refactor(api): TOML 配置 SSOT、统一错误契约、Auth/事务加固与可观测性 (#33)

配置 SSOT（TOML + .env）
统一错误契约
Auth 与事务边界
Redis / Celery 可靠性:业务 Redis（DB/0）与 Celery broker/backend（DB/1）显式拆分；连接池、sync client
可观测性（OpenTelemetry + LGTM）

api/app/features/conversation/ws/pipeline.py

@@ -14,7 +14,7 @@ from app.core.logging import get_logger
 if TYPE_CHECKING:
     from app.features.quota.service import QuotaService
 
-from sqlalchemy import select, update
+from sqlalchemy import select
 from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.agents.chat import ChatOrchestrator
@@ -27,6 +27,10 @@ from app.core.cos_url_keys import (
     extract_cos_object_key_if_owned,
 )
 from app.core.db import AsyncSessionLocal
+from app.features.conversation.ws.persist import (
+    persist_message_tts_url_segment,
+    persist_voice_segment_row,
+)
 from app.core.dependencies import get_asr_provider, get_object_storage, get_tts_provider
 from app.features.conversation.chat_turn import (
     ChatTurnContext,
@@ -37,7 +41,6 @@ from app.features.conversation.history_store import (
     AI_RESPONSE_SEGMENT_JOIN,
     ConversationHistoryStore,
 )
-from app.features.conversation.lineage_schemas import DialogueLineage
 from app.features.conversation.models import Conversation, ConversationMessage, Segment
 from app.features.conversation.ws.connection_manager import manager
 from app.features.conversation.ws.message_types import MessageType
@@ -47,11 +50,12 @@ from app.features.conversation.ws.profile_collector import (
     get_missing_profile_fields,
 )
 from app.features.conversation.ws.topic_chips_push import maybe_send_topic_chips_ws
-from app.features.memoir.state_service import get_or_create_state
 from app.features.memoir.background_runner import BackgroundTaskRunner
-from app.features.memoir.ingest_scheduler import MemoirIngestScheduler
+from app.features.memoir.ingest_scheduler import MemoirIngestScheduler, MemoirTrigger
+from app.features.memoir.state_service import get_or_create_state
 from app.features.user.models import User
 from app.ports.asr import ASRTranscriptionError
+from app.core.runtime_constants import tts_defaults
 
 logger = get_logger(__name__)
 
@@ -118,20 +122,20 @@ async def _send_tts_audio(
                 chunk_index,
                 language,
                 (text or "")[:30],
-                settings.tts_provider,
+                tts_defaults.provider,
             )
             return None
         if _tts_epoch_value(conversation_id) != tts_epoch_start:
             return None
-        ext = _tts_object_ext(settings.tts_codec)
-        content_type = _tts_codec_to_content_type(settings.tts_codec)
+        ext = _tts_object_ext(tts_defaults.codec)
+        content_type = _tts_codec_to_content_type(tts_defaults.codec)
         storage = get_object_storage()
         key = f"conversations/{conversation_id}/tts/{uuid.uuid4().hex}.{ext}"
         public_url = storage.upload(key, audio_bytes, content_type)
         # 与 `tts_delivery.apply_presigned_tts_urls_to_messages` / 回忆录图片 presign 一致：下发可播 URL
         playback_url = storage.get_url(key, expires=TTS_PRESIGNED_EXPIRES_SEC)
         payload_data: Dict[str, Any] = {
-            "format": settings.tts_codec,
+            "format": tts_defaults.codec,
             "audio_base64": base64.b64encode(audio_bytes).decode("utf-8"),
             "audio_url": playback_url,
             "index": chunk_index,
@@ -182,7 +186,7 @@ async def handle_tts_request_on_demand(
         segment_index,
         len(segment_text or ""),
         settings.enable_tts,
-        settings.tts_provider,
+        tts_defaults.provider,
     )
 
     conv = await db.get(Conversation, conversation_id)
@@ -260,7 +264,7 @@ async def handle_tts_request_on_demand(
                 "conversation_id": conversation_id,
                 "data": {
                     "audio_url": playback_url,
-                    "format": settings.tts_codec,
+                    "format": tts_defaults.codec,
                     "index": segment_index,
                     "total": chunk_total,
                     "assistant_message_id": assistant_message_id,
@@ -319,11 +323,7 @@ async def handle_tts_request_on_demand(
         )
         return False, "语音合成失败"
 
-    while len(urls) <= segment_index:
-        urls.append("")
-    urls[segment_index] = url_stored
-    msg.tts_audio_urls = urls
-    await db.commit()
+    await persist_message_tts_url_segment(db, msg, segment_index, url_stored)
 
     store = ConversationHistoryStore(db)
     await store._sync_redis_best_effort(conversation_id)
@@ -344,6 +344,24 @@ _background_runner = BackgroundTaskRunner()
 memoir_ingest_scheduler = MemoirIngestScheduler(_background_runner)
 
 
+async def _schedule_memoir_ingest_for_segment(
+    user_id: str,
+    segment: Segment,
+    *,
+    trigger: MemoirTrigger = "turn",
+) -> None:
+    """Queue memoir phase1 after segment text (and ideally lineage) is durable."""
+    text = (segment.user_input_text or "").strip()
+    if not text:
+        return
+    await memoir_ingest_scheduler.queue_segment(
+        user_id,
+        str(segment.id),
+        text_char_count=len(text),
+        trigger=trigger,
+    )
+
+
 # ── 分段流状态 ──────────────────────────────────────────────────
 
 
@@ -457,14 +475,6 @@ def _utc_now() -> datetime:
     return datetime.now(timezone.utc)
 
 
-def _mark_conversation_active(
-    conversation: Conversation, at: Optional[datetime] = None
-) -> datetime:
-    activity_time = at or _utc_now()
-    conversation.last_message_at = activity_time
-    return activity_time
-
-
 def _voice_session_id_from_client_segment_id(
     client_segment_id: Optional[str],
 ) -> Optional[str]:
@@ -825,15 +835,9 @@ async def process_audio_segment(
                     else None,
                     processed=False,
                 )
-                db.add(segment)
-                user_message_timestamp = _mark_conversation_active(conversation)
-                await db.commit()
+                await persist_voice_segment_row(db, segment, conversation)
+                user_message_timestamp = conversation.last_message_at
                 await db.refresh(segment)
-                await memoir_ingest_scheduler.queue_segment(
-                    conversation.user_id,
-                    segment.id,
-                    text_char_count=len((transcript_text or "").strip()),
-                )
 
             ready_segments: List[Tuple[int, str, Segment]] = []
             tts_flag_this_voice_session = False
@@ -943,6 +947,8 @@ async def process_user_message(
     *,
     force_skip_tts: bool = False,
     tts_this_turn: Optional[bool] = None,
+    memoir_trigger: MemoirTrigger = "turn",
+    schedule_memoir: bool = True,
 ) -> None:
     """处理用户消息，生成 Agent 回应。由 ChatOrchestrator 路由到 ProfileAgent 或 InterviewAgent。"""
     with business_span("conversation.ws.process_turn"):
@@ -956,6 +962,8 @@ async def process_user_message(
             user_message_timestamp,
             force_skip_tts=force_skip_tts,
             tts_this_turn=tts_this_turn,
+            memoir_trigger=memoir_trigger,
+            schedule_memoir=schedule_memoir,
         )
 
 
@@ -970,6 +978,8 @@ async def _process_user_message_inner(
     *,
     force_skip_tts: bool = False,
     tts_this_turn: Optional[bool] = None,
+    memoir_trigger: MemoirTrigger = "turn",
+    schedule_memoir: bool = True,
 ) -> None:
     store = ConversationHistoryStore(db)
     tts_urls: list[str] = []
@@ -1022,18 +1032,17 @@ async def _process_user_message_inner(
                 want_tts,
             )
 
-        segment.agent_response = AI_RESPONSE_SEGMENT_JOIN.join(responses)
-        _mark_conversation_active(conversation)
-        turn_ids = await store.record_human_ai_turn(
+        agent_response = AI_RESPONSE_SEGMENT_JOIN.join(responses)
+        turn_ids = await store.record_human_ai_turn_with_segment(
             conversation_id=conversation_id,
             user_message=user_message,
             responses=responses,
+            segment=segment,
             user_message_timestamp=user_message_timestamp,
             is_from_voice=is_from_voice,
             voice_session_id=voice_session_id,
             audio_duration_seconds=audio_dur,
-            tts_audio_urls=None,
-            segment_id=segment.id,
+            agent_response=agent_response,
             memory_retrieval_trace=turn.memory_retrieval_trace,
         )
         if not turn_ids:
@@ -1053,23 +1062,22 @@ async def _process_user_message_inner(
                         "timestamp": datetime.now(timezone.utc).isoformat(),
                     },
                 )
+            owner_id = (user.id if user is not None else None) or conversation.user_id
+            if schedule_memoir:
+                await _schedule_memoir_ingest_for_segment(
+                    owner_id,
+                    segment,
+                    trigger=memoir_trigger,
+                )
             return
 
-        lineage = DialogueLineage.for_single_turn(
-            conversation_id=conversation_id,
-            user_message_id=turn_ids.human_message_id,
-            assistant_message_id=turn_ids.assistant_message_id,
-            segment_ids=[str(segment.id)],
-        )
-        await db.execute(
-            update(Segment)
-            .where(Segment.id == segment.id)
-            .values(
-                user_message_id=turn_ids.human_message_id,
-                lineage_json=lineage.model_dump(mode="json"),
+        owner_id = (user.id if user is not None else None) or conversation.user_id
+        if schedule_memoir:
+            await _schedule_memoir_ingest_for_segment(
+                owner_id,
+                segment,
+                trigger=memoir_trigger,
             )
-        )
-        await db.commit()
 
         ai_msg_id = turn_ids.assistant_message_id
         tts_epoch_start = _tts_epoch_value(conversation_id)
@@ -1156,32 +1164,20 @@ async def _process_user_message_inner(
                 logger.warning("after-turn topic chips skipped: {}", chip_err)
 
         if tts_urls:
-            await store.attach_ai_tts_audio_urls(
+            await store.attach_ai_tts_for_turn(
                 conversation_id,
                 tts_audio_urls=tts_urls,
-                segment_id=segment.id,
+                segment=segment,
             )
-            await db.execute(
-                update(Segment)
-                .where(Segment.id == segment.id)
-                .values(tts_audio_urls=tts_urls)
-            )
-            await db.commit()
 
     except Exception as e:
         if tts_urls:
             try:
-                await store.attach_ai_tts_audio_urls(
+                await store.attach_ai_tts_for_turn(
                     conversation_id,
                     tts_audio_urls=tts_urls,
-                    segment_id=segment.id,
+                    segment=segment,
                 )
-                await db.execute(
-                    update(Segment)
-                    .where(Segment.id == segment.id)
-                    .values(tts_audio_urls=tts_urls)
-                )
-                await db.commit()
             except Exception as persist_error:
                 logger.warning("补写 TTS 元数据失败: {}", persist_error)
         logger.exception("处理用户消息失败: {}", e)