Wire the guarded conversational RAG answer layer end-to-end

apps/ai-service/tests/test_conversation_summary.py

@@ -0,0 +1,50 @@
+from rag.conversation import (
+    ConversationState,
+    DeterministicSummariser,
+    InMemoryConversationStore,
+    Turn,
+)
+
+
+def test_store_returns_fresh_state_for_unknown_id():
+    store = InMemoryConversationStore()
+    state = store.load("conv-new")
+    assert state.conversation_id == "conv-new"
+    assert state.turn_count == 0
+    assert state.recent == ()
+
+
+def test_store_round_trips_saved_state():
+    store = InMemoryConversationStore()
+    state = ConversationState("conv-1", summary="s", turn_count=3)
+    store.save(state)
+    assert store.load("conv-1") is state
+
+
+def test_summariser_records_topic_labels_only():
+    s = DeterministicSummariser()
+    dropped = (
+        Turn("user", "Chống chỉ định của metformin?", "t0",
+             drug_id="metformin", section_key="chong_chi_dinh"),
+        Turn("assistant", "Quá mẫn với metformin, suy thận Clcr < 60...", "t1",
+             drug_id="metformin", section_key="chong_chi_dinh"),
+    )
+    out = s.fold("", dropped)
+    # The label line is present...
+    assert "chong_chi_dinh của metformin" in out
+    # ...and no clinical value leaked from the assistant turn.
+    assert "Clcr" not in out
+    assert "60" not in out
+
+
+def test_summariser_stays_within_budget_dropping_oldest():
+    s = DeterministicSummariser()
+    dropped = tuple(
+        Turn("user", f"q{i}", f"t{i}", drug_id=f"drug{i}", section_key="lieu_luong")
+        for i in range(400)
+    )
+    out = s.fold("", dropped)
+    assert len(out) <= DeterministicSummariser.MAX_CHARS
+    # Most-recent topic survives, oldest is dropped.
+    assert "drug399" in out
+    assert "drug0 " not in out