feat: canonical intent taxonomy for AI operator (kb_answer -> intent_code)
deploy / deploy (push) Successful in 30s
deploy / deploy (push) Successful in 30s
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
This commit is contained in:
@@ -0,0 +1,2 @@
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ALTER TABLE kb_articles ADD COLUMN IF NOT EXISTS intent_code TEXT;
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CREATE INDEX IF NOT EXISTS idx_kb_articles_intent_code ON kb_articles(intent_code);
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@@ -0,0 +1,2 @@
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ALTER TABLE kb_articles ADD COLUMN intent_code TEXT;
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CREATE INDEX IF NOT EXISTS idx_kb_articles_intent_code ON kb_articles(intent_code);
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@@ -9,7 +9,7 @@ import os
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import re
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import time
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from threading import Lock
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from typing import Any
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from typing import Any, Iterable
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import httpx
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from fastapi import Depends, FastAPI, HTTPException, Query
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@@ -23,6 +23,7 @@ from services.shared.ai_context_summary import (
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update_context_summary_from_assistant_turn,
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update_context_summary_from_user_turn,
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)
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from services.shared.intents import normalize_intent
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from services.shared.kb_localization import normalize_kb_language
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from services.shared.kb_search import search_kb_rows
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from services.shared.models import (
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@@ -2315,6 +2316,7 @@ def _openai_prompt(
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"article_id": article.article_id,
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"title": article.title,
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"snippet": _article_snippet(article),
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"intent_code": getattr(article, "intent_code", None),
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}
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for article in kb_results
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]
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@@ -2410,10 +2412,15 @@ def _openai_compatible_decision(
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)
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def _sanitize_decision(raw: dict[str, Any], *, fallback_language: str) -> dict[str, Any]:
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def _sanitize_decision(
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raw: dict[str, Any],
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*,
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fallback_language: str,
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known_topic_codes: Iterable[str] = (),
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) -> dict[str, Any]:
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decision = {
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"language": str(raw.get("language") or fallback_language or "ru"),
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"intent": str(raw.get("intent") or "unknown"),
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"intent": normalize_intent(raw.get("intent"), known_topic_codes=known_topic_codes),
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"reply_text": str(raw.get("reply_text") or "").strip(),
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"extracted_name": str(raw.get("extracted_name") or "").strip() or None,
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"confidence": float(raw.get("confidence") or 0.0),
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@@ -2611,7 +2618,13 @@ def _decide_reply(
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raw["_model"] = _ai_model()
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raw["_latency_ms"] = 1
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raw["_finish_reason"] = "stop"
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return _sanitize_decision(raw, fallback_language=language)
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return _sanitize_decision(
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raw,
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fallback_language=language,
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known_topic_codes=[
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code for article in kb_results if (code := getattr(article, "intent_code", None))
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],
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)
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def _update_ai_session_context_summary_from_user_turn(
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@@ -179,4 +179,9 @@ def operator_system_prompt(*, language: str, channel_label: str, is_voice: bool,
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f"{delivery_hint} "
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"Return only a JSON object with keys: language, intent, reply_text, extracted_name, confidence, needs_handoff, "
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"handoff_reason, case_action, kb_refs. case_action must be one of none, close, escalate, keep_open. "
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"For `intent`: if your reply is grounded in one of the provided kb_results, set intent to that snippet's "
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"intent_code exactly as given (do not translate, reformat, or invent your own code). If no kb_results were "
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"used, use one of these fixed values as appropriate: identity_question, handoff_request, sensitive_request, "
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"resolution_confirmed, clarification, kb_answer, unknown. Never invent a new intent value outside of these "
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"two sources — the platform discards anything else."
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)
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@@ -1359,7 +1359,13 @@ def _voice_v2_enabled(metadata: dict[str, Any] | None = None) -> bool:
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return _voice_policy_mode() in {"v2_fast_conversational", "v2_streaming_duplex"}
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def _voice_early_intent_bucket(text: str) -> str:
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def _voice_ack_topic_bucket(text: str) -> str:
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"""Coarse keyword heuristic used only to pick an ack phrase / early clarifying
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question (see _voice_ack_kind_for_intent and _voice_early_plan) while the real,
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KB-grounded decision is still in flight. This is NOT the canonical FAQ intent
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(see services.shared.intents) and must never be echoed back as the final
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decision's `intent` value.
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"""
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normalized = " ".join(str(text or "").strip().lower().split())
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if not normalized:
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return "unknown"
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@@ -1509,7 +1515,7 @@ def _voice_v2_metadata(
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if not _voice_v2_enabled(request_metadata):
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return {}
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payload = request_metadata if isinstance(request_metadata, dict) else {}
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early_intent = _voice_early_intent_bucket(transcript_text)
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early_intent = _voice_ack_topic_bucket(transcript_text)
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metadata: dict[str, Any] = {
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"voice_v2_enabled": True,
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"early_intent": early_intent,
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@@ -1668,6 +1674,7 @@ def _voice_llm_prompt_messages(
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"article_id": article.article_id,
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"title": article.title,
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"snippet": app._article_snippet(article, limit=240),
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"intent_code": getattr(article, "intent_code", None),
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}
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for article in kb_results[:3]
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]
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@@ -1767,7 +1774,13 @@ def _voice_llm_decision(
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)
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except Exception:
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return None
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decision = app._sanitize_decision(raw, fallback_language=language)
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decision = app._sanitize_decision(
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raw,
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fallback_language=language,
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known_topic_codes=[
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code for article in kb_results if (code := getattr(article, "intent_code", None))
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],
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)
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if not str(decision.get("reply_text") or "").strip():
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decision["reply_text"] = _voice_generic_prompt(language)
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if decision.get("needs_handoff") and not decision.get("handoff_reason"):
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@@ -40,6 +40,7 @@ def _article_out(row: KBArticleRow) -> KBArticleOut:
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article_id=row.article_id,
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category_id=row.category_id,
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article_group_id=resolve_article_group_id(row.article_id, row.article_group_id),
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intent_code=row.intent_code,
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language=normalize_kb_language(row.language),
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title=row.title,
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body=row.body,
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@@ -49,6 +50,10 @@ def _article_out(row: KBArticleRow) -> KBArticleOut:
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)
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def _normalize_intent_code(value: str | None) -> str | None:
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return str(value or "").strip().upper() or None
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def _article_group_expr():
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return func.coalesce(KBArticleRow.article_group_id, KBArticleRow.article_id)
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@@ -133,6 +138,7 @@ def create_article(
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article_id=article_id,
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category_id=payload.category_id,
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article_group_id=article_group_id,
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intent_code=_normalize_intent_code(payload.intent_code),
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language=language,
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title=payload.title,
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body=payload.body,
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@@ -196,6 +202,8 @@ def update_article(
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if "article_group_id" in data:
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row.article_group_id = target_group_id
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if "intent_code" in data:
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row.intent_code = _normalize_intent_code(data["intent_code"])
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if "language" in data:
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row.language = target_language
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if "title" in data:
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@@ -0,0 +1,39 @@
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from __future__ import annotations
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from typing import Iterable
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# Fixed, code-level conversational signals — not FAQ topics. These strings are
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# already used as intent literals across ai_orchestrator_service/app.py,
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# voice.py, and asserted directly in tests; centralized here rather than
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# renamed so every call site validates against the same set.
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CONTROL_INTENTS: frozenset[str] = frozenset(
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{
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"identity_question",
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"handoff_request",
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"sensitive_request",
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"resolution_confirmed",
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"clarification",
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"kb_answer",
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"unknown",
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}
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)
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UNKNOWN_INTENT = "unknown"
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def normalize_intent(raw: str | None, *, known_topic_codes: Iterable[str] = ()) -> str:
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"""Validate a model-produced intent against control intents and KB topic codes.
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`known_topic_codes` are the `intent_code` values of the KB articles actually
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shown to the model for this turn — anything else the model invents collapses
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to UNKNOWN_INTENT rather than being trusted verbatim.
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"""
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candidate = str(raw or "").strip()
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if not candidate:
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return UNKNOWN_INTENT
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if candidate in CONTROL_INTENTS:
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return candidate
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normalized_topic_codes = {str(code or "").strip().upper() for code in known_topic_codes if str(code or "").strip()}
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if candidate.upper() in normalized_topic_codes:
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return candidate.upper()
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return UNKNOWN_INTENT
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@@ -25,6 +25,7 @@ class KBSearchRow(Protocol):
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title: str
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body: str
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tags_json: str
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intent_code: str | None
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T = TypeVar("T", bound=KBSearchRow)
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@@ -983,6 +983,7 @@ class KBCategoryOut(KBCategoryCreate):
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class KBArticleCreate(BaseModel):
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category_id: str
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article_group_id: str | None = None
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intent_code: str | None = None
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language: str = "ru"
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title: str
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body: str
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@@ -991,6 +992,7 @@ class KBArticleCreate(BaseModel):
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class KBArticleUpdate(BaseModel):
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article_group_id: str | None = None
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intent_code: str | None = None
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language: str | None = None
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title: str | None = None
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body: str | None = None
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@@ -583,6 +583,7 @@ def _apply_runtime_schema_compatibility() -> None:
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if "kb_articles" in table_names:
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columns = _table_columns(inspector, "kb_articles")
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_add_column_if_missing(conn, columns, "kb_articles", "article_group_id", "VARCHAR(64)")
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_add_column_if_missing(conn, columns, "kb_articles", "intent_code", "VARCHAR(64)")
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_add_column_if_missing(conn, columns, "kb_articles", "language", "VARCHAR(8) DEFAULT 'ru'")
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if "language" in columns:
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conn.execute(
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@@ -619,6 +620,13 @@ def _apply_runtime_schema_compatibility() -> None:
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"ON kb_articles(language)"
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)
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)
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if "idx_kb_articles_intent_code" not in indexes:
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conn.execute(
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text(
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"CREATE INDEX IF NOT EXISTS idx_kb_articles_intent_code "
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"ON kb_articles(intent_code)"
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)
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)
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if "sales_automation_tasks" in table_names:
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columns = _table_columns(inspector, "sales_automation_tasks")
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@@ -700,6 +700,7 @@ class KBArticleRow(Base):
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article_id: Mapped[str] = mapped_column(String(64), unique=True, index=True)
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category_id: Mapped[str] = mapped_column(String(64), index=True)
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article_group_id: Mapped[str | None] = mapped_column(String(64), nullable=True, index=True)
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intent_code: Mapped[str | None] = mapped_column(String(64), nullable=True, index=True)
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language: Mapped[str] = mapped_column(String(8), index=True, default="ru")
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title: Mapped[str] = mapped_column(String(512), index=True)
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body: Mapped[str] = mapped_column(Text)
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@@ -414,6 +414,7 @@ def seed_kb_article(
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*,
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language: str = "ru",
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article_group_id: str | None = None,
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intent_code: str | None = None,
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) -> dict[str, str]:
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session = get_session()
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try:
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@@ -434,6 +435,7 @@ def seed_kb_article(
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article_id=article_id,
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category_id=category_id,
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article_group_id=resolved_group_id,
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intent_code=intent_code,
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language=language,
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title=title,
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body=body,
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@@ -1347,6 +1349,88 @@ def test_voice_llm_guarded_decision_uses_operator_style_without_ai_or_kb(monkeyp
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assert "Do not say or imply that you are an AI" in system_prompt
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def test_voice_llm_decision_echoes_kb_article_intent_code(monkeypatch):
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monkeypatch.setenv("AI_VOICE_POLICY_MODE", "llm_guarded")
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monkeypatch.setattr(ai_module, "_ai_provider", lambda: "openai_compatible")
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def _fake_structured(messages, **kwargs):
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del messages
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return {
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"language": "ru",
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"intent": "voucher_activation",
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"reply_text": "Подтвердите СМС с номера 1414 командой 21*1, затем завершите активацию в eGov.",
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"confidence": 0.9,
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"needs_handoff": False,
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"handoff_reason": None,
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"case_action": "keep_open",
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"kb_refs": ["kba_voucher_1"],
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"_model": "gpt-test",
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"_latency_ms": 30,
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"_finish_reason": "stop",
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}
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monkeypatch.setattr(ai_module, "_request_structured_model_decision", _fake_structured)
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kb_article = SimpleNamespace(
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article_id="kba_voucher_1",
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title="Активация ваучера",
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body="Подтвердите СМС 1414 командой 21*1, затем перейдите по ссылке и завершите в eGov Mobile.",
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intent_code="VOUCHER_ACTIVATION",
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)
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decision = voice_module._voice_decision(
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language="ru",
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customer=None,
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interaction=SimpleNamespace(interaction_id="int_voice_voucher", customer_id=None, status="new", queue_id="que_voice", subject="voucher"),
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transcript_text="Что делать с СМС от 1414?",
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transcript_window=[SimpleNamespace(speaker="caller", text="Что делать с СМС от 1414?", sequence_no=1, source_type="voice_asr", barge_in_interrupted=False, created_at=utc_now_iso())],
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kb_results=[kb_article],
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disclosure_required=False,
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)
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assert decision["intent"] == "VOUCHER_ACTIVATION"
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def test_voice_llm_decision_rejects_invented_intent_not_in_kb_results(monkeypatch):
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monkeypatch.setenv("AI_VOICE_POLICY_MODE", "llm_guarded")
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monkeypatch.setattr(ai_module, "_ai_provider", lambda: "openai_compatible")
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def _fake_structured(messages, **kwargs):
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del messages
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return {
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"language": "ru",
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"intent": "totally_made_up_intent",
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"reply_text": "Подтвердите СМС с номера 1414 командой 21*1.",
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"confidence": 0.9,
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"needs_handoff": False,
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"handoff_reason": None,
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"case_action": "keep_open",
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"kb_refs": ["kba_voucher_2"],
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"_model": "gpt-test",
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"_latency_ms": 30,
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"_finish_reason": "stop",
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}
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monkeypatch.setattr(ai_module, "_request_structured_model_decision", _fake_structured)
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kb_article = SimpleNamespace(
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article_id="kba_voucher_2",
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title="Активация ваучера",
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body="Подтвердите СМС 1414 командой 21*1.",
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intent_code="VOUCHER_ACTIVATION",
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)
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decision = voice_module._voice_decision(
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language="ru",
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customer=None,
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interaction=SimpleNamespace(interaction_id="int_voice_voucher_2", customer_id=None, status="new", queue_id="que_voice", subject="voucher"),
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transcript_text="Куда отправлять 21*1?",
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transcript_window=[SimpleNamespace(speaker="caller", text="Куда отправлять 21*1?", sequence_no=1, source_type="voice_asr", barge_in_interrupted=False, created_at=utc_now_iso())],
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kb_results=[kb_article],
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disclosure_required=False,
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)
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assert decision["intent"] == "unknown"
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def test_voice_v2_fast_conversational_adds_ack_metadata_and_compacts_reply(monkeypatch):
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monkeypatch.setenv("AI_VOICE_POLICY_MODE", "v2_fast_conversational")
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monkeypatch.setattr(ai_module, "_ai_provider", lambda: "openai_compatible")
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@@ -0,0 +1,34 @@
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from services.shared.intents import CONTROL_INTENTS, UNKNOWN_INTENT, normalize_intent
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def test_control_intent_passes_through_unchanged():
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assert normalize_intent("handoff_request") == "handoff_request"
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assert normalize_intent("kb_answer", known_topic_codes=["VOUCHER_ACTIVATION"]) == "kb_answer"
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def test_matching_topic_code_passes_through_case_insensitively():
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assert normalize_intent("voucher_activation", known_topic_codes=["VOUCHER_ACTIVATION"]) == "VOUCHER_ACTIVATION"
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assert normalize_intent(" Voucher_Activation ", known_topic_codes=["voucher_activation"]) == "VOUCHER_ACTIVATION"
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def test_unknown_topic_code_falls_back_to_unknown():
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assert normalize_intent("made_up_intent", known_topic_codes=["VOUCHER_ACTIVATION"]) == UNKNOWN_INTENT
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assert normalize_intent("voucher_activation", known_topic_codes=[]) == UNKNOWN_INTENT
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def test_empty_or_missing_intent_falls_back_to_unknown():
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assert normalize_intent(None) == UNKNOWN_INTENT
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assert normalize_intent("") == UNKNOWN_INTENT
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assert normalize_intent(" ") == UNKNOWN_INTENT
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def test_control_intents_frozenset_matches_documented_values():
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assert CONTROL_INTENTS == {
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"identity_question",
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"handoff_request",
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"sensitive_request",
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"resolution_confirmed",
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"clarification",
|
||||
"kb_answer",
|
||||
"unknown",
|
||||
}
|
||||
@@ -40,6 +40,46 @@ def test_kb_lite_search():
|
||||
assert len(search.json()) >= 1
|
||||
|
||||
|
||||
def test_kb_article_intent_code_round_trips_through_create_get_update():
|
||||
client = TestClient(kb_app)
|
||||
headers = {"X-User": "analyst", "X-Role": "analyst"}
|
||||
|
||||
cat = client.post(
|
||||
"/knowledge/categories",
|
||||
json={"name": "Vouchers", "description": "Voucher help"},
|
||||
headers=headers,
|
||||
)
|
||||
assert cat.status_code == 200
|
||||
category_id = cat.json()["category_id"]
|
||||
|
||||
created = client.post(
|
||||
"/knowledge/articles",
|
||||
json={
|
||||
"category_id": category_id,
|
||||
"title": "Активация ваучера",
|
||||
"body": "Подтвердите СМС 1414 командой 21*1.",
|
||||
"tags": ["voucher"],
|
||||
"intent_code": "voucher_activation",
|
||||
},
|
||||
headers=headers,
|
||||
)
|
||||
assert created.status_code == 200
|
||||
assert created.json()["intent_code"] == "VOUCHER_ACTIVATION"
|
||||
article_id = created.json()["article_id"]
|
||||
|
||||
fetched = client.get(f"/knowledge/articles/{article_id}")
|
||||
assert fetched.status_code == 200
|
||||
assert fetched.json()["intent_code"] == "VOUCHER_ACTIVATION"
|
||||
|
||||
updated = client.patch(
|
||||
f"/knowledge/articles/{article_id}",
|
||||
json={"intent_code": "voucher_activation_v2"},
|
||||
headers=headers,
|
||||
)
|
||||
assert updated.status_code == 200
|
||||
assert updated.json()["intent_code"] == "VOUCHER_ACTIVATION_V2"
|
||||
|
||||
|
||||
def test_kb_lite_search_ranks_title_over_body_only_matches():
|
||||
client = TestClient(kb_app)
|
||||
headers = {"X-User": "analyst", "X-Role": "analyst"}
|
||||
|
||||
Reference in New Issue
Block a user