Finding a thing that does not use your words

Three pieces, and the first one is that they are all optional.

Extraction stops being constants. Upload size, image edge, JPEG quality, PDF
pages, extracted characters, orphan age and the text-extension list are settings
now, read through a process-level snapshot rather than a session -- `prepare` and
everything under it are called from routes, tool runners and the startup sweep,
and several of those have no session in hand. Two things deliberately stayed
constants: the decompression-bomb guard, which is a guard and not a preference,
and ORPHAN_AGE, which would have been evaluated at import if it stayed in the
signature and pinned the shipped 24 hours whatever anybody set.

An embedding model is picked from the models an administrator flagged for it, and
one that has since lost its flag is *named* rather than dropped from the picker:
a setting that vanishes is one nobody can tell from a setting never made. Nothing
here is required. Choosing none means no chunk rows, no requests, and
retrieval.search returning exactly what fts.search_ids returns in exactly that
order -- asserted, because it is what makes this safe to land on an instance that
never asked for it.

The two rankings are fused by reciprocal rank fusion: ranks and not scores,
because bm25 is a corpus-dependent negative and cosine is 0..1, and normalising
them onto one scale means picking a constant nobody can tune without a labelled
set they do not have. RRF's one constant is famously insensitive and degrades to
whichever list is non-empty -- which is what turns "no embedding model" into a
branch that does not exist.

A record scores as its best chunk rather than its average, or a long document
about something else outranks a short one that says the thing. Width and model
are stored beside every vector and a mismatch is skipped, because vectors from
two spaces score against each other perfectly happily and mean nothing -- a
search that works and is wrong is the worst failure this can have, and a model
change now leaves stale rows ignored rather than trusted.

Indexing is fired and forgotten, and how a change is noticed is a session event
rather than a call in each of the ten library writers. That is a departure from
this codebase's taste for explicit seams, for the reason tool_label is a Jinja
global: a step every writer has to remember is one that gets forgotten, and here
forgetting is silent -- the record saves, keyword search still finds it, and only
its recall goes stale. Chunks are embedded before anything is deleted, so a
failure leaves the old index rather than half a new one.

Also: `embeddings` joins the model capabilities, and the three tool flags that
had shipped with no checkbox -- canvas, scheduling and helpers -- have one.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
This commit is contained in:
Jaroslav Beneš
2026-08-06 16:15:21 +02:00
parent 78e5717f77
commit 20bb569b00
27 changed files with 2563 additions and 55 deletions
+529
View File
@@ -0,0 +1,529 @@
"""Keeping the semantic index current, and rebuilding it when it is not.
## The shape, and why it is a background task
Embedding is an HTTP request. Every writer in the library -- `documents.create`,
`notes.edit`, `skills.save`, `reports.create` -- is synchronous and is called
from a route or a tool runner that has just committed a row, and none of them
should wait on a model server to answer before saying "saved".
So indexing is **fired and forgotten**: `schedule(kind, id)` starts a task and
returns immediately. A save that cannot be indexed is a save; the row is written
either way and the search falls back to keywords for that record until the next
rebuild. That is the whole degradation story, and it is the same one that covers
having no embedding model at all.
## Nothing is written when no model is chosen
`embedding_model_id` empty means the FTS path exactly as it has always been --
no chunk rows, no requests, no cost. That is what makes this safe to add to an
instance that never asked for it, and it is asserted rather than assumed.
## Staleness is a hash, not a timestamp
Every chunk carries `source_hash` (of the text it was built from), `model_id`
and `dims`. Re-indexing an unchanged record is free; a record whose text moved
is rebuilt; a record embedded by a *different* model is rebuilt on the next pass
and, until then, ignored by the scorer rather than trusted. Vectors from two
spaces score against each other perfectly happily and mean nothing, which is a
search that works and is wrong -- the worst failure this feature can have.
## The rebuild is restartable and reports itself
A half-finished index has to be usable rather than empty, so the rebuild walks
records one at a time and commits each. `progress()` is what the admin page
polls; it is in-process, because a rebuild does not survive a restart and
pretending otherwise would mean a progress bar that never moves.
"""
from __future__ import annotations
import asyncio
import contextlib
import logging
from dataclasses import dataclass, field
from sqlalchemy import delete, func, select
from sqlalchemy.orm import Session as DBSession
from lembas.db.models import (
CHUNK_DOCUMENT,
CHUNK_KINDS,
CHUNK_NOTE,
CHUNK_REPORT,
CHUNK_SKILL,
Chunk,
Connection,
Document,
Model,
Note,
Report,
Skill,
)
from lembas.db.session import session_scope
from lembas.services import settings_store
from lembas.services.library import chunks as chunk_service
from lembas.services.llm.openai_client import Endpoint, LLMError
log = logging.getLogger(__name__)
# What each kind is, and how to get its text. One table rather than four
# branches, for the reason `tool_labels` is one table: four copies of "which
# columns make up the searchable text" is three chances to disagree.
SOURCES: dict[str, tuple[type, tuple[str, ...]]] = {
CHUNK_DOCUMENT: (Document, ("title", "description", "extracted_text")),
CHUNK_NOTE: (Note, ("title", "body")),
CHUNK_SKILL: (Skill, ("name", "description", "body")),
CHUNK_REPORT: (Report, ("title", "summary", "body")),
}
# Tasks in flight, so a record saved twice in quick succession is indexed once
# more rather than twice at the same time. Keyed on kind and id.
_TASKS: dict[tuple[str, str], asyncio.Task] = {}
# --- What the model is ----------------------------------------------------------
@dataclass(frozen=True)
class Embedder:
"""Which model turns text into vectors, resolved while a session is open."""
endpoint: Endpoint
model_id: str
batch: int = 16
def embedder(db: DBSession) -> Embedder | None:
"""The configured embedding model, or None.
None is the answer to every "no" -- none chosen, the model row deleted, its
connection disabled -- and every caller reads it the same way: do nothing,
and let the keyword search stand. That is deliberately not an error. An
instance that never configured this is the common case, not a broken one.
"""
values = settings_store.extraction(db)
wanted = str(values.get("embedding_model_id") or "").strip()
if not wanted:
return None
model = db.scalar(
select(Model)
.join(Connection)
.where(
Model.model_id == wanted,
Model.enabled.is_(True),
Connection.enabled.is_(True),
)
.order_by(Connection.position)
)
if model is None:
log.info("embedding model %r is configured but not available", wanted)
return None
connection = db.get(Connection, model.connection_id)
if connection is None:
return None
return Embedder(
endpoint=Endpoint.from_connection(connection),
model_id=model.model_id,
batch=int(values.get("embed_batch") or 16),
)
def enabled(db: DBSession) -> bool:
return embedder(db) is not None
# --- Reading a record -----------------------------------------------------------
def text_of(row) -> str:
"""The searchable text of one record, in the same order the FTS index uses.
Blank fields are dropped rather than joined as empty lines, so a note with
no body hashes the same before and after somebody clears its body twice.
"""
kind = kind_of(row)
if kind is None:
return ""
_, columns = SOURCES[kind]
parts = [str(getattr(row, name, "") or "").strip() for name in columns]
return "\n\n".join(part for part in parts if part)
def kind_of(row) -> str | None:
for kind, (model, _) in SOURCES.items():
if isinstance(row, model):
return kind
return None
def owner_of(row) -> str:
return str(getattr(row, "owner_id", "") or "")
# --- Writing the index ----------------------------------------------------------
def forget_resource(db: DBSession, kind: str, resource_id: str) -> int:
"""Drop every chunk of one record. Called when it is deleted.
A plain DELETE rather than a cascade, because `resource_id` has no foreign
key -- it points at one of four tables depending on `resource_type`, which
SQLite cannot express. Same reasoning as `Share.principal_id`.
"""
result = db.execute(
delete(Chunk).where(Chunk.resource_type == kind, Chunk.resource_id == resource_id)
)
db.commit()
return int(result.rowcount or 0)
def current_hash(db: DBSession, kind: str, resource_id: str) -> tuple[str, str]:
"""The hash and model of the chunks already stored for a record."""
row = db.execute(
select(Chunk.source_hash, Chunk.model_id)
.where(Chunk.resource_type == kind, Chunk.resource_id == resource_id)
.limit(1)
).first()
return (str(row[0] or ""), str(row[1] or "")) if row else ("", "")
async def index_resource(kind: str, resource_id: str, *, force: bool = False) -> int:
"""Rebuild one record's chunks. Returns how many were written.
Opens its own session, for the reason every background worker here does: it
outlives the request that scheduled it. Never raises -- a failure leaves the
old chunks in place, which is a slightly stale index rather than a hole, and
is strictly better than deleting first and failing to write.
"""
if kind not in SOURCES:
return 0
try:
with session_scope() as db:
model, _ = SOURCES[kind]
row = db.get(model, resource_id)
if row is None:
forget_resource(db, kind, resource_id)
return 0
worker = embedder(db)
if worker is None:
return 0
body = text_of(row)
owner = owner_of(row)
values = settings_store.extraction(db)
digest = chunk_service.digest(body)
stored_hash, stored_model = current_hash(db, kind, resource_id)
if not body.strip():
with session_scope() as db:
forget_resource(db, kind, resource_id)
return 0
if not force and digest == stored_hash and stored_model == worker.model_id:
return 0
pieces = chunk_service.split(
body, size=int(values["chunk_chars"]), overlap=int(values["chunk_overlap"])
)
if not pieces:
with session_scope() as db:
forget_resource(db, kind, resource_id)
return 0
vectors = await _embed_all(worker, pieces)
# Written only once every vector is in hand. Deleting first and failing
# half way through would leave a record indexed by half of itself, which
# ranks worse than not being indexed at all and looks like nothing.
with session_scope() as db:
db.execute(
delete(Chunk).where(
Chunk.resource_type == kind, Chunk.resource_id == resource_id
)
)
for ordinal, (piece, vector) in enumerate(zip(pieces, vectors, strict=True)):
db.add(
Chunk(
owner_id=owner,
resource_type=kind,
resource_id=resource_id,
ordinal=ordinal,
text=piece,
vector=chunk_service.pack(vector),
dims=len(vector),
model_id=worker.model_id,
source_hash=digest,
)
)
db.commit()
return len(pieces)
except LLMError as exc:
log.info("could not index %s %s: %s", kind, resource_id, exc)
return 0
except asyncio.CancelledError:
raise
except Exception: # noqa: BLE001 - one bad record must not stop a rebuild
log.exception("indexing %s %s failed", kind, resource_id)
return 0
async def _embed_all(worker: Embedder, pieces: list[str]) -> list[list[float]]:
from lembas.services.llm import embeddings as embeddings_service
vectors: list[list[float]] = []
for start in range(0, len(pieces), worker.batch):
batch = pieces[start : start + worker.batch]
vectors.extend(await embeddings_service.embed(worker.endpoint, worker.model_id, batch))
return vectors
# --- Scheduling -----------------------------------------------------------------
def schedule(kind: str, resource_id: str) -> None:
"""Index a record soon, without making its writer wait.
Called from synchronous writers that have just committed. Two things it is
careful about:
- **No running loop means do nothing.** A CLI command, a test, or the
startup sweep has no event loop to attach to, and building a coroutine
there produces "never awaited" at the caller's own line. The check is
before the coroutine, the same trap `push.announce_later` documents.
- **A record already being indexed is left alone.** Saving twice in a second
would otherwise embed the same text twice at once; the second call is
dropped and the record is picked up by the *next* save or rebuild, which
is why `index_resource` re-reads the row rather than taking text passed in.
"""
if kind not in SOURCES or not resource_id:
return
try:
asyncio.get_running_loop()
except RuntimeError:
return
key = (kind, resource_id)
existing = _TASKS.get(key)
if existing is not None and not existing.done():
return
task = asyncio.create_task(index_resource(kind, resource_id))
_TASKS[key] = task
task.add_done_callback(lambda _t, k=key: _TASKS.pop(k, None))
def schedule_for(row) -> None:
"""The same, given a record rather than its kind and id."""
kind = kind_of(row)
if kind is not None:
schedule(kind, str(getattr(row, "id", "") or ""))
# --- Noticing a change ----------------------------------------------------------
# Two SQLAlchemy session events rather than a call in each of the ten writers
# that touch these four tables. That is a departure from this codebase's taste
# for explicit seams, and the reason is the one `tool_label` gives for being a
# Jinja global: a step every writer has to remember is a step one of them will
# forget, and here forgetting is *silent* -- the record saves, the keyword search
# still finds it, and only its semantic recall is quietly stale.
#
# `after_flush` collects and `after_commit` acts, in that order and never
# merged. Inside a flush the transaction has not landed yet, so a task started
# there could read the row before it exists; and `session.deleted` is empty by
# the time the commit fires, so the collecting has to happen while it is not.
_PENDING = "lembas_index_pending"
def _collect(session, _flush_context) -> None:
seen: set[tuple[str, str]] = session.info.setdefault(_PENDING, set())
for row in (*session.new, *session.dirty, *session.deleted):
kind = kind_of(row)
if kind is None:
continue
resource_id = str(getattr(row, "id", "") or "")
if resource_id:
seen.add((kind, resource_id))
def _fire(session) -> None:
# A deletion is scheduled exactly like a change: `index_resource` finds no
# row and drops the chunks. One path rather than two, and the one that runs
# is the one that has to be right anyway.
for kind, resource_id in session.info.pop(_PENDING, set()):
schedule(kind, resource_id)
def _forget(session) -> None:
session.info.pop(_PENDING, None)
def install() -> None:
"""Listen for library records changing. Called once, from the app factory.
Idempotent: `event.contains` is checked, because the app factory is called
per test in the suite and registering the same listener a hundred times
would index every record a hundred times over.
"""
from sqlalchemy import event
from sqlalchemy.orm import Session
for name, handler in (
("after_flush", _collect),
("after_commit", _fire),
("after_rollback", _forget),
):
if not event.contains(Session, name, handler):
event.listen(Session, name, handler)
def sweep_orphans(db: DBSession) -> int:
"""Drop chunks whose record has gone.
A backstop for the one case the listeners cannot cover: a delete that
happened with no event loop running -- a CLI command, a test, a cascade from
deleting a user -- where `schedule` had nowhere to put its task. Cheap
enough to run at startup and at the end of every rebuild: one NOT IN per
kind, against an indexed column.
"""
removed = 0
for kind, (model, _) in SOURCES.items():
result = db.execute(
delete(Chunk).where(
Chunk.resource_type == kind,
Chunk.resource_id.not_in(select(model.id)),
)
)
removed += int(result.rowcount or 0)
if removed:
db.commit()
log.info("dropped %d orphaned chunk(s)", removed)
return removed
# --- Rebuilding everything ------------------------------------------------------
@dataclass
class Progress:
"""What a rebuild has done so far.
In-process, because a rebuild does not survive a restart. Persisting it
would mean a progress bar that stops moving and never finishes, which is
worse than one that admits it is gone.
"""
running: bool = False
total: int = 0
done: int = 0
written: int = 0
error: str = ""
kinds: dict[str, int] = field(default_factory=dict)
@property
def percent(self) -> int:
return int(self.done * 100 / self.total) if self.total else 0
_PROGRESS = Progress()
_REBUILD: asyncio.Task | None = None
def progress() -> Progress:
return _PROGRESS
def counts(db: DBSession) -> dict[str, int]:
"""How many chunks exist per kind. What the page shows when nothing is running."""
rows = db.execute(
select(Chunk.resource_type, func.count()).group_by(Chunk.resource_type)
).all()
return {str(kind): int(count) for kind, count in rows}
async def rebuild_all(*, force: bool = True) -> None:
"""Walk every record and index it, committing as it goes.
One at a time and never gathered. The far side is usually one local model
server, and twenty concurrent embedding requests against it is slower than
twenty sequential ones as well as being ruder.
"""
global _PROGRESS
_PROGRESS = Progress(running=True)
try:
with session_scope() as db:
if embedder(db) is None:
_PROGRESS.error = "No embedding model is configured."
return
work: list[tuple[str, str]] = []
for kind, (model, _) in SOURCES.items():
ids = [row[0] for row in db.execute(select(model.id)).all()]
work.extend((kind, str(row_id)) for row_id in ids)
_PROGRESS.total = len(work)
for kind, resource_id in work:
written = await index_resource(kind, resource_id, force=force)
_PROGRESS.done += 1
_PROGRESS.written += written
_PROGRESS.kinds[kind] = _PROGRESS.kinds.get(kind, 0) + written
# After the walk, not before: a record deleted while this was running
# would otherwise be swept and then re-indexed from a row that no longer
# exists. `index_resource` handles that case too, and doing it in this
# order means one pass reconciles both directions.
with session_scope() as db:
sweep_orphans(db)
except asyncio.CancelledError:
_PROGRESS.error = "Stopped."
raise
except Exception as exc: # noqa: BLE001 - a rebuild failing must be reportable
log.exception("rebuilding the index failed")
_PROGRESS.error = str(exc)
finally:
_PROGRESS.running = False
def start_rebuild(*, force: bool = True) -> bool:
"""Start a rebuild if one is not already going. True if this call started it."""
global _REBUILD
if _REBUILD is not None and not _REBUILD.done():
return False
try:
asyncio.get_running_loop()
except RuntimeError:
return False
_REBUILD = asyncio.create_task(rebuild_all(force=force))
return True
async def shutdown() -> None:
"""Cancel the rebuild and any in-flight indexing.
Nothing here is lost that matters: a chunk set is either written whole or
not at all, and the next rebuild picks up whatever was missed.
"""
global _REBUILD
tasks = [task for task in (_REBUILD, *_TASKS.values()) if task is not None]
_TASKS.clear()
_REBUILD = None
for task in tasks:
task.cancel()
for task in tasks:
with contextlib.suppress(asyncio.CancelledError, Exception):
await task
def clear() -> None:
"""For tests: forget the in-process state without touching the database."""
global _REBUILD, _PROGRESS
_TASKS.clear()
_REBUILD = None
_PROGRESS = Progress()
__all__ = [
"CHUNK_KINDS",
"SOURCES",
"Embedder",
"Progress",
"clear",
"counts",
"embedder",
"enabled",
"forget_resource",
"index_resource",
"kind_of",
"progress",
"rebuild_all",
"schedule",
"schedule_for",
"shutdown",
"start_rebuild",
"text_of",
]