When the user uploads a doc to a brand-new chat (a draft thread with
an assistant-ui __LOCALID_* id), the backend stores rag_documents
rows scoped to that id. On page reload assistant-ui mints a fresh
__LOCALID_* for the new mainThreadId, so useThreadDocuments asks the
backend for docs under the NEW id and gets nothing, even though the
original rows are still on disk under the OLD id.
- chat-runtime-store: persist activeThreadId in localStorage via
a new CHAT_ACTIVE_THREAD_KEY, restore on init, save on every
setActiveThreadId call (including clears, which write '').
- ActiveThreadSync: when aui's freshly-minted mainThreadId is a
__LOCALID_* and we already have a persisted __LOCALID_* draft,
keep ours instead of overwriting. This only affects RAG/doc
lookup; aui's chat history for the new draft starts empty
either way, so there's no regression for users who don't have
attached docs.
User-initiated thread switches (new chat, switching to a saved
thread, deleting the current thread) all go through setActiveThreadId
with the new id (or null), so they correctly replace/clear the
persisted value.
RAG is opt-in but the chat store had a hydration-time migration that
silently flipped ragToolEnabled to true whenever a persisted ragSource
was anything other than 'off'. Plus there was no logic to reset the
pill across model loads, so the pill stayed on across sessions even
after the user explicitly disabled and re-enabled it.
- Remove the migration block in chat-runtime-store.hydrate — the
embedder warmup still runs when ragToolEnabled is genuinely
persisted true.
- In use-chat-model-runtime's load-success handler, call
setRagToolEnabled(false) (via the setter, so localStorage stays
in sync) immediately after the loaded-state setState batch. Every
fresh model load now starts with the pill off and the user must
toggle it explicitly.
Auto-downloading a 1.1 GB cross-encoder at every studio start is
wrong for users who never use rerank — reranker is opt-in by design.
Move the precache from a startup daemon thread to an explicit
POST /api/rag/reranker/precache endpoint, and have the chat settings
sheet call it the moment the 'Use reranker' switch is flipped on.
- Backend: drop the startup _precache_reranker thread; add the
/api/rag/reranker/precache route that calls precache_reranker().
- Frontend: new precacheRagReranker() in rag-api, wired into the
Switch's onCheckedChange so the download runs synchronously
with a loading toast. On success: 'Reranker ready'. On failure:
error toast + auto-flip the switch back off so the next query
doesn't trigger another long hang.
First toggle-on pays the 1.1 GB download once; subsequent toggles
hit the HF cache and return ~instantly.
The RAG ingestion toast stack was pinned to bottom-right and rendered
its title and progress text with gap-0.5, so the stage label and
percentage rendered close enough to look concatenated (e.g.
'indexing5%') on narrow widths. The default Sonner toaster also
defaulted to bottom-right, so other notifications were inconsistent
with the new layout.
- Move the ingestion toast stack to top-right.
- Set Sonner's default position to top-right.
- Bump vertical gap between title and progress (gap-1.5).
- Add horizontal gap-3 between stage label and percentage, plus
shrink-0 + tabular-nums on the percent so it never collides with
the (truncatable) stage label.
If RAG is toggled on but the active scope (thread or KB) has zero
indexed documents, exposing search_knowledge_base to the model just
wastes a tool-call turn — the model calls the tool, gets back 'no
matching chunks', and has to re-plan. The system prompt nudge that
instructs the model to call the tool before answering is similarly
counterproductive.
Frontend: before computing ragToolPathTaken in chat-adapter, fetch the
document list for the current scope (KB or thread) and require docs to
exist. The flag now gates both the system prompt injection and the
enabled_tools list. Defensive fallback: if the docs lookup fails the
flag stays true so we don't silently swallow RAG.
Backend: add _drop_rag_tool_if_scope_empty in routes/inference.py that
counts rag_documents for the request's rag_scope and strips
search_knowledge_base from the tool list when 0. Applied at both
chat-completion tool-filter sites so the protection works regardless
of which streaming path serves the request.
Scores were only ever useful for debugging; surfacing them in chunk
cards (score X.XXX · dense Y.YYY) and citation hovers made the UI
noisy without giving the user anything actionable. Drop them in three
places:
- Backend search_knowledge_base no longer emits score / dense_score
attributes on the <chunk> tags fed to the LLM; the tool description
is updated to match.
- Chunk-card metadata in the assistant-ui tool result strips score /
dense lines.
- Source-badge hover tooltips drop the 'score N' meta line.
Also remove the 'Min relevance' slider from the chat settings sheet.
The backend min_score field stays plumbed (default 0 = no filter) so
the threshold can be re-exposed later or driven programmatically.
- chat-adapter pre-fetches retrieval on every turn when RAG is on,
regardless of provider. Users no longer have to phrase queries as
'the document I attached' for retrieval to fire. Local tool models
still get search_knowledge_base registered as a refinement path.
- New per-thread ragMinScore slider (Min relevance, 0..1) gates
retrieved hits by dense cosine similarity. Hits below the floor
(and BM25-only hits with no dense signal) are dropped server-side
so unrelated docs don't get injected when the user's query is
off-topic from what's indexed.
- Backend logs at search start (scope, top_k, min_score, query
preview), after retrieval (retrieved vs met_threshold counts),
and on return (final hit count) for both /api/rag/search and the
search_knowledge_base tool path.
- System-prompt nudge prepended when pre-fetch returns hits so the
model knows to cite [1], [2] rather than paraphrase silently.
When ragToolEnabled is on, the in-thread composer's + button now
opens a doc-only picker and uploads selected files to the per-thread
RAG pipeline (matching SharedComposer). Pending chips show
Uploading -> Indexing -> Ready status; Send is blocked while any
doc is in-flight. Previously these files were base64'd inline as
native attachments, which bypassed RAG entirely.
The Phase 4 RAG button only existed in shared-composer; the
assistant-ui in-thread composer renders its own pill set, so RAG
was missing once a thread had messages.
Fresh [] literals from useRagStore selectors triggered Zustand's
Object.is snapshot check on every render, causing React #185 on the
chat page when documentsByScope[key] was unpopulated.
Two useEffects added in Phase 2C and Phase 4 followed the anti-pattern
of calling a state setter inside the effect and listing the setter's
output in the dep array. Both could re-fire indefinitely when the
selected slice changed shape on each render — which the chat page hit
on first load.
chat-settings-sheet.tsx (thread settings loader)
- Before: `useEffect(load, [..., threadSettings, ...])` with
`if (!threadSettings) load()` inside. After load, the Zustand
selector returned a freshly-constructed slice, dep changed,
effect re-ran. If anything in between caused threadSettings to
briefly flicker undefined (e.g. a race during initial hydration
or a fast subsequent thread switch), the load fired again and the
cycle repeated.
- After: ref-guarded by activeThreadId — `threadSettingsLoadedRef`
tracks which threadId has been loaded; the effect deps shrink to
`[ragSource.kind, activeThreadId, loadThreadSettings]`, all
stable per-thread, removing the feedback loop.
ingestion-toast-stack.tsx (terminal-job auto-dismiss)
- Before: `useEffect(..., [jobs, dismissedJobs])` with
`setDismissedJobs(prev => new Set(prev).add(jobId))` inside the
scheduled setTimeout. Each setter creates a new Set reference;
the dep change re-triggers the effect, which clears and
reschedules timers. Under fast SSE event arrival or a strict-mode
double-mount, the scheduler runs faster than its cleanup and
React caps the depth.
- After: dismissedJobs is read via a ref (kept in sync at the top
of the component); the effect only depends on `[jobs]`. A
`scheduledJobsRef` prevents duplicate timer scheduling for the
same job across multiple effect runs, and the setDismissedJobs
updater no-ops when the job is already dismissed.
No behavior change for the happy path — toasts still auto-dismiss
after DISMISS_DELAY_MS; thread settings still load on first sight
of a thread.
Two errors surfaced by the frontend build (`tsc -b`) after the Phase 4
commit c74fc13eb landed:
src/features/chat/chat-settings-sheet.tsx(449,9): TS2451 — cannot
redeclare block-scoped 'activeThreadId'.
src/features/rag/stores/rag-store.ts(326,9): TS2774 — condition will
always return true since this function is always defined.
Fixes
- chat-settings-sheet.tsx: an `activeThreadId` declaration already
existed near the code-exec section (line 636). Phase 2B's RAG
retrieval-section block introduced a second declaration at line 449.
The earlier one is needed for the Retrieval block; drop the later
redeclaration — downstream code still resolves it via lexical scope.
- rag-store.ts subscribeJob: `get().jobUnsubscribers[jobId]` indexes a
`Record<string, () => void>`. Without `noUncheckedIndexedAccess` TS
infers the result as the function type (never undefined), so
`if (existing)` is always-truthy. Replace with `if (jobId in
get().jobUnsubscribers) return;` — same semantics, satisfies TS.
Promotes RAG to a first-class composer toggle alongside Think / Web
Search / Code, with tool-use semantics on local models that support
tools and a pre-fetch fallback on external providers. The model
decides when to call `search_knowledge_base` on local inference; on
external providers retrieval still fires before each message (the
existing pre-fetch path), gated on the same button.
Backend
- core/rag/tool.py (new): search_knowledge_base handler + JSON-schema
tool spec. Resolves scope (kb_id wins over thread_id) from the
request's rag_scope, runs retrieve_hybrid + optional rerank, then
hydrates filename / page_number / text from sqlite and formats as
numbered Markdown citations ('[1] file.pdf (page 5): ...') for the
LLM to cite. Empty scope returns a user-facing hint; empty results
return a clear no-match message instead of an empty string.
- core/inference/tools.py: SEARCH_KNOWLEDGE_BASE_TOOL added to
ALL_TOOLS (lazy import keeps tools.py importable on inference
paths that never touch RAG). execute_tool() gains a tool_context
parameter that carries per-request extras the LLM doesn't see
(currently just rag_scope). The new 'search_knowledge_base' branch
dispatches to the handler with scope unpacked from tool_context.
- core/inference/llama_cpp.py + safetensors_agentic.py +
orchestrator.py: thread tool_context through generate_chat_completion_
with_tools / run_safetensors_tool_loop / execute_tool. Both local
backends (GGUF llama-server and safetensors agentic) carry the same
context object.
- models/inference.py: ChatCompletionRequest gains optional
rag_scope: dict ({kb_id?, thread_id?, enable_rerank?, default_top_k?,
reranker_model?}). Ignored unless 'search_knowledge_base' is in
enabled_tools.
- routes/inference.py: both the GGUF and safetensors call sites for
generate_chat_completion_with_tools forward payload.rag_scope into
tool_context.
Frontend
- chat-runtime-store.ts: global ragToolEnabled boolean + setter +
CHAT_RAG_TOOL_ENABLED_KEY localStorage, mirroring toolsEnabled /
codeToolsEnabled. Settings-hydration migration auto-flips
ragToolEnabled=true for pre-Phase-4 users who already had ragSource
set, so existing RAG users don't silently lose retrieval on upgrade.
- shared-composer.tsx: new 'RAG' pill button after Images (uses
lucide BookOpenIcon, composer-pill-btn style, data-active toggle).
Disabled when no model is loaded. Toggling on from ragSource='off'
auto-flips source to 'thread' so the sidebar lands ready-to-go.
- chat-adapter.ts:
* The existing pre-fetch block is now gated on ragToolEnabled AND
only fires when the tool path isn't viable (external provider OR
local model without tool-use support). Tool-capable local models
skip pre-fetch and let the LLM decide.
* The local-model body assembly adds 'search_knowledge_base' to
enabled_tools and packs ragSource + enableRerank + ragTopK into a
rag_scope object the backend tool handler consumes.
- chat-settings-sheet.tsx: entire Retrieval CollapsibleSection is
wrapped in {ragToolEnabled && ...} so it hides when the button is
off — the button is now the single on/off control. The 'Off'
option is removed from the Source dropdown (the button handles
that). Default open when shown so settings are one click away.
Tests
- test_rag_tool_handler.py: handler covers empty query, missing
scope, kb_id > thread_id precedence, thread-only path, citation
formatting (numbered + page numbers + unknown source); tool spec
shape (function/name/required); execute_tool dispatch with and
without tool_context; ALL_TOOLS includes the new spec without
dropping the existing ones.
Verification scope
- Local GGUF with tools: toggle button on, upload doc, ask about
doc content → assistant emits a search_knowledge_base tool call
card (rendered by the existing ToolFallback component since no
custom UI exists yet — that's a v2 nice-to-have).
- External provider (Anthropic / OpenAI / etc.): same button, same
UX, but uses the pre-fetch path under the hood.
- Migration: pre-existing ragSource != off → button initializes ON
so retrieval keeps working.
Threads can now opt into late chunking or multimodal mode independently
of the KBs they reference. Per-thread settings persist in chat_settings
under thread:<id>:rag and fall back to the app-level defaults when the
thread hasn't set anything explicitly.
Backend (routes/rag.py)
- ThreadRagSettings / UpdateThreadRagSettingsRequest Pydantic models.
- GET/PUT /api/rag/threads/{thread_id}/settings backed by
chat_settings (upsert_chat_settings_merge). Same (multimodal, late)
constraint enforcement as the create + defaults endpoints.
- POST /api/rag/threads/{thread_id}/reingest now accepts the same
body shape — if any field is set, the new settings are persisted
via set_thread_rag_settings BEFORE the reingest, so subsequent
uploads pick up the change too.
- upload_thread_document reads the per-thread settings and passes
them through to _start_ingestion, replacing the previous hard-coded
('standard', 'text', RAG_EMBEDDING_MODEL) defaults.
Frontend
- rag-api.ts: ThreadRagSettings type + getThreadRagSettings /
setThreadRagSettings wrappers. reingestThreadDocuments now accepts
optional UpdateThreadRagSettingsRequest opts.
- rag-store.ts: threadSettings map keyed by threadId, plus
loadThreadSettings / updateThreadSettings actions. reingestThread
refreshes the local settings copy when opts were supplied.
- chat-settings-sheet.tsx Retrieval section: when source = thread,
shows side-by-side Mode + Chunking selects above the documents
list. Selecting a different value:
- persists immediately if the thread has no docs
- prompts "Re-index N documents?" if docs exist; on Yes calls
reingestThread with the new opts, on No reverts the select
The (multimodal, late) constraint is enforced via per-option
disabled + tooltip, matching the KB create dialog.
Power users can now set their preferred chunking strategy / mode /
embedder once in Settings → Knowledge Bases and have new KBs use those
values by default, instead of toggling on every create.
Backend
- routes/rag.py:
- GET /api/rag/defaults returns the stored RagDefaults (or sensible
fallbacks when nothing is set: standard / text / null embedder).
- PUT /api/rag/defaults is PATCH-style — only fields present in the
body overwrite. The (multimodal, late) constraint is enforced
here too, so users can't poison the defaults with a combination
the create path would reject.
- Persistence reuses the existing chat_settings store via
upsert_chat_settings_merge; the values live under a single
rag.defaults key as a nested JSON dict.
Frontend
- rag-api.ts: getRagDefaults / setRagDefaults wrappers + RagDefaults
+ UpdateRagDefaultsRequest types.
- rag-store.ts: defaults state, loadDefaults / updateDefaults
actions. loadDefaults swallows errors so a missing endpoint just
leaves defaults null.
- rag-defaults-section.tsx (new): self-contained mode + strategy +
embedding-model controls, persists on change. Used in the Settings
KB tab below the ThreadIndexList section.
- knowledge-bases-tab.tsx: mounts RagDefaultsSection below thread
indexes with a separator.
- kb-create-dialog.tsx: loads defaults on open and prefills the form
with them (falls back to hard-coded standard / text when defaults
haven't loaded yet). reset() returns to the latest defaults rather
than the hard-coded ones.
Adds a floating progress-card stack mounted at the app root that
watches useRagStore.jobs and renders one card per in-flight ingestion
job, regardless of which page the user is on. Wraps the existing
IngestionProgress component so the progress UI stays consistent with
the per-doc chips in the KB detail panel and chat sidebar.
- Terminal cards (complete/error) linger for 4s then auto-dismiss.
- A manual dismiss button is always available.
- Reduced-motion preference is respected (no slide animation).
- Positioned bottom-right, z-50, pointer-events-none container so
clicks pass through to the page underneath.
Mounted in app/routes/__root.tsx next to the existing SettingsDialog
so it's visible across every authenticated route. Closes the last
deferred item from Phase 2.
Closes the upgrade-path gap from Phase 3: a KB or thread whose chunks
were ingested under one strategy can now be rebuilt under a different
one without losing the uploaded files.
Backend
- routes/rag.py:
- POST /api/rag/knowledge-bases/{kb_id}/reingest takes optional
chunking_strategy / mode / embedding_model in the body. Validates
the (multimodal, late) constraint via _validate_mode_combo, updates
the rag_knowledge_bases row, wipes scope artifacts (sqlite chunks
via cascade, Qdrant collection, bm25), and re-INSERTs a fresh
rag_documents row + ingestion job per stored file. Returns the new
job IDs so callers can stream progress via the existing SSE.
- POST /api/rag/threads/{thread_id}/reingest is the simpler thread
variant — no body, rebuilds with current defaults.
- Shared _reingest_scope helper strips the UUID upload prefix when
re-naming docs so users see the original filenames again.
Frontend
- rag-api.ts: reingestKnowledgeBase(kbId, opts) and
reingestThreadDocuments(threadId) wrappers + ReingestResponse type.
- rag-store.ts: reingestKB / reingestThread actions refresh the KB +
doc lists and subscribe to every returned job so the existing
IngestionProgress chips render without further wiring.
- kb-reconfigure-dialog.tsx (new): mirrors KBCreateDialog but
pre-fills with the KB's current strategy / mode / embedder, enforces
the same (multimodal + late) constraint with disabled options, and
confirms before submitting. Submit label flips between "Re-index"
(no settings change) and "Reconfigure & re-index".
- kb-detail-panel.tsx: header gains the chunking + mode summary and
a "Reconfigure…" button that opens the dialog. Button is disabled
when the KB has no documents.
- chat-settings-sheet.tsx Retrieval section: "Re-index" button beside
the existing "Clear thread index" when the thread has documents.
Tests
- test_rag_reingest.py: ReingestKBRequest accepts optional fields,
rejects unknown enum values via Pydantic, and the shared mode-combo
guard still bites on the reingest path.
When a KB has mode = 'multimodal', ingestion extracts images alongside
text and embeds both into a shared 512-d vector space via BGE-VL-base.
Image hits become first-class search results — useful for slides,
reports, and diagrams where text-only retrieval loses ~30-50% of the
content.
Backend
- embeddings.py: new encode_images(image_bytes_list) — opens bytes via
PIL and routes to the SentenceTransformer (BGE-VL accepts PIL images
in the same encode call as text).
- ingestion.py: _subprocess_worker gains document_id arg and a new
_stream_image_chunks() helper. For multimodal KBs the standard text
chunking runs first, then images are saved to
rag_uploads_root() / 'images' / <document_id> / img-NNNN.<ext> and
embedded; for each image with an adjacent caption, both an
'image'-kind chunk (vector = encoded image) and a 'caption'-kind
chunk (vector = encoded caption text) are streamed back with a
shared pair_group field.
- ingestion.py parent: _insert_chunks_and_collect_for_bm25 now reads
kind / image_path / pair_group from the subprocess message,
populates the new rag_chunks columns, and runs a second pass that
sets linked_chunk_id for each image ↔ caption pair. BM25 indexes
text + caption chunks only — image chunks have no tokenisable body.
- retrieval.py: Hit gains a `kind` field plumbed through bm25, dense,
RRF, and rerank paths.
- reranker.py: image-kind hits skip CrossEncoder rerank (text-only
model) but are appended back in their original relative position
rather than dropped.
- routes/rag.py: new GET /api/rag/images/{document_id}/{filename}
static-file route with realpath containment check. SearchHit gains
`kind` and `image_url` fields so the chat UI can render image
thumbnails alongside text hits. KB-doc upload threads kind/mode
through to ingestion.
Frontend
- rag-api.ts: SearchHit gains optional `kind` and `image_url`.
- kb-create-dialog.tsx: new Mode select (Text / Multimodal) alongside
the existing Chunking strategy select. The forbidden
(multimodal + late) combo is enforced in the UI — each side
disables the conflicting option on the other side with a tooltip
explaining why. Embedding-model placeholder cycles through the
three valid defaults (bge-small / nomic / BGE-VL).
- kb-list.tsx + chat-settings-sheet.tsx: 🖼️ MM badge alongside the
⚡ Late one so multimodal KBs are obvious at a glance.
Tests
- test_rag_multimodal.py: parser returns images when want_images=True
and skips them when False; _validate_mode_combo rejects the
forbidden (multimodal, late) pair with 400; RAG_EMBEDDER_MATRIX
contains the three valid combos and excludes the forbidden one;
image URL construction shape is verified. A server-marked test
loads BGE-VL-base end-to-end and confirms image + text vectors
share the same dimension.
Phase 3 of the plan is now feature-complete on the backend; the
remaining items (re-ingest UX for changing strategy on existing KBs)
are tracked under "Backfill UX" and can land separately.
When a KB has chunking_strategy = 'late', ingestion takes a separate
code path that embeds the full document in a single forward pass and
mean-pools token embeddings per chunk span. Each chunk vector carries
full-document context via the encoder's bidirectional attention —
Jina's published technique, ~+6.5 nDCG@10 on long docs.
Backend
- chunking.py: new chunk_pages_with_spans() that joins all pages into a
single full_doc, runs the existing recursive splitter, and returns
per-chunk (char_start, char_end) offsets. Page-number metadata is
recovered by overlap with the original page ranges so PDF citations
still work. Existing chunk_pages() unchanged.
- embeddings.py: new late_chunk_encode(doc_text, char_spans). Tokenizes
the doc with return_offsets_mapping, runs the underlying transformer
to get per-token last_hidden_state, then mean-pools per chunk span.
When the doc exceeds the embedder's context, falls back to windowed
late chunking with a 512-token overlap so cross-window context is
partially preserved.
- ingestion.py _subprocess_worker: branches on chunking_strategy.
'late' path: chunk_pages_with_spans -> late_chunk_encode -> one big
chunks_batch message. 'standard' path unchanged. Both reuse the same
parent-side pump.
- ingestion.enqueue_ingestion: new chunking_strategy + mode kwargs;
defaults to 'standard' / 'text' for legacy callers. embedder model
resolved via resolve_embedder() from the (mode, strategy) matrix.
- routes/rag.py: KB-doc upload reads chunking_strategy + mode from the
KB row (defensive .get for pre-Phase-3 schemas) and threads them
through _start_ingestion.
Frontend
- kb-create-dialog.tsx: new "Chunking strategy" select with Standard /
Late options. Embedding-model placeholder switches to nomic when
Late is picked. createKB request now carries chunking_strategy.
- kb-list.tsx + chat-settings-sheet.tsx: small "⚡ Late" badge next to
late-chunking KB names in the settings KB list and the chat sidebar
dropdown so users see the mode at a glance.
Tests
- test_rag_late_chunking.py: pure-python tests for chunk_pages_with_spans
(chunks index back into full_doc; page numbers inherited by overlap;
pages joined with blank line). A server-marked test loads
all-MiniLM-L6-v2 to exercise late_chunk_encode end-to-end.
No multimodal yet; that's Phase 3B-multimodal (next PR).
Phase 3 lays two orthogonal per-KB knobs in the data and API layers so
follow-up commits (Phase 3B-late, Phase 3B-multimodal) only need to add
their code path and UI selector, not schema or types.
Schema (studio/backend/storage/studio_db.py)
- rag_knowledge_bases gains chunking_strategy ('standard'|'late', default
'standard') and mode ('text'|'multimodal', default 'text'). Both are
immutable after KB creation — changing either invalidates existing
chunks because they were ingested through a specific pipeline.
- rag_chunks gains kind ('text'|'image'|'caption', default 'text'),
image_path (NULLABLE), linked_chunk_id (NULLABLE) — used by Phase
3B-multimodal to pair image chunks with their captions.
- Idempotent ALTER TABLE additions for existing installs (mirrors the
chat_threads display_name / *_code_exec_container_id pattern earlier
in the file).
API (studio/backend/routes/rag.py)
- ChunkingStrategy + KBMode Literal aliases.
- CreateKBRequest accepts both fields with backward-compat defaults.
- KBResponse exposes both.
- _validate_mode_combo rejects (multimodal, late) with 400 — no public
open-weight embedder supports both at once. Surface the constraint
early rather than failing silently during ingestion.
Config (studio/backend/utils/rag/config.py)
- RAG_EMBEDDER_MATRIX dict keyed by (mode, strategy) → embedder name.
- resolve_embedder() helper falls back to RAG_EMBEDDING_MODEL for legacy
KBs that pre-date the columns.
- (multimodal, late) intentionally absent.
Frontend (studio/frontend/src/features/rag/)
- api/rag-api.ts: ChunkingStrategy + KBMode types; KnowledgeBase
interface and createKnowledgeBase request type updated.
- stores/rag-store.ts: createKB signature uses the shared request type.
No user-visible UI changes yet — the only currently-usable combination
is (text, standard), so adding one-option selectors would be UX noise.
Phase 3B-late and Phase 3B-multimodal each add the relevant selector
option as part of shipping the code path.
Bundles three independent CI regressions hitting the maintainer PR
backlog. Each one is verified end-to-end on a staging fork against
real Ubuntu / macOS / Windows GitHub-hosted runners before this
lands.
1. Windows --no-torch install: pydantic + pydantic-core drift to
incompatible versions under `uv pip install --no-deps -r
no-torch-runtime.txt` because pip resolves each independently
from latest. pydantic.VERSION 2.13.4 pins pydantic-core==2.46.4
but pydantic-core 2.47.0 was the freshest published wheel, so
`import pydantic` raised
`SystemError: pydantic-core 2.47.0 is incompatible with the
current pydantic version`. Resolve pydantic WITH deps in a
focused pip call (install.sh, install.ps1,
install_python_stack.py) before the --no-deps no-torch-runtime
pass so pip pins pydantic-core to the version pydantic declares.
pydantic's transitive deps (annotated-types, pydantic-core,
typing-extensions, typing-inspection) are torch-free. Drop the
redundant `Patch Studio venv with full typer / pydantic dep
trees` workaround from the four Windows smoke YAMLs.
Supersedes #5733 + #5734.
2. Linux Studio Update CI: upstream llama.cpp b9261+ split each
binary's entry code into a paired `libllama-<binary>-impl.so`
shared library. `llama-server` and `llama-quantize` NEEDED-link
against `libllama-server-impl.so` / `libllama-quantize-impl.so`
with RUNPATH `$ORIGIN`, so the prebuilt overlay must copy those
alongside the binaries. Without that, ldd reports them missing,
preflight rejects, the installer falls back to source build, and
studio-update-smoke annotates `setup.sh idempotency regressed`.
Add `libllama-*-impl.so*` to the Linux runtime patterns and lock
the pattern in test_rocm_support.TestRuntimePatterns.
3. Mac Studio UI Chat: change-password submit clicked while
disabled. The disable gate only checked new + confirm password
length, but Playwright's first click landed before the
current-password field's React state had committed, so the form
was simultaneously logically-invalid (current_password empty) and
the button was disabled. Tighten the gate to require
`currentPassword.length >= 8` and mirror the same check in the
submit handler so Enter / autofill cannot bypass.
Supersedes #5738.
The pill wired the request end of the loop but the response was lost
on the client: the backend emits a `tool_end` _toolEvent carrying the
base64 PNG on `image_b64` / `image_mime`, but the chat-adapter only
read the `result` string and the generic ToolFallback printed the
prompt as JSON args with an empty Result block -- the "I see no
image" symptom in the chat.
- chat-adapter: when the closing `tool_end` is for `image_generation`,
repackage `image_b64` + `image_mime` (+ size/quality/background)
into a structured result object instead of dropping them.
- New `ImageGenerationToolUI` reads that result and renders the image
inline via `<img src="data:image/...;base64,...">` with the prompt
as a caption. Falls back to a spinner while the request is still
running.
- Register the component under `image_generation` in thread.tsx's
tools.by_name map so it preempts ToolFallback for this tool only.
#5685 wired the backend to honor `prompt_cache_ttl` on the request,
but there was no UI to actually pick it -- every Studio chat ended up
on Anthropic's default 5 minute pool. This adds a Cache TTL selector
to the chat settings sheet's Provider section, visible only when the
provider supports the choice (Anthropic today) and Prompt caching is
on.
- New `promptCacheTtl?: "5m" | "1h"` on `ExternalProviderConfig`.
Normalizer drops the field on providers that don't support the
choice so localStorage stays clean across provider swaps.
- `supportsProviderPromptCacheTtl` + `isPromptCacheTtl` helpers so
the picker, normalizer, and adapter all agree on which values are
valid.
- Settings sheet renders a small Select (5 minutes / 1 hour) right
under the Prompt caching switch when the toggle is on; flipping
it persists on the provider config like the other per-provider
knobs.
- chat-adapter passes `prompt_cache_ttl` on outbound requests when
the value is valid; omitted otherwise so the backend keeps
inheriting Anthropic's 5m default.
The backend already wires OpenAI's Responses-API image_generation
server tool: when `enabled_tools` carries "image_generation" on an
OpenAI cloud request, _stream_openai_responses appends
`{type: "image_generation"}` to the request's tools array and emits
`image_generation_call` output items back to the assistant stream
(see backend/core/inference/external_provider.py and
backend/tests/test_openai_image_generation.py for the round-trip).
This wires the frontend half so a user can actually opt into it from
the composer next to the Search and Code pills, instead of the tool
sitting dormant.
- `providerSupportsBuiltinImageGeneration` gates on OpenAI cloud
(`api.openai.com`) + a Responses-API model prefix (gpt-5.x, o3).
Mirror of the backend's `is_openai_cloud` guard so the pill is hidden
on custom OpenAI-compat backends (ollama / llama.cpp / vLLM) that
report `provider_type="openai"` but would 400 on the tool.
- New `imageToolsEnabled` flag in chat-runtime-store, persisted under
`unsloth_chat_image_tools_enabled` and reset on model change in
chat-page exactly like `codeToolsEnabled`.
- `chat-adapter` appends "image_generation" to `enabled_tools` and
flips `enable_tools: true` when the pill is on, so the existing
backend dispatch picks it up.
- Composer renders an Images pill (lucide `ImageIcon`) immediately
after the Code pill, only when the active model advertises the
capability. The in-thread composer (assistant-ui/thread.tsx) gets
the matching `ImagesToggle` for parity.
The first pass only wired the localStorage mirror into `setCheckpoint`,
but the main chat-page picker actually selects an external model by
calling `setParams({ ...store.params, checkpoint: value })`. That path
never hit `setCheckpoint`, so the persisted slot stayed empty and a
refresh fell back to whatever `/api/inference/status.active_model`
returned -- the previously loaded local model (Qwen3.5 etc) or null
("Select model") when nothing was loaded locally.
Mirror the persistence in `setParams` whenever the checkpoint changes
so every entry point converges on the same behavior. `setCheckpoint`
still does it directly so the load path (compare, GGUF auto-load,
gemma fallback in chat-adapter) keeps working.
* Add Anthropic prompt guards for disabled tools
* fix: merge Anthropic tool guard into structured system prompts
* fix: scope Anthropic disabled-tool guard wording
* chore: adjust claude guard prompt
* chore: add openai to list of prompt guarded providers
* Studio: include web_fetch in the per-turn disabled-tool guard
Add webFetchEnabledForThisTurn alongside webSearchEnabledForThisTurn
and codeExecEnabledForThisTurn. Use it in the enabled_tools payload
so web_fetch follows the Search pill the same way web_search does,
and mention "web fetch" in the disabled-tool guard prose on providers
that ship the tool (Anthropic today; other providers stay inert via
providerSupportsBuiltinWebFetch).
---------
Co-authored-by: Roland Tannous <115670425+rolandtannous@users.noreply.github.com>
Co-authored-by: Daniel Han <danielhanchen@gmail.com>
Selecting a connected external provider (Anthropic, OpenAI, Google, etc.)
and refreshing the page reverted the picker back to no selection. Root
cause is that `PersistedInferenceParams` in `chat-settings-api.ts`
excludes `checkpoint` from the server-side settings payload by design.
Local model selections survive refresh because the backend re-derives
them from `/api/inference/status.active_model`, but external selections
have no backend mirror, so they were lost.
Fix: persist `external::*` checkpoints to a small dedicated
`localStorage` key (`unsloth_chat_last_external_checkpoint`) and hydrate
from it on store init. Local checkpoints continue to come from the
backend status as before; only external ids are mirrored client-side.
`setCheckpoint` writes the key when an external id is selected and
clears it when switching back to a local id, and `clearCheckpoint`
clears it so the picker does not snap back after an explicit reset.
Deleting a connection in one browser left the same connection stuck in
every other browser/tab. The user could not delete or edit it from there
because the local state never caught up with the server, and clicks
either no-op'd or threw on a missing-row backend response.
Two pieces caused the bug:
1. `ChatProvidersSettings` ran its backend sync once on mount and then
silently kept localStorage providers whenever `listProviderConfigs`
returned an empty array, on the assumption that an empty server
response had to be a transient glitch. That assumption is wrong when
another browser removed the last connection. With the guard gone,
trust any successful API response, including an empty list. A focus /
visibilitychange listener now triggers a silent re-sync so the dialog
does not need to be closed and reopened to pick up remote deletes.
2. `deleteProviderConfig` threw on HTTP 404, so once Browser A deleted a
connection, Browser B's "Delete" click failed and the local row stuck
around. Treat 404 as success: the server's job is already done and
the local cache only needs to be pruned.
* 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.
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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>
* Studio: wire Anthropic web_fetch server-side tool
Studio's Anthropic passthrough only forwarded web_search and
code_execution when enabled_tools was set. Asking Claude through Studio
to fetch a URL produced no fetch (the tool was not in the outbound
tools array), so users had to fall back to web_search even when they
already had the exact URL they wanted.
This change opts in web_fetch_20250910 when enabled_tools contains
"web_fetch". The new tool entry is appended alongside any existing
web_search / code_execution entries:
{"type": "web_fetch_20250910", "name": "web_fetch", "max_uses": 5}
No anthropic-beta header is required (web_fetch is GA); the existing
code-execution-2025-08-25 flag continues to merge cleanly when both
tools are enabled in the same turn.
SSE translation mirrors the web_search path. A `server_tool_use` block
with name="web_fetch" emits a `tool_start` _toolEvent carrying the
URL the model asked to fetch; the matching `web_fetch_tool_result`
block emits a `tool_end` _toolEvent whose result string follows the
Title / URL / Snippet shape parseSourcesFromResult on the frontend
already expects, so the source pill renders identically. Error blocks
(`web_fetch_tool_error`) are surfaced as "Error: <error_code>" matching
the code_execution error path.
The final "Anthropic stream complete" log line picks up web_fetch_
requested / web_fetch_invocations / web_fetch_urls so support reports
of "the model did not fetch anything" can be triaged from the log.
Verified end to end against claude-haiku-4-5 with
`enabled_tools=["web_fetch"]`: the model emitted tool_start with
url=https://example.com and tool_end with the page Title + URL +
Snippet, plus the assistant message correctly read back "Example
Domain" as the title.
Tests:
- 5 new unit tests in test_anthropic_web_fetch.py covering tool
registration, the combined web_search + web_fetch + code_execution
request body, the pill-off case, and SSE translation for both
success and error paths.
- All 242 existing Anthropic + OpenAI provider tests still pass.
The enabled_tools field description in models/inference.py is updated
so OpenAPI consumers see the new option.
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* web_fetch: title fallback to URL, log parse failures, drop dead checks
Three review nits on the previous commit:
1. `_format_web_fetch_result` left `title` empty when Anthropic omitted
`document.title`. The frontend `parseSourcesFromResult` only emits
a source pill when both `Title:` and `URL:` lines are present, so
fetches against pages without an HTML title tag silently lost
their citation in the UI. Fall back to `title = title or url`,
matching the web_search formatter.
2. The broad `except Exception` around `json.loads(buffer)` for the
web_fetch input swallowed the failure with no trace. Log at debug
so a malformed partial_json buffer can be triaged from the server
log without changing behavior.
3. `inner` was already sanitised to a dict at the matching
content_block_start and `_format_web_fetch_result` always returns
a non-empty string (defaulting to "(fetch complete)"), so the
`isinstance(inner, dict) else {}` guard and the
`result_text or "(fetch complete)"` fallback at the emit site
were dead code. Removed.
Added a test exercising the titleless path so the fallback stays
covered.
* chat-adapter: emit source pills for web_fetch tool calls
`parseSourcesFromResult` was only wired up for tool calls where
`toolName === "web_search"`, so the Title / URL / Snippet block the
backend formatter emits for `web_fetch_tool_result` never reached the
source-pill renderer. Users saw the raw tool result in the tool card
but the dedicated source-pill row at the message tail stayed empty.
Both web_search and web_fetch ship the same text shape today, so the
fix is to broaden the gate.
* Address review: wire web_fetch from Search pill + fix pause_turn truncation
Two reviewer follow-ups on the Anthropic web_fetch PR:
1. The backend tool wiring landed but the frontend chat-adapter
never put `web_fetch` in `enabled_tools`, so toggling the Search
pill only ever attached `web_search` -- web_fetch was unreachable
from the UI. Added providerSupportsBuiltinWebFetch() (Anthropic
today) and paired the entry with the existing Search pill, since
the canonical workflow is "search returns URLs, fetch reads
them" and there is no separate UI toggle yet.
2. `pause_turn` from Anthropic's stop_reason vocabulary fell through
the finish_reason map's "stop" default, which the OpenAI-format
client renders as end-of-message and truncates the answer. Per
the docs pause_turn means "Claude paused a long server-tool
turn (web_search / web_fetch) and will resume". Mapped to None
and skipped the chunk emission so the SSE stream still ends with
[DONE] on message_stop but no terminal finish_reason lands on
the client. While there: added explicit mappings for `tool_use`
(-> tool_calls) and `refusal` (-> content_filter) which were
also falling through to "stop".
Tests added: pause_turn emits no finish_reason, end_turn still
emits "stop", refusal maps to "content_filter".
Sourcing: https://platform.claude.com/docs/en/api/messages#response-stop-reason
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
