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AgentLab/backend/app/api/knowledge.py
T
ThearchyHelios df935599f2 知识库:换 embedding 模型不再 500,检索能回指了
三件事,都是"这三个模块一条测试都没有"的后果。

**换 embedder 会让检索整体 500。** 库里是 512 维的本地向量、查询是 1536 维的
远端向量时,cosine 直接 `shapes (1536,) and (512,) not aligned`。from_blob 有
dim 参数,但 kb.py 和 memory/store.py 调用时都没传;而且存量向量属于哪个模型
代码里没有任何地方记着,所以也无从降级。

Chunk / MemoryItem 各加 embed_model + embed_dim(走现成的 _COLUMN_MIGRATIONS,
存量回填空值,正好表示"不知道是谁建的")。检索遇到对不上的向量整体退回纯
关键词并说破,不是把它们当 0 分静默沉底——那样用户看到的是结果莫名其妙变差,
而不是"这里有一批索引该重建了"。配套 kb.reindex + POST /api/kb/reindex。

长期记忆那份一起修了。判重那条更危险:维度碰巧相同但模型不同时 cosine 算出来
是随机数,会把不相关的旧记忆认成"重复",然后把新内容丢掉。

**默认 embedder 没有语义能力,而开关藏在一个环境变量里。** LocalEmbedder 是
特征哈希 + TF,和 BM25 吃同一批词;alpha 默认 0.5 等于给了它一半权重,同义
改写一条都召不回。开启真模型的唯一开关是 AGENTLAB_USE_OPENAI_EMBEDDINGS——
没界面、没人会发现。改成设置项(照 COPILOT_SETTING_KEY 的路子),知识库页顶部
能选能看能重建。

配置失败必须响:第一版写成静默退回本地,但选了 OpenAI 却拿到哈希向量的人,
在搜不出同义表达时完全无从怀疑到这里。现在抛 EmbedderUnavailable,API 400
原样交回"检查 OPENAI_API_KEY 是否配了",且不会把配置改掉。

**检索结果不进工件库。** db_query、工具节点、agent 工具调用都落 put_json 快照,
run_retrieve 什么都不落——于是结论只要来自知识库,"这个数是哪来的"就断在这儿,
而数字回指正是这个项目的签名能力。现在落 kind="retrieval_snapshot",并发一条
retrieve.end 带 artifact id。解码层补了正式映射(原来会掉进"未知事件"兜底,
画成一坨原始 JSON)。

新增 test_kb.py 11 条,补上这三个模块此前的零覆盖,包括 embeddings.py 里
注释记着、但一直没有测试守的那个归一化边界(单条候选被 min_score 误杀)。

端到端在真实服务上验过:撞上存量向量返回 200 + 降级说明(以前 500)、
重建后 stale 归零、配不起来的远端模型 400 且配置不变。
2026-09-19 09:27:07 +08:00

317 lines
10 KiB
Python

from __future__ import annotations
from typing import Any
from fastapi import APIRouter, Depends, File, HTTPException, Query, UploadFile
from pydantic import BaseModel, Field
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.db.base import get_session
from app.db.models import Document, MemoryItem, Skill
from app.memory import kb, store
# --------------------------------------------------------------------------
# 长期记忆
# --------------------------------------------------------------------------
memory_router = APIRouter(prefix="/api/memory", tags=["memory"])
class MemoryIn(BaseModel):
content: str = Field(min_length=1)
scope: str = "default"
kind: str = "fact"
importance: float = Field(default=0.5, ge=0, le=1)
meta: dict[str, Any] = Field(default_factory=dict)
class MemoryOut(BaseModel):
id: str
scope: str
kind: str
content: str
importance: float
use_count: int
meta: dict[str, Any]
created_at: Any = None
model_config = {"from_attributes": True}
@memory_router.get("/scopes")
async def memory_scopes(session: AsyncSession = Depends(get_session)) -> list[dict[str, Any]]:
return await store.list_scopes(session)
@memory_router.get("", response_model=list[MemoryOut])
async def list_memory(
scope: str | None = None,
limit: int = Query(default=200, le=500),
session: AsyncSession = Depends(get_session),
) -> list[MemoryItem]:
return await store.list_memories(session, scope=scope, limit=limit)
@memory_router.post("", response_model=MemoryOut, status_code=201)
async def add_memory(
payload: MemoryIn, session: AsyncSession = Depends(get_session)
) -> MemoryItem:
return await store.remember(
session,
scope=payload.scope,
content=payload.content,
kind=payload.kind,
importance=payload.importance,
meta=payload.meta,
)
@memory_router.get("/search")
async def search_memory(
q: str,
scope: str = "default",
limit: int = 10,
session: AsyncSession = Depends(get_session),
) -> dict[str, Any]:
hits = await store.recall(session, scope=scope, query=q, limit=limit)
return {"query": q, "scope": scope, "results": hits}
@memory_router.delete("/{memory_id}", status_code=204)
async def delete_memory(
memory_id: str, session: AsyncSession = Depends(get_session)
) -> None:
if not await store.forget(session, memory_id):
raise HTTPException(404, "记忆不存在")
@memory_router.delete("/scope/{scope}")
async def clear_scope(scope: str, session: AsyncSession = Depends(get_session)) -> dict[str, int]:
return {"removed": await store.clear_scope(session, scope)}
# --------------------------------------------------------------------------
# 知识库
# --------------------------------------------------------------------------
kb_router = APIRouter(prefix="/api/kb", tags=["knowledge"])
class DocumentOut(BaseModel):
id: str
collection: str
title: str
source: str
mime: str
chunk_count: int
created_at: Any = None
model_config = {"from_attributes": True}
@kb_router.get("/collections")
async def collections(session: AsyncSession = Depends(get_session)) -> list[dict[str, Any]]:
return await kb.list_collections(session)
@kb_router.get("/documents", response_model=list[DocumentOut])
async def list_documents(
collection: str | None = None,
session: AsyncSession = Depends(get_session),
) -> list[Document]:
stmt = select(Document).order_by(Document.created_at.desc()).limit(300)
if collection:
stmt = stmt.where(Document.collection == collection)
return list((await session.execute(stmt)).scalars())
class IngestIn(BaseModel):
collection: str = "default"
title: str = ""
content: str = Field(min_length=1)
source: str = ""
@kb_router.post("/documents", response_model=DocumentOut, status_code=201)
async def ingest(payload: IngestIn, session: AsyncSession = Depends(get_session)) -> Document:
return await kb.ingest_document(
session,
collection=payload.collection,
title=payload.title,
content=payload.content,
source=payload.source,
)
@kb_router.post("/upload", response_model=DocumentOut, status_code=201)
async def upload(
file: UploadFile = File(...),
collection: str = "default",
session: AsyncSession = Depends(get_session),
) -> Document:
raw = await file.read()
if len(raw) > 10 * 1024 * 1024:
raise HTTPException(413, "文件超过 10MB")
try:
content = raw.decode("utf-8")
except UnicodeDecodeError:
raise HTTPException(415, "目前只支持 UTF-8 文本文件(txt / md / json / csv 等)") from None
return await kb.ingest_document(
session,
collection=collection,
title=file.filename or "上传文档",
content=content,
source=file.filename or "",
mime=file.content_type or "text/plain",
)
@kb_router.get("/search")
async def search_kb(
q: str,
collection: str | None = None,
limit: int = 5,
alpha: float = Query(default=0.5, ge=0, le=1, description="1=纯向量, 0=纯关键词"),
session: AsyncSession = Depends(get_session),
) -> dict[str, Any]:
notes: list[str] = []
hits = await kb.search(session, collection=collection, query=q, limit=limit,
alpha=alpha, on_degrade=notes.append)
# 退回关键词这件事要跟着结果一起交出去,而不是只写进服务端日志——
# 调用方(设置页的"试一下"、外部脚本)看到的是结果变差,得知道为什么
return {"query": q, "collection": collection, "results": hits, "degraded": notes}
@kb_router.get("/embedding")
async def embedding_status(
collection: str | None = None, session: AsyncSession = Depends(get_session)
) -> dict[str, Any]:
"""当前用的是哪个 embedder,以及有多少条向量已经对不上了。"""
from app.memory.embeddings import EMBEDDING_SETTING_KEY, embedder_dim, embedder_id
from app.db.models import Setting
row = await session.get(Setting, EMBEDDING_SETTING_KEY)
saved = (row.value if row else {}) or {}
return {
"embedder": embedder_id(),
"dim": embedder_dim(),
"configured": bool(saved.get("kind")),
"kind": saved.get("kind", "local"),
"model": saved.get("model", ""),
"stale_chunks": await kb.stale_count(session, collection),
}
class EmbeddingIn(BaseModel):
kind: str = Field(default="local", pattern="^(local|openai)$")
model: str = ""
@kb_router.put("/embedding")
async def set_embedding(
payload: EmbeddingIn, session: AsyncSession = Depends(get_session)
) -> dict[str, Any]:
"""换 embedding 模型。
建不起来就 400 原样交回原因——选了远端却静默退回本地哈希向量,
用户会以为自己在用语义检索,而搜不出同义表达时完全无从怀疑到这里。
"""
from app.memory import embeddings as emb
from app.db.models import Setting
try:
emb.configure(payload.kind, payload.model)
except emb.EmbedderUnavailable as e:
raise HTTPException(400, str(e)) from e
row = await session.get(Setting, emb.EMBEDDING_SETTING_KEY)
value = {"kind": payload.kind, "model": payload.model}
if row:
row.value = value
else:
session.add(Setting(key=emb.EMBEDDING_SETTING_KEY, value=value))
await session.commit()
return {
"embedder": emb.embedder_id(),
"dim": emb.embedder_dim(),
"stale_chunks": await kb.stale_count(session),
}
@kb_router.post("/reindex")
async def reindex(
collection: str | None = None, session: AsyncSession = Depends(get_session)
) -> dict[str, Any]:
"""用当前 embedder 重算向量。换了模型之后唯一的恢复手段。"""
return await kb.reindex(session, collection)
@kb_router.delete("/documents/{doc_id}", status_code=204)
async def delete_document(doc_id: str, session: AsyncSession = Depends(get_session)) -> None:
if not await kb.delete_document(session, doc_id):
raise HTTPException(404, "文档不存在")
# --------------------------------------------------------------------------
# Skill(方法论)
# --------------------------------------------------------------------------
skills_router = APIRouter(prefix="/api/skills", tags=["knowledge"])
class SkillIn(BaseModel):
name: str = Field(min_length=1, max_length=100)
description: str = ""
instructions: str = ""
examples: list[dict[str, Any]] = Field(default_factory=list)
suggested_tools: list[str] = Field(default_factory=list)
tags: list[str] = Field(default_factory=list)
enabled: bool = True
class SkillOut(SkillIn):
id: str
created_at: Any = None
model_config = {"from_attributes": True}
@skills_router.get("", response_model=list[SkillOut])
async def list_skills(session: AsyncSession = Depends(get_session)) -> list[Skill]:
return list((await session.execute(select(Skill).order_by(Skill.created_at.desc()))).scalars())
@skills_router.post("", response_model=SkillOut, status_code=201)
async def create_skill(payload: SkillIn, session: AsyncSession = Depends(get_session)) -> Skill:
if (await session.execute(select(Skill).where(Skill.name == payload.name))).scalar_one_or_none():
raise HTTPException(409, "同名 Skill 已存在")
row = Skill(**payload.model_dump())
session.add(row)
await session.commit()
await session.refresh(row)
return row
@skills_router.patch("/{skill_id}", response_model=SkillOut)
async def update_skill(
skill_id: str, payload: SkillIn, session: AsyncSession = Depends(get_session)
) -> Skill:
row = await session.get(Skill, skill_id)
if not row:
raise HTTPException(404, "Skill 不存在")
for key, value in payload.model_dump().items():
setattr(row, key, value)
await session.commit()
await session.refresh(row)
return row
@skills_router.delete("/{skill_id}", status_code=204)
async def delete_skill(skill_id: str, session: AsyncSession = Depends(get_session)) -> None:
row = await session.get(Skill, skill_id)
if not row:
raise HTTPException(404, "Skill 不存在")
await session.delete(row)
await session.commit()