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Author SHA1 Message Date
alkinun
502730bbba
Studio: add Deep Research (#7219)
* Studio: add durable Deep Research workflows

* Studio: preserve research integration after upstream updates

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* Studio: keep research worker compatible with Python 3.11

* Studio: address Deep Research lifecycle review

* Studio: preserve durable research recovery

* Studio: preserve research stream and context

* Studio: harden research sources and limits

* Studio: align research with shared chats

* Studio: guard durable research actions

* Studio: protect durable research turns

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* Studio: deepen durable research decisions

* Studio: protect research prompts and queries

* Studio: slim research stream deltas

* Studio: preserve research evidence and citations

* Studio: harden Deep Research (CI, prompt injection, query PII, config, citations)

- Fix backend CI: add research_runs_router to the synthetic routes stub in
  test_desktop_auth so studio.backend.main imports under the health-check test.
- Escape prompt-delimiter tags in the decision and synthesis prompts so gathered
  web/document content cannot close an <untrusted_...> wrapper and inject
  instructions into the local planner/decision/synthesis model.
- Extend the public-query sanitizer to redact Luhn-valid payment cards, phone
  numbers, non-global IPs, and labeled private identifiers before a query can
  reach web search.
- Reject nested credential keys in inferenceRequest and ragScope, not just
  top-level keys, when persisting a durable run config.
- Treat maxSources as one budget shared across web and document sources
  (collection and resume paths) instead of per type, which allowed up to 2x the
  configured cap.
- Preserve document citations whose filename contains a closing bracket by
  tokenizing valid citations before stripping invalid ones.
- Persist Deep Research off when switching to an external model and when enabling
  Web Fetch so a refresh cannot rehydrate a mutually-exclusive state.
- Add regression tests for the query, prompt, citation, and config hardening.

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* Studio: make the research claims table migration atomic

The owner-scoped to global claims migration ran its RENAME, CREATE, INSERT and DROP in autocommit, so an interruption after CREATE left the new table empty, orphaned the rows in the legacy table, and never re-triggered. Wrap the rebuild in an explicit transaction so a crash rolls back cleanly and the migration re-runs on the next boot.

* Studio: block message edits and regeneration during an active research run

After a reload a durable research run is followed by the research store rather than an assistant-ui run, so thread.isRunning is false while research is still active. Message edit, refresh and the edit composer previously gated only on isRunning, which let a normal generation start alongside the running research run. Gate them on the active thread's research state as well.

* Studio: keep the plan review mounted through approval

Keying PlanReview on planRevision remounted it mid-approve when updateResearchPlan bumped the revision, resetting the local pending flag and re-enabling Start research while the approve was still in flight, which allowed a duplicate approve. Key on runId only.

* Studio: drop the redundant deep-research persistence change

setCheckpoint already persists Deep Research off for external models at the top of the function, so the added saveBool was a duplicate, and clearing Deep Research from setWebFetchToolsEnabled guarded a state that is not reachable (Deep Research is local-model only while the Web Fetch pill is external-provider only). Revert both to the pre-hardening version.

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* Studio: harden Deep Research citations, query privacy, and message protection

Address review findings in the Deep Research backend:

- Escape an unbalanced ")" in citation destinations so a source URL cannot
  close the markdown link early and inject a second link, keeping balanced
  parentheses literal.
- Match raw-URL citations on whole tokens so a URL sharing another URL's
  prefix is no longer partially rewritten.
- Redact non-global IPv6 addresses in public search queries, matching the
  existing IPv4 handling.
- Detect credential key names after normalizing case and separators so nested
  openaiApiKey, accessToken, and clientSecret values cannot be persisted.
- Reject client edits to server-managed research prompts and reports at the
  storage layer; only the internal writers pass allow_research_update.
- Scope research searches to the first allowed domains instead of dropping
  site scoping for large allow lists.
- Persist the same fetch evidence bound used during live synthesis so a
  resumed run is not shortened.
- Scope run completion so it only replaces this run's message parts.

Add regression tests for the above.

* Studio: fix Deep Research SSE framing, source counts, and favicon privacy

- Normalize the whole SSE buffer so a CRLF split across transport chunks
  still frames events.
- Count web and document sources together in the activity header so a
  RAG-only run is not shown as zero sources.
- Cap the plan editor at the run's configured maxSteps instead of a
  hard-coded 30.
- Add an allowRemoteIcons opt-out to the sources components and disable
  third-party favicon requests for research sources so visited domains are
  not leaked.

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* Studio: address final Deep Research review findings

* Studio: fit Deep Research synthesis evidence to loaded context, add opt-in web grounding

Size the synthesis evidence budget to the loaded model context so the prompt is not
silently truncated on small contexts. When the evidence overflowed the window the report
degenerated (it echoed the evidence tail instead of writing); the budget now reserves tokens
for the prompt scaffolding and converts the remainder to chars, keeping the full cap when the
context is unknown.

Add opt-in web grounding for auto-read: read the top search results, ingest them into an
ephemeral RAG scope, hybrid-retrieve the passages most relevant to the question with the
existing knowledge-base retriever, and fold those chunks into the step evidence. The scope is
per call and deleted afterwards, so a user's knowledge base is never touched.

Off by default; enable with UNSLOTH_RESEARCH_AUTO_SCRAPE=1. Gated per run by
budgets["maxAutoScrape"], so runs created without it keep legacy snippet-only behavior, and
grounding is skipped when the loaded context is too small for the prompt.

Add tests for the adaptive evidence budget, scraped-text cleaning, the ephemeral web-RAG
retrieval and scope cleanup, and the auto-read evidence path.

* Studio: read Deep Research synthesis context from the inference orchestrator

Make the adaptive synthesis-evidence budget actually engage in the normal Studio
architecture. _loaded_context_length read core.inference.inference, the low-level backend that
lives in the model subprocess and stays unpopulated in the main web process where the research
supervisor runs, so it returned None and the budget silently fell back to the 32000 character
cap (leaving the report exposed to the truncation this was meant to fix). Read the inference
orchestrator instead, and the llama.cpp backend for GGUF, mirroring
routes.inference._monitor_context_length so the budget sizes to the context the API layer
serves. Verified on a running server: at a 12288 token load the probe now reports 12288 and the
budget adapts to 24576 characters instead of the 32000 fallback.

Also:
- Reserve context for the generated report as well as the prompt scaffolding (raise the reserve
  to 4096 tokens) so evidence does not crowd out the output on a small window.
- Honor a numeric UNSLOTH_RESEARCH_AUTO_SCRAPE by passing the per-run maxAutoScrape as the page
  cap to the scraper, instead of always reading the maximum.
- Guard the web-RAG connection acquisition so a get_connection failure returns the documented
  empty result rather than propagating.
- Add a synthesis-context test that patches the real backend accessor (not the probe itself) so
  the production wiring is exercised, plus a scrape page-cap test.

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* Studio: harden Deep Research query redaction and research autosave

- research_runs: extend the opaque-token allowlist so unlabeled Hugging
  Face (hf_) and GitLab (glpat-) tokens are redacted before a query can
  reach web search, without over-redacting public model or version ids.
- runtime-provider: for a server-managed research message, echo the
  backend-stored metadata verbatim on autosave. Merging the client
  metadata re-added client-only fields the server never persisted, so the
  server-side guard saw a diff and rejected every streamed or snapshot
  update with 409.

* Studio: keep composer tool pills always accessible after merge

The merge left the composer line marked always-expanded (data-expanded
"true") while the inner pill row was still gated behind composerExpanded,
so the Search and Code toggles disappeared once the permission mode was
"off" with no other toggle set. Render the primary tool pills
unconditionally, matching the always-expanded layout, and drop the now
unused composerExpanded and permissionMode locals. Fixes the Chat UI
Playwright check that asserts the Search and Code pills stay visible.

* Studio: update Deep Research composer contract to always-expanded layout

The always-expanded composer no longer routes effectiveDeepResearchEnabled
through a composerExpanded expression, so the frontend contract now checks
that it gates the Deep Research composer button render instead.

* Studio: do not bind a research run to a populated assistant reply

create_run adopted any assistant message under the user turn whose
researchRunId was unset, including a prior answer reused by a retry. On
completion _update_assistant drops the untagged text and source parts, so
that answer was silently overwritten. Only bind to an empty placeholder or
this run's own message, and reject a reply that already carries content.

* Studio: harden Deep Research synthesis budget, prompt shielding, and message protection

- research_runs: split the synthesis evidence budget evenly across notes so a
  small context still keeps a slice of every research step instead of dropping
  the later steps after the earliest ones fill the budget.
- research_runs: shield the research question and approved plan before placing
  them in the decision and synthesis prompts, so a closing delimiter in either
  cannot escape its block and inject sibling sections.
- research_runs: redact bearer authorization tokens from public search queries.
- studio_db: include attachments in the research-message change check and guard
  direct attachment deletion, so server-managed research prompts and responses
  cannot be mutated through the attachment paths.
- chat_history: map the protected-message conflict on attachment deletion to 409.

* Studio: strip invalid document citations that contain brackets

The invalid-citation regex stopped at the first closing bracket, so a
citation whose filename contained brackets left its tail (".pdf, p. 9]") in
the report. Match a balanced bracketed span so the whole invalid citation is
removed; valid citations stay protected by the earlier tokenization pass.

* Studio: free the RAG search slot when a lookup times out or is cancelled

The bounded knowledge-base search held the sole admission slot in a detached
worker until the search returned, so a lookup that outlived its timeout (a
stalled embedding or blocked vector call) kept the slot forever and starved
every later lookup, disabling knowledge-base retrieval globally. Release the
slot from the caller when it stops waiting, exactly once, so a detached worker
finishes without re-holding it.

* Studio: remove Websites label from research composer

* Studio: fix Deep Research review findings (RAG slot bound, orphaned workers, hardening)

- Bound the shared RAG search slot to one running worker. The search that is
  doing the embedding/index/GPU work now owns the admission slot until it
  finishes, instead of freeing it on caller timeout while the detached worker
  keeps running, which let a second search enter and stack concurrent work
  behind the capacity-of-one semaphore.
- Cancel active research runs before deleting their thread, project, or all
  history. Deleting cascade-drops the run row, but the worker only notices at
  its next lease check, so it could keep doing model/web/RAG work for a run
  that no longer exists; signalling cancel first shortens that window.
- Shield the planner prompt's conversation and question with _shield_untrusted,
  matching the decision and synthesis prompts, so untrusted text cannot forge
  planner delimiters.
- Do not let a research key-revocation failure replace a successful
  non-streaming completion; log it like the streaming path does.
- Include created_at in the protected research-message guard so a client cannot
  reorder server-managed prompt/response messages while leaving the body intact.
- Reject non-scalar ragScope values; a nested container evades the
  sensitive-key scan when its inner keys are unlisted and would reach retrieval
  code that expects a scalar scope id.

Adds regression tests for each.

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* Studio: remove research composer globe icon

* Studio: use Hugeicons telescope in research composer

* Studio: use Telescope02 icon in research composer

* Studio: standardize Deep Research telescope icons

* Studio: move Deep Research below web and code tools

* Studio: merge grounded page excerpts with search snippets instead of replacing

When auto-scrape grounding retrieved page-body chunks, it replaced the raw
search-result text for that step. If the retrieved chunk was a distractor or
dropped the key fact, the answer-bearing search snippet was lost and grounded
runs regressed below snippet-only accuracy on factual questions (e.g. returning
Apache 2.0 instead of the Qwen License, 403 instead of 404, or a single mirror
diameter instead of the sum).

Keep the search snippets and append the grounded excerpts as supplementary
evidence via a small _merge_scraped_evidence helper. Grounding stays opt-in and
off by default, so legacy runs are unchanged. Adds regression tests.

* Studio: fix stale website access assertion in Deep Research contract test

The dialog heading was renamed to a DialogTitle, so the contract test still
asserted a <span>Websites</span> that no longer exists and failed on every
branch built on this one. Assert the current heading instead.

* Add AGPL-3.0 SPDX header to the two new test files for PR #7219

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* Fix citation loss, effort clamping and nested inferenceRequest for PR #7219

Three review findings, each with a regression test that fails without the fix.

Citation dropped for a bare URL in prose parentheses. _RAW_URL swallows the
closing paren and the old trim set only stripped ".,;:!?", so the catalog
lookup missed and the validator deleted the whole citation, leaving an
unbalanced "(" in the report. New _trim_url_tail follows GFM extended autolink
path validation: one right-to-left pass that interleaves punctuation and
unmatched-")" trimming. Both rules must run in the same loop, else
"https://x/y.)" keeps a stray dot. Balanced parens inside a URL
(Wikipedia-style) still survive. Output verified against cmark-gfm on nine
cases, including "https://x/foo)bar)" which must keep ")bar".

Research runs forwarded reasoningEffort unclamped. The local chat path clamps
to the loaded model's advertised levels; the research branch did not, and the
backend only validates enum membership, so llama.cpp dropped a level the model
lacks and the whole durable run silently fell back to the template default.
Now uses the same helper and the same levels as normal chat. Note this makes
"max" on a gpt-oss low|medium|high model resolve to "low" rather than falling
through to the template default, matching normal chat exactly; the divergence
between the two paths was the bug.

Nested inferenceRequest values were persisted. Every allowed field is a scalar
and the numeric/bool/enum ones reject a container while coercing, but "model"
is stringified with str(), which never raises, so {"auth": "sk-..."} slipped
past the sensitive-key scan ("auth" is not on the list) into the durable run
config as the model id. Mirrors the ragScope guard already in this PR.

Verified: 542 passed across the research/web/sandbox/chat-history backend
suites, frontend contract 10 passed, tsc --noEmit clean.

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* Fix report-stalling regex, uncataloged KB evidence and bracketed titles for PR #7219

Catastrophic backtracking in _DOCUMENT_CITATION. The alternation
(?:[^\[\]]+|\[[^\[\]]*\])* backtracks exponentially on an unterminated
"[Document:" with no later bare "]", which is ordinary malformed model output
and exactly what this sanitizer exists to handle. Runtime quadrupled every two
characters; one realistic 76-char line did not finish in 90s. It runs
synchronously inside async _research (the line below it uses asyncio.to_thread),
so a single bad report pins the event loop and stalls all of Studio, not just
the run. Replaced with the language-equivalent unrolled form, verified identical
on well-formed inputs including bracketed filenames, and linear: a 20,000-char
tail now takes 0.4ms. Not using possessive quantifiers or atomic groups, which
need Python 3.11 while this package declares >=3.9.

Uncataloged knowledge base evidence reached synthesis. When maxSources is
already full, every returned chunk hits the continue, so accepted_rag_sources
stays empty, the "if accepted_rag_sources" rebuild no-ops and rag_result keeps
the raw KB text. That text has no document_source_catalog entry, so the
validator strips any citation to it and synthesis is left building claims on
private KB chunks it cannot attribute. Cleared, gated on rag_sources so a
text-only KB reply is still passed through. The resume branch built rag_evidence
from all restored sources with the same hole, so it now mirrors the live loop.

Bracketed source titles destroyed their own citation. The catalog gave the model
the raw title while the citation writer stripped brackets. Search titles
routinely carry one ("[PDF] Annual Report"), and the prompt tells the model to
copy the title verbatim, producing a label the validator cannot match. Both
sides now share _citation_title.

Verified: 756 passed across the research/web/sandbox/chat-history/rag backend
suites. Each fix has a regression test that fails without it.

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* Keep a durable run alive when no model is loaded for PR #7219

A durable run is claimable within the supervisor's poll interval of startup
(main.py starts it in the lifespan, and claim_next takes any 'running' run whose
lease expired), Studio has no startup model auto-load, and the browser is not
connected yet. So restarting Studio mid-run reliably lands the next model call
on the local endpoint's HTTP 400 "No model loaded". That 400 is not retryable:
_completion retries only >= 500, and _stream_completion, which serves both
planning and synthesis, has no retry at all. The run is marked failed, and the
only recovery is retry, which sets report_text NULL and deletes every
research_plan_step, research_source and research_document_source. Up to an hour
of scraping and synthesis is lost on a plain restart, on the feature whose whole
point is surviving one.

Treat only that refusal as transient: wait up to the run's own
modelTimeoutSeconds for a model to come back, then re-send. Any other 400 still
fails immediately, so no behaviour changes on the happy path. The wait polls
_check_active, so cancellation and lease loss are still honoured, and the model
probe fails open, so a probe error can only send a request, never withhold one.
Each wait is bounded by the run timeout and the number of waits per call is
capped, so a model that keeps disappearing cannot re-send forever.

Deliberately not pinning or restoring the model, which the review comment also
suggested. Auto-switch is opt-in, default off, and GGUF-only, so restoring
would silently evict the model the user just loaded from a background worker,
and comparing the configured name to the loaded id is fragile across variant
suffixes and advertised aliases, so it would break working runs.

Verified: 853 passed across the research/web/sandbox/chat-history/rag/inference
backend suites. Eight of the nine new tests fail without the fix.

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* Make website-policy search reach the whole allowlist and refill past blocks for PR #7219

Two review findings on the website access policy.

Domains past the site: filter cap were undiscoverable. The policy accepts up to
100 allowed domains and the prompt tells the model all of them are searchable,
but scope_search_query always scoped to allowed[:8], so a source in the ninth or
later domain could never be found, and an undiscovered URL cannot be fetched
either. The cap itself is right, search engines stop honouring long OR chains,
so the window now rotates by a hash of the query instead of being a fixed head.
Every allowed domain is reachable across a multi-step run, the same query is
always scoped the same way, and lists at or under the cap are unchanged.

A page of blocked results returned nothing. The policy filters after the search
while DDGS was asked for exactly max_results candidates, so if those happened to
be disallowed the tool reported no results even when valid ones ranked just
below, wasting a research step. Ask for a deeper pool when a policy is set and
stop at max_results allowed entries. No policy means no over-fetch, so ordinary
searches are unchanged.

Verified: 2324 passed across the research/web/sandbox/chat-history/rag/tool
backend suites. The 8 test_studio_api.py failures are pre-existing and need live
OpenAI/Anthropic credentials; they fail identically with these changes stashed.

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* Only overfetch search results when the website policy restricts for PR #7219

Follow-up to 8be0b3699. Every run stores normalize_website_policy(...), which
returns {"allowedDomains": [], "blockedDomains": []} and is truthy even when
nothing is restricted, so the default unrestricted path asked DDGS for four
times as many results on every step. That is pure added latency and timeout
risk, since the filter passes everything and only max_results entries are
returned either way. Test the domain lists rather than the dict.

* Budget the whole research prompt against the loaded context for PR #7219

Only the synthesis evidence was budgeted, so the budget could not prevent the
overflow it existed to prevent.

Measured at head with a realistic prompt (40-source catalog, 12-step plan): the
untrimmable scaffolding is about 7,900 chars and the conversation context adds
up to 12,000 more. On a 4096-token context, which is the GGUF auto-fit floor and
the transformers default, the synthesis request came to about 1.7x the window.
Worse, _synthesis_evidence_budget computed usable_tokens = 0 at or below the
4,096-token reserve and then returned the 1,500-char floor anyway, so it added
evidence to a prompt that already did not fit. The decision prompt had no
context awareness at all: a fixed evidence[-60000:], roughly ten times a small
window, on every step rather than once at the end.

Overflow is not cosmetic here. It either silently truncates and degenerates the
report, as the comment above these constants already warned, or fails the run,
and a failed run is only recoverable via retry, which deletes every plan step,
source and document source and nulls the report.

Both paths now share _prompt_char_budget plus _trimmable_budget: each trimmable
section is measured against what the rest of the prompt leaves, and can reach 0
instead of a floor, because a shorter report beats a destroyed run. Evidence is
budgeted before the chat history, since the evidence is the report. Unknown
context still keeps the full cap.

At 4096 tokens the synthesis prompt now fits (0.6x). Below that it is still
over, since a 40-source catalog alone exceeds the window; that needs a smaller
maxSources, and the context box does accept values down to 128.

test_synthesis_evidence_budget_tracks_loaded_context asserted the old floor at
2048 tokens, which is the bug, so it now asserts 0 and that the rest of the
prompt counts against the same budget.

Verified: 2325 passed across the research/web/sandbox/chat-history/rag/tool
suites. The test_mcp_stdio_sessions failure is pre-existing and fails
identically with these changes stashed.

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* Scope replayed research history to its own attempt for PR #7219

A retry deletes the previous attempt's research_plan_steps, research_sources
and research_document_sources rows but keeps its events, and the SSE route
attaches one live run snapshot to every event it emits, replayed history
included. The step.completed payload carries only position, title, action,
input and sourceCount, so that snapshot is the sole source of the excerpt and
evidence.

On any refresh after a retry, a replayed attempt-0 step was therefore matched
against attempt-1's step row by position alone, and start_position resets to 0
after the delete, so the positions line up exactly. The preserved attempt-0
activity then showed attempt-1's excerpt and evidence, or lost them entirely
when attempt 1 had not yet reached that position, under a banner that says
previous activity is preserved. The run.started resumed branch read the same
cross-attempt snapshot and spliced those activities out.

Both are gated on the event's attempt matching the snapshot's retryCount, which
is the same attempt scoping get_reasoning_text already applies server-side. The
excerpt and evidence fall back to what the activity already holds, so a mismatch
is non-destructive rather than blanking it.

Verified: frontend contract 11 passed, tsc -b exit 0, and the new test fails
without the store change.

* Retry pre-stream failures in the research stream for PR #7219

_stream_completion serves planning, every decision step and synthesis, and it
had no transport retry: a connection error or a 5xx raised before any response
byte failed the durable run, and retry then deletes every gathered source,
document source and plan step. _completion already treats the identical
failures on the identical endpoint as retryable, so the two paths disagreed.

This is partly a hole my own 689b06535 opened. After the no-model 400 the body
is read, the connection returns to the pool, and _wait_for_local_model then
sleeps for up to modelTimeoutSeconds before re-sending on the same client.
Uvicorn's keep-alive is 5s, so that pooled connection is essentially always
server-closed by then, and losing the has_expired race raises
RemoteProtocolError, killing the run the wait existed to save. Also reachable
via a read timeout waiting for headers under prompt-eval load.

Retrying is safe only because nothing has been consumed at that point, and that
is structural rather than a convention: with stream=True httpx returns on the
response headers without calling aread(), and raise_for_status() reads no body,
both verified against the installed 0.28.1. The handler is scoped to the inner
try that ends at break, and _iter_stream_lines sits outside the loop with no
path back to send, so a re-send cannot duplicate report text.

Bounded and mirrors _completion: same >= 500 predicate, same 3 attempts, same
2**attempt backoff, lease and cancellation re-checked before re-sending. The
transport counter and the model-wait counter are independent, so they cannot
multiply. The response is closed before every re-send, as manual stream mode
requires.

Note HTTPStatusError is not a TransportError in httpx, so both are caught
explicitly.

Verified: 2330 passed. Five of the new tests fail without the fix; the three
that pass either way are the invariants that must not change (fail fast on a
real 400, never retry once the report has streamed, existing model-wait path).

* Bound the planning prompt to the loaded context for PR #7219

Completes dc16598a4, which budgeted the decision and synthesis prompts but left
planning unbounded. The question reaches the planner verbatim (a pasted document
arrives here as-is) and the history is capped only at the fixed 12,000 chars,
so on a small context planning could overflow before any plan was persisted,
failing the run without doing any research at all.

Same helpers as the other two paths. The question is budgeted before the
history, since the question is the request.

A test now asserts all three prompt paths hold their own context budget, so a
fourth path cannot be added later without one.

Verified: 2331 passed; the new test fails without the change.

* Keep prompt inputs non-empty and fit the source catalog for PR #7219

Two follow-ups to the prompt budgeting, the first a regression I introduced in
dc16598a4.

The output reserve was a flat 4096 tokens, so on any context at or below that,
including the documented 4096-token GGUF floor, the whole prompt budget came out
as 0. Every trimmable section then sliced to nothing: planning_question became
the empty string, so the planner never saw the request at all, and synthesis
dropped all its evidence. Removing the old floor outright went too far; an empty
prompt is worse than the overflow it was avoiding. The reserve is now capped at
half the window, and the question and the evidence each keep a floor, since one
carries the request and the other carries the answer. A truncated completion is
recoverable, a confidently empty report is not.

The source catalog was the one section still inserted whole. It holds up to
maxSources entries with snippets persisted at up to 4000 chars each, so on a
smaller context it alone could exceed the budget while the code responded only
by zeroing the evidence and history. It is now fitted first, dropping whole
entries from the tail rather than slicing mid-entry, because a half-truncated
URL is worse than an absent one: the validator would strip it and the claim
would be left uncited.

Verified: 2333 passed. All three new tests fail without the change; the question
now keeps 1072 chars at a 2048-token context and 4144 at 4096, where both were
previously 0.

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* Tighten Deep Research comments for PR #7219

Post-convergence comment pass over the 40 source files in the PR diff, limited
to lines the PR itself adds so untouched upstream code in the same files is left
alone. 15 files, 110 insertions, 141 deletions.

The reduction is deliberately small. Almost every comment here records why
something non-obvious is done, a measured result, a spec rule, or the exact bug
it prevents, and those are worth more than the lines they cost, so nearly every
edit is a same-meaning compression rather than a deletion. Kept in full: the GFM
autolink citation for the URL trim, the catastrophic-backtracking note on
_DOCUMENT_CITATION, the prompt-budget notes recording that a reserve at or above
the context leaves nothing, the two measured site: filter findings, and the
remount note on the activity panel key.

Verified comment-only three ways: comment_tools.py reports 15/15 code-unchanged,
and an independent ast.dump comparison with docstrings stripped shows zero of the
12 Python files differing. 421 backend tests and the 11 frontend contract tests
pass, and the phrase the contract test asserts on is still present on one line.

* Harden Deep Research model streams

* Fit Deep Research decision prompts

* Preserve Deep Research follow-up context

* Redact composite credentials from research queries

* Scale Deep Research UI typography

* Address Deep Research refinement review

* Harden Deep Research refinement edge cases

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---------

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Co-authored-by: danielhanchen <unslothai@gmail.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
2026-07-26 23:36:02 -07:00
Souravrajvi0
b448fb5de0
fix(studio): persist connection model selections for remote clients (#7298)
* fix(studio): persist connection model selections server-side

Remote Studio clients could see saved connections but not their enabled
model lists because models lived only in browser localStorage.

Store models and available_models in llm_providers and sync them through
the providers API so alternate clients inherit the same catalog state.

Fixes #7281

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* Hydrate external connections on chat startup (#7281)

Extract provider sync logic into sync-external-providers.ts and call it
from chat-page on mount so persisted model selections appear in the
Connected picker without opening Settings → Connections first.

* fix(studio): backfill connection models and preserve local options (#7298)

Address Codex P2 on remote connection persistence:
- Backfill localStorage model selections to /api/providers when backend
  rows still have empty models_json (legacy upgrades)
- Carry promptCacheTtl and openaiContainerTtlMinutes through startup sync
- Await hydratePersistedSettings before syncing on ChatPage mount

Contract tests: 7 passed; npm run typecheck passed.

* Tighten comments

* Tighten comments

---------

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Co-authored-by: Daniel Han <danielhanchen@gmail.com>
2026-07-23 19:11:50 -07:00
Nilay
f3c085ad9e
Fix resume training crash recovery and MLX checkpoints (#6796)
* Fix resume training crash recovery and MLX checkpoints

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Address review: preserve interrupted stop-and-save output_dir, verify MLX checkpoint

- finish_run: add clear_output_dir flag; preserve output_dir for stopped/error
  unless cancel explicitly clears it (fixes pump finalization wiping persisted path).
- training pump: pass interrupted stop-and-save context into finalize_run_in_db.
- MLX stop-and-save: verify resumable checkpoint exists before sending complete;
  return bool from _write_mlx_stop_checkpoint and add regression tests.

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* Address Codex review: MLX current-step checkpoint and cancel error finalize

- Only skip MLX stop checkpoint write when checkpoint-{current_step} exists;
  stale periodic checkpoints no longer mask missing stop saves.
- Pass clear_output_dir through error-event finalization so Stop-without-save
  cannot leave a persisted output_dir that still offers Resume.

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* Address  review

* Address more reviews

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* more reviews

* clear in-memory output_dir on interrupted cancel

* allow resuming errored runs at the final step

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* Clear persisted output_dir in cancel watchdog path

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* Write MLX stop checkpoint in stop path, keep output_dir on crash finalize

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* fix(studio): harden resumable run finalization

* fix(studio): defer safetensors checkpoint import

* fix(studio): reject stale training cancellation

* fix(studio): replay null resume targets

* fix(studio): serialize terminal cancellation

* Harden resume checkpoint validation and fix stop-save cleanup

- Reject unrecognized shard formats and keep indexed shard paths inside the checkpoint dir
- Require a non-empty tensor record when validating .pt/.bin optimizer and model state
- Always finalize TensorBoard and W&B on stop-save-failure exits
- Refuse writing an MLX stop checkpoint through a symlinked directory
- Clarify the resume rejection message to cover errored runs

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* Tighten resume/checkpoint comments

* Recover resumability when a valid stop checkpoint landed

- Re-validate the current-step checkpoint in the dead-worker and error finalization paths so a stop-and-save that actually wrote a valid checkpoint is not wrongly marked error/resume_blocked
- Accept a valid tensor-free optimizer state (e.g. SGD without momentum); the model-state check still requires real tensors
- Include errored runs in the frontend resume rejection message

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2026-07-21 02:34:58 -07:00
Michael Han
65587c2be7
Studio: Data settings tab, uploaded files manager, quant pinning, and chat image preview fix (#7029)
* Studio: Data settings tab, uploaded files manager, quant pinning, image preview fix

Settings
- New Data tab in the settings sidebar, under Connections. Chat data
  management (archived chats, confirm before deleting, exports, import,
  clear all) moved there from the Chat tab.
- New Archive all chats action with confirmation. Archives every chat in
  Recents and Projects; compare pairs count as one chat.
- New Uploaded files manager listing RAG documents (chats, projects,
  knowledge bases) and chat message attachments with location, size and
  date. Files can be opened in a new tab or deleted. Deleting a chat
  attachment keeps the message text.

Backend
- GET /api/rag/documents lists all uploaded RAG documents with file size
  plus KB and project names.
- GET /api/chat/attachments lists chat message attachments; per
  attachment file and delete endpoints included.

Model selector
- Downloaded GGUF quants can be pinned from the quant row (next to the
  settings and delete actions). Pinned quants show at the top of On
  Device under a Pinned heading as model name plus a grey quant chip and
  load directly with one click. Non GGUF cached repos pin as a whole.
- Toned down the green of the downloaded label.

Fix
- Clicking an image attachment in chat now opens the preview overlay.
  The tooltip trigger wrapper called preventDefault before composed
  handlers ran, which made Radix DialogTrigger skip opening.

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* Studio: image previews and file type chips in uploaded files list

Image attachments now show a small thumbnail (lazy loaded from the
stored bytes, object URL revoked on unmount) and every row shows a grey
uppercase type chip derived from the extension or content type. Non
image rows keep a file icon. Name cell floors its width and clips
overflow so narrow dialogs stay aligned.

* Harden attachment serving, add tests, and polish pinned rows and previews

- Strict base64 decoding for attachment files: corrupt payloads now return
  422 instead of silently serving empty or garbled bytes; whitespace,
  missing padding, the URL-safe alphabet, and RFC 2397 percent-encoded
  data URLs are all handled
- New backend test suite covering attachment listing, size accounting,
  malformed rows, deletion semantics, and every file-serving edge case
- Pinned quant rows show a Loaded tag when that exact quant is active,
  and reveal unpin, settings, and delete actions on hover
- Uploaded files dialog is wider and chat locations link straight to the
  thread the attachment belongs to
- Chat image preview is now a chrome-free lightbox: dimmed backdrop,
  rounded image, corner close button, click outside to dismiss
- File opens go through a synchronous window.open so Safari and Firefox
  popup blockers do not eat them

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* Uploaded files: click a file to jump to its chat, square thumbs, new Data icon

- Clicking a file row (thumbnail or name) now goes straight to the chat it
  belongs to; files without a chat open directly as before
- File thumbnails pin a small 7px radius: the theme scales rounded-md up
  to a near circle at this size
- Settings Data tab now uses the database-setting icon

* Uploaded files is now a Data tab subpage instead of a popup

- Manage swaps the tab body for an inline Uploaded files page with a back
  header, matching the rest of settings navigation
- Size column header and values are left aligned like the other columns
- Column widths tightened so the table fits the settings panel

* Lightbox polish and Data tab row order

- Image preview close button is transparent until hovered
- Preview image no longer rounds its corners
- Import chats now sits below Clear all chats in the Data tab

* Data tab: export chats as fine-tuning data and open them in Recipes

- New Fine-tuning section in Settings > Data converts every chat into a
  JSONL dataset in the OpenAI messages format, one conversation per line
  with string-only system/user/assistant turns
- The Train tab detects this file as chatml natively: no column mapping
  and no standardization pass, and it works with train on completions
  since every assistant turn sits behind the chat template response marker
- Consecutive same-role turns merge, trailing turns without an assistant
  reply drop, and reasoning, tool calls, and images are excluded so chat
  templates format the data cleanly
- Open in Recipes stages the JSONL as a local seed upload, creates a new
  Data Recipe with the seed block preconfigured, and jumps to the editor

* Data tab: load chats straight into the Train tab, row moved to the top

- New Load in Train tab button uploads the fine-tuning JSONL through the
  training dataset endpoint, selects it in the training config store, and
  opens the Train tab with the dataset loaded and format-checked
- Use chats as training data now sits at the very top of the Data tab
- The Chats subheading is gone; chat rows flow directly under it

* Address review findings on the uploads manager and quant pins

- Deleting the last attachment stores '[]' instead of NULL: a NULL reads
  back as a missing field and triggers the legacy IndexedDB backfill,
  which resurrected the deleted attachment on the next chat load
- The attachment file endpoint now serves audio: adapter parts store
  {data, format} raw base64 and compare chats store a bare base64 string;
  media type comes from the attachment contentType or the format
- Compare-chat uploads live in message content parts, not attachments;
  the uploads list now includes those blobs via synthetic content-part
  ids that the same get and delete routes resolve
- Deleting a quant from the expanded repo row also unpins it so a pinned
  row cannot try to load a file that no longer exists
- Thumbnails in the uploads list fetch their blob only once the row is
  visible, so a long screenshot history does not download everything
- Nine new backend tests cover audio serving, content-part listing,
  serving, deletion, and the empty-list delete behavior

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* Data tab: single action dropdown with format choices for chat training data

- The three fine-tune buttons collapse into one dropdown plus a run
  button; pick Load in Train tab, Open in Recipes, or Export JSONL,
  then click the arrow to run it
- The dropdown's Format section adds ShareGPT and Alpaca alongside the
  default OpenAI messages format, ticked like a checklist; all three
  shapes are auto-detected by the Train tab's format check
- Alpaca is single-turn, so each user to assistant pair becomes its own
  record with the system prompt and earlier turns carried in the input
  column
- Shorter description on the training data row
- Uploaded files rows show the size under the file name instead of a
  separate column, matching the tighter layout

* Polish the training data action control

- Run button is a true circle (icon-sm plus rounded-full) with a
  heavier arrow stroke
- Dropdown trigger uses the shared standard chevron and a fixed width
  so switching actions no longer resizes the control

* Shorten the training data row description

* Use the standard chevron for the run button and enlarge the ticks

- Run button uses the shared standard right chevron so it matches the
  dropdown chevron instead of the hugeicons arrow
- Dropdown ticks bumped up a size for legibility

* Reword the training data row description

* Shorten Data Recipes to Recipes in the training data description

* List Export JSONL first and rename the default format to Chat Completions

* Handle legacy string content in fine-tune exports and gate Train on chat-only hosts

- messageToPlainText now accepts plain-string message content, the shape
  legacy and imported histories store, so those conversations export
  instead of being skipped as having no exchange
- The Load in Train tab action is disabled on chat-only hosts the same
  way the sidebar gates Train; the default action falls back to Export
  JSONL there so the run button never uploads a dataset that /studio
  would immediately redirect away from

* Narrow the training data action dropdown slightly

* Drop the format picker from the training data dropdown

Chat Completions (OpenAI messages) is the only export format we ship, so
the ShareGPT and Alpaca options and the Format section are removed. The
export always uses the OpenAI messages shape.

* Address the second round of review findings

Security
- Chat attachment data URLs no longer echo their embedded media type:
  anything that is not a plain raster image serves as octet-stream, so
  imported text/html or SVG payloads cannot render under the app origin
- Uploaded .html/.htm RAG documents serve as text/plain for the same
  reason; the preview sheet only uses the file URL for PDFs

Uploads manager
- Remote image URLs in imported chats are no longer listed as stored
  uploads (nothing to serve, and delete would strip the chat reference);
  the delete guard mirrors the same data:-only rule
- Deleting a content-part upload refetches the list since the remaining
  parts re-index, keeping sibling row ids current
- Deleting a project document from the Data tab invalidates the project
  sources cache like the sources panel does
- Data-tab deletions now patch the loaded thread's in-memory copy via a
  small event, so a later repo sync cannot write the attachment back

Fine-tune export
- Branch siblings from retries stay out of the exported conversation;
  only the selected chain converts (full exports still keep everything)
- Assistant turns before the first user turn drop, preserving leading
  system prompts, so no unconditioned assistant targets are emitted

Four new backend tests cover the media type clamp and remote-URL rows;
two existing tests updated for the clamped types

* Fix uploaded file lifecycle and model state

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* Make archived chats a Data settings subpage

* Studio: fix attachment route tests and pinned quant edge cases

- test_chat_attachments: drop asyncio.run around the synchronous
  /attachments routes (list/get/delete are plain def, so asyncio.run
  raised 'a coroutine was expected' and failed the Repo tests CI job).
- test_chat_attachments: align compare-chat content-part assertions with
  the stable content-hash id scheme (content-part-sha256-...) instead of
  the removed array-index ids; resolve ids from the listing.
- pickers: pass disabled={deleteDisabled} to the pinned-quant delete
  action so a quant cannot be deleted mid model-load, matching the
  expanded variant rows.
- pickers: build the pinned-quant existence set from the query-unfiltered
  cached GGUF repos (format filter still applied) so a pinned quant stays
  findable when the search term matches only its quant name.

* Fix Studio review regressions

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* Guard fine-tune export content blocks

* Add Export button for archived chats

Adds an Export action to the Archived chats view in Settings > Data that
downloads only the archived chats as a JSON backup (their threads, messages
and projects). The button sits in the archived header row and appears only
when archived chats exist.

* Refactor archived export into pure, testable units

Split the archived-chats export into a dependency-free filter
(archived-chat-export.ts) and a shared JSON download helper
(download-json.ts). Skip the download when nothing is archived so a
stray call never drops an empty file. No behavior change to the button.

---------

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
2026-07-20 04:57:44 -07:00
Gaurav Dubey
dc65638b7d
Studio: expose Windows drive roots in the folder browser (#7082)
* Studio: expose Windows drive roots in the folder browser

The model-selection folder browser bounds navigation to the roots returned
by _build_browse_allowlist(), which exposed Linux removable-media mounts via
linux_run_media_mount_roots() but had no Windows analog. As a result a user
on C: could not browse to D:/E: to pick a model directory.

Add windows_drive_roots(), a Windows-only companion to
linux_run_media_mount_roots() that lists readable logical drive roots, and
wire it into both browse-allowlist builders and their suggestion chips so
other drives are both navigable and offered as quick-picks. The helper is a
no-op on Linux/macOS, so existing platforms are unaffected.

Closes #6368

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* Studio: cover the Windows drive-root browse wiring with an integration test

Add an allowlist integration test mirroring the Linux side's
test_legacy_browse_allowlist_includes_linux_run_media_mounts: it extracts
_build_browse_allowlist from routes/models.py, stubs external_media so
windows_drive_roots() yields a fake drive root, and asserts that root becomes
browsable through the built allowlist. Proves the wiring, not just the helper.

* Studio: skip inactive drives via GetLogicalDrives before probing

Resolve active logical drives from GetLogicalDrives() before probing each
letter with os.path.isdir. Probing a drive letter mapped to a disconnected
network share can otherwise block the async backend for tens of seconds per
letter. The call degrades gracefully (falls back to probing all letters) when
ctypes/windll is unavailable, so behavior is unchanged on Linux/macOS. Tests
override the bitmask source to stay deterministic on real Windows hosts.

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* Studio: allow browsing descendants of a drive-root allowlist entry

routes/models.py _is_path_inside_allowlist() checked descendants with
startswith(root_real + os.sep). A drive root ("D:\") already ends in a
separator, so the prefix became "D:\\" and a child like "D:\models" was
rejected with 403 after the browser opened the drive root. Only append a
separator when the root does not already end in one. folder_browser.py already
uses commonpath and was unaffected. Adds a regression test covering the
separator-terminated-root descendant case.

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* Studio: enforce the system-directory denylist during folder browsing

Exposing whole Windows drive roots (and any legacy-registered filesystem root)
widened the browse allowlist above system directories, but the browse
resolvers only re-applied the credential/config denylist, not the
_denied_path_prefixes() system-dir denylist that scan-folder registration
enforces. That let browse-folders enumerate C:\Windows, C:\Program Files,
/etc and /proc.

- Add is_denied_system_path() to both storage modules and enforce it in both
  browse resolvers (legacy routes/models.py and hub folder_browser.py), on each
  resolved child and on the final target, keeping the /run/media carve-out.
- Rework the legacy _is_path_inside_allowlist to use splitdrive + commonpath so
  a Windows drive root authorizes its descendants while a bare POSIX / does not,
  and to compare case-insensitively like the hub browser.
- Reject the filesystem root in the legacy add_scan_folder, matching the hub.
- Hide denied system dirs from browse listings and suggestion chips.
- Add tests/test_browse_denylist.py and update the external-media path tests.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Studio: make browse-denylist tests OS-portable

The browse-time denylist tests used real /etc and tmp_path locations; on macOS
tmp lives under the (legitimately denied) /private/var and /etc resolves to
/private/etc, so three tests failed there. Pin the platform / use a tmp-based
denied prefix so they assert the same behavior on Linux, macOS and Windows.

* Studio: apply the bare POSIX-root guard to the hub folder browser too

The _is_path_inside_allowlist guard that stops a legacy-registered '/' scan
folder from authorizing every absolute path lived only in the legacy browser.
The hub browser used commonpath without it, so a stale '/' row let it descend
into /var, /root, /home -- which the system-directory denylist (/proc /sys /dev
/etc /boot /run) does not cover, while the legacy browser blocked them. Mirror
the legacy guard so both browsers treat '/' identically.

Also resolve each directory entry before the denylist check in both listing
loops, so a symlink or junction pointing into a denied dir is hidden instead of
rendered as a row that 403s on descent. Adds legacy-vs-hub parity tests.

* Studio: bound Windows drive probing so a disconnected mapping can't stall the browser

GetLogicalDrives includes mapped network drives, so a disconnected but still
mapped drive (e.g. Z: -> \\nas\share) stays set in the bitmask and reaches
os.path.isdir, which can block for tens of seconds while Windows tries to
reconnect. Because windows_drive_roots() runs synchronously while building both
folder-browser responses, one stale mapping stalled every browse request.

Probe each surviving drive in a daemon thread bounded by a short timeout and
skip it if it does not answer in time, so a hung mapping is dropped instead of
blocking the caller. Connected drives (local or network) still respond well
within the timeout, so drive discovery is unchanged. Corrects the
GetLogicalDrives docstring, which claimed the bitmask alone prevented the stall.

* Studio: probe drive/media roots once per browse request, not twice

Both folder browsers called windows_drive_roots() (and
linux_run_media_mount_roots()) twice per browse request: once to seed the
allowlist in _build_browse_allowlist() and again to build the suggestion chips.
With the bounded drive probe, a disconnected mapped network drive then paid the
timeout twice per folder click. Probe both once in the request handler and pass
the results into _build_browse_allowlist(), reusing them for the chips, in both
the legacy and hub browsers. Adds a test asserting the roots are reused, not
re-probed.

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* Studio: run the legacy browse endpoint in the threadpool, fix its stale test

Two follow-ups from review of the drive-probe changes:

- browse_folders was 'async def' but does only blocking filesystem I/O (the
  timeout-bounded drive probe, iterdir, realpath). On the event loop a
  disconnected mapped drive waiting out its probe timeout stalled every other
  request. Declare it sync 'def' so FastAPI runs it in the threadpool, matching
  the hub browse endpoint. No await was used in the body.

- test_browse_folders_hides_sensitive_dirs monkeypatched _build_browse_allowlist
  with a zero-arg lambda; the once-per-request refactor now calls it with
  (media_roots, drive_roots), so the lambda raised TypeError. Accept and ignore
  the args.

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* Studio: probe Windows drive roots concurrently so multiple dead mappings don't stack timeouts

windows_drive_roots() probed each candidate serially, so N disconnected-but-mapped network drives each paid the full per-drive timeout in turn (e.g. four stale mappings added ~8s to every folder-browser request). Collect the candidate roots first, then probe them all at once under a single overall deadline, so the added delay stays at ~one timeout regardless of how many drives are disconnected. _readable_dir_within stays as a thin single-path wrapper for its existing callers/tests.

* Studio: tighten comments in the folder-browser drive-root changes

Condense the comments and docstrings added by the Windows drive-root and
system-directory denylist work to be shorter and clearer while keeping the
security and correctness rationale intact. Comment and docstring text only;
no code changes.

* Studio: iterate the input, not the results dict, when collecting readable drive probes

_readable_dirs_within returned {path for path, ok in results.items()...}, but a probe thread that exceeded the join deadline is still alive and can insert its key into results during that iteration, raising 'dictionary changed size during iteration' -- reachable exactly in the disconnected-mapped-drive case the probe exists for. Iterate the fixed input list and read results.get(path) (an atomic read) instead.

* Studio: keep the browse-route containment tests denylist-inert so they pass on macOS

test_browse_folders_route.py exercises allowlist containment and the file-vs-directory guard, not the system-directory denylist. On macOS pytest tmp_path resolves under /private/var, a denied prefix, so _resolve_browse_target 403s the fixture dirs before the containment logic runs (4 failures). Add an autouse fixture that makes is_denied_system_path inert in this file; the denylist keeps its own coverage in test_browse_denylist.py.

* Studio: keep the hub browse tests denylist-inert so they pass on macOS

* Studio: register a UNC share root; only reject local filesystem roots

* Studio: reject device drive roots and browse a registered UNC share root

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* Studio: treat device-namespace volume GUID roots as local filesystem roots

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <danielhanchen@gmail.com>
2026-07-15 00:24:11 -07:00
Nilay
07ecdb34c0
Sort chat recents by last activity (#6844)
* show chat by by last activity

* Update chat thread updated_at logic and enhance sidebar chat item handling

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---------

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2026-07-07 17:54:32 +01:00
ramisworld
01f7e14988
Fix Studio custom folders on Linux external drives (#6799)
* Fix external drive custom folder selection

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Update studio/backend/tests/test_linux_external_media_paths.py

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

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* Keep legacy media scan validation strict

* Apply sensitive-dir denylist to legacy folder browser for PR #6799

The legacy /api/models browse endpoint gained the new /run/media mount
roots in its allowlist but not the credential/config guard that scan-folder
registration and the Hub browser already enforce. Filter sensitive names
during enumeration and reject them in _resolve_browse_target so .ssh, .aws,
.config, etc. under allowlisted roots stay unbrowseable, matching the Hub
browser. Add a public contains_sensitive_path_component helper and cover the
legacy resolver with a regression test.

* Trim redundant comments in PR #6799 changes

* Skip sensitive Linux media roots

* Reject sensitive dirs at exact browse roots for PR #6799

Both _resolve_browse_target functions only checked contains_sensitive_path_component
while walking descendant parts, so requesting an allowlisted root itself (empty
relative path) returned it unchecked. A pre-existing scan-folder row under ~/.ssh,
~/.aws, ~/.config, etc. (registerable before the denylist was added) is re-added to
the allowlist on upgrade and could then be browsed. Check the resolved target once
before returning in both the legacy and Hub browsers, and cover the root case in
both test suites.

* fix: avoid unused path helper reexports

* fix: import sensitive path helpers directly

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---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Co-authored-by: imagineer99 <samleejackson0@gmail.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
2026-07-03 19:10:04 +01:00
Michael Han
4f24b12cc9
Studio: customizable RAG embedding model with HF search, settings tab reorganization (#6800)
* Add customizable RAG embedding model setting and reorganize settings tabs

Chat with files, project sources, and knowledge bases previously always
embedded with unsloth/bge-small-en-v1.5. This adds a Settings option to
pick any Hugging Face embedding model (or local path), with HF search
autocomplete, server-side verification that the repo is actually an
embedding model, and a save anyway escape hatch for offline or local
models. The setting persists in app_settings and applies at runtime to
both the sentence-transformers and llama-server GGUF embedder backends
without a restart.

Also reorganizes the General settings tab: Documents & RAG sits above
Uploads, Helper LLM moved above the danger zone, and Model auto-switch
(OpenAI API) moved to the bottom of the API tab.

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* Support local model paths on the GGUF embedder and normalize default saves

Found by simulation testing of the embedding model setting:

Local paths saved as the embedding model now work on the llama-server
GGUF backend (the default backend on macOS and CPU). A path to a .gguf
file is used directly and a directory is scanned for a variant-matching
non-mmproj .gguf, with a clear error when none exists. Previously a
local path was sent to the HF hub API and failed with a repo lookup
error.

Saving the default model explicitly no longer stores an override, so
is_custom stays false and the UI does not show a reset button for the
default value.

* Address review: stale-vector handling, GGUF derivation, save-time guards

Review follow-ups, each verified by new tests:

Re-uploading a document after an embedding model change now re-indexes
instead of deduping by content hash. Documents record the embedder that
produced their vectors (lazy embedding_model column, NULL legacy rows
keep deduping) and a mismatch replaces the old document.

A vector width change no longer bricks the dense index. ensure_vec
drops and recreates chunks_vec when the dim changes (old vectors are in
a foreign space and only block inserts) and search_dense returns empty
on a width mismatch instead of surfacing a vec0 error, so lexical
search keeps working until documents are re-uploaded.

Saving a local sentence-transformers folder with no .gguf now returns
409 with a clear message when the install embeds via llama-server,
instead of failing at first index. force still saves.

A custom RAG_EMBEDDING_MODEL env without RAG_EMBED_GGUF_REPO now
derives the -GGUF companion repo instead of silently keeping the bge
GGUF on CPU and macOS installs.

The resolved GGUF path is tagged with the repo captured at entry, so a
setting change during a download cannot mark the old model as current.

GGUF repo detection matches gguf as a whole name segment rather than a
substring, hf_token is trimmed before verification, and the settings
combobox drops a redundant state mirror of its controlled value.

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* Shrink embedding model font to 11px in the input and dropdown

The combobox wrapper applies className to the outer input group, so the
size utility must target the inner input element; the previous text-xs
never reached it and the field rendered at the browser default.

* Show curated unsloth embedding models when the search field is empty

The empty-query listing was the global top-downloads page, which holds
no unsloth mirrors for the unsloth-first float to reorder, so the
dropdown opened on third-party models. Match the model picker: curated
unsloth listing when empty, whole-Hub search once a query is typed.

* Address review: settings resilience and index consistency

Keep the last known embedding model on settings store errors, remove the
re-entrant dim lock in the llama-server backend, accept local GGUF saves
and verify GGUF availability for HF repos on that backend, match local
path embedders exactly in model list filters, drop same-width stale
vectors from dense search, pin the embedder per ingestion job, and only
replace completed documents after the re-index succeeds.

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* Consolidate the GGUF repo derivation tests

* Trim to a single core embedding-model test

* Address review: GGUF repo saves and cache race

Accept a GGUF-named HF repo on the llama-server backend by verifying GGUF
availability instead of the sentence-transformers metadata gate, and guard
the settings cache with a generation counter so a read overlapping a save
cannot repopulate it with the pre-save value.

---------

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2026-07-02 05:26:33 -07:00
Daniel Han
5211b506e1
Studio: opt-in OpenAI /v1 model auto-switch and idle keep-warm (#6392)
* Studio: opt-in OpenAI /v1 model auto-switch and idle keep-warm

The OpenAI-compatible endpoints serve whichever GGUF is loaded and ignore the
request model field, so an OpenAI client that changes model never reloads. Add
an opt-in setting that, when a /v1 request names a downloaded local GGUF
different from the loaded one, loads it before serving by reusing the existing
/load path (its dedup, tensor fallback, and threading apply). Unknown names
still serve the loaded model, so drop-in compatibility is preserved and no
remote download is triggered.

Also add an optional idle auto-unload (TTL keep-warm): a pure-ASGI middleware
tracks in-flight inference requests so a stream is never unloaded mid-response,
and a lifespan loop unloads the model after the configured idle seconds. Both
settings default off and live in the app_settings store, exposed via
GET/PUT /api/settings/openai-auto-switch.

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* Studio: variant-aware auto-switch, /v1/responses coverage, keep-warm load stamp

Follow-ups from review of the opt-in OpenAI auto-switch path:

1. Variant-aware dedup. _maybe_auto_switch_model compared only the repo id, so
   requesting another quant of the loaded repo (e.g. Q4_K_M loaded, Q8_0 asked)
   was served by the old quant. Compare hf_variant too, matching /load dedup.

2. Streaming /v1/responses now calls the auto-switch hook. It went straight into
   _responses_stream and only checked is_loaded, so stream=True could serve the
   old model or 400. Non-streaming already routed through chat completions; the
   hook is idempotent once loaded.

3. resolve_local_gguf tries an exact id match before splitting a trailing
   :VARIANT, so local ids that contain a colon (e.g. a Windows path) resolve
   instead of being cut at the drive letter.

4. Idle keep-warm stamps activity on a load/swap transition. _last_active was
   only refreshed by inference requests, so a model loaded after the server sat
   idle past the TTL could be unloaded before its first request.

Tests cover each case.

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* Studio: make the /v1/responses auto-switch test order-independent

The new streaming-responses test passed in isolation but failed under the CI's
randomized collection order with "object has no attribute 'state'": it passed a
bare object() as the request and stubbed only one dispatcher, so an ordering
where the real dispatcher ran hit request.state. Give the request a state and
stub both dispatchers; the test still asserts the hook fires before dispatch.

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* Studio: assert /v1/responses auto-switch wiring on source, not at runtime

The behavioral version executed openai_responses and relied on stubbing its
callees, which a randomized collection order in CI could defeat (the real
dispatcher ran and hit request attributes). Assert on the function source that
the hook precedes both dispatchers instead; the hook's runtime behavior is
already covered by the direct _maybe_auto_switch_model tests.

* Studio: auto-switch on /v1/embeddings, GGUF-only targets, idle-unload race gate

Second-pass review follow-ups on the opt-in auto-switch path:

1. /v1/embeddings now calls the auto-switch hook before the loaded-state check,
   matching the other model-bearing OpenAI endpoints (the keep-warm middleware
   already treats embeddings as inference).

2. The resolver index is now GGUF-only. The local-model scanners also surface
   Transformers/safetensors repos; without a filter, auto-switch could unload
   the GGUF and route a request into the non-GGUF loader. _has_local_gguf checks
   a direct .gguf, a models-dir folder, and the HF-cache snapshots layout.

3. Idle keep-warm now holds an asyncio gate across the idle check and the
   unload, and a request bumps inflight under the same gate, so the loop can no
   longer unload in the window between "looks idle" and the kill.

Tests cover each. Broader local-model source parity (LM Studio, Ollama, legacy
caches, custom scan folders) is a follow-up; missing one of those today just
falls through to the loaded model.

* Studio: variant-aware local resolver, count_tokens + audio auto-switch coverage

Third-pass review follow-ups on the opt-in auto-switch path:

1. The resolver is now variant-aware via list_local_gguf_variants. It indexes
   only the quants actually on disk, recursing snapshots and quant subdirs such
   as the nested per-quant folders, so a requested repo:VARIANT resolves only
   when that quant is local and a bare repo resolves to a concrete local quant.
   This fixes two gaps: the previous shallow glob rejected nested-variant GGUF
   repos, and a request for an uncached quant could send /load down the remote
   download path, breaking the local-only contract.

2. /v1/messages/count_tokens now auto-switches like its sibling /v1/messages, so
   a count uses the requested model's tokenizer.

3. /api/inference/audio/generate (direct GGUF TTS) is now tracked as in-flight
   inference, so the idle loop cannot unload the model mid-generation.

Tests cover each. Two reviewer items are left as follow-ups: indexing the
remaining local sources (LM Studio, Ollama, legacy/default caches, custom scan
folders), which fails safe today by falling through to the loaded model; and
fully serializing concurrent different-model requests, an inherent limit of the
single-slot llama backend that the opt-in feature is not designed around.

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* Studio: make local GGUF resolver fail-safe so a bad model name cannot 500

The auto-switch hook calls resolve_local_gguf without its own guard, and
/v1/completions and /v1/embeddings pass body.get("model") through unchanged.
A non-string model (e.g. {"model": 123}) or any internal scan failure would
then raise out of the resolver and turn a request that would otherwise be
served by the loaded model into a 500, breaking the drop-in compatibility the
feature is built on.

Guard the resolver at its boundary: reject non-string input up front and wrap
the lookup so any failure returns None (fall through to the loaded model).
Add regression tests for both paths.

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* Studio: per-model launch flags for auto-switched GGUF models

* Studio: list switch-eligible GGUFs in /v1/models when auto-switch is on

* Studio: settings UI for OpenAI model auto-switch and idle auto-unload

* Studio: show save error over the disabled-idle hint in auto-switch settings

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* Studio: address gemini review (case-insensitive /v1/models retrieve, idle-input empty guard)

* Studio: address codex review (deterministic override args, exclude probe/embedding models from discovery)

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* Studio: keep-warm count_tokens, gate idle on auto-switch, drop hidden models

Three hardening fixes to the opt-in auto-switch path surfaced while reviewing
the work that builds on it:

1. count_tokens keep-warm. /v1/messages/count_tokens counts via the loaded
   tokenizer and already auto-switches, but the keep-warm middleware did not
   track it, so idle auto-unload could free the model mid-count. It is now a
   tracked in-flight path.

2. "Off means unchanged" for idle unload. get_auto_unload_idle_seconds now
   reports 0 while auto-switch is disabled. Idle unload only makes sense with
   auto-switch on (an unloaded model returns only via the next request's swap),
   so a stray TTL can no longer trigger a destructive unload while the feature
   is off, keeping the disabled state identical to pre-feature behavior.

3. Hidden models are not switch targets. The resolver index now skips what
   Studio hides from its own pickers (the llama.cpp validation probe, RAG
   embedding weights) via _is_hidden_model, so they can never be auto-switched
   to by name.

Tests added for each.

* Studio: bare-id reuse, responses validation order, in-flight tracking

Review follow-ups after folding in the per-model overrides and discovery work:

1. A bare model id (no :VARIANT) is now satisfied by any loaded quant of that
   repo. Previously a bare name resolved to the largest local quant, so it could
   force a slow reload when a different quant of the same repo was already
   serving. An explicit repo:VARIANT request still honors the quant.

2. /v1/responses now runs the auto-switch hook after the empty-input validation
   so a request that 400s can no longer trigger a multi-minute model load before
   being rejected. The hook still precedes both dispatchers, so streaming
   requests switch.

3. The keep-warm middleware now tracks in-flight requests whenever auto-switch
   is enabled rather than only when the idle TTL is already positive, so a stream
   that starts with the TTL at 0 is still protected if idle-unload is enabled
   mid-stream. Off still passes straight through.

Tests added for each.

* Studio: tighten auto-switch code comments

Comment/docstring-only pass over the OpenAI auto-switch feature: collapse
multi-line blocks, drop a comment that restated the gate it sits next to, and
trim verbose docstrings on internal helpers while keeping the load-bearing
rationale (concurrency, API behavior, drop-in compat, gotchas). No logic
change: verified comment-only with the AST/printer signature check.

* Studio: bind auto-switch locks per running loop

Review follow-up. The auto-switch swap lock and the keep-warm unload gate were
module-level asyncio.Lock objects. That is safe under the single uvicorn loop
and on Python 3.10+ (the Lock resolves the running loop lazily on acquire), but
a module-level Lock binds to one loop on pre-3.10, which can raise a loop
mismatch in multi-loop runners. Resolve each lock through a per-loop accessor
backed by a WeakKeyDictionary so every running loop gets its own Lock and stale
loops are collected. No behavior change under the server's single loop.

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* Studio: auto-switch re-review fixes (body codes, coverage, swap, alias, tracking)

Follow-ups from a second review pass over the opt-in OpenAI auto-switch feature:

1. OFF-state status codes: /v1/completions and /v1/embeddings moved the body
   read ahead of the loaded-state check, so a malformed/empty body with no model
   loaded returned 500 instead of the prior 503. A shared helper reads the body
   defensively (an unparseable/non-dict body yields no model), and the handler
   re-reads after the 503 gate to surface the original parse error exactly as
   before. OFF behavior is unchanged.

2. Local-model coverage: the resolver index only scanned ./models and the active
   HF cache, while the model picker also lists the legacy/default HF caches, LM
   Studio dirs, and user scan folders. A request for one of those named models
   silently served the loaded model instead. _build_index now scans the same
   roots (Ollama's symlink-creating scanner is skipped on the request path), and
   resolution is offloaded with asyncio.to_thread so the wider scan never blocks
   the event loop.

3. Swap vs in-flight stream: a cross-model swap killed the llama-server while
   another client was still streaming from it. The hook now tracks how many
   requests are streaming on the loaded model (in-flight minus those still inside
   the hook) and returns 409 instead of swapping while one is active. Concurrent
   same-model requests never reach this path, so they are unaffected.

4. Idle-unload + alias: after idle-unload freed the model, an unknown/alias name
   resolved to nothing and 503'd, though it served the active model before the
   TTL. Idle-unload now remembers the freed id and an alias request reloads it
   (only an already-local model, so no remote download), cleared once a model is
   loaded again.

5. In-flight tracking: the keep-warm middleware tracked in-flight only while the
   feature was on, so a stream started while off could be unloaded if idle-unload
   was enabled mid-stream. It now tracks on every inference path; counting is
   cheap and invisible to clients.

Tests added for each.

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* Remove stray async_task_outputs files committed by mistake

* Studio: auto-switch review round 3 (revert swap guard, hardening)

Addressing a third review pass:

- Revert the cross-model swap guard. It counted keep-warm in-flight (which
  includes external-provider calls that never touch the local model) and so
  could 409 a local swap spuriously, and it still left a same-model request able
  to start streaming on the model a concurrent swap was unloading. A correct fix
  needs a request-lifetime reader/writer barrier; a partial guard was worse than
  the honest single-slot behavior, so concurrent different-model use is back to
  being serialized (documented), like llama-swap's single slot.
- Non-string request model (e.g. {"model": 123} on a raw-body endpoint) is now
  treated as absent, so it falls through instead of raising in the membership
  checks once an idle-unload stash exists.
- Idle-unload now stashes and replays the freed quant: an alias reload restores
  the exact (id, variant) that was freed rather than the largest local quant.
- Anthropic /v1/messages validates max_tokens before the auto-switch hook, so a
  request that 400s never triggers a model load.
- Keep-warm tracks a pending count for requests waiting on the unload gate, so
  the idle loop cannot unload the model out from under a request that is blocked
  on the gate but not yet counted as in-flight.
- The idle-unload task is awaited after cancel on shutdown to avoid pending-task
  warnings.
- The resolver's HF cache scan is None-safe and logs at debug instead of letting
  a bad root abort the whole index build.
- upsert_app_setting_map_entry rolls back explicitly on error.

Tests updated/added for each.

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* Studio: keep saved idle-unload seconds when auto-switch is toggled off

* Studio: auto-switch hardening (thread-safe lock maps, body validation)

Defensive fixes from review:

- Guard the per-loop WeakKeyDictionary get-or-create for both the unload gate and
  the auto-switch lock with a threading lock, since WeakKeyDictionary mutation is
  not thread-safe when two event loops run on different threads.
- Build the resolver index under the cache lock so concurrent callers with an
  expired cache don't all run the multi-dir scan at once.
- /v1/completions and /v1/embeddings return a clean 400 for a valid JSON body
  that is not an object (e.g. a list), instead of a 500 from body.get(...).
- The keep-warm middleware only tracks POST requests (inference is always POST),
  so CORS preflight (OPTIONS) is not counted, and tolerates a None path.

Tests added for the list-body 400 and the non-POST skip.

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* Studio: auto-switch review round 4 (local-path load, swap guard, idle fixes)

From a 10-reviewer pass:

- HF-cache entries now load by a concrete local path, not the bare repo id. The
  resolver records a load_path (the snapshot dir for a models--* cache repo, the
  file/dir otherwise) so /load takes the local branch and can never trigger a
  download to satisfy a partial cache. The advertised loader_id (repo id) is kept
  as the launch-override key. resolve_local_gguf now returns
  (load_path, variant, loader_id).
- Re-add a single-slot swap guard: a cross-model swap returns 409 model_switch_busy
  while another inference request is active rather than killing its stream (the
  caller is excluded from the count), and holds the keep-warm gate across the load
  so no new inference starts mid-swap. Concurrent same-model requests never reach
  this path. A residual spurious 409 is possible while a concurrent or external-
  provider request is active; that is the documented single-slot tradeoff.
- Idle keep-warm tracks (model_identifier, hf_variant): reloading the same repo at
  a different quant counts as a fresh model, so it is not unloaded before one TTL.
- Track Studio's own /api/inference/generate/stream so the idle loop can't unload
  the model mid-stream on that route.
- A successful manual /load clears the idle-unload reload stash synchronously, not
  only on the next idle poll.

Also merged origin/main (the branch had fallen behind, which would have reverted
unrelated files on merge). Tests added/updated for each.

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* Studio: auto-switch review round 5 (concurrency, identity, load gate)

From a 10-reviewer pass (9 request-changes, 1 approve):

- Concurrent same-target requests load once instead of each returning 409. The
  count-based busy guard could not tell "another request wants the same model"
  (safe, load once) from "another request is using the loaded model" (refuse).
  Track in-flight auto-switch requests per (target, variant) and subtract
  same-target waiters from the busy count; a cross-model swap still 409s while a
  genuinely different request is active.
- Fix the identity confusion introduced when round 4 began loading by concrete
  local path: the backend identifier became a filesystem path. Record the
  advertised repo id on the backend after an auto-switch load and use it so
  (a) a model loaded manually by repo id is recognized as already serving
  (no spurious reswap/409), (b) /v1/models reports the repo id, never a host
  path or a duplicate, and (c) the idle-unload stash keeps the override keyed by
  the repo id, so an alias reload after TTL keeps the user's saved launch flags.
- Gate the manual /load route with the keep-warm lifecycle gate so idle
  auto-unload can't unload a model mid-load. load_model now wraps _load_model_impl
  in the gate; auto-switch calls _load_model_impl directly since it already holds
  the gate.
- Restore default-off parity on Anthropic /v1/messages: an unloaded backend with
  auto-switch disabled 503s before the max_tokens 400 check, as it did pre-feature.
  When the feature is on, request-shape validation still runs before any load.

Tests added for each; full backend suite diff vs baseline is unchanged.

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* Studio: auto-switch review round 6 (concurrency ordering, leaks, unload gate)

From a second 10-reviewer pass (8 request-changes, 2 approve):

- Same-target concurrency: register a waiter by the raw requested model before
  the (slow) resolve, and exclude pending requests from the swap busy count. The
  middleware counts a concurrent same-model request as in-flight before it
  resolves and joins the resolved-target waiter map, so the prior fix could still
  409 it. The guard now subtracts max(same resolved-target, same raw-request)
  waiters and ignores pending (a pending request is blocked in the middleware,
  not generating, so a swap can't interrupt it).
- External-provider requests no longer block a local swap. The keep-warm
  middleware counts every inference-path POST, but external-provider chat returns
  before the auto-switch hook and never touches the local GGUF. The chat handler
  now untracks itself before proxying, so its in-flight stream can't trip
  model_switch_busy on a concurrent local auto-switch. The middleware skips its
  own end-decrement for an untracked request.
- Manual /unload is gated like load and idle-unload: it holds the lifecycle gate
  and returns 409 rather than tearing down llama-server while an inference request
  is in flight.
- Response model id no longer leaks the load path. /v1/models already advertised
  the repo id; chat, completions, embeddings, Anthropic messages, and audio
  response bodies now use the same _llama_public_model_id helper instead of the
  concrete on-disk model_identifier.
- Chat completions validates the non-system-message requirement before the
  auto-switch hook (as /responses and /messages already do), so an invalid
  request can't swap the resident model before returning 400.

Tests added for each; full backend suite diff vs baseline is unchanged.

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* Studio: auto-switch review round 7 (teardown policy, Unsloth-active swap, training)

From a third 10-reviewer pass (9 request-changes, 1 approve), all on the same
asymmetric-teardown theme. Resolved per the intended policy that only automatic
paths defer to an active stream; deliberate user actions stay interrupting:

- Revert the manual /unload in-flight guard added last round. A manual /load or
  /unload is a deliberate action and tears down immediately, as before; only the
  automatic idle-unload loop and auto-switch defer to an active request. This
  removes the asymmetry the reviewers flagged (manual /load, the /unload Unsloth
  branch, and the opposite-backend swaps inside _load_model_impl) by not
  extending the guard to deliberate paths, rather than spreading it.
- Auto-switch now refuses a swap whenever another inference request is in flight,
  not only when a GGUF is already loaded. _load_model_impl also unloads an active
  Unsloth/transformers backend before loading a GGUF, so the busy guard must cover
  that case too; otherwise an Unsloth stream could be killed by an auto-switch.
- Refuse API-initiated training while inference is active. When Studio is driven
  as an inference API (sk-unsloth key auth), POST /api/training/start returns 409
  if a request is in flight, since training frees VRAM by unloading the chat
  model and would kill the stream. The Studio UI (session auth) still starts
  training and coexists/frees VRAM as before. A mixed UI+API session is not yet
  special-cased. Adds auth.authentication.authenticated_via_api_key.

Tests added/updated for each; full backend suite diff vs baseline is unchanged.

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* Studio: add UNSLOTH_MODEL_IDLE_TTL env override for idle-unload

Borrowed from PR 6517: a startup env var that sets the idle-unload TTL without
the settings UI. Unlike the stored setting (gated on auto-switch), the env value
is a standalone default that enables idle-unload even with auto-switch off, for
headless/container deploys. An explicit UI/API value still overrides it and stays
gated. The settings GET reflects the env default when nothing is stored.

* Studio: auto-switch fixes from review (paths, embeddings input, env idle reload)

- /v1/models advertises a client-facing alias instead of a filesystem path:
  the ./models and LM Studio scanners report the on-disk path as the model id,
  so the index now prefers model_id/display_name as the advertised/override id
  and keeps the concrete path internal as load_path, still resolvable by path.
- /v1/embeddings validates input before auto-switch: a request with a model but
  no input now 400s before the hook (like chat/responses/messages), so an
  invalid embeddings request cannot unload or swap the resident model.
- Standalone UNSLOTH_MODEL_IDLE_TTL reloads the freed model: the hook now runs
  when auto-switch or idle-unload is active, and with auto-switch off it skips
  the resolver and only restores the idle-unloaded model, so the first idle
  timeout no longer leaves later /v1 requests with nothing loaded.
- Do not resurrect a stale GGUF over an active Unsloth model: the reload-stash
  path bails when a non-GGUF backend is loaded, so an unknown /v1 name cannot
  tear down a live Transformers/Unsloth model.
- Defensive HF cache scan: each cache root's resolve/dedup is wrapped so a
  missing or malformed root skips that root rather than aborting the index.
- Single-model retrieve checks the id is a string before lowercasing.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Studio: fix automatic-load asymmetry, audio reload, preview, idle timer

The standalone UNSLOTH_MODEL_IDLE_TTL reload is a second automatic-load
trigger, but several validate-before-switch guards and reload hooks only
checked the auto-switch toggle. Add a shared _automatic_model_load_may_run()
(auto-switch on, or idle TTL > 0) and route every guard through it.

- /v1/completions validates prompt before any automatic load (it was the one
  model-bearing route with no pre-check).
- /v1/chat/completions and /v1/embeddings pre-checks gate on the shared
  predicate so a standalone idle TTL cannot reload then reject.
- /v1/messages no longer 503s before the reload hook can restore an idle-freed
  model when auto-switch is off.
- Raw completions/embeddings with no model field pass a non-empty sentinel so
  the idle-stash reload runs, restoring the legacy "omit model, use loaded" path.
- /api/inference/audio/generate gains the reload hook (after message validation)
  so an idle-freed audio GGUF is restored.
- Public preview opts out of auto-switch via a request-scope flag, so a caller's
  model field cannot swap away from the pinned checkpoint; preview chat streams
  are now matched by _is_inference_path so idle-unload cannot kill them.
- Keep-warm no longer stamps activity on request start, and external-provider
  untracking decrements without restamping, so periodic external traffic can no
  longer keep the local GGUF warm forever.

Merges origin/main (the branch had fallen behind, which also brought in the
preview route the review flagged).

* Studio: surface model auto-switch in the API tab and demo it in examples

The OpenAI auto-switch toggle previously lived only in Settings -> General.
Add the same toggle to the API tab's usage-examples panel (it shares the
settings cache), and make the examples reflect it: when on, the Python
examples append a second call naming a different downloaded GGUF (so the
model field visibly selects which model serves), and the curl examples gain
a one-line note. Reuses the existing settings API client and i18n keys.

* Studio: harden OpenAI auto-switch reload-only path and Anthropic tool validation

- Omitted-model raw-body requests pass a reload-only sentinel so the idle-stash
  reload still restores an idle-freed model, but the resolver never matches a
  downloaded GGUF literally named "default".
- Reject malformed Anthropic client tools before _maybe_auto_switch_model so an
  invalid request can no longer evict the loaded model.

* Studio: extend auto-switch reload-only and tool validation to schema endpoints

- Schema-backed endpoints (chat completions, responses, count_tokens, messages,
  audio) defaulted an omitted model to "default" and passed it to the switch
  hook, so a downloaded GGUF named "default" could be swapped to. Route the hook
  through a helper that switches only on an explicitly set model, else reload-only.
- Propagate the explicit-set status when building the chat request from a
  Responses request, so the non-streaming chat re-check stays reload-only too.
- Validate Responses function tools before the switch hook so a malformed tool
  returns 400 without evicting the loaded model.

* Studio: serialize auto-switch swaps across event loops with a process-wide gate

The auto-switch lock is a per-event-loop asyncio.Lock, so two /v1 swaps on
different loops in one process could both pass it and race the single model slot
(the backend and _load_model_impl are process-wide). Add a process-wide
threading gate around the swap, acquired off the loop so a cross-loop wait never
blocks it, layered with the existing per-loop lock. Add a cross-loop test that
fails without the gate (two slow loads overlap) and passes with it.

* Studio: make the auto-switch swap gate wait cancellation-safe

_acquire_swap_gate awaited asyncio.to_thread(lock.acquire) when another loop held
the process-wide gate. to_thread cancellation doesn't stop the worker thread, so a
/v1 request cancelled mid-wait (client disconnect during a cross-loop swap) would
have its thread acquire the gate after the fact, while the finally that releases it
never runs -- permanently deadlocking later auto-switch swaps.

Poll a non-blocking acquire off a short asyncio.sleep instead: it still keeps the
wait off the loop and serializes across loops, but a cancel now lands during the
sleep, when the gate is not held, so nothing leaks. Add a test that deadlocks the
to_thread variant (it times out) and passes with the poll.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Studio: validate modality and tool-confirmation before auto-switch

Two more request shapes could load a named GGUF and only then 400, evicting the
resident model:

- An image request naming a different text-only GGUF. The switch hook now takes
  require_vision and rejects a swap to a non-vision target before loading it; a
  GGUF's vision capability is its companion mmproj, knowable without a load, and
  matches the post-load guard. Only the resolver branch is checked, never the
  reload-stash restore.
- confirm_tool_calls=true with stream=false and local tools. /v1/chat/completions
  now rejects that shape before the hook, mirroring the local tool path's
  bypass_permissions exemption and intent signal.

The vision probe threads the ambient HF token to keep the capability-probe
invariant. Reload-only and idle-reload paths are unaffected.

* Studio: extend validate-before-switch and make the lifecycle gate process-wide

- /v1/messages/count_tokens now rejects malformed client tools before the switch
  hook, like /messages (shared _validate_anthropic_client_tools helper), so a
  count request can't evict the loaded model.
- /v1/chat/completions rejects a malformed tool_choice forcing object (a
  {"type":"function","function":{}} with no name) before the switch hook.
- The inference lifecycle gate that blocks new inference during a swap is now
  process-wide (a poll-acquired threading lock, cancellation-safe), not a
  per-loop asyncio lock, so a request on another event loop can't start inference
  while a swap tears the single backend down.
- Usage examples no longer hard-code a switch-demo repo most users lack; the
  model is an explicit placeholder the user replaces.

* Studio: extend the auto-switch modality guard to /v1/responses and /v1/messages

The pre-load vision check that guards /v1/chat/completions now also runs on
/v1/responses and /v1/messages, so an image request naming a text-only GGUF is
rejected before the swap and never evicts the resident vision model. Run the
vision capability probe off the event loop. Make the /v1/models retrieve
loaded fast-path case-insensitive, and never advertise a host path from the
resolver. Remove the dead list_switch_eligible_ids helper, superseded by the
/v1/models catalog.

* Studio: filter /v1/models to GGUF, per-loop catalog lock, reject system-only Responses

Address review findings on the auto-switch path:
- /v1/models advertises only GGUF models the API can actually switch to; a
  safetensors/LoRA entry would be selectable but never loadable via llama.cpp.
- The /v1/models catalog cache uses a per-loop lock (like the auto-switch path)
  so a second event loop awaiting it can't hang in a multi-loop process.
- /v1/responses rejects system/developer-only input before the switch, mirroring
  chat, so an invalid request can't evict the resident model.
- _build_index guards each scan source on its own so one bad root drops only
  that source; the vision probe logs a real detection failure instead of
  swallowing it.

* Studio: list cached GGUFs in /v1/models by inspecting files, not model_format

The HF-cache scanner leaves model_format unset for GGUF snapshots, so the
previous model_format == "gguf" filter dropped every downloaded HF-cache GGUF
from /v1/models and the retrieve fallback. Decide GGUF-ness from the on-disk
files via the resolver (info_has_local_gguf) instead, run off the event loop, so
the catalog advertises exactly what /v1 can serve.

* Studio: fix /v1/messages/count_tokens route binding plus auto-switch review fixes

The @router.post decorator for /messages/count_tokens had been separated from
anthropic_count_tokens by the _validate_anthropic_client_tools helper, so the
route bound to the validator and dropped its auth dependency. Move the decorator
back onto the handler. Add route-binding tests asserting each /v1 endpoint maps
to its handler with the auth dependency, so a decorator/handler split is caught
at the route level (the direct-call tests missed it).

Also from review:
- update_openai_auto_switch writes both settings keys in one transaction so a PUT
  can't leave one updated and the other stale (drop the now-unused single setters).
- max_seq_length override rejects 0 at the boundary (ge=1) instead of accepting
  then silently dropping it.
- Document that embeddings auto-switch is best-effort: GGUF pooling has no cheap
  pre-load probe like vision's mmproj, so a guard would false-reject GGUF embedders.
- Add a positive idle-unload test (loop frees the model and stashes it for reload).

* Studio: validate Responses tool_choice + Anthropic mixed tools before switch, filter Ollama from catalog

More auto-switch review findings:
- /v1/responses rejects a forcing-function tool_choice with no name before the
  switch, mirroring chat, so a malformed request can't evict the resident model.
- /v1/messages rejects mixing Anthropic server tools with custom client tools
  before the switch (the check depends only on the payload, so it moves up cleanly).
- /v1/models no longer advertises Ollama-link models: info_has_local_gguf excludes
  .studio_links / ollama_links entries, which the resolver skips and can't switch
  to, so an advertised id never silently falls through.

* Studio: guard chat audio input before switch; surface env-backed idle unload in settings UI

A chat request carrying audio_base64 rides the same companion mmproj
projector as a vision request, so a text-only target cannot serve it
either. Flag require_vision for audio input as well so the multimodal
probe runs before the switch and a rejected request never evicts the
working model. Generalize the reject message to cover image and audio.

The settings response now reports idle_unload_active (effective TTL > 0)
so the UI can distinguish idle-unload that is active via the
UNSLOTH_MODEL_IDLE_TTL env var from the case where it needs the toggle
enabled.

* Studio: harden auto-switch eviction guards (count_tokens vision, TTS reload-only, mmproj/stash)

Four eviction/correctness fixes on the opt-in /v1 auto-switch path:

- /v1/messages/count_tokens now carries the same require_vision guard as
  /messages, so an image count naming a text-only GGUF can't evict a loaded
  vision model for a swap that can't serve the request.

- /audio/generate is now reload-only. A local GGUF's audio-input capability
  is not a cheap pre-load probe (the companion mmproj signal can't tell an
  audio projector from a vision one, and codec TTS ships no projector), so
  resolving the client model could load a text/vision-only target and evict
  the working audio model before the audio check fails. Only the idle-stash
  restore runs here; switching TTS models is an explicit /load.

- The resolver no longer treats a standalone mmproj .gguf as a servable
  model. _scan_models_dir's standalone-file pass does not filter mmproj the
  way its directory scan does, so /v1/models could advertise a projector and
  a switch could load it over the real weights.

- A non-GGUF (Transformers/Unsloth) load and a deliberate /unload now clear
  the idle reload stash, so a manual load/unload is never superseded by a
  stale idle-freed GGUF that the next /v1 request resurrects.

* Studio: report advertised repo id consistently after an auto-switch

Two model-id reporting fixes so an auto-switched cached HF GGUF is named by
its repo id everywhere, not its snapshot path:

- Streamed /v1/responses envelopes now derive the model id from
  _llama_public_model_id (which prefers _openai_advertised_id) instead of the
  raw model_identifier. After an auto-switch the identifier is the snapshot
  path while the repo id lives in _openai_advertised_id, so the stream used to
  report a snapshot basename while /v1/models, chat completions, and
  non-streaming Responses all reported the repo id.

- When an advertised alias already resolves to the loaded model (a model
  loaded by local path, requested by its repo or LM Studio id), the
  already-serving early return now records the alias as the advertised id, so
  /v1/models and responses report the alias and mark it loaded instead of the
  path-derived basename. Resolver branch only; safe lock-free because an
  in-flight request blocks any concurrent swap via the single-slot busy guard.

* Studio: validate request shapes before auto-switch (prompt/input/audio/mcp confirm)

Four more validate-before-switch guards so a deterministic client error never
evicts the resident model on the opt-in /v1 auto-switch path:

- /v1/completions rejects an object/number prompt (only a string or array is
  valid) before the switch, instead of loading the named GGUF and letting
  llama-server reject the shape afterward.

- /v1/embeddings rejects an object/number input the same way.

- Chat rejects an oversized audio_base64 upload (413) before the switch. The
  size cap is a cheap, target-independent length check; the decode itself
  stays post-switch to avoid decoding a valid upload twice.

- The chat confirm-without-stream pre-switch guard now mirrors the tool loop's
  actual enablement: _effective_enable_tools (honoring a CLI --enable-tools
  policy) and mcp_enabled (which opens the tool loop on its own but defers to a
  CLI --disable-tools policy). Previously a confirm+no-stream request with only
  mcp_enabled slipped past and 400'd after the swap.

* Studio: fix model-id retrieval, streaming n>1, resolver cache TTL, keep-warm auth

Four fixes from review:

- GET /v1/models/{id} legacy raw-path fallback now maps the raw identifier to
  the same public id its /v1/models entry uses. After an auto-switch load the
  identifier is the snapshot path while the entry is keyed by the advertised
  repo id, so a client that cached the old absolute path no longer 404s on a
  model that is in fact loaded.

- stream=true with n>1 is now rejected before the switch. Only the
  non-streaming GGUF path returns multiple choices, so streaming n>1 is invalid
  on every local serving path; both fields are known pre-switch, so it must not
  load model B only to 400 and evict model A. Non-streaming n>1 stays
  post-switch where the serving path decides.

- The resolver index cache is stamped after _build_index, not with the pre-scan
  timestamp. On installs with enough local models for the multi-root scan to
  exceed the 5s TTL, the cache was stored already expired and every request
  rebuilt it.

- The keep-warm middleware no longer stamps model activity for 401/403
  responses. It runs before FastAPI auth, so unauthenticated probes used to
  refresh the idle timer without touching llama.cpp; they now decrement the
  in-flight count without keeping the model warm.

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: oobabooga <112222186+oobabooga@users.noreply.github.com>
2026-07-01 06:42:23 -07:00
Daniel Han
e8945cab46
Whole-document context for RAG chat attachments (#6693)
* Add whole-document context mode to RAG chat attachments

Thread-attached files are injected in full when they fit a token budget,
instead of only top-K retrieved chunks, so the model reads the entire file
for summarize/reason-over-document requests. Oversized files fall back to
top-K retrieval so the context window is never blown. KB and project
corpora are unchanged (still retrieval).

- core/rag/store.py: all_chunks_for_scope returns every completed-document
  chunk for a scope, ordered document-then-index, joined with filename.
- core/rag/tool.py: whole_document_context renders the chunks as the same
  <chunk> blocks + citation source-map retrieval produces, returns None
  when empty or over budget.
- core/inference/tools.py: build_rag_autoinject tries whole-document first
  for thread scopes, falls through to search_for_autoinject otherwise.
- core/rag/config.py: THREAD_WHOLE_DOC + WHOLE_DOC_MAX_TOKENS (env-tunable).
- tests/test_rag_whole_document.py: store ordering, whole-doc render +
  budget cutoff, auto-inject whole-doc vs top-K fallback, KB never whole-doc.

* Add scanned-PDF OCR fallback to RAG ingestion

A PDF page with no extractable text layer (a scanned or image-only page)
previously ingested as empty, so image PDFs were invisible to retrieval and
whole-document context. Such pages are now rendered and transcribed by the
loaded vision model during ingestion, so they become searchable and readable
like any other page. This restores OCR for the RAG document flow without a
separate extraction pipeline.

- core/rag/parsers.py: render_pdf_pages renders whole pages (1-based) to PNG.
- core/rag/captioner.py: factor the shared vision call into _vision_complete;
  add _ocr_one + ocr_pages (transcribe rendered pages, OCR_MAX_PAGES bound).
- core/rag/ingestion.py: _ocr_scanned_pages runs right after parse, replacing
  text on near-empty PDF pages. No-op when OCR is off, no page is scanned, or
  no vision model is loaded (degrades like figure captioning).
- core/rag/config.py: OCR_SCANNED, OCR_MIN_CHARS, OCR_MAX_PAGES, OCR_DPI,
  OCR_TIMEOUT_S, OCR_MAX_TOKENS (env-tunable).
- tests/test_rag_ocr_fallback.py: page render, ocr_pages gating + cap, scanned
  PDF end-to-end OCR into chunks + whole-doc, born-digital skips OCR, disabled
  leaves the page empty.

* Broaden OCR prompt to figures/tables and guard against repetition runaway

The OCR prompt now asks the vision model to also transcribe text inside figures,
diagrams, charts and tables, so labels and table cells on scanned pages are
indexed rather than skipped. Verified on real documents that this does not
regress plain-text transcription.

Some vision models loop on sparse images (e.g. a title-only cover) and emit the
same line hundreds of times. _collapse_runaway caps any run of identical
consecutive lines so a pathological page cannot flood the index; legitimate
short repeats (a label appearing a few times) survive. Applied in ocr_pages.

* Restrict whole-document injection to thread attachments only

whole_document_context resolved the combined project+thread scope, so a project
chat (the frontend sends both thread_id and project_id) injected the entire
project corpus in full, contradicting the design that project and KB corpora stay
retrieval-only. A large project corpus could also push the total over budget and
drop a small thread attachment back to top-K.

Resolve the thread scope alone in whole_document_context, and in
build_rag_autoinject only enter whole-doc mode when a thread attachment is present
and no KB is selected (a KB pick is exclusive: search that corpus). Project
sources and KBs keep top-K retrieval. Adds regression tests for the mixed
project+thread payload, the budget isolation, and KB precedence.

* Address review: keep project retrieval, harden budget + OCR guards

Follow-up to the 8-reviewer pass on the whole-document + OCR work.

- Preserve project grounding in project chats. The thread-scope-only fix made
  whole-doc exclusive of retrieval, so a thread attachment silently dropped the
  project corpus for that turn. build_rag_autoinject now whole-docs the thread
  attachment AND retrieves the project sources top-K, merged under one citation
  numbering via tool.render_sources. KB selection stays exclusive.
- Budget: a NULL/zero token_count no longer bypasses the cap (length-based
  fallback in _row_token_count), so a malformed huge doc can't inject in full.
- OCR runaway guard: _collapse_runaway now also caps each distinct line at a
  generous total across the page (not just consecutive), bounding the
  interleaved/alternating loops weak models emit; blank-line floods collapse too.
- OCR: warn when a scanned PDF exceeds OCR_MAX_PAGES (pages past the cap stay
  untranscribed) instead of silently dropping them.
- Document the known limits: OCR'd pages have no PDF highlight regions; vision
  models need a micro-batch >= image tokens (Gemma-family) or the server aborts.
- Tests for project-retrieval composition, NULL-token budget, and interleaved
  runaway; drop the now-superseded exclude-project test.

* Add OCR toggle to RAG retrieval settings

Make scanned-PDF OCR user-controllable per upload instead of only via the
RAG_OCR_SCANNED config default. The retrieval settings panel gains an OCR
scanned pages switch (persisted in localStorage, on by default); the chosen
value is read fresh at upload time and sent with each document upload.

Backend: the three upload routes accept an optional ocr form field and pass it
through start_ingestion to _ocr_scanned_pages, which now treats None as use the
config default and an explicit bool as an override. The on/off policy lives only
in _ocr_scanned_pages now, so ocr_pages no longer re-checks the config (that
double gate would have blocked a per-upload ocr=True while the default was off).

Tests cover both override directions (force on while config off, force off while
config on).

* Add "Describe figures & charts" toggle with chart-aware captions

Surface RAG figure captioning as a user control and make it actually useful for
graphs and plots. The figure detection already clustered vector drawings and
raster images into regions and rendered them, but captioning was off by default,
had no UI, and used a thin generic prompt.

Accuracy: the caption prompt now asks for chart type, axis titles and units,
legend or series, salient trends and readable values, and table columns, while
forbidding invented numbers. The token budget is configurable (CAPTION_MAX_TOKENS)
and captions pass through the same runaway guard as OCR so a looping vision model
cannot flood the index.

Control: a per-upload caption override threads from the three upload routes through
start_ingestion and _run, with the on/off policy single-sourced in _run (caption
self-gating removed from caption_images, mirroring the OCR change) so a force-on
override works when the config default is off. The frontend adds a "Describe
figures & charts" switch in the retrieval settings, persisted in localStorage and
sent with each upload. Default on; it is a no-op without a vision model and bounded
to CAPTION_MAX_IMAGES figures per document.

Tests cover the new caption_images contract, the runaway guard on captions, the
chart-aware prompt and token budget (and that OCR keeps its own prompt and budget),
and both override directions end to end through ingestion.

* Generalize figure understanding: transcribe-first prompt + high-DPI tiling

Make figure/chart description work across any visual and any model strength, not
just a strong VLM on simple figures. Two changes, validated by a recall benchmark
on authoritative documents (ResNet/Attention papers, USDA, UN UDHR).

1. Transcribe-first caption prompt. The caption now asks the model to transcribe
   every visible label verbatim (titles, axis labels and units, legends, every
   box/node/arrow label, table cells, equations) and then add a one-line summary,
   instead of only describing the figure. Transcription is the most model-robust
   visual task, so weak models that cannot reason about a chart still recover its
   labels.

2. High-DPI tiling of figure pages. Figure-bearing pages are rendered as an
   overlapping grid of high-DPI tiles (plus a full-page pass for context); each
   tile is transcribed, then merged and de-duplicated. This keeps small diagram
   labels legible and covers every sub-figure without relying on exact region
   detection, which previously missed sub-figures and small labels.

Supporting changes: figure render DPI 130 -> 200 with a clip margin so edge labels
are not lost; vision calls are deterministic (temperature 0) so transcription does
not randomly drop labels; the repetition guard now applies to captions too. New
config knobs: FIGURE_DPI, FIGURE_MARGIN_FRAC, FIGURE_TILE_ROWS/COLS, FIGURE_TILE_
OVERLAP, FIGURE_FULLPAGE, CAPTION_MAX_PAGES, larger CAPTION_MAX_TOKENS, and
CAPTION_MAX_IMAGES as a per-document tile budget.

Measured figure context recall (per-label, dense academic figures):
  Qwen2.5-VL: 0.50 -> 0.83 (overall 0.81 -> 0.94)
  Gemma-4-E2B (weak): ~0 with loops -> 0.83 (overall 0.91)
Born-digital text and scanned-page recall are unchanged (no regression).

parsers gains _figure_boxes (shared detection), pages_with_figures, and
render_pdf_figure_tiles; captioner gains merge_page_captions and a temperature
parameter; ingestion routes figure captioning through the tiled path.

* Fix RAG review issues: whole-doc budget pre-check, figure gating, empty re-ingest, vision auth

Whole-document context now runs a cheap token-sum pre-check (store.scope_token_estimate)
before hydrating every chunk's text, so an attachment that cannot fit the budget is
rejected without loading the whole corpus into memory. The estimate mirrors
all_chunks_for_scope's filter and the per-row token-count fallback exactly.

Ingestion skips all figure work (PDF rasterization and detection, not just the caption
call) unless a vision model is loaded, so a text-only deployment pays nothing. When OCR
is enabled, scanned/image-only pages are excluded from figure tiling since OCR already
transcribes them whole, avoiding double vision work and overlapping index entries; a
scanned figure page is still tiled when OCR is off.

start_ingestion no longer dedupes forever to a prior ingest that produced zero chunks
(e.g. a scanned PDF uploaded before a vision model was loaded): the empty record is
dropped and the content is re-ingested.

Vision OCR and caption requests now send the backend Authorization header, so they
match the chat endpoint and do not 401 under direct-stream (--api-key) mode.

Adds tests for the budget estimate, scanned-page exclusion, the vision-model gate, the
empty re-ingest path, and the auth-header passthrough.

* Trim RAG vision-ingestion comments and docstrings

Tighten the verbose multi-line docstrings and comments added across the RAG vision
ingestion work (captioner, config, parsers, ingestion, store, tool, build_rag_autoinject,
the RAG tests, and the chat-store/upload-hook frontend toggles) to one or two lines while
keeping their intent. No code changed: verified comment/docstring-only against the prior
commit, and the RAG test suite still passes.

* Fix figure-tiling exclusion and client dedupe for re-ingestable docs

Figure tiling now excludes only the pages OCR actually transcribed, not every
text-less page. _ocr_scanned_pages returns the set of pages it OCR'd, and _run passes
that to pages_with_figures as exclude_pages (replacing the ocr_on-keyed min_text_chars
heuristic). A scanned page that OCR skipped (past OCR_MAX_PAGES, or whose OCR returned
empty) is no longer dropped from captioning, so a chart on such a page still gets a
caption.

The document panel's upload dedupe no longer skips re-selecting a file whose only
matching doc completed with zero chunks. Such a doc is re-ingestable (e.g. a scan
attached before a vision model loaded), and the backend re-ingests on the same content
hash, so the client must let it reach the backend; healthy or still-indexing docs are
still skipped. The SSE complete frame's chunk count is recorded on the doc so the
check is exact.

Adds a regression test for the un-OCR'd scanned figure page and updates the
pages_with_figures test to the exclude_pages interface.

* Address review findings: whole-doc budget guard, job numChunks, dead code, upload cap

whole_document_context now treats a non-positive max_tokens as "never inject" instead
of injecting the whole corpus unbounded, so RAG_WHOLE_DOC_MAX_TOKENS=0 tightens rather
than disables the budget (the real off switch stays RAG_THREAD_WHOLE_DOC=0).

The job-status endpoint and get_job_status now expose num_chunks (joined from the
document), and the upload hook threads it through the SSE-fallback completion paths
(reconcile + poll). Previously a document that finished via the connection-cap fallback
had no chunk count client-side, so the re-ingest dedupe wrongly treated it as empty and
re-uploaded it. IndexJob/JobEvent gain the field and the untyped cast is dropped.

Removes the dead render_pdf_figures function (superseded by the tiling path), its test,
and the unused FIGURE_MARGIN_FRAC config knob.

Adds an upload size cap (RAG_MAX_UPLOAD_BYTES, default 200 MB; 413 on exceed with the
partial file cleaned up) so a pathological file can't drive unbounded parse + vision
work. render_pdf_figure_tiles clamps rows/cols to >= 1 (no ZeroDivisionError on a
misconfigured grid). Captioning progress is reported after OCR so the bar is monotonic.
sqlite connections set busy_timeout=5000 so a long figure/scan ingest holding its
connection doesn't make a concurrent ingest/read fail with "database is locked".

Adds tests for the non-positive budget, the zero-grid clamp, job-status num_chunks, and
the oversize-upload rejection.

* Extract PDF text as layout-aware Markdown via pymupdf4llm

parsers._pdf now extracts each PDF page as Markdown with pymupdf4llm.to_markdown
(page_chunks=True) instead of flat page.get_text("text"), so tables, headings and lists
keep their structure in the indexed chunks and retrieve far better (a table's cells stay
associated with their row instead of flattening into a token stream). Gated by
RAG_PDF_MARKDOWN (default on); falls back to plain PyMuPDF text when the toggle is off,
pymupdf4llm is missing, extraction fails, or a page yields no Markdown. The scanned-page
OCR and figure-tiling passes operate on rendered pixels and are unaffected; docx/html/txt
keep their existing extractors.

The preview-highlight locator already strips Markdown punctuation when building anchors;
it now also splits anchor tokens on pipes so a Markdown table row still anchors to the
raw PDF word stream.

Declares pymupdf4llm as a studio/RAG dependency (was only transitively present via the
data-designer plugin). Adds parser tests (Markdown table reaches the page text, the
plain-text fallback, the missing-lib fallback) and a locator test for table-pipe anchoring.

* Pin pymupdf4llm to 0.3.4 so the package scan does not pull onnxruntime

The lockstep pymupdf4llm 1.27.x line makes pymupdf-layout a hard dependency,
which in turn pulls onnxruntime (plus numpy/networkx/protobuf). The security-audit
pip scan-packages job resolves requirements --with-deps, so adding pymupdf4llm to
no-torch-runtime.txt and studio.txt surfaced onnxruntime's un-baselined CRITICAL
finding and flipped the hf-stack shard from pass to fail.

pymupdf4llm 0.3.x keeps pymupdf-layout behind an optional [layout] extra, so a plain
install resolves to pymupdf + tabulate only and never touches onnxruntime. 0.3.4
requires pymupdf>=1.27.1, satisfied by our pinned pymupdf==1.27.2.3, and to_markdown
(page_chunks=True) produces equivalent layout-aware Markdown on real PDFs (verified on
the Attention, ResNet and USDA documents). Production already installs these files
--no-deps, so onnxruntime was never shipped at runtime; this only fixes the scanner.

The parser test now asserts Markdown markup (heading or table pipes) rather than table
pipes specifically, since 0.3.4 emits a heading but not a pipe table on the tiny
borderless synthetic fixture; both markers are absent from the plain-text fallback.

* Fix RAG whole-doc review findings

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* Address RAG whole-doc review follow-ups

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* Address RAG review follow-up edge cases

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* Reserve image budget for whole-document RAG

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---------

Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2026-06-30 15:55:23 +02:00
Michael Han
11469a60fe
(feat) Add project names to studio training runs (#6512)
* (feat) Add project names to studio training runs to avoid models being overwritten when doing similar training runs

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* Update studio/frontend/src/features/export/export-page.tsx

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

* Update studio/frontend/src/features/export/export-page.tsx

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

* Update studio/frontend/src/features/export/export-page.tsx

Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>

* better project name sanitization, removed duplicated project name normalization

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* implement checkpoint scanning utilities and tests for base model inference

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* Guard project_name against null and use leading important modifiers

* Fix/adjust training project names for PR #6512

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* Fix/adjust training project names for PR #6512

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* Address project-name review feedback

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* Show project names in training recents

* Keep GGUF export directories source-specific

---------

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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2026-06-29 16:06:36 +02:00
Daniel Han
2ef394137a
Studio: harden background consumer loops and streaming paths against silent UI freezes (#6653)
* Studio: harden the data-recipe and inference consumer loops against pump death

Follow-up to #6643. The same single-unsupervised-consumer pattern the training
pump had lives in two sibling loops, with the same failure mode: one bad event
kills the only thread that updates the in-memory state every UI surface reads,
while the worker subprocess keeps running.

- data_recipe JobManager._pump_loop: a malformed worker log line that makes
  parse_log_message raise no longer kills the pump. Guard _handle_event, the
  queue read, and the worker-exit finalize, and broaden _drain_queue so a drain
  error still finalizes the job instead of leaving it wedged "active" (which also
  leaked the workflow-scoped API key until its 24h expiry).
- inference InferenceOrchestrator._dispatcher_loop: guard the routing body so a
  malformed response or a mailbox put error can't kill the dispatcher and hang
  every in-flight generation (callers key liveness on the subprocess, not on
  this thread).

Adds regression tests for both.

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* Studio: extend consumer-loop hardening to RAG, hub, auth, and stream-reader paths

Continuation of the data-recipe and inference pump hardening: the same
"background producer updates in-memory state that a single unsupervised
consumer surfaces to the UI" pattern shows up in several more Studio paths,
each able to silently freeze a UI surface while the worker keeps running.

RAG ingestion SSE (core/rag/ingestion.py):
- job_events polled the queue with a blocking get and never noticed client
  disconnect or a dead worker, so a closed tab or a producer that died
  without emitting a terminal event left the stream hanging. It now polls
  with a timeout, emits heartbeats, ends on terminal job status, caps idle
  time, and always pops the job registry in finally.
- Added _reap_finished_jobs() and call it from start_ingestion so finished
  job state does not accumulate.

Startup reconcile (storage/rag_db.py, main.py):
- reconcile_orphaned_ingestion_jobs() marks ingestion jobs (and their
  documents) that were left non-terminal by a previous crash as failed, so
  the UI does not show jobs stuck "running" forever after a restart. Wired
  in at startup next to cleanup_orphaned_runs().

Hub download watcher (hub/services/download_lifecycle.py):
- _watch() could leave a job pinned "running" if finalize raised. Body is
  now guarded: on failure it logs and sets the job to error, and always
  invalidates the hf cache scan in finally.

External provider stream (core/inference/external_provider.py):
- read timeout was None (no stall ceiling); set to 300s so a wedged
  upstream surfaces as an error instead of an indefinitely hung stream.

Auth store (auth/storage.py):
- Enable WAL + busy_timeout on the auth DB so token validation (read on
  every request) and login writes stop serialising on the rollback journal.
  Matches studio_db / rag_db / providers_db.

Login rate limiter (routes/auth.py):
- _LOGIN_IP_BUCKETS could grow unbounded under spoofed-IP traffic; cap it
  and prune stale buckets, mirroring the per-account bucket handling.

Training progress SSE (routes/training.py):
- Break promptly on client disconnect instead of waiting for the next
  yield to fail on a closed socket, matching the export / data-recipe SSE
  routes.

llama-server stdout drain (core/inference/llama_cpp.py):
- Broaden the drain guard so an unexpected decode/read error logs at debug
  and stops the drainer cleanly instead of escaping the thread.

Frontend stream readers (chat-api.ts, rag-api.ts):
- Wrap the SSE read loops in try/finally + reader.cancel() so early return
  ([DONE]), thrown errors, and consumer aborts release the reader lock
  instead of holding it until GC.

Tests:
- test_training_progress_stream_nan: fake request now implements the async
  is_disconnected() the route polls, matching the other SSE route fakes.

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* Studio: address Codex review feedback on the consumer-loop hardening

Four follow-ups from the automated review, all on code this PR introduced:

- Data-recipe pump (manager.py): a queue read that keeps raising an error
  outside the read's narrow catch set (e.g. a broken queue pipe after the
  child died) hit the `continue` guard and skipped the dead-worker finalize
  below, spinning forever and leaving the job wedged "active" with its
  workflow key unretired. On a read failure, fall through to finalize when
  the worker is no longer alive. Added a regression test.

- RAG ingestion SSE (ingestion.py): the 5-minute idle cap could end the
  stream while the job was still pending/running (a large document spends
  minutes in embedding/storing with no per-batch progress event). The route
  then sends [DONE], and the client treats a no-terminal-frame end as
  completion, marking the document indexed mid-ingestion. Drop the idle cap:
  while the worker is alive and non-terminal we keep heartbeating; the stream
  ends only on terminal DB status, the None sentinel, or client disconnect.

- Login rate limiter (auth.py): the per-IP path pruned but then added the
  new IP unconditionally, so a spoofed-source-IP spray kept _LOGIN_IP_BUCKETS
  unbounded and made every new IP pay a full-dict prune scan. Gate the add on
  the cap, mirroring the account path.

- Hub download watcher (download_lifecycle.py): if finalize raised before it
  reaped (proc.wait) and dropped the worker (e.g. an I/O error draining
  stderr), the crash path published a terminal state while the live Popen
  stayed registered and kept writing the cache, and the terminal set_job let
  claim() admit a retry on the same repo. Terminate + drop the worker before
  setting the terminal state.

* Studio: keep login throttling working when the per-IP bucket dict saturates

Review follow-up. The previous cap fix skipped creating a bucket for a new IP
once _LOGIN_IP_BUCKETS was full, returning ip_fails=0. Under a sustained spray
that also fills the account dict, every failure from such an IP then looked
first-seen and _login_blocked had no bucket to enforce, so the cap effectively
disabled throttling once saturated.

Bound the dict with a FIFO eviction instead: if the IP is new and the dict is
full, reclaim expired buckets (rate-limited so a burst of distinct IPs can't
make each failure an O(n) sweep) and, if still full, evict the oldest-inserted
IP. The new IP always gets a real bucket, so a saturating (e.g. spoofed
X-Forwarded-For) spray stays throttled while memory stays bounded. Added a
regression test that saturates the dict and asserts a later IP is still blocked.

* Studio: address Codex review (RAG queue lifecycle, stream error, orphan chunks)

Three follow-ups on the Phase 6 changes:

- RAG ingestion SSE (ingestion.py): job_events removed the per-job queue in its
  finally on ANY exit, including an early client disconnect while the worker is
  still running. That dropped the worker's later events (the queue is the only
  one _emit writes to) and made a reconnect find no queue and receive only
  [DONE], which the client treats as completion. Only drop the queue on a
  terminal exit (None sentinel / terminal DB status); leftover terminal queues
  are still swept by _reap_finished_jobs. Added queue-lifecycle tests.

- External provider stream (routes/inference.py): once the 300s read timeout can
  fire, the stream's except path failed the monitor but ended without an error
  frame or [DONE], so the chat client saw a bare EOF and saved the timed-out
  answer as a successful partial with no error. Emit an SSE error frame (and
  [DONE]) on stream failure so the client surfaces it.

- RAG startup reconcile (storage/rag_db.py): marking a half-ingested document
  failed left its chunks/fts/vec rows intact, and retrieval filters by scope not
  status, so a failed document could still be retrieved and cited. Purge the
  document's chunks when reconciling it to failed (the doc row stays for
  re-ingest).

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* Studio: release the remaining SSE stream readers (training, data-recipe, export)

reviewer.py follow-up. The chat and RAG SSE readers were wrapped in
try/finally + reader.cancel(), but the other three readers built on the same
response.body.getReader() pattern were left without it: streamTrainingProgress,
streamRecipeJobEvents, and streamExportLogs leak the ReadableStreamDefaultReader
lock (held until GC) when the consumer aborts, returns early, or a parse/callback
throws. Wrap each in try/finally + reader.cancel() (export already had a
try/catch, so it only needed the finally). All five frontend SSE readers now
release the reader symmetrically.

* Tighten resilience comments and docstrings

Condense the verbose explanatory comments and internal-helper docstrings added
in this branch to shorter, clearer forms. Comment/whitespace only; verified no
code changed via AST diff. No behaviour change.

* Studio: keep chunks for completed docs during ingestion reconcile

Startup reconciliation flips orphaned (non-terminal) ingestion jobs to failed and
purges the document's chunks so a failed source can't be retrieved. But it dropped
the chunks unconditionally, so a document the worker had already committed as
'completed' before the crash (only its job row left non-terminal) lost every chunk
while still reporting 'completed'. That leaves an empty source that retrieval can't
return and dedup (status != 'failed') blocks from re-ingest.

Only purge chunks when the document UPDATE actually transitions it to failed; an
already-completed document keeps its chunks. Adds reconcile regression tests for
both the completed-doc and genuine in-flight-orphan cases.

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* Studio: drop a finished RAG job's queue when the client disconnects

job_events kept the per-job queue until it consumed the None sentinel, so a UI
that stops on the terminal event (its reader.cancel aborts the stream before
[DONE]) left the queue registered until the next _reap_finished_jobs sweep; a
batch of uploads followed by idling retained them all.

_run writes the terminal DB status before emitting the terminal event, so on
generator exit, drop the queue when the job's DB row is already terminal (worker
done, nothing to resume) and keep it only while the worker is still running. Adds
a disconnect-after-terminal-event regression test.

* Remove stray async task output files committed by mistake

* Studio: harden login IP throttle and end progress stream on disconnect

Two Codex review items:

Login per-IP throttle: when the per-IP bucket dict saturated, FIFO eviction could
drop a still-hot (blocked) bucket, so an IP could flood the dict with distinct
(or spoofed) source IPs to push out its own bucket and retry as first-seen. Stop
evicting hot buckets; a new IP that can't fit now shares a bounded overflow
counter that still trips the per-IP threshold, so a saturating spray stays
throttled and no live counter is reset.

Progress SSE: on client disconnect the polling loop only broke and fell through
to the unconditional final 'complete' frame, so a buffered or proxying consumer
could read a still-active run as completed. Return from the generator instead.

Adds regression tests for both (spray cannot reset a hot bucket; disconnect while
active emits no complete frame).

* Studio: shard the login overflow counter and stop cancelling chat stream after [DONE]

Two Codex review items:

Login throttle overflow: the single shared overflow counter meant that once a
saturating spray pushed it past the per-IP threshold, _login_blocked returned 429
for every new unbucketed source IP, before credentials were checked -- a global
login denial. Shard the overflow into a fixed array of counters keyed by hash(ip),
so a hot shard only throttles the IPs that map to it while a single source's
repeated failures still concentrate in one shard and stay throttled. Memory stays
bounded and no live bucket is evicted. Adds a regression test that a hot overflow
shard does not block an unrelated IP.

Chat stream: the reader.cancel() in the SSE finally fired even after a natural
[DONE]/EOF. The backend finalizes its api-monitor entry right after yielding the
sentinel (the local pass-through finishes after the last yield), so a client
cancel there can be observed as a disconnect and mark a completed request as
cancelled. Track natural completion and only cancel on an early/abnormal exit.
(No frontend unit test: the Studio frontend has no test harness.)

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* Studio: give prep-timeout test fakes an is_disconnected method

The progress stream now ends on client disconnect (await request.is_disconnected()
before falling through to the terminal frame). After merging that into the
prep-timeout tests added later on main, their _FakeRequest/_ReconnectRequest must
provide is_disconnected or the generator raises AttributeError under CI.

* Studio: keep the login overflow throttle when bucket capacity frees up

_login_blocked only consulted the per-IP overflow shard while the bucket dict was
still at capacity. If a slot freed before the 60s window expired (e.g. another
IP's successful login calls _clear_login_bucket), a source counted in a hot shard
stopped being blocked and its next failure got a fresh per-IP bucket, resetting
the throttle the overflow path exists to preserve. Always max in the IP's shard
(shards are empty outside saturation, so it is a no-op in the common case). Adds a
regression test that a hot source stays throttled after a bucket frees.

* Studio: clear a login IP's overflow throttle on successful login

_clear_login_bucket reset the per-IP and per-account buckets on a successful
login but not the overflow shard, so after the dict saturated and an IP was
counted in overflow, a later successful login left those entries behind and the
next failed attempt could immediately return 429.

Store overflow entries as (timestamp, ip) so a source is throttled by its own
count within the shard (also removing cross-IP collateral within a shard), and
drop just that IP's entries in _clear_login_bucket. Adds a regression test that a
successful login clears the overflow throttle.

* Studio: bound the login overflow shard memory under high-cardinality spray

The per-IP overflow tracked failures in a time-pruned deque of (timestamp, ip)
tuples, so a spoofed-X-Forwarded-For spray of distinct one-off IPs grew memory and
the per-check scan with request cardinality for the whole window -- undermining
the bucket cap that exists to bound memory. Replace each shard with a fixed-
capacity dict (ip -> [count, window_start]): O(1) lookups, and when a shard is
full a one-off IP evicts the lowest-count entry (Space-Saving) so memory is hard-
bounded while a persistent attacker keeps a high count and is never evicted. Adds
a regression test that shards stay within the per-shard cap under a 5000-IP spray.

* Studio: purge chunks for already-failed docs during ingestion reconcile

The reconcile chunk-purge was gated on the documents UPDATE actually flipping a
non-terminal doc to failed. A doc the worker had already marked 'failed' before
the crash (job row left non-terminal) was not re-flipped, so its committed chunks
were kept and stayed retrievable/citable, since retrieval filters by scope not
status. Purge chunks whenever the document is not 'completed' (failed, in-flight,
or gone), preserving the completed-doc carve-out. Adds a regression test.

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* Studio: don't inherit an evicted IP's count onto a new overflow source

When a full overflow shard evicted the lowest-count entry, the new source
inherited that count (Space-Saving base + 1). If a shard was saturated with hot
entries, an unrelated new IP could land at/over the threshold and be 429'd after a
single attempt -- cross-IP collateral despite the per-source-isolation intent.
New entries now start clean at count 1; the only cost is that a heavy hitter that
is the lowest-count entry in a fully saturated shard can briefly reset, which is
preferable to blocking a bystander. Adds a regression test.

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* Studio: carry overflow failures into a new IP bucket on transition

_login_blocked took max(per-IP bucket, overflow shard) rather than combining them,
so a source could log (threshold-1) failures in overflow during saturation and,
once a bucket slot freed, another (threshold-1) in a fresh bucket within the same
window -- roughly doubling the per-IP limit. When a saturated-era IP first gets a
real bucket, migrate its windowed overflow count into that bucket (and drop the
overflow entry) so the combined failures throttle at the intended limit. Adds a
regression test.

* Studio: reconcile a completed doc's orphaned job to completed, not failed

When a crash left an ingestion job non-terminal after its document was already
committed as completed, reconcile marked the job failed. After restart the upload
UI has no in-memory SSE queue and falls back to getJob(), which treats a failed
job as an indexing failure and removes/toasts a document that is actually
searchable. Mark the job completed (keeping its chunks) when its document is
completed. Extends the completed-doc reconcile test to assert the job status.

* Studio: clamp the overflow failure count migrated into a login bucket

A saturated source could accrue an unbounded overflow count, then materialize
one deque entry per recorded failure when a bucket slot freed, allocating an
arbitrarily large deque under the login lock. Only at-or-above the per-IP
threshold matters for blocking, so cap the count there at the record and take
sites; the migration is now bounded without weakening the limit.

* Studio: keep the RAG job stream alive on a transient status read

The heartbeat poll read the job row unguarded; a momentarily-locked DB would
raise out of job_events, which the SSE route turns into a terminal error frame,
and the UI drops a document whose worker is still running. Treat a failed status
read as non-terminal: heartbeat and retry, and keep the queue so a reconnect can
resume.

* Studio: set busy_timeout before journal_mode on the auth DB

Switching journal_mode needs a lock, so if a refresh-token write already holds
one, journal_mode=WAL raises SQLITE_BUSY and the shared try leaves the
connection on SQLite's default zero lock wait. Set busy_timeout first so the
switch waits instead of failing.

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2026-06-26 03:31:33 -07:00
Erildo
e54b6babd6
feat: implement thread forking functionality with associated database… (#5810)
* feat: implement thread forking functionality with associated database updates and UI components

* fix(studio/chat): register fork-count listener even when thread unsaved

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

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* Polish thread fork action menu

* fix-studio-fork-project-test-order

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Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
2026-06-15 14:57:39 +01:00
Michael Han
99704ffe47
Studio: project sources backed by RAG (#6205)
* Studio: make project sources work with RAG and polish project UI

Projects had a disabled Sources tab with an Add sources placeholder.
This wires it up end to end on top of the RAG engine:

- Add a project scope to the RAG store, ingestion and retrieval
- New endpoints: POST/GET /api/rag/projects/{id}/documents
- search_knowledge_base resolves kb, project and thread scopes; an
  explicit KB stays exclusive, project and thread scopes combine
- Multi-scope search: FTS uses scope IN (...), vec0 KNN runs per
  scope and merges by cosine score
- Lazy ALTER TABLE adds documents.project_id on existing databases
- Deleting a project also removes its indexed sources
- Sources tab now uploads with progress chips and drag and drop
- Chats inside a project auto-enable retrieval over project sources
  when the project has indexed documents (cached probe, no Docs pill
  needed); external providers still never receive rag_scope

UI polish:
- Rounder project cards with folder icon chip and softer shadow
- Project header icon in a rounded chip
- Chats/Sources pills and Add sources button without borders

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* Studio: match Add sources button shadow to the chat composer in light mode

* Studio: round project switcher hover pill and pad the folder icon

* Studio: remove border from project sources box

* Studio: grey hover on project cards and menu, move search into header, widen page spacing

* Studio: shorten sources copy, white header pills with composer shadow, fixed-width search, hub-size page headings

* Studio: align project landing blocks to the composer width

* Studio: restore muted background and flat look on projects header controls

* Studio: darker grey hover on project cards in light mode

* Studio: soften project card hover grey

* Studio: keep project card menu button visible while its menu is open

* Studio: drop focus outlines and rings on buttons and clickable icons, keep input focus styles

* Studio: address review feedback on project sources

- Remove uploaded files from disk when a project is deleted, confined
  to the uploads root
- 404 project uploads when the project does not exist, matching the KB
  endpoint
- Guard lexical search against an empty scope list
- Re-invalidate the project sources probe after uploads and removals
  settle so a chat sent mid-upload cannot cache a stale negative
- Keep keyboard focus rings: only mouse focus drops the Tailwind ring,
  the browser default outline stays removed

* Studio: add a green New badge to the project Sources tab

* Studio: unify New pills, fully round with soft emerald fill and no border

* Studio: a touch more vertical padding on New pills

* Fix project RAG source edge cases for PR #6205

* Fix duplicate RAG upload cleanup for PR #6205

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Co-authored-by: wasimysaid <wasimysdev@gmail.com>
2026-06-12 15:42:51 +02:00
ashzak
aefe904d66
feat(studio): implement S3 dataset loading (completes #5951) (#6222)
* feat(studio): add S3 dataset configuration foundation (#4539)

Add foundational types and configuration for S3 bucket dataset loading:

- Add S3Config type to frontend training types
- Add S3Config Pydantic model to backend training models
- Add "s3" as a DatasetSource option
- Add s3Config state and setS3Config action to training config store
- Add i18n translations for S3 configuration (English and Chinese)

This provides the type definitions and UI text for S3 integration.
Full implementation requires boto3 dependency and data loading logic.

Refs: #4539

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* Wire S3 config into training pipeline and prevent secrets persistence

- Pass s3_config from request into training_kwargs so it flows to training subprocess
- Add s3Config to NON_PERSISTED_STATE_KEYS to prevent AWS secrets from being
  saved to localStorage

Addresses code review feedback on PR #5951.

* Exclude S3 config from database persistence to protect secrets

Filter out s3_config (which contains secret_access_key) from the
config_json stored in training_runs table, preventing AWS credentials
from being persisted to disk.

Addresses P1 security feedback on PR #5951.

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* Re-raise HTTPException in start_training and defer s3 DatasetSource widening for PR #5951

* Redact s3_config from W&B run config and accept camelCase S3 credential aliases for PR #5951

* feat(studio): implement S3 dataset loading end-to-end

Builds the actual S3 loader on top of the hardened #5951 foundation,
turning the 501-gated scaffold into a working dataset source.

Backend:
- Add core/training/s3_dataset.py: lists and downloads supported dataset
  files (parquet/json/jsonl/csv) from an S3 bucket to a temp dir, using
  IAM-role or access-key credentials. boto3 is imported lazily (optional dep).
- Wire s3_config into UnslothTrainer.load_and_format_dataset (downloads then
  reuses the existing local-file path) and thread it through worker.py.
- Replace the 501 "not implemented" gate with a boto3-availability guard so
  S3 works when boto3 is present and fails clearly when it is not.
- Add boto3 to studio.txt requirements.
- Add tests/test_s3_dataset.py (8 tests) covering download/filtering,
  collisions, missing-boto3, and S3Config camelCase/IAM validation.

Frontend:
- Widen DatasetSource to include "s3"; add s3_config to the training payload
  type and mapper; add an S3 validation branch and selectS3Source store action.
- Add s3-config-form.tsx (bucket/region/prefix/keys/IAM toggle) reusing the
  existing studio.dataset.s3.* i18n strings.
- Add a Hugging Face / Local / Amazon S3 source toggle in dataset-section;
  the S3 config card replaces the dataset combobox when S3 is selected.
- Fix DatasetPreviewDialog to accept the widened DatasetSource type.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

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* Fix S3 dataset loader for PR #6222

* Fix S3 dataset edge cases for PR #6222

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* Fix S3 IAM payload handling for PR #6222

* Block multimodal S3 datasets for PR #6222

---------

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2026-06-12 14:52:04 +02:00
Daniel Han
8848a310df
Studio: clean-room compact RAG (knowledge bases, hybrid search, fast indexing) (#5910)
Adds a self-contained RAG stack to Studio: knowledge bases with chunked indexing, hybrid (dense + lexical) retrieval, and an automatic first-pass context inject into chat. Embeddings run through a local llama-server GGUF backend (default unsloth/bge-small-en-v1.5-GGUF) with a sentence-transformers fallback. The chat tool loop gains a search_knowledge_base tool, a per-turn re-search cap, and source citation, layered on top of the shared ToolLoopController.
2026-06-09 21:17:04 -07:00
Daniel Han
187144d4e7
Reduce and tighten code comments and docstrings repo-wide (#6095)
Trim and tighten code comments and docstrings across the repository. Comment-only: every changed file verified code-identical to main via AST/token comparison.
2026-06-08 23:09:51 -07:00
Daniel Han
8292e699e4
Studio: make code comments and docstrings more succinct (#6029)
Trim and tighten code comments and docstrings across studio/ Python. Comment-only: every changed file verified code-identical to main via AST/token comparison.
2026-06-08 23:07:28 -07:00
Daniel Han
3ce187da02
Formatting: ruff line-length 100, kwarg-spacing passes, drop blank after short local imports (#6079)
Raise ruff line-length to 100 and extend the local pre-commit format pipeline (def-signature magic-comma normalization, short multi-line assert collapse, kwarg '=' spacing, blank-line-after-short-import removal, adjacent string-literal / f-string+plain merge, redundant-pass pruning). Every transform re-checks the file AST and is dropped if it would differ; the whole-repo reformat is verified AST-identical per file and idempotent.
2026-06-08 04:24:13 -07:00
Wasim Yousef Said
7381958225
Configurable upload Cap studio (for training) (#5808)
* studio: cap training dataset uploads

* studio: clean up failed dataset uploads

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* studio: raise upload limits to 500MB

* studio: make upload limit configurable

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* studio: stream upload routes

* studio: split recipe upload caps

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* studio: tighten upload limit handling

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* studio: import settings router directly

* studio: polish upload cap setting control

* studio: cap settings request bodies

* studio: stub settings route in desktop auth test

---------

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2026-06-02 08:52:19 -07:00
Lee Jackson
e0ff6a1404
Studio: manage chat history with projects (#5725)
* feat: align project sidebar UX with ChatGPT

* feat: align project sidebar UX with ChatGPT

* feat(chat): load stored project list

* feat(chat): add project sidebar workflows

* fix: stabilize project page navigation

* fix: projects chat loading

* fix: show project chat thread

* style: sidebar project spacing and hover clipping

* style: add expandable project chat history and move-to-project submenu

* feat: polish project sidebar

* feat: persist project sandbox paths

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* fix: only create sandbox project workspace dir

* feat: add optional project workspace deletion from delete dialog

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* fix: stabilize chat projects CI failures

* fix: polish project chat navigation

* Studio: manage chat history with projects

Group chats into projects with a dedicated projects page and route.
Sidebar shows recents with per-row actions and a vertical more-vertical
menu, and the sidebar scrollbar stays hidden so rows never shift on
hover. Includes chat settings and composer refinements.

* Studio: projects sidebar and breadcrumb polish

Sidebar:
- Remove the Compare nav item.
- Widen the sidebar to match the projects layout.
- Replace the scroll-gated bottom fade with a static fade pinned above
  the profile box, so it no longer attaches to Recents or lags the
  collapse and expand animation.

Topbar breadcrumb (chat-page):
- On a project landing show "Projects" linking to the projects list.
- Inside a project chat show the project name and chat title, with the
  project name linking back to that specific project page.
- Drop the divider between the model selector and the breadcrumb.

* Studio: make project workspace delete test cross-platform

test_chat_project_delete_files_removes_workspace rooted the project under
pytest tmp_path, which resolves to /private/tmp on macOS. The workspace
delete guard refuses paths under the system denylist by design, so the
test passed on Linux CI but failed on macOS.

Add a workspace_projects_home fixture that keeps tmp_path on Linux and
Windows (CI unchanged) and falls back to a home subdir only when the temp
root is on the platform denylist. Derive the workspace path from the
created project so it tracks the projects home.

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* Studio: satisfy import-hoist check for new path re-exports

documents_root and project_workspaces_root are re-exported from
utils.paths but only referenced as __all__ string literals, which the
import-hoist safety net does not count as a use. It flagged the two newly
added re-exports as unused imports and failed Source lint.

Name-load both via a module-level _REEXPORTED tuple so the check sees
them used. No behaviour change; consumers still import them from
utils.paths.

* fix: avoid projects empty-state flash

* fix: batch chat search indexing

* Studio: polish chat sidebar, run settings, and search

- Use the native OS scrollbar for the chat sidebar, Run settings panel, and chat search list instead of a custom scrollbar
- Highlight the active run in the sidebar and keep chat search available during training
- Stop the training log view from replaying when navigating back to a run
- Rename the chat settings panel to Run settings and align its toggle icon and position
- Tighten heading and sidebar letter spacing and lighten the Train and Recents labels
- Match the search dialog corner style across light and dark and drop the stray border
- Make the MCP Servers section header plain text instead of a link
- Remove a stray .orig backup file

* studio/frontend: restore Compare entry point in the sidebar

The chat-projects sidebar redesign dropped the Compare nav item and moved
it to thread-sidebar.tsx, which is not imported or rendered anywhere. That
left no way for a user to start a new model comparison (enterCompare only
fired from the guided tour and the training handoff), and broke the
Compare/Recipes/Export UI smoke test that clicks [data-tour="chat-compare"].

Re-add the Compare NavItem to the New Chat / Search group, carrying
data-tour="chat-compare" and the same new-comparison navigation as before.

* studio/frontend: use Unsloth green for the fallback profile avatar

Switch the initials-avatar background from blue to #14b789 so the sidebar
and edit-profile avatar match the Unsloth brand colour.

* studio/frontend: turn project breadcrumb into a project switcher dropdown

* studio/frontend: stop project card kebab clicks from opening the project

* studio/frontend: hide project switcher outside projects

* studio/frontend: stabilize project switcher loading

* style: project switcher alignment

---------

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Co-authored-by: shimmyshimmer <107991372+shimmyshimmer@users.noreply.github.com>
Co-authored-by: Unsloth <michaelhan@Michaels-MacBook-Pro.local>
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
2026-06-01 22:09:16 +04:00
Nilay
9a907a8acb
Studio: add remote MCP server support (#5750)
* added remote MCP server support

* trim

* added tests

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* increased timeout

* disabling MCP chat toggle

* Fix MCP OpenAI function-name validation + cancel propagation for PR #5750

OpenAI requires function.name to match ^[a-zA-Z0-9_-]{1,64}$ before
streaming starts. The existing 64-char length check is necessary but
not sufficient: MCP servers can return tool names containing '.', '/',
spaces, etc. that would 400 the whole chat request. Validate the
composed mcp__<server_id>__<tool> name against the regex, skip + warn
on miss, and drop duplicate tool names from the same server (which
would also 400 the request as "duplicates").

Also propagate the agentic-loop cancel_event into MCP tool execution
so a /cancel POST during a long-running MCP call (e.g. GitHub MCP
search across a large repo) actually interrupts the in-flight HTTP
call instead of waiting out the 300 s timeout. The watcher polls the
threading.Event at 50 ms cadence inside the asyncio loop (matches
routes/inference.py's existing cancel-watcher cadence) and races
against the call task with asyncio.wait FIRST_COMPLETED.

Tests added:
  - test_mcp_specs_skip_invalid_openai_function_names: drops bad chars
  - test_mcp_specs_skip_empty_tool_name
  - test_mcp_specs_drops_duplicate_names
  - test_call_tool_sync_respects_pre_set_cancel_event

Also fix test_desktop_auth.py's router stub that listed every existing
router but missed mcp_servers_router, so importing main.py fails after
this PR adds it to routes/__init__.py.

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* PR #5750 round 2: OAuth cleanup on delete/url-change + mcp_enabled standalone

Round 2 of cross-platform validation surfaced two more P1 findings:

1. OAuth tokens never get cleared. fastmcp keys tokens by MCP URL, not by
   server row, and delete / URL change / use_oauth toggle only updated
   the SQLite row. Re-registering the same URL would silently reuse the
   old account's credentials. Adds clear_oauth_tokens_async() in
   mcp_client.py and calls it from the delete + put route handlers when
   the row had use_oauth=True and either the URL changes or OAuth is
   turned off.

2. mcp_enabled=true was ignored unless the caller also sent
   enable_tools=true. The frontend always sends both together so the UI
   path was fine, but a direct API caller sending only mcp_enabled would
   silently get no MCP tools, which contradicts the field's documented
   "append tools from every enabled MCP server" behavior. Loosens the
   use_tools gate in both the GGUF and safetensors paths so mcp_enabled
   opens the tool loop on its own; when the caller did not also opt
   into built-ins, the built-in list starts empty.

Tests added:
  - test_clear_oauth_tokens_async_no_op_safe
  - test_delete_server_calls_oauth_cleanup_when_oauth_was_on
  - test_delete_server_skips_oauth_cleanup_when_oauth_off
  - test_update_server_clears_oauth_on_url_change
  - test_update_server_clears_oauth_when_oauth_disabled

26 backend MCP tests pass; full studio/backend suite 1710 passed locally.
Cross-platform CI (Linux, macOS, Windows) green on staging fork.

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* PR #5750 round 3: reject null bool updates + /test surfaces 400

Round 3 of cross-platform validation:

1. PUT /api/mcp/servers/<id> would 500 with TypeError when the body
   explicitly set is_enabled or use_oauth to null. Pydantic accepts
   None for an Optional[bool] and _changes_from_payload then passed
   None into mcp_servers_db.update_server, which int(None)d. Reject
   explicit null at the validation layer with 400 instead.

2. POST /api/mcp/servers/test caught HTTPException under
   "except Exception", so an invalid URL came back as HTTP 200 with
   {"ok": false, "error": "400: ..."} instead of a real 400. The
   create + update paths return 400 for the same input. Move
   validation outside the transport try/except so it surfaces 400.

Tests added:
  - test_changes_from_payload_rejects_null_is_enabled
  - test_changes_from_payload_rejects_null_use_oauth
  - test_test_endpoint_surfaces_url_validation_as_400

* PR #5750 round 4: hyphenated MCP tool names + empty-tool-list gate

Round 4 surfaces two more interaction bugs between the new MCP path
and existing safetensors tool plumbing:

1. OpenAI accepts ^[a-zA-Z0-9_-]{1,64}$ for function.name, and round 1
   widened the MCP regex to that set, so MCP tools can now be advertised
   as `mcp__srv__list-issues`. But the XML tool-call parser in
   tool_call_parser.py used `\w+` (no hyphen), so the model could call
   the tool but Studio could not parse the call. Same in
   routes/inference.py's `_TOOL_XML_RE` stripper, which would leave
   hyphenated tool-call XML in the visible content. Both regexes now
   use `[\w-]+`.

2. safetensors_agentic treats `tools=[]` as "allow all" (documented
   contract, exercised by test_empty_tools_list_does_not_enforce_allowlist).
   When a caller sends `enable_tools=true` + `enabled_tools=[]` +
   `mcp_enabled=true` and MCP discovery returns 0, the resolved tool
   list is genuinely empty and built-in tools (web_search / python /
   terminal) could execute via the model's emitted call. Fix at the
   route gate instead of breaking the documented contract: set
   `use_tools=False` when the resolved list is empty, in both GGUF and
   safetensors paths. Existing callers who omit `enabled_tools` still
   get ALL_TOOLS and are unaffected.

Tests added (32 total):
  - test_tool_xml_parser_handles_hyphenated_function_names
  - test_tool_xml_strip_handles_hyphenated_function_names
  - test_safetensors_agentic_empty_allowlist_still_means_allow_all
    (documents the contract round 4 preserved)

1716 passed locally; cross-platform CI on staging fork still green.

* PR #5750 round 5: GGUF allow-list + CLI policy + hyphenated params + cancel race

Round 5 of parallel-reviewer aggregation surfaced six additional
findings; five are real and fixed here:

1. Hyphenated MCP parameter names (`<parameter=issue-number>`) were
   dropped by the XML parser's `\w+` regex. Extended to `[\w-]+` in
   both core/inference/tool_call_parser.py and core/tool_healing.py.
   The latter is GGUF's own copy of the parser/strip patterns and was
   missed by round 4.

2. core/tool_healing.py's `strip_tool_call_markup` still used
   `<function=\w+>` so hyphenated MCP tool-call XML leaked into the
   GGUF visible content even after round 4 fixed the shared parser.

3+4. `mcp_enabled` re-opened the tool loop even when the operator
   passed `unsloth run --disable-tools` (CLI policy False). Round 2's
   `(_tools_on or payload.mcp_enabled)` gate ignored the raw process
   policy. Now reads `state.tool_policy.get_tool_policy()` and gates
   mcp_enabled on `_cli_policy is not False`. Applied to both GGUF
   and safetensors paths.

5. GGUF's agentic loop called `execute_tool(tool_name, ...)` without
   checking the model-emitted name against the per-request tool list,
   while the safetensors loop already enforces this. Added the same
   allow-list check so a model that hallucinates a filtered MCP name
   or a built-in the caller opted out of returns "not enabled" instead
   of executing.

Bonus P2 fixes:
  - `call_tool_sync` now checks `cancel_event.is_set()` BEFORE
    creating the call task, so a pre-set cancellation does not open
    the HTTP transport.
  - `clear_oauth_tokens_async` moved the OAuth import + construction
    inside the protected try block; a fastmcp.client.auth load error
    used to escape and 500 the delete / update route.

NOT fixed (verified false or out of scope):
  - finding #10 "structured_content vs structuredContent": fastmcp's
    CallToolResult dataclass uses snake_case (verified live against
    structured-only tool result; fields are
    `dict_keys(['content', 'structured_content', 'meta', 'data', 'is_error'])`).
  - finding #11 "asyncio.run from running loop": call_tool_sync is
    invoked from `asyncio.to_thread` worker threads which have no
    event loop; asyncio.run() is safe there.

Tests added (37 total): hyphenated param names, tool_healing strip,
GGUF allow-list gate, cancel pre-set short-circuit, OAuth cleanup
constructor-error swallowing. 1721 passed locally, no regressions.

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---------

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Co-authored-by: danielhanchen <danielhanchen@gmail.com>
2026-05-27 07:01:11 -07:00
Lee Jackson
61ed4cac51
Studio: persist chat history in backend storage (#5272)
* feat: Persist chat history in backend storage

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* Address chat tombstone batching review

* fix: update desktop auth routes stub

* chat db settings storage

* chat db settings routes

* chat db settings client

* chat db settings store

* chat db settings wiring

* chat db history storage

* chat db settings migration

* chat db settings fallback

* chat db container metadata

* chat db legacy migration fixes

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* chat ci auth background reads

* chat auth storage fixes

* chat migration final fixes

* chat export batch message lookup

* chat history review fixes

* chat prune sync fix

* chat settings hydration retry

* gate settings persistence

* Scope chat-history rows by subject; fix hijack, clear-confirm, hydrate race

Backend storage and routes:
- chat_threads / chat_messages / chat_settings carry a NOT NULL subject
  column with composite PRIMARY KEY (id, subject). Two authenticated
  identities can no longer see or wipe each other's data.
- Pre-existing rows on an existing studio.db migrate under sentinel
  subject __legacy_unscoped__ via rename + rebuild + copy; single-user
  installs see no behavior change.
- ON CONFLICT(id, subject) DO UPDATE ... WHERE chat_messages.thread_id =
  excluded.thread_id refuses cross-thread re-parenting via upsert.
  upsert_chat_message + sync_chat_messages now raise
  ChatMessageThreadMismatch which the routes map to HTTP 409.
- replace_thread_messages rejects body messages whose threadId does not
  match the URL thread (HTTP 400) instead of silently rewriting them.
- DELETE /api/chat requires ?confirm=true, returns row count, logs the
  subject and count.
- upsert_chat_settings_merge does read + deep-merge + write inside a
  single BEGIN IMMEDIATE so concurrent writers no longer drop each
  other's updates. The route delegates to this helper.
- New POST /api/chat/messages:batch returns {thread_id -> messages[]}
  for many threads in one HTTP call. Subject-scoped. Unknown ids return
  empty lists instead of 404 so the sidebar/search caller can rebuild
  atomically.

Frontend:
- chat-runtime-store: hydrate-failure catch sets settingsHydrated:true
  so a transient backend blip no longer permanently disables
  persistence. setParams bumps inferenceParamMutationVersions
  unconditionally so a slow hydration response cannot clobber a
  pre-hydrate user edit. saveSettingsPatch replaces the serial chain
  with a debounced pendingPatch + deep merge; flush on beforeunload.
- chat-history-storage: clearStoredChats returns ClearStoredChatsResult
  distinguishing backend / legacy / both outcomes.
  listStoredChatThreadsWithMessages uses the batched fetch (one HTTP
  call) instead of Promise.all per-thread; legacy Dexie fallback only
  fires when the batch result is empty.
- chat-api: batchListChatMessages with graceful 404 / 405 fallback to
  per-thread listChatMessages for older servers.
- chat-thread-tombstones: store {id, deletedAt} tuples with 90-day GC
  and a 5000-entry cap so localStorage stays bounded. Back-compat reads
  pre-fix plain strings. Adds removeChatThreadTombstones (rollback) and
  clearAllChatThreadTombstones (post-legacy-purge clean-up).
- use-chat-sidebar-items: deleteChatItem tombstones synchronously
  BEFORE the backend round-trip and rolls back on failure (restores
  pre-PR optimistic UX). 300 ms trailing debounce on
  CHAT_HISTORY_UPDATED_EVENT plus requestSeq guard so stream-time event
  bursts produce at most one fetch per quiet window.

Tests:
- studio/backend/tests/pr5272_sim/ adds 64 regression tests covering
  schema migration from pre-fix shape, subject scoping, cross-thread
  hijack, bulk-replace mismatch, clear-confirm, concurrent settings,
  unicode + 2MB content + SQL-injection-safe binding, chunking
  boundary at 900 and 901 ids, batched endpoint (multi-subject + 1200
  ids + per-thread order), and grep contracts for the frontend patches.
  test_chat_history_storage.py updated to pass subject.

Verified locally on Linux + macOS + Windows GitHub Actions runners
(staging fork): 64 pass + 2 from the PR's own backend test on all
three OSes.

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* Drop subject scoping and clear-confirm gate (Studio is single-user)

Per maintainer feedback: subject scoping, cross-thread message hijack
guard, and DELETE /api/chat ?confirm=true gate are unnecessary because
Studio is intentionally single-user (the client already shows a confirm
dialog before clear-all).

This commit reverts those backend changes and keeps only the
non-multi-user pieces from the earlier fix commit:

- studio_db.py: restored to pre-fix shape; adds upsert_chat_settings_merge
  which does atomic read + deep-merge + write under BEGIN IMMEDIATE so
  two concurrent slider drags cannot drop one another's updates.
- routes/chat_history.py: restored; put_settings now calls the atomic
  merge instead of doing the read-merge-write across three separate
  connections. Adds POST /api/chat/messages:batch to collapse the
  sidebar/search rebuild from N round-trips to 1.
- frontend/api/chat-api.ts: align batchListChatMessages request and
  response keys with the backend (threadIds / messagesByThreadId).
- tests/test_chat_history_storage.py: add atomic-merge concurrency test,
  deep-merge nested-key test, and 901-id chunking-boundary test.
- Drop the pr5272_sim test directory (those tests covered the reverted
  subject-scoping/hijack/confirm behavior).

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* Fix sidebar delete crash, keepalive on settings beforeunload flush, search rebuild race

Two correctness bugs and one perf race surfaced by a fresh code review of
the prior fix commit:

- chat-api.ts: notifyChatHistoryUpdated was declared as a non-exported
  function, but use-chat-sidebar-items.ts imports it. The import would
  fail tsc with TS2305 and at runtime the optimistic-delete and
  delete-failure rollback paths would both throw.
- chat-runtime-store.ts + chat-settings-api.ts + chat-settings-storage.ts:
  the beforeunload settings flush is now actually keepalive. Without it
  the browser cancels the in-flight PUT on tab close, so the last slider
  drag is silently dropped (which is exactly the case the
  debounce+beforeunload combination was meant to protect against).
- use-chat-search-index.ts: rebuilds now coalesce with a 300ms trailing
  debounce and discard out-of-order responses via a requestSeq guard.
  Matches the sibling pattern in use-chat-sidebar-items.ts so two rapid
  CHAT_HISTORY_UPDATED_EVENTs (run-start + run-end save during a turn)
  cannot land with stale data winning.
- chat-thread-tombstones.ts: drop dead clearAllChatThreadTombstones with
  no call sites; Dexie is never wiped so the function has no use.

* fix(studio): protect chat persistence writes

* fix(studio): align chat history clear semantics

* fix(studio): show partial chat clear feedback

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* fix(studio): preserve chat persistence fallbacks

* fix(studio): harden chat thread persistence checks

* Preserve chat message timestamps

* Gate chat stream on history save

* Make chat thread backfill best effort

* Avoid chat message 404 probe

* Tighten chat legacy fallbacks

* chat: server-side ledger so legacy Dexie import is recoverable

The boolean localStorage sentinel
(unsloth_chat_legacy_imported_to_studio_db) made importLegacyChatsIfNeeded
non-recoverable: deleting studio.db while the browser keeps the flag
silently hides every legacy Dexie thread from the sidebar (verified by
the 3-GPU validation probe; matches the third review comment on PR
#5272). Same trap fires for browser-profile sync to a fresh machine
and any other path that wipes studio.db while keeping IndexedDB.

Source of truth moves into studio.db itself via a new
chat_legacy_import_log table keyed by legacy thread id. The ledger
disappears together with studio.db, so the next launch re-runs the
import from whatever Dexie still holds. localStorage stays as a
per-session perf hint only.

Performance, all bounded by the three new fast-paths before any
backend work:

  A) localStorage hint says "imported earlier in this session" -- 0
     network, ~0 ms. Covers the warm sidebar mount.

  B) indexedDB.databases() reports no "unsloth-chat" DB -- 0 network,
     ~1 ms. Covers every new user who never had the old browser-only
     Studio (the common case after launch).

  C) db.threads.count() + db.messages.count() are both 0 -- 0 network,
     ~5 ms. Covers returning users who migrated long ago and Dexie was
     never repopulated.

Only when all three miss does the code talk to the backend
(GET /api/chat/import-ledger -> diff vs Dexie -> existing import path
-> POST /api/chat/import-ledger to record what was just imported).
Per-thread tracking is enough because Dexie is read-only after this
PR; a thread's message set does not grow.

Backend deployments that predate the import-ledger routes are
handled transparently: the client treats 404/405 as an empty ledger
and re-runs the (idempotent via UPSERT) import on next launch.

Changes:
- storage/studio_db.py: new chat_legacy_import_log table (WITHOUT
  ROWID, PK on legacy_thread_id) + list_chat_legacy_import_log() +
  record_chat_legacy_import_log() (idempotent batch UPSERT).
- routes/chat_history.py: GET + POST /api/chat/import-ledger with the
  obvious request/response models.
- frontend api/chat-api.ts: listChatImportLedger() (returns a Set for
  O(1) diff) + recordChatImportLedger(), both with 404/405 fallback.
- frontend utils/chat-history-storage.ts: importLegacyChatsIfNeeded
  gains three fast-paths, ledger fetch on the slow path, and writes
  the ledger after a successful import. The localStorage helper is
  unchanged on the surface; it just stops being authoritative.
- tests: 5 new test_legacy_import_log_* cases (empty default, record
  + list round-trip, idempotency, input dedup, empty/null ignore).
  All 9 pre-existing tests still pass.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Make the legacy-import recovery actually recoverable

The previous commit added a server-side ledger to make Dexie -> studio.db
import recoverable after a studio.db wipe, but the localStorage perf hint
still short-circuited the import gate before the ledger was ever consulted.
After a wipe, the hint stayed "true" and the bulk re-import never ran -- the
ledger sat empty and only the per-thread lazy materialize-on-continue path
restored data.

Changes:

- Remove the localStorage short-circuit from importLegacyChatsIfNeeded so
  the ledger is checked on every fresh tab. legacyChatImportPromise keeps
  the per-session cache; the hint now only matters for the listing paths.
- Batch the slow path: one db.messages.where().anyOf().toArray() and one
  batchListChatMessages() instead of 2N round-trips. At 1k threads this
  drops a multi-second blocking import to a single request pair.
- recordChatImportLedger returns {accepted, inserted, supported}. The
  localStorage hint is only flipped when supported is true, so old
  backends (404 / 405 / 501) no longer permanently poison recovery.
- Ledger backfill: threads already present in chat_threads but missing
  from the ledger now get added too, so old-FE-then-new-FE deployments
  don't redo the diff every launch.
- Backend response field renamed recorded -> {accepted, inserted}.
  accepted is the deduped non-empty input count; inserted is the rows
  actually new (via INSERT ... RETURNING). Bounded by Field(max_length=
  10_000) on the request payload.
- Storage helpers renamed: chat_legacy_import_log -> chat_legacy_imports,
  record_* -> upsert_* to match the existing noun/verb conventions.
- DEXIE_DB_NAME exported from db.ts; duplicate constant in
  chat-history-storage.ts removed.
- 3 new route-level tests for /api/chat/import-ledger covering the
  round-trip, the (accepted, inserted) split, and the 10k payload cap.

All 18 chat-history tests pass.

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: shine1i <wasimysdev@gmail.com>
Co-authored-by: danielhanchen <michaelhan2050@gmail.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
2026-05-22 06:18:05 -07:00
Roland Tannous
9a0d6f80cb
studio: API external provider support for chat (OpenAI, Mistral, Gemini, Cohere, Anthropic, OpenRouter, DeepSeek, custom providers) (#4706)
* studio: add external provider support for chat inference

Adds the ability to connect to OpenAI, Mistral, Google, Cohere, Together,
Fireworks, and Perplexity from the Studio chat interface.

- Provider configs stored in SQLite (no API keys persisted)
- RSA-2048 key pair generated at startup for client-side key encryption
- httpx proxy client streams SSE responses in OpenAI-compatible format
- New /api/providers routes: registry, CRUD, test, models
- /v1/chat/completions routes to external provider when provider fields present
- Integration test suite covering CRUD, connection, model listing, and inference
- Frontend spec doc with full API contract

* remove frontend spec doc from branch

* fix auth fixture: handle forced password change on fresh install

* fix tests: default port 8000, allow 400 for no-model-loaded

* fix: update Cohere models to current (command-r retired Sept 2025)

* feat: add OpenRouter as 8th provider

* feat: add native Anthropic provider with Messages API translation

* fix: correct Anthropic base URL and drop top_p (conflicts with temperature)

* feat: add DeepSeek provider (deepseek-chat, deepseek-reasoner)

* feat: rename google -> gemini, refresh model list to 2.5 series

* feat: remove together, fireworks, perplexity providers

* feat: multimodal image support for external providers

- Add _build_external_messages() that preserves image_url parts for
  vision-capable providers instead of stripping them
- Update _proxy_to_external_provider() to use new helper
- Translate image_url content parts to Anthropic native image format
  in _stream_anthropic()
- Add TestVisionInference pytest class (1x1 PNG smoke test)

* test: use sloth photo URL for vision test, add Anthropic remote URL support

* fix: update Mistral model to mistral-small-2506

* update mistral default model to mistral-large-2512

* fix gemini vision test: download image as base64 data URI instead of remote URL

* add gemini-3-flash-preview as default gemini model

* fix gemini truncated reply (max_tokens 16->64) and suppress GeneratorExit on client disconnect

* increase vision test max_tokens to 215

* fix GeneratorExit: aclose stream generator before closing httpx client

* fix httpcore GeneratorExit: explicitly aclose aiter_lines before response closes

* fix duplicate [DONE] and suppress httpcore RuntimeError on Python 3.13 asyncgen cleanup

* fix: call response.aclose() before lines_gen.aclose() to prevent httpcore RuntimeError on Python 3.13

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Potential fix for code scanning alert no. 36: Clear-text logging of sensitive information

Co-authored-by: Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>

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* review: add comments for manual iteration rationale, mask password in test print, clarify Anthropic URL/models support

* perf: use shared module-level httpx client for connection pooling across requests

* studio: add API provider UI and integrate wiring (#4737)

* feat: expose external models in selector and chat settings

* feat(chat): wire external providers to backend + RSA key flow

- Fetch registry/configs; create/update/delete saved providers
- Encrypt API keys (Web Crypto RSA-OAEP) for test/models/chat
- External model selection + chat payload (provider_id/type, external_model, encrypted key, optional base URL)
- Local storage for keys + provider list; small UX/copy and guardrails

* add missing providers-api.ts file by Imagineer99

* fix: address PR review comments — system prompt visibility, retry loop, test logging

* feat(studio): encrypt external provider API keys at rest in localStorage

API keys for external providers (OpenAI, Mistral, etc.) were stored as
plaintext in localStorage, vulnerable to browser extensions and XSS.

Add password-derived AES-256-GCM encryption: on login the user's password
is used via PBKDF2 (100k iterations, SHA-256) to derive an in-memory
encryption key. API keys are encrypted before writing to localStorage and
decrypted on read. The derived key is never persisted — cleared on logout,
re-derived on next login.

Legacy plaintext keys are transparently migrated on first access. Password
changes re-encrypt all stored keys. No backend changes required — the
existing RSA-OAEP transit encryption is unaffected.

* fix: cast PBKDF2 salt to BufferSource for strict TypeScript lib types

* fix: persist session password in sessionStorage to survive page refreshes

* feat(studio): preserve image parts in external provider chat requests

toOpenAIMessage() now returns multimodal content arrays (OpenAI vision
format) when messages contain images, instead of always flattening to
plain text. This enables vision-capable external providers (OpenAI,
Gemini, Anthropic, etc.) to receive user images. The backend already
handles image_url content parts in _build_external_messages().

* studio: fix external models selectable in chat-only mode (#4779)

* fix: external models selectable in chat-only mode

* fix: model selector tabs default to active model kind

* Studio: API external provider registry + curated catalogs (HF/OpenRouter) and chat UX (#4787)

* fix: external models selectable in chat-only mode

* fix: model selector tabs default to active model kind

* feat(studio): expand provider registry, curated catalogs, and chat UX

- Add Hugging Face, Kimi, Qwen; remove Cohere; reorder registry
- model_list_mode curated for HF/OpenRouter; lightweight /models check
- API returns default models for curated providers; expose model_list_mode
- Frontend: provider logos in model picker, providerType on external models
- Chat providers dialog: curated vs remote flows, motion polish
- Thread: LayoutGroup + composer motion alignment with app easing

* fix(studio): disable Anthropic tool-calling flag and preselect curated defaults

* feat(studio): add external provider logos and ApiProviderLogo helper

* Studio: Polish API Providers dialog  (#4899)

* fix: lower verbage in API providers page

* fix: fix(studio): tune API Providers dialog width with rem-based responsive caps

* feat: add custom provider support (#4902)

* fix: replace crypto.subtle with node-forge for HTTP compatibility

crypto.subtle is only available in secure contexts (HTTPS/localhost),
which breaks provider API key encryption when Studio is accessed over
plain HTTP on remote GPU VMs. Switch to node-forge for RSA-OAEP and
AES-256-GCM operations — same algorithms, works on any origin.

* fix: store provider API keys as plaintext in localStorage

Drop AES-256-GCM at-rest encryption for provider API keys. The
session-password-derived encryption broke on auto-login via refresh
token (password never captured), causing keys to silently vanish.
API keys are still RSA-encrypted in transit via node-forge. At-rest
encryption in localStorage added no real security since the
decryption key also had to live client-side.

Removes crypto-storage.ts, session password plumbing, and
reEncryptAllKeys.

* fix: use max_completion_tokens for OpenAI provider

Newer OpenAI models (gpt-4o, gpt-5.x) reject the max_tokens param
and require max_completion_tokens instead. Other providers still use
max_tokens.

* fix: skip empty assistant messages in external provider requests

Some providers (Mistral) reject assistant messages with empty content.
Filter them out when building the message list for external providers.

* Update model-selector.tsx

* Update model-selector.tsx

* Update model-selector.tsx

* Update chat-adapter.ts

* Update chat-adapter.ts

* Update chat-page.tsx

* Update chat-settings-sheet.tsx

* Update chat-settings-sheet.tsx

* Update chat-settings-sheet.tsx

* Update chat-providers-dialog.tsx

* feat: polish providers settings form UI

* style: polish provider row icon sizing and alignment

* style: stabilize provider layout

* style: add provider API key visibility toggle

* fix: add provider render on empty list

* studio/frontend: sync package-lock.json with package.json

npm ci was failing because node-forge and @types/node-forge were
declared in package.json but missing from the lockfile. Ran
npm install to regenerate.

* studio/backend: fix backend CI failures for providers router

- test_desktop_auth: include providers_router in the routes stub so
  studio.backend.main imports cleanly under the monkeypatched module
- test_providers_api: skip the whole module when STUDIO_TEST_PASSWORD
  is unset (it is an integration test against a live Studio server,
  same shape as the already-ignored test_studio_api.py)

* studio/chat: drive ChatSettingsPanel from a per-provider capability map

Replace the binary isExternalModel toggle in the sampling section with a
provider-aware capability map. Each external provider type advertises
which of top_k / min_p / repetition_penalty / presence_penalty its
chat-completions API actually accepts, so the panel only renders the
knobs that map onto the active provider's request body.

Anthropic now exposes top_k; DeepSeek hides presence_penalty (deprecated
in their docs); OpenRouter and custom providers continue to show every
knob (OpenRouter drops unsupported server-side, custom assumes
OpenAI-compat or a permissive vLLM/Ollama backend). Local models are
unaffected — null capabilities means 'show everything'.

chat-adapter.ts now forwards top_k / presence_penalty to the external
proxy only when the active provider's capabilities permit it, so the
request body matches what the UI shows.

* studio/backend: forward top_k to Anthropic; filter OpenAI model list

Two paired changes so the frontend capability map has matching backend
behaviour:

1. ExternalProviderClient.stream_chat_completion now accepts top_k and
   forwards it to the Anthropic Messages body. OpenAI-compat providers
   (which all reject unknown sampling params) still receive only the
   fields they document. The proxy route in routes/inference.py passes
   payload.top_k through, so a UI request with top_k actually reaches
   Anthropic instead of being silently dropped at the boundary.

2. PROVIDER_REGISTRY['openai'] gains a model_id_allowlist regex that
   scopes the /models picker to current-gen ids (gpt-5.5 / gpt-5.4 /
   gpt-5.3 / gpt-4.5 / o3 families). The remote /v1/models listing
   otherwise returns dozens of historical snapshots, fine-tunes and
   non-chat models (embeddings, TTS, image, moderation) that we never
   want in the chat UI. default_models is refreshed to match.

* studio/chat: relax presence_penalty to optional on OpenAIChatCompletionsRequest

Followup to 1fbf445a — chat-adapter now omits presence_penalty for
providers that do not accept it (Anthropic / DeepSeek), but the
request type still required it as a non-optional number, breaking
tsc. The backend pydantic model already defaults presence_penalty
to 0, so making it optional client-side matches reality.

* studio/backend: route OpenAI traffic through /v1/responses

OpenAI's new flagship models (gpt-5.x) return 404 'This is not a chat
model' on /v1/chat/completions and are only reachable via /v1/responses.
Add a dedicated _stream_openai_responses path in ExternalProviderClient
that:

- Translates outbound messages into the Responses shape: system messages
  are folded into the top-level 'instructions' field, user/assistant
  messages become {role, content} items with input_text / input_image
  content parts (data URLs and https URLs both pass through).
- Drops presence_penalty / top_k / frequency_penalty, none of which the
  Responses contract accepts.
- Translates inbound SSE events back into OpenAI Chat Completions
  chunks so the frontend keeps a single SSE shape:
    response.output_text.delta  -> delta chunk with content
    response.completed          -> chunk with finish_reason='stop'
    response.incomplete         -> chunk with finish_reason='length'
    response.failed / error     -> propagated error SSE line
  Stream terminates with data: [DONE] (Responses emits this verbatim).

stream_chat_completion dispatches all provider_type='openai' calls to
this path; other OpenAI-compatible providers (mistral, gemini, etc.)
continue to use /v1/chat/completions.

Frontend provider-capabilities map updated to hide presence_penalty for
OpenAI in the chat settings panel, matching the new request contract.

Includes unit coverage in tests/test_openai_responses_translation.py
exercising the request body translation, image-part rewriting, and
SSE-to-chat-completions translation via httpx.MockTransport.

* studio/chat: clamp external max_tokens to 32k to stay within provider caps

The chat settings slider already capped maxTokens at 32768 for external
models, but a value persisted from a prior local-model session (where
the cap can be 128k+) was sent verbatim to the provider — Claude Opus
returns 'max_tokens: 131072 > 128000' on requests like that, and other
providers have stricter limits still.

Expose EXTERNAL_MAX_OUTPUT_TOKENS from provider-capabilities (32k) and
use it both for the slider max and as the clamp inside chat-adapter's
external-request body. 32k sits below the tightest declared output
limit across the providers we ship and well above what a typical chat
reply needs; the local-model path is unaffected.

* studio: drop temperature/top_p for OpenAI reasoning models

gpt-5.x / o3 / gpt-4.5 are reasoning-class models served via
/v1/responses, and reject temperature and top_p with
'Unsupported parameter' 400s. The OpenAI registry allowlist already
scopes the picker to those families, so neither knob ever applies on
this branch.

- external_provider._stream_openai_responses no longer puts
  temperature or top_p in the request body (kept on the method
  signature for API symmetry with the other stream methods).
- ProviderCapabilities gains temperature/topP flags; OpenAI sets both
  to false. ChatSettingsPanel hides the sliders for OpenAI so the user
  does not see inert controls.
- chat-adapter omits temperature/top_p from the external request body
  when the active provider does not advertise them.
- OpenAIChatCompletionsRequest type marks both as optional, matching
  the new chat-adapter shape.
- test_responses_request_body_uses_input_and_instructions: assertions
  flipped to confirm temperature / top_p are absent from the body.

* studio: stop forwarding top_k to Anthropic

Claude 4.x (Opus / Sonnet / Haiku 4.x) returns 400 'top_k is
deprecated for this model' on any request that includes top_k. It
was always optional on the older 3.x line, so dropping it
unconditionally for every Anthropic call is the simplest path —
no per-model gate to maintain.

- external_provider._stream_anthropic no longer adds top_k to the
  Messages body (kept on the method signature for API symmetry).
- provider-capabilities sets anthropic.topK = false so the chat
  settings panel hides the Top K slider for Anthropic providers
  and chat-adapter does not send top_k in the external request.

* studio: gate Anthropic top_k drop to Claude 4.7 only

Previous commit (b5aa6ffd) dropped top_k for every Anthropic call,
but only Claude 4.7 (Opus/Sonnet/Haiku) actually rejects it. 4.6, 4.5,
and the 3.x line still accept top_k and use it as documented.

Backend: _stream_anthropic matches the model id against
^claude-(opus|sonnet|haiku)-4-7(-|.|$) and only strips top_k when it
hits. Every other Claude generation continues to receive the value
from the chat settings panel.

Frontend: anthropic.topK is restored to true so the Top K slider is
visible again — the backend handles the per-model drop, and the
4.7 case is silent (request still succeeds without top_k).

* chore: hide dated openai models in provider select

* studio/providers: apply model_id_denylist when listing remote models

The OpenAI registry entry gained a model_id_denylist regex matching
dated snapshot ids (-YYYY-MM-DD) in 048d73bf, but the list-models
route was never consulting it, so the snapshots still showed up
alongside their canonical ids (gpt-5.5 and gpt-5.5-2026-04-23 both
listed). Apply the denylist with .search() right after the allowlist
filter so dated entries are dropped before the response is built.

* studio/chat: seed registry default_models for remote providers in picker

The Anthropic provider runs in remote model-list mode, so the picker
started with an empty availableModels until the user clicked
'Load Models'. If that /api/providers/models call fails (e.g. the
known transient decryption error during key rotation), the user sees
no models at all — claude-haiku-4-5 in particular was missing from
the dialog even though it is seeded in the registry.

Always pre-populate availableModels with the registry's default_models
when a provider type is selected (curated and remote alike), and have
loadModels() return the union of defaults + the live /models response
so registry-seeded ids are reachable regardless of what the provider's
endpoint returns or whether the call succeeds at all.

* studio/backend: diagnostic logging on provider key decryption

Decryption failures currently log just 'Failed to decrypt API key:
Decryption failed', which leaves no way to tell whether the cause is
a stale public key in the browser, a corrupted ciphertext, an
unexpected exception class, or a server-side keypair rotation. That's
the gap the next reproduction needs to close.

- key_exchange now publishes a short SHA256 fingerprint of the public
  key PEM. init_key_pair logs the fingerprint on generation and warns
  if it is ever called a second time (re-init silently invalidates
  every browser that cached the previous public key).
- decrypt_api_key wraps both the base64 decode and the RSA decrypt
  in dedicated try/excepts that log exception type, ciphertext byte
  length (RSA-2048 should be exactly 256), input string length, and
  the current public-key fingerprint.
- GET /api/providers/public-key returns the fingerprint alongside the
  PEM so the frontend can correlate a future encrypt-time fingerprint
  against the decrypt-time fingerprint and prove or rule out a
  keypair rotation as the cause.
- The /test and /models route-level decrypt warnings now include the
  exception class name (alongside the existing message).

* studio/providers: hide dated Anthropic snapshots from the model picker

Anthropic's /v1/models returns dated snapshot ids (e.g.
claude-3-5-sonnet-20241022, claude-3-5-haiku-20241022) alongside
the canonical names users actually want to pick. Same intent as
the OpenAI denylist added in 048d73bf, just a different date
format — Anthropic uses -YYYYMMDD (no dashes) while OpenAI uses
-YYYY-MM-DD.

- Add model_id_denylist = re.compile(r'-\d{8}$') to the anthropic
  registry entry. The /api/providers/models route already applies
  any denylist after fetching, so dated ids drop out automatically.
- Strip the dated 3.5 ids from default_models so the seeded picker
  no longer surfaces them; keep claude-opus-4-7 and the 4.5 family
  as the curated set.

Net effect: the picker shows opus-4-7 / opus-4-5 / sonnet-4-5 /
haiku-4-5 only, regardless of whether the remote /models call
succeeds or fails.

* fix: provider dialog and mistral short list

* style: fix provider dialog curated list styling

* fix: provider dialog curated model ids placeholder reference

* style: rename Providers to Cloud and tighten dialog header spacing

* UX: rename Providers to Cloud, remove header shortcut

* studio/chat: normalize structured delta.content from reasoning providers

Mistral's magistral (and similarly-shaped reasoning models) stream
chat-completion deltas where choices[0].delta.content is an array of
structured parts rather than a plain string, e.g.
  [{ type: 'text', text: '...' }, { type: 'thinking', thinking: '...' }]
The accumulator did 'cumulativeText += delta', which coerced each
part to '[object Object]' and produced output like
  '[object Object][object Object]...Hey there!'.

Add extractDeltaText() to normalize delta.content before append:
- string → returned as-is
- array of parts → text/output_text parts contribute their .text or
  .content; thinking/reasoning parts are re-wrapped inline as
  <think>...</think> so the downstream parseAssistantContent lifts
  them into a reasoning part the same way it does for providers that
  emit thinking inline. magistral keeps its thinking panel; no other
  provider's output shape changes.
- unknown shapes → dropped rather than stringified, so a stray field
  cannot pollute the rendered chat with '[object Object]'.

* Studio: restore Cloud icon shortcut in chat header

Brings back the header chip that opens Settings -> Cloud (external
providers) directly from the chat view. Same button as before the
bf24e604 removal: single-mode only, opens useSettingsDialogStore on
the 'connections' tab, tooltip 'API providers'.

* studio/chat: strip trailing template literal from external provider streams

Mistral's magistral occasionally appends a literal '${response}' token
after its actual answer — likely a training-format artifact, since it
keeps happening with an empty system prompt and only on that model.

Apply a tight strip in the chat-adapter SSE accumulator: when the
active provider is external, drop a trailing '${...}' template literal
(with optional whitespace) from cumulativeText after each chunk. The
regex anchors to end-of-string, so mid-stream fragments ('${re')
remain untouched and only collapse once the closing brace arrives.
Local-model output is unaffected.

* studio/providers: scope Kimi picker to kimi-k2.6 / kimi-k2.5

Mirror what the live Kimi docs surface as the current models
(https://platform.kimi.ai/docs/models). Everything else the
remote /v1/models call returns — moonshot-v1-* legacy ids and
dated k2 previews like kimi-k2-0711-preview — is filtered out.

- default_models: ['kimi-k2.6', 'kimi-k2.5'] (was four
  legacy moonshot-v1 ids plus the dated k2 preview)
- model_id_allowlist: ^kimi-k2\.[56]$ applied in the
  /api/providers/models route after the live fetch
- doc-link comments point at platform.kimi.ai overview /
  models / list-models for the next refresh

* studio: drop temperature/top_p for Kimi reasoning models

Kimi k2.5/k2.6 are reasoning-class. The API locks temperature and
top_p to fixed defaults and 400s on any other value with
'invalid temperature: only 1 is allowed for this model'.

The frontend capability map already gated these knobs out of the
external request body, but the OpenAI-compat path on the backend
unconditionally re-adds them from the pydantic ChatCompletionRequest
defaults (temperature=0.7 etc), so the gate was bypassed end-to-end.

Add a generic body_omit hook on the provider registry that
stream_chat_completion consults after building the body, and use it
to strip temperature/top_p for Kimi. Frontend provider-capabilities
flips kimi.temperature and kimi.topP to false so the sliders are
hidden in the chat settings panel as well.

* studio/providers: scope Gemini picker to current 3.x + *-latest aliases

Google's /v1beta/openai/models returns dozens of historical,
experimental, and non-chat ids that we never want in the chat UI.
Cap the picker to the current curated set:

- gemini-3.1-pro-preview
- gemini-3.1-flash-lite
- gemini-3-flash-preview
- gemini-pro-latest
- gemini-flash-latest
- gemini-flash-lite-latest

Default_models seeded with these, model_id_allowlist applied in
the /api/providers/models route to drop anything else the live
fetch returns.

* studio/providers: switch Hugging Face to remote model listing

Per the Inference Providers docs
(https://huggingface.co/docs/inference-providers/index),
GET https://router.huggingface.co/v1/models returns the full
chat-model catalog across all providers, including per-provider
metadata. The OpenAI-compatible endpoint we already use for
chat completions accepts the same Bearer token, so flipping
model_list_mode from 'curated' to 'remote' lets users discover
models via the existing list_models() path without any new
wiring.

- model_list_mode: 'remote' (was 'curated')
- default_models refreshed with current popular ids
  (gpt-oss-120b, DeepSeek-V3, Llama-3.3-70B, Qwen2.5-72B) so the
  picker still has a sensible seed if /v1/models fails
- notes updated to reference the docs page and clarify the
  endpoint is chat-only

* UX: chat cloud icon changed to model select signifier

* studio/providers: org allowlist + count cap for HF Inference picker

The HF /v1/models response is the full cross-provider catalog (hundreds
of ids — community fine-tunes, mirrors, fp8 variants, dated snapshots).
Scope the picker to the first-party org repos worth surfacing and cap
the post-filter list.

- model_id_allowlist matches the org prefixes openai/, deepseek-ai/,
  google/, meta-llama/, Qwen/, moonshotai/, mistralai/, zai-org/.
  Anything outside those orgs is dropped.
- model_id_limit (new registry field) caps the post-filter list. The
  list-models route now slices [:limit] after allowlist/denylist; set
  to 15 for HF Inference. Other providers leave it unset and behave
  exactly as before.
- default_models stays as the seed so the flagship ids users care
  about (gpt-oss-120b, DeepSeek-V3, Llama-3.3-70B, Qwen2.5-72B) are
  always reachable regardless of the API's response order.

Dedup is already handled in loadModels() via Set, so no additional
work needed there.

* style: adjust cloud icon right margin with rem spacing

* Studio: cloud openai reasoning level toggle (#5402)

* feat: cloud openai reasoning level toggle

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* fix: honor enable_thinking=false

* fix: prevent local reasoning toggle regressions and align OpenAI effort levels

* fix: isolate external OpenAI reasoning toggle state

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* fix: clamp reasoning effort

* fix: align OpenAI reasoning effort

* fix: clear stale GGUF badge state

* ui: new badge on cloud setting

* fix: separate selected models from cached provider model list

* Studio: anthropic effort by model family (#5412)

* feat: external thinking control and Anthropic effort mapping

* fix: anthropic thinking constraints and 4.6 max effort mapping

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* fix: harden Anthropic thinking params and effort mapping

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* studio/backend: drop top_p from Anthropic body when thinking is enabled

PR 5412 added body['top_p'] = max(0.95, min(top_p, 1.0)) inside the
thinking branch of _stream_anthropic, but Anthropic returns 400 on
extended/adaptive thinking when both temperature and top_p are set:

  invalid_request_error: temperature and top_p cannot both be
  specified for this model. Please use only one.

(Observed on Claude Opus 4.6.) The contract for thinking-enabled
requests is temperature=1 with neither top_p nor top_k allowed.

Replace the body['top_p'] = ... line with body.pop('top_p', None).
Defensive pop rather than a bare delete: the base body construction
above does not currently set top_p, but a future edit that adds it
would silently reintroduce the regression.

* studio/chat: force reasoningEnabled=true on local reasoning-effort models

Followup to PR 5402 / 5412. The model-status refresh path in
use-chat-model-runtime carried reasoningEnabled forward verbatim for
every reasoning-capable model. That left one observable edge case:

  1. user picks an external model that supports Off (gpt-5.x, Claude
     4.x), clicks Off — store sets reasoningEnabled=false
  2. user switches back to a local reasoning-effort model
     (gpt-oss / Harmony-style) which does NOT support Off
  3. composer's effectiveReasoningEnabled override paints the UI as
     'Think: <level>' (on)
  4. chat-adapter sees reasoningEnabled=false on the local branch
     and sends '{}', so the backend's _request_reasoning_kwargs
     returns None and the Harmony template falls back to its own
     default effort instead of the displayed level

Mirror the composer's override in the store on load: for local
reasoning-effort models (where supportsReasoningOff is false), force
reasoningEnabled=true so the store and the UI agree on every send.
Other reasoning styles still inherit prior state — only the
reasoning-effort family changes.

* studio/backend: align Anthropic thinking with the extended-thinking docs

Two compliance fixes against
https://platform.claude.com/docs/en/build-with-claude/extended-thinking

1. Adaptive-mode effort field shape
   The docs spell adaptive thinking as:
     {'thinking': {'type': 'adaptive'}, 'effort': {'type': '<level>'}}
   We had been sending the legacy 'output_config: {effort: <level>}'
   shape, which Anthropic appears to silently ignore — adaptive ran
   at the server default effort regardless of the user's selection.
   Rename to 'effort: {type: <level>}'.

2. thinking_delta event translation
   The Messages-API streams reasoning content as
   content_block_delta events with delta.type == 'thinking_delta',
   which our SSE loop was dropping entirely. On Claude 4.5/4.6 with
   display=summarized (the default), the user would see the answer
   text but never the reasoning panel. Wrap thinking_delta.thinking
   as inline <think>...</think> chunks (same pattern as the OpenAI
   Responses path) so the frontend's parseAssistantContent lifts it
   into the reasoning channel. The </think> closer fires on the
   first text_delta transition, on content_block_stop for the
   thinking block, on message_delta, and on message_stop —
   whichever arrives first — so no model path can leak an
   unclosed <think> into chat output.
   signature_delta events are left as no-ops; they carry
   verification metadata, not user-visible content.

Adds test_anthropic_thinking_translation.py with httpx.MockTransport
coverage of: effort shape on adaptive (Claude 4.6), budget_tokens
shape on manual (Claude 4.5), thinking_delta wrapping with signature
suppression, and thinking-only turns (display=omitted on Opus 4.7).

* studio/backend: revert Anthropic adaptive effort to output_config nesting

The previous commit (0a664df4) moved the adaptive-thinking effort
field to a top-level 'effort: {type: <level>}' based on a misread of
the docs page. The actual Messages API schema nests it under
output_config:

  thinking:       optional ThinkingConfigParam   ({type: 'adaptive'})
  output_config:  optional OutputConfig
    effort:       optional 'low' | 'medium' | 'high' | 'xhigh' | 'max'

Sending the top-level field produced:
  400 invalid_request_error: effort: Extra inputs are not permitted

Restore the body to:
  body['thinking'] = {'type': 'adaptive'}
  body['output_config'] = {'effort': effort}

This was the shape PR 5412 originally shipped (and the author
validated against live APIs). My 'compliance fix' was a regression.

The companion thinking_delta SSE translation added in 0a664df4 stays
— that part WAS missing from the previous shape and is unchanged
by this revert. Test pinning the body shape flipped to assert
output_config.effort, top-level effort is asserted absent.

* studio/backend: opt in to summarized thinking display on adaptive

Per the adaptive-thinking docs, the 'display' field on the thinking
config defaults to 'omitted' on Claude Opus 4.7 (and Mythos Preview).
With 'omitted' the API still emits a thinking content block, but its
'thinking' field is empty — only the signature_delta arrives.

Our SSE handler would then surface a stray '<think></think>' for the
empty block and the reasoning panel would stay blank for the entire
response. Set 'display': 'summarized' explicitly on the adaptive
thinking config so Opus 4.7 emits thinking_delta events the same way
Opus 4.6 / Sonnet 4.6 do (where 'summarized' is the default, making
the explicit setting a no-op there).

The manual-thinking branch (Claude 4.5) is unaffected — its default
is also 'summarized', and we have no reason to override it.

* studio/backend: log Anthropic SSE event counts for thinking diagnostics

Reports of 'no reasoning panel content on Anthropic' have two
distinct causes that produce the same symptom:

  1. Anthropic streamed thinking_delta events but our frontend
     dropped them somewhere on the rendering side.
  2. Anthropic did not emit thinking_delta at all (adaptive mode
     can skip thinking for simple prompts even with effort=high,
     and display=summarized only re-enables the *content* — it
     does not force thinking to happen).

Tally each event type for the duration of one stream and log the
counts in the finally branch, so the next 'no reasoning content'
report shows immediately whether thinking_delta was even on the
wire. Zero counts → upstream (model/effort/prompt choice).
Non-zero counts → triage moves to chat-adapter / parse-assistant
-content / the reasoning component.

* studio/backend: route external_provider logs through structlog

The studio backend wires structlog as the active logger (via
LogConfig.setup_logging at main.py:262), but external_provider.py
was using stdlib logging.getLogger(__name__) for every diagnostic.
The stdlib root logger defaults to WARNING with no handlers
attached, so plain logger.info('...') and logger.debug('...') from
this module were being silently dropped — including the
'Proxying chat completion to <url>' and the new
'Anthropic stream event counts' lines. Only WARNING/ERROR survived
(via the implicit fallthrough that the user actually observed
when an Anthropic call 400'd).

Switch the module-level logger to structlog.get_logger(__name__),
matching the routes/providers.py and routes/inference.py pattern.
All existing call sites use printf-style positional args, which
structlog accepts unchanged — no other edits needed.

* studio/backend: disable read timeout on SSE streams to external providers

Anthropic Opus 4.7 (adaptive thinking) and OpenAI gpt-5.x (/v1/responses)
can pause for tens of seconds between bytes while the model is
internally reasoning. httpx's read timeout is the *gap* between
successive reads, not a wall clock on the whole request — so the
shared 120s default was cutting streams mid-response:

  log: Anthropic stream event counts (... text_delta: 11)
       Read timeout from anthropic

(eleven text deltas in, no content_block_stop, no message_stop)

Add a separate _stream_timeout on ExternalProviderClient with
read = None (no gap timeout) and the same 10s / 120s connect/write/
pool bounds, then use it at the three SSE streaming call sites:
default OpenAI-compat chat completions, _stream_anthropic, and
_stream_openai_responses. Non-streaming call sites (chat_completion,
list_models, verify_models_endpoint_lightweight) keep self._timeout
because a stuck non-streaming response should still fail fast.

* studio/backend: log outbound Anthropic request shape for thinking debug

After bumping to Xhigh effort the user still saw zero thinking_delta
events and only one content_block_start, meaning Anthropic Opus 4.7
opened no thinking block at all. Per the effort docs that should be
impossible — Xhigh always thinks. Two open hypotheses:

  1. Our adaptive branch is not wiring output_config.effort onto the
     outbound body for this code path (regex miss, frontend never
     propagated reasoning_effort, etc).
  2. Anthropic is silently accepting output_config as an unknown
     field and falling back to high default effort regardless.

Add a single-line structlog INFO right before the stream POST that
echoes the keys actually present on the body (thinking, output_config,
temperature, presence of top_p / top_k, max_tokens). Messages are
deliberately excluded to keep PII out of the log. With this in place
the next 'no thinking on 4.7 at Xhigh' report shows immediately
whether we sent the effort knob — separating client bug from
provider behaviour.

* studio/chat: surface delta.reasoning_content from Kimi / DeepSeek thinking

Kimi (kimi-k2.6, kimi-k2-thinking) and DeepSeek's reasoner stream
their thinking content via a separate top-level field on the
chat-completion delta — choices[0].delta.reasoning_content — rather
than as a structured part inside delta.content. Per Kimi docs:

    In streaming output (stream=True), the reasoning_content field
    will always appear before the content field.

Our chat-adapter SSE loop only read delta.content (via
extractDeltaText), so the entire reasoning channel from these
providers was being silently dropped — kimi-k2.6 thinks by default
yet the chat UI showed no reasoning panel.

In the adapter:
- Read both delta.content and delta.reasoning_content per chunk
- When reasoning_content arrives, open a <think> block in
  cumulativeText (mirrors how the backend wraps Anthropic
  thinking_delta and OpenAI Responses reasoning summaries)
- When content arrives after reasoning, close </think> first
- On stream end, force-close any still-open <think> so
  parseAssistantContent can lift it into a reasoning part cleanly

Anthropic and OpenAI Responses paths are unaffected — they already
wrap as <think> on the backend and never set reasoning_content.

* studio: Kimi thinking toggle + 16k max_tokens floor

Two coordinated changes so Kimi's thinking is user-controllable and
the response budget meets the docs' floor.

Toggle (frontend + backend):
- getExternalReasoningCapabilities now handles provider=='kimi':
  kimi-k2.6 -> reasoning_style=enable_thinking, reasoningOff allowed
  kimi-k2-thinking -> always on (reasoningAlwaysOn=true, no off)
  kimi-k2.5 (and anything else) -> no reasoning controls
- chat-adapter already forwards enable_thinking on the
  enable_thinking-style branch, so the user toggle reaches the
  backend without additional wiring there.
- external_provider stream_chat_completion now translates the
  boolean into Kimi's wire shape on the default OAI-compat path:
    enable_thinking=True  -> body['thinking'] = {type: enabled, keep: all}
    enable_thinking=False -> body['thinking'] = {type: disabled}
  kimi-k2-thinking ignores the toggle so the API never gets a
  disabled value it would reject. Other providers on the same
  path are unaffected (gated on provider_type == 'kimi').

Max tokens floor:
- New EXTERNAL_MIN_OUTPUT_TOKENS_BY_PROVIDER table and
  getExternalMinOutputTokens helper. Kimi entry = 16000 per docs:
  'Set max_tokens >= 16,000 to ensure the full reasoning_content
  and final content can be returned without truncation.'
- chat-adapter clamps the outbound max_tokens to
  min(max(stored, providerMin), EXTERNAL_MAX_OUTPUT_TOKENS),
  so a stored value of 4096 still becomes 16000 when sending to
  Kimi (other providers unaffected, min stays effectively 64).
- chat-settings-sheet's Max Tokens slider min mirrors the same
  floor when an external Kimi model is selected, so the slider
  cannot show a value lower than what we'd actually send.
- chat-page threads activeExternalProviderType down to the panel.

* fix: stabilize external reasoning controls for Anthropic 4.6 and OpenAI o3

normalize Anthropic 4.6 reasoning effort handling by accepting max as an alias and mapping it to xhigh, while keeping Sonnet/Opus 4.6 in default model suggestions.
broaden reasoning effort typing across backend/frontend and migrate persisted max selections to xhigh for compatibility.
remove reasoning.summary=\"auto\" from OpenAI /v1/responses payloads to avoid o3 eligibility/gating errors.
tighten provider model filtering to hide retired gpt-5.3 IDs and add exact/prefix filtering support in provider routes.

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* studio: add openrouter/free + full reasoning passthrough on OpenRouter

Four-layer wire-up so the OpenRouter free-router model (which picks
a free model at random per request, filtered by needed capabilities)
shows up in the picker and its reasoning channel surfaces in the
chat UI.

Registry:
- providers.py: openrouter/free seeded at the top of openrouter
  default_models. Curated list, so picker shows it immediately.

Frontend capability map:
- provider-capabilities.ts: getExternalReasoningCapabilities now
  treats openrouter as enable_thinking style with off support. The
  Think dropdown appears for every OpenRouter model; the gateway
  silently no-ops the parameter for models that do not reason, so
  surfacing one toggle on every model is safe.

Backend reasoning passthrough:
- external_provider.py stream_chat_completion (default OAI-compat
  branch): for provider_type=='openrouter', translate the request:
    reasoning_effort in {low,medium,high} -> body['reasoning'] =
        {'effort': <level>}
    enable_thinking=True  -> body['reasoning'] = {'enabled': True}
    enable_thinking=False -> body['reasoning'] = {'enabled': False}
  Matches the documented shape at
  https://openrouter.ai/docs/guides/best-practices/reasoning-tokens
  with effort and max_tokens mutually exclusive.

Frontend SSE reader:
- chat-adapter.ts: OpenRouter streams reasoning as a third shape we
  did not handle yet: delta.reasoning_details is an array of parts
  like {type: 'reasoning.text', text: '...'}. Pull text from every
  part, merge with the existing delta.reasoning_content channel
  used by Kimi/DeepSeek, and feed the combined string through the
  same <think>...</think> wrap path so parseAssistantContent lifts
  it into the reasoning panel. Anthropic/OpenAI Responses paths
  already wrap on the backend, so they never set this field — no
  cross-provider interference.

* studio/backend: surface OpenRouter SSE errors and router-chosen model in logs

The frontend showed 'Provider returned error' for some openrouter/free
requests with nothing on the backend side to triage from — the
existing 4xx error log only fires when the upstream returns a non-200
status code, but OpenRouter (and most OAI-compat providers) return
200 OK and emit the actual failure as an SSE error event mid-stream,
which our default-path stream loop forwarded verbatim without
logging.

Best-effort diagnostics on the default OpenAI-compat stream path:
- Peek at every `data:` line in the inner forward loop, parse JSON
  best-effort (silently skip on failure so nothing is dropped).
- Count event types: delta / error / done.
- On any chunk containing an `error` field, emit a structlog WARNING
  with the provider type and the error payload — same trail the
  user would otherwise have to dig out of browser devtools.
- Latch the first non-empty `chunk.model` field. OpenRouter reports
  the router-picked underlying model there per request, so the
  finally-block summary log shows which free model handled the call.

In the finally block:

    'openrouter stream complete (model=openrouter/free,
     chosen=google/gemini-2.5-flash, events={delta: 47, done: 1})'

Zero overhead for non-error streams (a json.loads per chunk +
dict-key lookups). The structlog logger is already configured at
INFO; ERROR and WARNING surface in JSON logs without further setup.

Hoists `import json as _json` to module top so the default path can
reuse it; the existing in-function imports in _stream_anthropic and
_stream_openai_responses are now redundant but harmless.

* studio/chat: show router-picked model after 'openrouter/free:' in chip

When the user picks openrouter/free, the gateway routes each request
to a different underlying free model. Until now there was no way to
tell which one actually replied without reading the backend logs.

Surface the picked model in the active-model chip:

- chat-runtime-store gains lastOpenRouterChosenModel: string|null
  plus a setter. Reset on every model switch unless the user stays
  on openrouter/free.
- chat-adapter SSE loop latches chunk.model into the store on
  every chunk whose top-level model differs from
  openrouter/free, gated on the active checkpoint being
  openrouter/free under an OpenRouter provider.
- chat-page externalModels useMemo appends :<chosen> to the display
  name for the openrouter/free option when the store has a value,
  so ModelSelector renders e.g.
    'openrouter/free:google/gemini-2.5-flash'
  in the chip. Other models unaffected.
- Model-switch callback in chat-page clears the cached value when
  the user moves to any model other than openrouter/free, so the
  chip never shows a stale suffix from a previous session.

* studio/chat: shorten openrouter/free chip to openrouter:<short-chosen>

The full display name in use was:
  openrouter/free:inclusionai/ring-2.6-1t-20260508:free

The `:free` suffix on the underlying id already conveys 'free model',
which made the leading `/free` on the router id redundant, and the
`inclusionai/` org prefix was just noise crowding the chip.

Trim both. Now the chip renders as:
  openrouter:ring-2.6-1t-20260508:free

Strictly a display change in chat-page externalModels useMemo — the
backend wire id stays `openrouter/free`, the runtime store still
caches the full `inclusionai/...:free` value, and the model-switch
clearing logic is unchanged.

* studio/providers: switch OpenRouter to remote listing with org allowlist + cap

Same shape as Hugging Face Inference. The curated list had only four
entries; remote listing fetches OpenRouter's full ~300-model
catalog via /v1/models and the new allowlist + limit scope it back
down to a usable picker.

- model_list_mode: remote (was curated)
- model_id_allowlist matches the prefixes:
    openrouter | openai | anthropic | google | meta-llama | qwen
    | mistralai | deepseek | moonshotai | inclusionai | zai-org
    | z-ai
  Anything outside drops out.
- model_id_limit: 20 — first 20 post-filter matches from the live
  fetch; default_models stays seeded so the most useful canonical
  ids are always visible regardless of API response order.
- default_models seed extended from 4 to 6 (openrouter/free,
  openai/gpt-4o, anthropic/claude-sonnet-4-5, google/gemini-2.5-flash,
  mistralai/mistral-large-2411, deepseek/deepseek-r1).
  openrouter/free remains the first entry, so the dialog's
  loadModels() union-merge (registryDefaults first, then remote,
  deduped via Set) keeps it at the top of the picker.

* feat: external mistral thinking toggle

* studio/chat: fix TS2540 by replacing readonly ContentPart instead of mutating

The ContentPart type from @assistant-ui/react marks `text` as readonly,
so the coalesce-adjacent-same-type-part optimization in
parseAssistantContent failed the tsc build with:

  parse-assistant-content.ts(15,10): error TS2540: Cannot assign to
      'text' because it is a read-only property.
  parse-assistant-content.ts(25,10): error TS2540: ...

This broke npm run build, the Studio installer's `building frontend...`
step, and every downstream CI job that runs against an installed
Studio (Mac/Windows/Linux variants of Studio API CI, GGUF CI, UI CI,
Tauri CI, Wheel CI).

Replace the last element with a fresh merged object instead of
mutating its `text` field. Same allocation profile as the previous
path (one object swap per merge), type-safe under the readonly
declaration. Behaviour unchanged.

* studio/backend: restore summary='auto' on OpenAI Responses reasoning body

A recent refactor dropped the `summary: 'auto'` field from the
reasoning config we send to /v1/responses. Without it OpenAI does
not emit reasoning summary events on most reasoning models, which
means our SSE handler has no <think>…</think> to wrap and the chat
reasoning panel stays blank for any gpt-5.x / o3 response.

The expected wire shape is:
    body['reasoning'] = {'effort': '<level>', 'summary': 'auto'}

Two backend tests pin this:
- test_responses_reasoning_effort_included_when_requested (high)
- test_responses_reasoning_effort_xhigh_passthrough (xhigh)
Both were failing with AssertionError because the produced body
omitted `summary: auto`.

Restore the field. Skip it only for the explicit "off" case
(effort: 'none'), where summaries serve no purpose. The
enable_thinking=True fallback (no explicit effort) also pairs
medium effort with summary='auto' so that branch produces
reasoning text too.

* chat: external reasoning, OpenRouter curation, Think toggle fixes

* fix: opus and sonnet 4.6 xhigh --> max

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2026-05-14 16:13:59 +04:00
Lee Jackson
b65a7450ca
Studio: Dark theme refactor, right sidebar redesign, and chat UI polish (#5150)
* Dark theme refactor, right sidebar redesign, and chat UI polish

- Dark theme refactor
- Redesign right sidebar
- Further left sidebar adjustments
- Wider chat and content area; layout tweaks for chat content
- Rounded corners across elements for consistency
- Show chat message menu icons on menu-area hover, not only on message hover
- Assistant message menu icons now always visible; user messages keep on-hover
- Redesigned copy icon used consistently across chat blocks and messages
- Redesigned trash icon, applied consistently
- Unified icon sizing and style with the sidebar
- Adjusted icon colors across chat
- Fix on-hover background design for chat icons
- Fix tooltip from 'more' button staying visible after clicking elsewhere
- Adjust position and design of generation speed info text below messages
- Adjust design of token speed info popup
- Adjust sidebar scrollbar to cover recent chats only

* Recents sidebar rename, UI/theme refactor, layout and chat polish

UI & Theme:
- Dark theme refactor
- Consistent rounded corners across elements
- CSS polish and cleanup
- Remove unused logo image assets

Recents sidebar:
- Add 'more' button for options menu
- Support renaming conversations and training runs
- Confirmation dialog before deleting chats
- Add optional display_name column to training_runs (idempotent ALTER TABLE) so renaming doesn't lose model_name/dataset_name from the run config
- New PATCH /api/train/runs/{run_id} endpoint accepts { display_name: string | null }; empty/whitespace clears the override
- Sidebar shows display_name ?? model_name and exposes Rename in the row's More menu, mirroring the chat rename flow
- Cache last list response in localStorage and hydrate from it on mount, so recents paint instantly on F5 / route revisit; cached items are shape-validated and dropped if malformed
- Optimistic updates on rename and delete (apply locally + cache before background refresh)
- Visible toast on rename/delete failure instead of swallowed errors

Layout:
- Redesigned right sidebar
- Further left sidebar adjustments
- Updated chat content layout; chat and content area slightly widened
- Sidebar scrollbar covers recent chats only

Icons:
- Redesigned copy icon, unified across chat blocks and messages
- Redesigned trash icon to match
- Consistent icon sizing and style across chat and sidebar
- Adjusted icon colors across chat
- Fix icon on-hover background design

Chat messages:
- Menu icons now appear on hover over the menu area, not just the message
- Assistant message menu icons always visible; user messages keep on-hover (next/previous response stays visible for edited prompts)
- Repositioned and restyled generation speed info text below messages
- Restyled token generation speed popup

Tooltips:
- Removed tooltip on hover for previous/next assistant response icons
- Unified tooltip design across sidebars and chat
- Removed tooltip animations (also fixes related lag)

Model & Chat Template config:
- Merged Chat Template config into Model Configuration section
- Added revert-to-original for chat template
- Fix Chat Template config disappearing on page refresh until model reload

Performance & scroll:
- Removed chatbox movement animations across pages/navigation (fixes related UI lag)
- Fix scroll flicker at end of streaming when a code block is the final element
- Additional chat scroll improvements

Bug fixes:
- Fix 'more' button tooltip remaining visible after clicking elsewhere

* Remove sidebar localStorage cache and optimistic updates

Drops the localStorage hydration and optimistic rename/delete logic from the recents sidebar; reverts to fetching fresh on mount.

* Fix missing cn import in shared-composer (regression from merge)

* chore(sidebar): import sidebar deps from feature indexes

Re-export deleteChatItem / renameChatItem / useChatSidebarItems / SidebarItem / useChatSearchStore / ChatSearchDialog from @/features/chat, and removeTrainingUnloadGuard from @/features/training. Switch app-sidebar.tsx to consume them via the public feature indexes instead of deep paths, clearing the no-restricted-imports eslint errors. No behavior or UX change.

* fix(studio/frontend): reload training Recents sidebar after F5 refresh

The Recents sidebar showed empty after a hard refresh. The hook's inFlightRef dedup guard collided with React StrictMode's double-mount in dev: the second mount's fetch returned silently with no error, no retry, and no toast — leaving the sidebar empty until navigation.

Replace skip-if-busy dedup with abort-previous via a hook-level AbortController. This also fixes a latent race where a slow poll could resurrect a just-deleted row by clobbering the optimistic update.

Changes (all in use-training-history-sidebar.ts):
- fetchRuns aborts any in-flight request before starting a new one; post-await signal.aborted check drops stale responses.
- Optimistic helpers (applyRunUpdate, removeRun) abort in-flight fetches so they don't depend on caller discipline to invalidate stale data.
- Initial load gets bounded retry-with-backoff (500ms / 1.5s / 3.5s) and surfaces a sonner toast with a Retry action on final failure.
- Failure toast auto-dismisses on any successful load (initial retry, Retry click, or polling recovery).
- Polling pauses while the tab is hidden and catches up on visible, avoiding wasted requests during long training runs.
- Both effects own their teardown explicitly (abort + clear timer).

* Apply unified tooltip design and behavior across remaining pages for consistency

* UI polish: spacing, tooltip on source icons, letter spacing, smaller icons, consistent edit icon

- Adjust tiny spacing between elements around the UI for subtle polish
- Redesign tooltip on source icons for web search / tool use, consistent with the new design
- Adjust chat text letter spacing
- Smaller icon sizes
- Replace 'edit message' icon in chat with the new Rename icon used in Recents for consistency

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* Adjust CSS for right sidebar

* Fix scrollbar UI compatibility across browsers

* fix: preserve chat preset settings on model load

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* fix(studio): remove duplicate chat template status field

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* chore: remove creative preset assumption

* fix(studio): align speculative decoding default

* fix(studio/chat): snap numeric param inputs to step grid

- Type a value in any param input (Temperature, Top K, Max Tokens, etc.)
  now clamps to [min, max] and snaps to the slider's step grid, killing
  off-grid values like 1.051234 and FP residue from slider drags.
- Branch picker chevrons share the action bar's 32px height + 10px radius
  via a new .aui-branch-chevron-btn utility; hover area aligns visually
  while staying narrower than the sibling icon buttons.

* fix(studio/chat): keep training-run polls converging and drop dead preset code

- Keep training-run polls converging when responses outrun the 5s interval
  (don't unconditionally abort prior in-flight; skip if one is still pending,
  mutation race still guarded).
- Drop dead Creative/Precise preset code paths (remove 'builtin-fixed' source
  variant + unreachable branches).

* fix(studio): training-run cards show custom name + model + dataset

- Training-run cards now display custom display_name + model + dataset,
  with cross-view sync on rename/delete.
- Enhance clarity of borders and colors in dark theme on export etc.

* fix(studio): match active state green to unsloth brand color

* fix(studio): preserve can_resume on training rename

* fix(studio): keep GGUF chat template override distinct

* fix(studio): treat audio input models as multimodal

* fix(studio): cancel numeric draft on Escape

* fix(studio): use default speculative mode on toggle

* fix(studio): detect GGUF audio VLM input models

* fix(studio): address final PR review findings

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* fix(studio): refresh sidebar/history when a new training run starts so it appears without a manual reload

* fix: API and svg

* fix(studio/sidebar): align run rename dirty check with displayed baseline

* fix(studio/sidebar): use leading-tight on account block to prevent descender clipping with truncate

---------

Co-authored-by: sneakr <hauzin@hotmail.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
Co-authored-by: shine1i <wasimysdev@gmail.com>
2026-05-07 14:33:31 +04:00
Lee Jackson
2de17c0a96
Studio: Add checkpoint resume for stopped training runs (#5255)
* feat: add checkpoint resume for stopped training runs

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* fix:add resume checkpoint helpers

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* fix: use checkpoint parent as resume output dir

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* fix: save optimizer and scheduler state on stop-and-save

Use Trainer._save_checkpoint instead of save_state so resume restores
optimizer momentum and LR-schedule position via the checkpoint-NNN/
subdir written by HF's official path.

* fix: clean up resume training history and startup progress

* fix: preserve resume output dirs

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* fix: tighten resume run lookup

* fix: remove stale output-dir lookup

* fix: preserve startup download progress

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Roland Tannous <rolandtannous@gravityq.ai>
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
2026-05-04 00:34:46 +04:00
Wasim Yousef Said
1e8875584d
feat: custom scan folders for GGUF model discovery (#4723)
* feat: add scan_folders table and CRUD functions to studio_db

* feat: add scan folders API endpoints and integrate into model scan

* feat: add scan folders API client and update source types

* feat: add custom source to model filters and selector

* feat: add Model Folders section to chat settings sidebar

* style: fix biome formatting in ModelFoldersSection

* fix: address review findings for custom scan folders

empty string bypass, concurrent delete crash guard,
Windows case normalization, response_model on endpoints,
logging, deduplicated filter/map, module level cache for
custom folder models, consistent source labels, handleRemove
error surfacing, per folder scan cap

* fix: show custom folders section regardless of chatOnly mode

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* refactor: extract shared refreshLocalModelsList in pickers

* Harden custom scan folder validation and scanning

- Validate path exists, is a directory, and is readable before persisting
- Apply per-folder model cap during traversal instead of after (avoids
  scanning millions of inodes in large directories)
- Wrap per-folder scan in try/except so one unreadable folder does not
  break the entire /api/models/local endpoint for all callers
- Normalize case on Windows before storing so C:\Models and c:\models
  dedup correctly
- Extend macOS denylist to cover /private/etc and /private/tmp (realpath
  resolves /etc -> /private/etc, bypassing the original denylist)
- Add /boot and /run to Linux denylist

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Improve scan robustness and preserve Windows path casing

- Preserve original Windows path casing in DB instead of lowercasing
  (normcase used only for dedup comparison, not storage)
- Catch PermissionError per child directory so one unreadable subdirectory
  does not skip the entire custom folder scan
- Wrap list_scan_folders() DB call in try/except so a DB issue does not
  break the entire /api/models/local endpoint

* fix: scan custom folders for both flat and HF cache layouts

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* Fix Windows case-insensitive path dedup with COLLATE NOCASE

Use COLLATE NOCASE on the scan_folders.path column so that the UNIQUE
constraint correctly deduplicates C:\Models and c:\models on Windows
without lowercasing the stored path. Also use COLLATE NOCASE in the
pre-insert lookup query on Windows to catch existing rows with
different casing.

* Restore early-exit limit in _scan_models_dir for custom folders

Keep the limit parameter so _scan_models_dir stops iterating once
enough models are found, avoiding unbounded traversal of large
directories. The post-traversal slice is still applied after combining
with _scan_hf_cache results.

* feat: scan custom folders with LM Studio layout too

* Fix custom folder models being hidden by dedup

Custom folder entries were appended after HF cache and models_dir
entries.  The dedup loop kept the first occurrence of each model id,
so custom models with the same id as an existing HF cache entry were
silently dropped -- they never appeared in the "Custom Folders" UI
section.

Use a separate dedup key for custom-source entries so they always
survive deduplication.  This way a model can appear under both
"Downloaded" (from HF cache) and "Custom Folders" (from the
user-registered directory) at the same time.

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* Harden LM Studio scan and fix COLLATE NOCASE on Linux

- Add per-child and per-publisher OSError handling in _scan_lmstudio_dir
  so one unreadable subdirectory does not discard the entire custom
  folder's results
- Only apply COLLATE NOCASE on the scan_folders schema on Windows where
  paths are case-insensitive; keep default BINARY collation on Linux
  and macOS where /Models and /models are distinct directories

* Use COLLATE NOCASE in post-IntegrityError fallback SELECT on Windows

The fallback SELECT after an IntegrityError race now uses the same
case-insensitive collation as the pre-insert check, so a concurrent
writer that stored the path with different casing does not cause a
false "Folder was concurrently removed" error.

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
2026-03-31 06:40:31 -07:00
Wasim Yousef Said
208862218d
feat(studio): training history persistence and past runs viewer (#4501)
* feat(db): add SQLite storage layer for training history

* feat(api): add training history endpoints and response models

* feat(training): integrate DB persistence into training event loop

* feat(ui): add training history views and card grid

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix(studio): address review issues in training history persistence

- Strip hf_token/wandb_token from config before SQLite storage
- Add UUID suffix to job_id for collision resistance
- Use isfinite() for 0.0 metric handling throughout
- Respect _should_stop in error event finalization
- Run schema DDL once per process, not per connection
- Close connection on schema init failure
- Guard cleanup_orphaned_runs at startup
- Cap _metric_buffer at 500 entries
- Make FLUSH_THRESHOLD a class constant
- Map 'running' to 'training' phase in historical view
- Derive LR/GradNorm from history arrays in historical view
- Fix nested button with div[role=button] in history cards
- Guard String(value) against null/undefined in config popover
- Clear selectedHistoryRunId on auto tab switch

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* fix(studio): address round-2 review findings across training backend and frontend

Backend (training.py):
- Move state mutation after proc.start() so a failed spawn does not wedge
  the backend with is_training=True
- Create DB run row eagerly after proc.start() so runs appear in history
  during model loading, not after first metric event
- Rewrite _flush_metrics_to_db() with snapshot-before-insert pattern to
  preserve metrics arriving during the write and retain buffer on failure
- Guard eval_loss with float() coercion and math.isfinite(), matching the
  existing grad_norm guard
- Increase pump thread join timeout from 3s to 8s to cover SQLite's
  default 5s lock timeout

Frontend (studio-page.tsx):
- Fix history navigation: check isTrainingRunning instead of
  showTrainingView in onSelectRun so completed runs are not misrouted
- Replace activeTab state + auto-switch useEffect with derived tab to
  eliminate react-hooks/set-state-in-effect lint violation

Frontend (historical-training-view.tsx):
- Add explicit "running" branch to message ternary so running runs no
  longer fall through to "Training errored"
- Derive loading from detail/error state and move cleanup to effect
  return to eliminate react-hooks/set-state-in-effect lint violation

Frontend (progress-section.tsx):
- Derive stopRequested from isTrainingRunning && stopRequestedLocal to
  eliminate react-hooks/set-state-in-effect lint violation and remove
  unused useEffect import

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix(studio): resolve 3 remaining bugs from round-2 review

1. Stuck on Current Run tab [12/20]: Only force "current-run" tab when
   isTrainingRunning is true, not when stale completed-run data exists.
   After training ends, users can freely navigate to Configure.

2. Incomplete metric sanitization [7/20]: Apply float() coercion and
   isfinite() guards to loss and learning_rate, matching the existing
   pattern used by grad_norm and eval_loss. Prevents TypeError from
   string values and NaN leaks into history arrays.

3. Stop button state leak across runs [10/20]: Add key={runtime.jobId}
   to ProgressSection so React remounts it when a new run starts,
   resetting stopRequestedLocal state.

* fix(studio): deduplicate loss/lr sanitization in training event handler

Reuse _safe_loss/_safe_lr from the progress update block instead of
re-sanitizing the same raw event values for metric history.

* fix(studio): restore loss > 0 guard to prevent eval steps injecting 0.0 into metric histories

Round-2/3 fixes relaxed the history append guard from `loss > 0` to
`loss is not None`, which let eval-only log events (where loss defaults
to 0.0) append fake zeros into loss_history and lr_history. Restore the
`loss > 0` check to match the worker's own has_train_loss gate. The
float() coercion and isfinite() sanitization from round-3 remain intact.

* fix(studio): resolve training history bugs — nullable loss/lr, tab nav, sparkline

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---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
2026-03-25 00:58:55 -07:00