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…feat/rolling-context-window

…window

# Conflicts:
#	studio/backend/tests/test_gguf_completion_usage.py

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Rolling context eviction currently drops turns with no way for a caller to
learn which ones went. Extract the turn grouping so the eviction unit is
reusable, add an identity-based diff of what a fit removed, and let a caller
reserve room for content it intends to add back after fitting.

The reserve deliberately does not affect whether trimming happens at all, only
how far it goes once it is already required, so a conversation that fits today
is still returned untouched.

An evicted turn is currently gone for the rest of the session, so the model
will state the conversation began wherever its visible context begins. Keep the
turns the rolling window drops in a searchable scope built on the existing
store, chunker, embedder and hybrid retrieval.

The archive is cumulative: every compaction adds to it and nothing is cleared,
so a later compaction can still find what an earlier one evicted. It lives in
its own scope rather than the thread's document scope, because thread documents
are injected in full on every request and would re-inject the whole history.

Idempotent by content hash, since the same turns are evicted again on every
later request. Every entry point degrades to a no-op rather than raising.

Given only a search tool, a model decides for itself whether to look, and
mostly does not. Measured on MRCR v2, a 35B declined on 56% of rows, scoring
0.099 when it skipped against 0.461 when it searched. Forcing one retrieval on
the compaction turn took tool-only 0.258 to 0.604, and the model then called
the tool on 0% of rows, so the common path costs nothing extra.

Recall fires at most once per request, since the tool loop refits on every
iteration. The tool loop renders it as an ordinary tool exchange through the
builder shared with document auto-inject; the plain path prefixes the latest
user message instead, because it sends no tools array and a tool role without
one breaks strict chat templates.

Only scalar counts join the context_truncated event, so no message content
reaches the wire.

Forced recall answers the turn that evicted, but a later turn can refer to
something the forced pass had no reason to fetch. Add search_conversation so
the model can go looking, scoped to the thread's own archive and sharing the
admission slot with document search so the two cannot race for the embedder.

The tool is offered only once a thread has actually had turns archived, so an
ordinary short chat never pays for the schema, and it is classified read-only
so auto mode does not prompt on every call. A matching system-prompt note tells
the model the session was compacted, since otherwise it assumes the
conversation began where its visible context begins.

Deleting a thread now drops its archive rather than leaking a scope per chat.

_select_request_tools also serves the token-count request model, which has no
thread_id field, so the archive gate raised there.

Recalling your own conversation is mostly an exact-match problem: a name, a
number, an identifier someone pasted twenty turns ago. Those live or die on
rare-token matching, and hybrid fusion was losing them.

Measured on a 30-turn walkthrough of a 230k-character document at a 16k window,
where every turn shared the same wrapper text. The chunk holding the needle
ranked 3rd lexically at any k, was never returned by dense retrieval at all,
and RRF pushed it to 16th because it had 30 useless dense hits to fuse with.
End to end the model answered with the exact code once lexical leads, and could
not answer at all before.

Dense still fills whatever the lexical pass leaves, for paraphrased recall.

Editing an earlier message rewinds a thread and continues down a new branch,
but the archive is append-only and still holds everything the abandoned
continuation produced. Verified against a live build: after rewinding past a
turn, querying its distinctive text still returned it, so the model could be
handed a turn that on this branch never happened.

Recall now drops archived turns that are absent from the thread's saved
transcript. Threads with no saved transcript are left unfiltered, since an API
caller may pass a thread_id without persisting messages and an empty transcript
is absence of evidence rather than evidence the turns are gone.

Containment on a normalised prefix rather than a digest, because the archived
copy is rendered from the inference projection and the saved copy comes back
through the message store.

The only signal that a long chat had been compacted was a toast, which vanishes after
a few seconds and does not survive a reload. A user who scrolls back later has no way
to find out why the model seemed to forget the start of the conversation.

The notice renders from metadata.custom.contextTruncation inside the assistant
message's own container, so it is not part of the conversation sent to the model, is
not editable, and is not exported as content, but it stays attached to the turn it
describes. It reports how many messages were dropped and, when the conversation
archive is on, that they are still searchable and how many passages were recalled.

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…ode like JSON.stringify

Reasoning lives in reasoning_content on the wire and never in content, so forwarding
the stored part list rendered a reasoning model's thinking where the request sends only
the answer. And json.dumps escapes non-ASCII by default while JSON.stringify does not,
so a multilingual tool result reconstructed differently from the archived copy. Both
cost the turn its transcript seat.

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…ttempt

The anchor rides in every truncation event and every assistant turn's metadata while the
boundary stays sticky, so a large pasted message was copied across the thread; cap it at
a head on both sides, where the read side already clamps only shallower. And a budget
below one chunk is not no budget: CHUNK_TOKENS is a ceiling, not the size of a turn, so
try one and let the exact recount reject it.