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

apps/ai-service/tests/test_conversational_service.py

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+from rag.conversation import DeterministicSummariser, InMemoryConversationStore
+from rag.conversational import ConversationalRagService, TurnResolution
+from rag.reasoning import ClarifyReason, MAX_LLM_CALLS, MAX_RETRIEVAL_ROUNDS, TurnBudget
+
+
+class FakeResolver:
+    """Maps a turn's text to what it resolves on its own (no context)."""
+
+    def __init__(self, table):
+        self._table = table
+
+    def resolve_turn(self, text):
+        for needle, resolution in self._table:
+            if needle in text:
+                return resolution
+        return TurnResolution(drug_id=None, section_key=None, drug_status="not_found")
+
+
+def _service(resolver, retrieve, generate):
+    return ConversationalRagService(
+        store=InMemoryConversationStore(),
+        summariser=DeterministicSummariser(),
+        resolver=resolver,
+        retrieve=retrieve,
+        generate=generate,
+    )
+
+
+def test_followup_inherits_drug_and_answer_names_it():
+    resolver = FakeResolver([
+        ("metformin", TurnResolution("metformin", "chong_chi_dinh", "resolved")),
+        # "còn trẻ em" names no drug on its own — must inherit.
+        ("trẻ em", TurnResolution(None, None, "not_found")),
+    ])
+    # Evidence mentions "trẻ em" so the population assessor is satisfied.
+    retrieve = lambda q: ("Ở trẻ em, liều metformin điều chỉnh theo cân nặng.",)
+    generate = lambda q, ev, st: "liều theo cân nặng"
+    svc = _service(resolver, retrieve, generate)
+
+    first = svc.answer("c1", "Chống chỉ định của metformin?")
+    assert first.inherited_drug is None
+
+    second = svc.answer("c1", "còn trẻ em thì sao?")
+    assert second.inherited_drug == "metformin"
+    assert second.answer.startswith("Về metformin:")
+
+
+def test_no_drug_and_no_context_asks_without_spending_budget():
+    resolver = FakeResolver([])  # nothing resolves
+    calls = {"retrieve": 0, "generate": 0}
+
+    def retrieve(q):
+        calls["retrieve"] += 1
+        return ("x",)
+
+    def generate(q, ev, st):
+        calls["generate"] += 1
+        return "x"
+
+    svc = _service(resolver, retrieve, generate)
+    budget = TurnBudget()
+    out = svc.answer("c2", "cái này thế nào?", budget=budget)
+
+    assert out.answer is None
+    assert out.clarification is not None
+    assert out.clarification.reason == ClarifyReason.AMBIGUOUS_DRUG
+    # Asking short-circuits before any spend.
+    assert calls == {"retrieve": 0, "generate": 0}
+    assert budget.retrieval_rounds == MAX_RETRIEVAL_ROUNDS
+    assert budget.llm_calls == MAX_LLM_CALLS
+
+
+def test_state_persists_across_turns():
+    resolver = FakeResolver([
+        ("metformin", TurnResolution("metformin", "chi_dinh", "resolved")),
+    ])
+    svc = _service(resolver, lambda q: ("Chỉ định của metformin.",), lambda q, ev, st: "ok")
+    svc.answer("c3", "chỉ định metformin?")
+    state = svc._store.load("c3")
+    assert state.turn_count == 2  # user + assistant
+    assert state.focus.drug_id == "metformin"