- MemoryService 异步路径委托 MemoryIngestService / MemoryRetrievalService;富化派发经 MemoryEnrichmentScheduler - WebSocket pipeline 经 ChatTurnService 与显式 DTO 编排单轮对话;回忆录片段入队由 MemoirIngestScheduler 封装 - 新增 LlmGateway(LlmUseCase),各 agent、任务与适配器对齐 ports - 补充 memory 提示适配、runtime 类型、memory-retrieval 文档、ai-touchpoints 说明与扫描脚本及配套测试 Made-with: Cursor
148 lines
5.4 KiB
Python
148 lines
5.4 KiB
Python
"""评测台:查询用户 segment 是否已完成回忆录 Phase1(topic_category 已写入)。"""
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from __future__ import annotations
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import time
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from datetime import datetime, timezone
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from sqlalchemy import select
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.db import utc_now
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from app.features.conversation.models import Conversation, Segment
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from app.features.conversation.ws.pipeline import memoir_ingest_scheduler
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from app.features.evaluation.errors import (
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EvaluationBadRequestError,
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EvaluationNotFoundError,
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)
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from app.features.evaluation.phase1_job_timing import (
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load_phase1_job_meta,
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record_phase1_job_submitted,
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)
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from app.features.evaluation.schemas import MemoirPhase1ReadyOut, MemoirSubmitOut
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class MemoirReadinessService:
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def __init__(self, db: AsyncSession) -> None:
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self._db = db
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async def memoir_phase1_ready_for_segments(
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self,
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*,
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conversation_id: str,
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segment_ids: list[str],
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) -> MemoirPhase1ReadyOut:
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cid = (conversation_id or "").strip()
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if not cid:
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raise EvaluationBadRequestError("conversation_id is required")
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ids = [s.strip() for s in segment_ids if (s or "").strip()]
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if not ids:
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raise EvaluationBadRequestError("segment_ids is required")
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conv = await self._db.get(Conversation, cid)
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if not conv or conv.deleted_at is not None:
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raise EvaluationNotFoundError("conversation not found")
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stmt = select(Segment).where(
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Segment.id.in_(ids),
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Segment.conversation_id == cid,
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)
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result = await self._db.execute(stmt)
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rows = list(result.scalars().all())
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found_ids = {s.id for s in rows}
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missing = [i for i in ids if i not in found_ids]
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if missing:
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raise EvaluationBadRequestError(
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"segment not in conversation: "
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+ ", ".join(missing[:5])
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+ ("…" if len(missing) > 5 else "")
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)
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pending = [s.id for s in rows if s.topic_category is None]
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ready = len(pending) == 0
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job_submitted_at_utc: datetime | None = None
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elapsed_ms_since_submit: int | None = None
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durations_ms: dict[str, int] = {}
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meta = await load_phase1_job_meta(cid)
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if meta:
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raw_sub = meta.get("submitted_at_utc")
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if isinstance(raw_sub, str) and raw_sub.strip():
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try:
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iso = raw_sub.strip().replace("Z", "+00:00")
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job_submitted_at_utc = datetime.fromisoformat(iso)
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if job_submitted_at_utc.tzinfo is None:
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job_submitted_at_utc = job_submitted_at_utc.replace(
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tzinfo=timezone.utc
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)
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now = utc_now()
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elapsed_ms_since_submit = max(
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0,
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int((now - job_submitted_at_utc).total_seconds() * 1000),
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)
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durations_ms["since_playground_submit"] = elapsed_ms_since_submit
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except ValueError:
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job_submitted_at_utc = None
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elapsed_ms_since_submit = None
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return MemoirPhase1ReadyOut(
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ready=ready,
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checked_segment_ids=ids,
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pending_segment_ids=pending,
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job_submitted_at_utc=job_submitted_at_utc,
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elapsed_ms_since_submit=elapsed_ms_since_submit,
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durations_ms=durations_ms,
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)
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async def submit_memoir_phase1_for_conversation(
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self,
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*,
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conversation_id: str,
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) -> MemoirSubmitOut:
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"""本会话内尚待 Phase1 的 segment 合并提交 Celery(与对话结束 flush 语义对齐)。"""
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cid = (conversation_id or "").strip()
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if not cid:
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raise EvaluationBadRequestError("conversation_id is required")
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conv = await self._db.get(Conversation, cid)
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if not conv or conv.deleted_at is not None:
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raise EvaluationNotFoundError("conversation not found")
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uid = str(conv.user_id)
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stmt = (
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select(Segment.id)
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.where(
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Segment.conversation_id == cid,
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Segment.processed.is_(False),
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Segment.topic_category.is_(None),
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)
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.order_by(Segment.created_at.asc())
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)
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result = await self._db.execute(stmt)
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segment_ids = [str(i) for i in result.scalars().all()]
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if not segment_ids:
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return MemoirSubmitOut(
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conversation_id=cid,
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user_id=uid,
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segment_ids=[],
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celery_task_id=None,
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submitted_at_utc=None,
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elapsed_ms=None,
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)
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t0 = time.perf_counter()
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_, task_id = await memoir_ingest_scheduler.flush_pending(
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uid,
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extra_segment_ids=segment_ids,
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trigger="manual_flush",
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)
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elapsed_ms = max(0, int((time.perf_counter() - t0) * 1000))
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submitted_at = await record_phase1_job_submitted(
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cid,
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celery_task_id=task_id,
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segment_count=len(segment_ids),
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)
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return MemoirSubmitOut(
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conversation_id=cid,
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user_id=uid,
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segment_ids=segment_ids,
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celery_task_id=task_id,
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submitted_at_utc=submitted_at,
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elapsed_ms=elapsed_ms,
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)
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