graph["memory"])
+    assert all("timestamp" in n for n in graph["nodes"])