Qwen3-Embedding and models like it are trained with an instruction on the
query side only. The prefix goes before the question a knowledge-base
search embeds, at answer time and in the admin API's search; documents
reach /v1/embeddings from llmgw-kb as they are.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
An adapter now has an owner (org, team, project, user or key): only callers
there see it, and to anyone else it is a model that does not exist, absent
from /v1/models too. A training job's owner defaults to the one collection
its pairs come from, must be able to read every collection they come from,
and pairs from a knowledge base are never made public. ctl train publish
keeps the GGUF or PEFT files on the mirror, which accepts uploads now, and
sets the owned adapter after the usual architecture check.
The knowledge bases' cache_salt follows the collections searched rather
than the organization, so two teams of one organization no longer share
cached passages.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
A chat model of the cluster reads each chunk and writes questions a person
might ask of it with the answers it holds, streamed as NDJSON a chunk at a
time, for people to correct before an adapter is trained on it. A chunk that
gave no pairs says so on its own line.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
On an organization, team, project or key, the narrowest winning: llmgw ctl
kb default, POST /api/v1/kb/defaults, and the console's Knowledge screen. A
request's own X-Llmgw-Knowledge overrides it and none turns it off. A default
never refuses a request: a collection the caller cannot read is left out, and
a failed search answers without passages. Removing a collection takes it out
of every default.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Fused by rank, a full-text match on a question's everyday words outvoted a
far nearer meaning: on the PoC, "how much leave do fathers get" found the
annual-leave page before the paternity one (cosine distance 0.44 against
0.25). Now a chunk scores its similarity to the question plus up to 0.3 for
a full-text match, each search brings four times k candidates, the text
search drops Turkish and English stop words, and an operator's search says
when the embedding model did not answer rather than quietly searching text.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Collections made for an organization, team, project or person, their
dimension asked of the embedding model; granted and revoked by path, never
outside their organization; their documents listed and removed; and a search
an operator can try. In the OpenAPI document.
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
