Revert "fix: let voice early-plan turns answer from the FAQ knowledge base"

This reverts commit 8ced7a59e3.

services/ai_orchestrator_service/voice.py

@@ -19,7 +19,6 @@ from services.shared.ai_context_summary import (
 )
 from services.shared.core import new_id, utc_now_iso
 from services.shared.db import get_session
-from services.shared.intents import normalize_intent
 from services.shared.models import VoiceAIStartIn, VoiceAIStartOut, VoiceAITurnDecisionOut, VoiceAITurnIn, VoiceStartResult
 from services.shared.sql_models import (
     AISessionRow,
@@ -1535,7 +1534,6 @@ def _voice_early_plan(
     transcript_text: str,
     context_summary: str | dict[str, Any] | None = None,
     request_metadata: dict[str, Any] | None = None,
-    kb_results: list[Any] = (),
 ) -> dict[str, Any]:
     v2_metadata = _voice_v2_metadata(transcript_text, request_metadata)
     payload = request_metadata if isinstance(request_metadata, dict) else {}
@@ -1578,56 +1576,10 @@ def _voice_early_plan(
                 "reply_phase": "early_plan",
             },
         }
-    if early_intent == "operator_request":
-        return {
-            "language": language,
-            "intent": "handoff_request",
-            "reply_text": _voice_compact_reply_text(_voice_handoff_reply(language), language=language),
-            "confidence": 0.62,
-            "needs_handoff": True,
-            "handoff_reason": "Запрос требует участия живого оператора.",
-            "case_action": "keep_open",
-            "kb_refs": [],
-            "summary_text": "Early domain plan is prepared.",
-            "model": "voice_early_plan_domain",
-            "latency_ms": 1,
-            "metadata": {
-                **v2_metadata,
-                "reply_phase": "early_plan",
-                "early_intent": early_intent,
-            },
-        }
-    if early_intent in {"schedule", "address", "price", "status", "problem"} and kb_results:
-        # A cheap lexical KB lookup fits the early-plan latency budget (no LLM
-        # round-trip), unlike the properly grounded/paraphrased "final" decision.
-        # Answering from the KB here beats guessing a generic clarifying question
-        # when the FAQ already has the answer — see the plan doc for why this
-        # branch exists at all (the early reply can win the race and get spoken
-        # before the final, LLM-grounded decision is ready).
-        article = kb_results[0]
-        snippet = _app()._article_snippet(article, limit=220)
-        reply_text = f"Қысқаша айтайын: {snippet}" if language == "kz" else f"Коротко подскажу: {snippet}"
-        topic_code = getattr(article, "intent_code", None)
-        return {
-            "language": language,
-            "intent": normalize_intent(topic_code or "kb_answer", known_topic_codes=[topic_code] if topic_code else []),
-            "reply_text": _voice_compact_reply_text(reply_text, language=language),
-            "confidence": 0.7,
-            "needs_handoff": False,
-            "handoff_reason": None,
-            "case_action": "keep_open",
-            "kb_refs": [article.article_id],
-            "summary_text": "AI ответил по базе ЧЗВ на предварительной стадии.",
-            "model": "voice_early_plan_kb",
-            "latency_ms": 1,
-            "metadata": {
-                **v2_metadata,
-                "reply_phase": "early_plan",
-                "early_intent": early_intent,
-            },
-        }
-    if early_intent in {"schedule", "address", "price", "status", "problem"}:
+    if early_intent in {"schedule", "address", "price", "status", "problem", "operator_request"}:
         reply_text = _voice_summary_slot_prompt(language, context_summary) or _voice_topic_prompt(language, [transcript_text])
+        if early_intent == "operator_request":
+            reply_text = _voice_handoff_reply(language)
         if not reply_text and language == "kz":
             if early_intent == "schedule":
                 reply_text = "Qai filialdyn, mekenjaidyn nemese qalanyng jumys uaqyty qyzyqtyratynyn aitnyz."
@@ -1653,11 +1605,15 @@ def _voice_early_plan(
         if reply_text:
             return {
                 "language": language,
-                "intent": "clarification",
+                "intent": "handoff_request" if early_intent == "operator_request" else "clarification",
                 "reply_text": _voice_compact_reply_text(reply_text, language=language),
                 "confidence": 0.62,
-                "needs_handoff": False,
-                "handoff_reason": None,
+                "needs_handoff": early_intent == "operator_request",
+                "handoff_reason": (
+                    "Запрос требует участия живого оператора."
+                    if early_intent == "operator_request"
+                    else None
+                ),
                 "case_action": "keep_open",
                 "kb_refs": [],
                 "summary_text": "Early domain plan is prepared.",
@@ -1880,7 +1836,6 @@ def _voice_decision(
             transcript_text=transcript_text,
             context_summary=context_summary,
             request_metadata=request_metadata,
-            kb_results=kb_results,
         )
 
     if persona.is_identity_request(normalized):
@@ -2582,17 +2537,13 @@ def turn_voice_session(session_id: str, payload: VoiceAITurnIn) -> VoiceAITurnDe
             )
             ai_session.context_summary_json = dump_context_summary(user_context_summary)
             ai_session.context_summary_updated_at = now
-        # Unlike name extraction/context-summary writes above (skipped for
-        # early_plan_only since they're stateful and heavier), KB search is a
-        # cheap in-memory lexical scan over a DB-cached row set (see
-        # _load_kb_rows_cached) and comfortably fits the early-plan latency
-        # budget, so it always runs — this lets _voice_early_plan answer from
-        # the FAQ instead of guessing a generic clarifying question.
-        kb_results = app._kb_search(
-            session,
-            payload.transcript_text,
-            language=ai_session.language,
-        )
+        kb_results = []
+        if not early_plan_only:
+            kb_results = app._kb_search(
+                session,
+                payload.transcript_text,
+                language=ai_session.language,
+            )
         disclosure_required = voice_session.disclosure_played_at is None
         decision = _voice_decision(
             language=ai_session.language or "ru",

tests/test_ai_orchestrator_service.py

@@ -1589,79 +1589,6 @@ def test_voice_v2_streaming_duplex_early_plan_returns_domain_followup_without_ll
     assert decision["metadata"]["early_intent"] == "schedule"
 
 
-def test_voice_v2_streaming_duplex_early_plan_answers_from_kb_without_llm(monkeypatch):
-    monkeypatch.setenv("AI_VOICE_POLICY_MODE", "v2_streaming_duplex")
-
-    def _unexpected_llm(messages, **kwargs):
-        raise AssertionError(f"LLM should not be called for early plan: {messages!r}")
-
-    monkeypatch.setattr(ai_module, "_request_structured_model_decision", _unexpected_llm)
-
-    kb_article = SimpleNamespace(
-        article_id="kba_early_schedule",
-        title="График работы филиалов",
-        body="Филиалы работают с понедельника по пятницу с 9:00 до 18:00.",
-        intent_code="BRANCH_SCHEDULE",
-    )
-    decision = voice_module._voice_decision(
-        language="ru",
-        customer=None,
-        interaction=SimpleNamespace(interaction_id="int_voice_early_schedule_kb", status="new", queue_id="que_voice", subject="unknown"),
-        transcript_text="Мне надо узнать график работы",
-        transcript_window=[],
-        kb_results=[kb_article],
-        disclosure_required=False,
-        request_metadata={
-            "voice_v2_enabled": True,
-            "reply_phase": "early_plan",
-            "response_plan_id": "rsp_early_schedule_kb",
-            "early_intent": "schedule",
-        },
-    )
-
-    assert decision["model"] == "voice_early_plan_kb"
-    assert decision["intent"] == "BRANCH_SCHEDULE"
-    assert decision["kb_refs"] == ["kba_early_schedule"]
-    assert decision["needs_handoff"] is False
-    assert "9:00" in decision["reply_text"] or "9" in decision["reply_text"]
-    assert decision["metadata"]["reply_phase"] == "early_plan"
-
-
-def test_voice_v2_streaming_duplex_early_plan_operator_request_skips_kb(monkeypatch):
-    monkeypatch.setenv("AI_VOICE_POLICY_MODE", "v2_streaming_duplex")
-
-    def _unexpected_llm(messages, **kwargs):
-        raise AssertionError(f"LLM should not be called for early plan: {messages!r}")
-
-    monkeypatch.setattr(ai_module, "_request_structured_model_decision", _unexpected_llm)
-
-    kb_article = SimpleNamespace(
-        article_id="kba_should_not_be_used",
-        title="Unrelated article",
-        body="Should not be referenced for an operator handoff.",
-        intent_code="SOMETHING_ELSE",
-    )
-    decision = voice_module._voice_decision(
-        language="ru",
-        customer=None,
-        interaction=SimpleNamespace(interaction_id="int_voice_early_operator", status="new", queue_id="que_voice", subject="unknown"),
-        transcript_text="Соедините меня с оператором",
-        transcript_window=[],
-        kb_results=[kb_article],
-        disclosure_required=False,
-        request_metadata={
-            "voice_v2_enabled": True,
-            "reply_phase": "early_plan",
-            "response_plan_id": "rsp_early_operator",
-            "early_intent": "operator_request",
-        },
-    )
-
-    assert decision["intent"] == "handoff_request"
-    assert decision["needs_handoff"] is True
-    assert decision["kb_refs"] == []
-
-
 def test_voice_decision_hearing_check_keeps_active_topic_without_llm(monkeypatch):
     def _unexpected_llm(messages, **kwargs):
         raise AssertionError(f"LLM should not be called for hearing check: {messages!r}")