* 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.
---------
Co-authored-by: shimmyshimmer <shimmyshimmer@users.noreply.github.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Etherll <61019402+Etherll@users.noreply.github.com>
Co-authored-by: Unsloth <michaelhan@Michaels-MacBook-Pro.local>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
* 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.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* 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
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address RAG whole-doc review follow-ups
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Address RAG review follow-up edge cases
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Reserve image budget for whole-document RAG
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
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>
* 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
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* 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
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Lee Jackson <130007945+Imagineer99@users.noreply.github.com>
Co-authored-by: wasimysaid <wasimysdev@gmail.com>
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.
Michael Han