feat: canonical intent taxonomy for AI operator (kb_answer -> intent_code)

Centralizes fixed control intents and adds a data-driven intent_code
field on kb_articles so many phrasings of the same FAQ question
resolve to one stable code (e.g. VOUCHER_ACTIVATION) instead of a
free-form, unvalidated string the LLM invented on the fly.

- services/shared/intents.py: CONTROL_INTENTS + normalize_intent()
- kb_articles.intent_code column (ORM + dev/sqlite runtime compat +
  migrations/sql/0034_* for postgres/sqlite)
- kb_service CRUD exposes intent_code
- orchestrator surfaces intent_code to the LLM and validates its
  intent output against control intents + the KB codes shown that turn
- voice.py: _voice_early_intent_bucket renamed to _voice_ack_topic_bucket
  to stop it being conflated with the canonical FAQ intent

services/shared/sql_models.py

@@ -700,6 +700,7 @@ class KBArticleRow(Base):
     article_id: Mapped[str] = mapped_column(String(64), unique=True, index=True)
     category_id: Mapped[str] = mapped_column(String(64), index=True)
     article_group_id: Mapped[str | None] = mapped_column(String(64), nullable=True, index=True)
+    intent_code: Mapped[str | None] = mapped_column(String(64), nullable=True, index=True)
     language: Mapped[str] = mapped_column(String(8), index=True, default="ru")
     title: Mapped[str] = mapped_column(String(512), index=True)
     body: Mapped[str] = mapped_column(Text)