ilker/llmgw
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841ee21c12d3a6f7cf933d52906d0ab663e83f45
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4 Commits
Author SHA1 Message Date
Ilker ManapandClaude Opus 5.5 841ee21c12 Batches: OpenAI's Files and Batch APIs, served at the lowest priority under a store lease, each line a request of the key that made it 
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
 2026-10-04 21:00:01 +02:00
Ilker ManapandClaude Opus 5.5 29a7347df2 Requests can be tagged: metadata, x-llmgw-tags and the user field on the usage record, and counted by the tags router.tag_labels names 
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
 2026-10-04 19:45:37 +02:00
Ilker ManapandClaude Opus 5.5 2f07b2ba0b Document guardrails, correct what data.md said leaves the cluster, and regenerate the reference 
Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
 2026-10-04 12:36:37 +02:00
Ilker ManapandClaude Opus 5 b7a97468e0 Answer the two questions asked before a gateway is allowed near anything
CI / test (push) Successful in 1m34s
Details 
Neither had a page. "We have GPUs, now what" was left to the reader, and what
llmgw stores was scattered across four documents and a changelog — which is
the same as not being written down when somebody is doing a security review.

docs/data.md describes the behaviour and leaves the legal mapping to whoever
holds the obligation. Every claim in it was checked against the source, and it
names where to look for each: usage rows carry no text field, keys are stored
hashed, conversations are off until a named project turns them on and cannot be
turned on without a retention window.

It also states the egress exactly, which took reading every outbound call to
say honestly: nothing on the serving path leaves the cluster, and the two
things that can reach outside — fetching weights, and ctl plan reading a model's
architecture — are both started by an operator. Weight fetching points wherever
you tell it, including an internal mirror.

docs/choosing-models.md is the opinion llmgw itself does not have. Three jobs
rather than one model, with the third — embeddings — being the one that gets
forgotten and the one that decides whether the deployment can answer questions
about your company or only questions in general.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
 2026-09-27 08:16:08 +02:00