309a051038
数据库与模型：新增多版迁移（章节证据快照、对话血缘、记忆事实/时间线 lineage 等），把「成稿 ↔ 对话/记忆」的溯源信息落到表结构里。 业务链路：会话与 WS、回忆录/故事流水线、记忆写入与 enrichment 等跟着接上线索与快照；新增章节证据快照与评测侧 EvalTraceService 等模块，方便组评审用的证据包。 内部评测：自动化 run 与手工 memoir 评审共用可追溯证据；rubric/ judge 相关脚本与文档有配套调整。 app-eval-web：Memoir/实验详情里能展开看证据摘要与 evidence_trace（含对话轮次 id）；Vite 代理与 development.sh 注入的 API 端口与当前默认内部评测端口一致，避免改端口后页面连错服务。 工程杂项：GitHub Actions / 仓库说明有更新；各适配器与支付/配额/plan 等多处为小改动或跟随主改动的收尾；新增/扩充了?
320 lines
10 KiB
Python
320 lines
10 KiB
Python
"""评测取证 repo：所有查询显式携带 user_id，避免跨租户串数据。"""
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from __future__ import annotations
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from sqlalchemy import or_, select
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy.orm import joinedload
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from app.features.conversation.models import Conversation, ConversationMessage, Segment
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from app.features.memoir.models import Chapter, ChapterStoryLink
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from app.features.memory.models import (
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MemoryChunk,
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MemoryFact,
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MemorySource,
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MemorySummary,
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TimelineEvent,
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)
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from app.features.story.models import Story, StoryEvidenceLink
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def normalize_source_segment_ids(raw: object) -> list[str]:
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"""chapter.source_segments：历史为 list[str]。"""
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if not raw:
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return []
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if isinstance(raw, list):
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out: list[str] = []
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for x in raw:
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s = str(x).strip()
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if s:
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out.append(s)
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# 保序去重
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seen: set[str] = set()
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deduped: list[str] = []
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for s in out:
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if s not in seen:
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seen.add(s)
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deduped.append(s)
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return deduped
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return []
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async def get_chapter_for_eval_trace(
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db: AsyncSession, *, user_id: str, chapter_id: str
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) -> Chapter | None:
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stmt = (
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select(Chapter)
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.where(Chapter.id == chapter_id, Chapter.user_id == user_id)
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.options(joinedload(Chapter.current_evidence_snapshot))
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)
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result = await db.execute(stmt)
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return result.unique().scalar_one_or_none()
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async def get_story_for_eval_trace(
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db: AsyncSession, *, user_id: str, story_id: str
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) -> Story | None:
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stmt = (
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select(Story)
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.where(Story.id == story_id, Story.user_id == user_id)
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.options(joinedload(Story.evidence_links))
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)
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result = await db.execute(stmt)
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return result.unique().scalar_one_or_none()
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async def list_chapter_ids_for_story(
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db: AsyncSession, *, user_id: str, story_id: str
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) -> list[str]:
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stmt = (
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select(ChapterStoryLink.chapter_id)
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.join(Chapter, ChapterStoryLink.chapter_id == Chapter.id)
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.where(ChapterStoryLink.story_id == story_id, Chapter.user_id == user_id)
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)
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result = await db.execute(stmt)
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return list(result.scalars().all())
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async def fetch_segments_for_user(
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db: AsyncSession, *, user_id: str, segment_ids: list[str]
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) -> list[Segment]:
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if not segment_ids:
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return []
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stmt = (
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select(Segment)
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.join(Conversation, Segment.conversation_id == Conversation.id)
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.where(
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Segment.id.in_(segment_ids),
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Conversation.user_id == user_id,
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Conversation.deleted_at.is_(None),
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)
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.order_by(Segment.created_at)
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)
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result = await db.execute(stmt)
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rows = list(result.scalars().all())
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order = {sid: i for i, sid in enumerate(segment_ids)}
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return sorted(rows, key=lambda s: order.get(s.id, 9999))
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async def fetch_turn_refs_for_segments(
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db: AsyncSession, *, user_id: str, segment_ids: list[str]
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) -> dict[str, dict[str, str | None]]:
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"""
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segment_id -> { user_message_id, assistant_message_id }（按 message created_at 取首条配对）。
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"""
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if not segment_ids:
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return {}
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human_stmt = (
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select(ConversationMessage.segment_id, ConversationMessage.id)
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.join(Conversation, ConversationMessage.conversation_id == Conversation.id)
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.where(
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ConversationMessage.segment_id.in_(segment_ids),
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ConversationMessage.role == "human",
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Conversation.user_id == user_id,
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Conversation.deleted_at.is_(None),
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)
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.order_by(ConversationMessage.created_at)
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)
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ai_stmt = (
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select(ConversationMessage.segment_id, ConversationMessage.id)
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.join(Conversation, ConversationMessage.conversation_id == Conversation.id)
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.where(
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ConversationMessage.segment_id.in_(segment_ids),
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ConversationMessage.role == "ai",
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Conversation.user_id == user_id,
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Conversation.deleted_at.is_(None),
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)
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.order_by(ConversationMessage.created_at)
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)
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h_result = await db.execute(human_stmt)
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u_map: dict[str, str] = {}
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for seg_id, mid in h_result.all():
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if seg_id and str(seg_id) not in u_map:
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u_map[str(seg_id)] = str(mid)
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a_result = await db.execute(ai_stmt)
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a_map: dict[str, str] = {}
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for seg_id, mid in a_result.all():
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if seg_id and str(seg_id) not in a_map:
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a_map[str(seg_id)] = str(mid)
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out: dict[str, dict[str, str | None]] = {}
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for sid in segment_ids:
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ss = str(sid)
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out[ss] = {
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"user_message_id": u_map.get(ss),
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"assistant_message_id": a_map.get(ss),
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}
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return out
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async def fetch_ai_messages_for_segments(
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db: AsyncSession, *, user_id: str, segment_ids: list[str]
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) -> dict[str, str]:
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"""segment_id -> AI 消息正文（优先 durable log）。"""
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if not segment_ids:
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return {}
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stmt = (
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select(ConversationMessage.segment_id, ConversationMessage.content)
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.join(Conversation, ConversationMessage.conversation_id == Conversation.id)
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.where(
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ConversationMessage.segment_id.in_(segment_ids),
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ConversationMessage.role == "ai",
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Conversation.user_id == user_id,
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Conversation.deleted_at.is_(None),
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)
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.order_by(ConversationMessage.created_at)
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)
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result = await db.execute(stmt)
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out: dict[str, str] = {}
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for seg_id, content in result.all():
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if seg_id and seg_id not in out:
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out[str(seg_id)] = str(content or "")
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return out
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async def fetch_memory_closure_for_conversations(
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db: AsyncSession, *, user_id: str, conversation_ids: list[str]
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) -> tuple[list[str], list[str], list[str], list[str]]:
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"""
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返回 (chunk_ids, fact_ids, timeline_event_ids, summary_ids)，均限定 user_id。
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路径：MemorySource(conversation_id) -> chunks；facts by source_chunk_id；
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timeline by memory_source_id；summaries 仅 rolling + 与会话 chunk 有交集的（轻量近似）。
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"""
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if not conversation_ids:
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return [], [], [], []
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conv_set = list({c for c in conversation_ids if c})
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src_stmt = select(MemorySource).where(
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MemorySource.user_id == user_id,
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MemorySource.conversation_id.in_(conv_set),
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)
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src_result = await db.execute(src_stmt)
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sources = list(src_result.scalars().all())
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source_ids = [s.id for s in sources]
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if not source_ids:
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return [], [], [], []
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ch_stmt = select(MemoryChunk).where(
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MemoryChunk.user_id == user_id,
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MemoryChunk.source_id.in_(source_ids),
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MemoryChunk.is_excluded.is_(False),
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)
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ch_result = await db.execute(ch_stmt)
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chunks = list(ch_result.scalars().all())
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chunk_ids = [c.id for c in chunks]
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if not chunk_ids:
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fact_rows: list[MemoryFact] = []
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else:
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f_stmt = select(MemoryFact).where(
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MemoryFact.user_id == user_id,
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MemoryFact.source_chunk_id.in_(chunk_ids),
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or_(MemoryFact.status.is_(None), MemoryFact.status != "stale"),
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)
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f_result = await db.execute(f_stmt)
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fact_rows = list(f_result.scalars().all())
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fact_ids = [f.id for f in fact_rows]
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te_stmt = select(TimelineEvent).where(
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TimelineEvent.user_id == user_id,
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TimelineEvent.memory_source_id.in_(source_ids),
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)
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te_result = await db.execute(te_stmt)
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ev_rows = list(te_result.scalars().all())
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timeline_ids = [e.id for e in ev_rows]
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sum_stmt = (
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select(MemorySummary)
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.where(MemorySummary.user_id == user_id)
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.order_by(MemorySummary.updated_at.desc())
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.limit(12)
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)
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sum_result = await db.execute(sum_stmt)
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summaries = list(sum_result.scalars().all())
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chunk_set = set(chunk_ids)
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summary_ids: list[str] = []
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for sm in summaries:
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if sm.summary_type == "rolling":
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summary_ids.append(sm.id)
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continue
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scids = sm.source_chunk_ids or []
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if isinstance(scids, list) and chunk_set.intersection({str(x) for x in scids}):
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summary_ids.append(sm.id)
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return chunk_ids, fact_ids, timeline_ids, summary_ids
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async def load_chunks_by_ids(
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db: AsyncSession, *, user_id: str, chunk_ids: list[str]
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) -> list[MemoryChunk]:
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if not chunk_ids:
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return []
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stmt = select(MemoryChunk).where(
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MemoryChunk.user_id == user_id,
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MemoryChunk.id.in_(chunk_ids),
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MemoryChunk.is_excluded.is_(False),
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)
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result = await db.execute(stmt)
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return list(result.scalars().all())
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async def load_facts_by_ids(
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db: AsyncSession, *, user_id: str, fact_ids: list[str]
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) -> list[MemoryFact]:
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if not fact_ids:
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return []
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stmt = select(MemoryFact).where(
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MemoryFact.user_id == user_id,
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MemoryFact.id.in_(fact_ids),
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or_(MemoryFact.status.is_(None), MemoryFact.status != "stale"),
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)
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result = await db.execute(stmt)
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return list(result.scalars().all())
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async def load_timeline_by_ids(
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db: AsyncSession, *, user_id: str, event_ids: list[str]
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) -> list[TimelineEvent]:
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if not event_ids:
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return []
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stmt = select(TimelineEvent).where(
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TimelineEvent.user_id == user_id,
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TimelineEvent.id.in_(event_ids),
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)
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result = await db.execute(stmt)
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return list(result.scalars().all())
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async def load_summaries_by_ids(
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db: AsyncSession, *, user_id: str, summary_ids: list[str]
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) -> list[MemorySummary]:
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if not summary_ids:
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return []
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stmt = select(MemorySummary).where(
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MemorySummary.user_id == user_id,
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MemorySummary.id.in_(summary_ids),
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)
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result = await db.execute(stmt)
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return list(result.scalars().all())
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def story_link_ids_by_type(links: list[StoryEvidenceLink]) -> tuple[
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list[str], list[str], list[str], list[str]
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]:
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chunks: list[str] = []
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facts: list[str] = []
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timelines: list[str] = []
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summaries: list[str] = []
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for ln in links:
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et = (ln.evidence_type or "").strip()
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eid = (ln.evidence_id or "").strip()
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if not eid:
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continue
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if et == "chunk":
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chunks.append(eid)
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elif et == "fact":
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facts.append(eid)
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elif et == "timeline_event":
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timelines.append(eid)
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elif et == "summary":
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summaries.append(eid)
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return chunks, facts, timelines, summaries
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