* Studio: read model text as utf-8 so umlauts survive on Windows
Chat rejects or mangles non-ASCII on Windows: "ä ö ü" in a prompt, a chat
template, or a model path comes back as mojibake, or the load dies with
UnicodeDecodeError.
open() and Path.read_text() fall back to locale.getencoding() when no encoding
is passed. On Windows that is the ANSI codepage (cp1252, cp932, cp1251, ... by
system locale), never UTF-8. Hugging Face writes these files as raw UTF-8, so
every read of one decodes with the wrong codec:
- tokenizer_config.json, which holds the chat template. Templates routinely
carry -> arrows, smart quotes and CJK, so this is the common path into chat
- config.json and adapter_config.json
- modules.json, Ollama manifests, and the .py sources the remote-code scanner
reads before a model is allowed to load
The llama-server and embedding-server stdout readers have the same problem via
subprocess(text = True); they now decode utf-8 with errors = "replace" so a
stray byte cannot kill a log reader.
Encoding arguments only, no logic changes.
tests/test_chat_text_encoding.py covers a config.json and a chat template
holding umlauts, arrows and CJK, plus the remote-code scanner reading a source
file with umlauts. Those pass anywhere the locale is already UTF-8, so a fourth
test re-runs the readers under -X warn_default_encoding and fails on any
platform if an encoding argument goes missing again.
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* Studio: name utf-8 explicitly on the remaining text I/O, with an AST guard (#7465)
* Studio: name utf-8 explicitly on the remaining text I/O
Follow-up to the model-text reads in #7467, covering the rest of the backend:
system probes (nvidia-smi, amd-smi, powershell, git, node), package installers,
/proc and /sys readers, and internal marker files (pid, install id, bootstrap
password, Colab credentials).
Same reason as #7467. open(), Path.read_text()/write_text() and
subprocess(text = True) fall back to locale.getencoding(), which on Windows is
the ANSI codepage rather than UTF-8. These paths are mostly ASCII today, so this
is hardening, not a live bug. Encoding arguments only, no logic changes.
Adds tests/test_text_io_encoding.py: an AST guard walking every backend source
and asserting text I/O names its encoding, so the class of bug cannot creep back
in one call at a time. 275 files.
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* Catch aliased subprocess and positional Path.open, migrate legacy JSONL
The guard only matched a receiver literally named subprocess, so worker.py's
`import subprocess as _sp` hid three text = True installs that decode pip
output with the ANSI codepage. It also skipped any .open() with more than one
positional argument, though Path.open takes buffering/encoding/errors/newline
positionally.
Resuming a scrape written by an older release is the other half: those JSONL
lines are in the locale codepage, so the UTF-8 preload raised, the dedup keys
were silently forgotten and duplicates were appended to a now mixed-encoding
file. Decode with the locale codepage as fallback and rewrite as UTF-8 before
the append handle opens, since Windows cannot replace a file it holds open.
* Stream the JSONL preload and keep a torn line from relabelling the shard
Reading the whole shard to migrate it was wrong twice over. These files reach
gigabytes on a large scrape, so the preload now streams line by line and the
rewrite streams through a temp file.
Worse, one interrupted append used to condemn the file: the whole-file UTF-8
decode failed, every byte was retried as cp1252, and the rewrite persisted
mojibake over records that were fine. A line now counts as legacy only if the
locale codepage both decodes it and yields valid JSON, which a torn UTF-8 line
does not. Damaged lines are skipped and copied through byte for byte.
When the rewrite cannot be written at all, the append handle opens with the
legacy encoding rather than mixing UTF-8 into the file.
install_wheel takes run = subprocess.run as a parameter, so the guard cannot
see it. Both wheel installs there now name their encoding.
* Decide the shard's encoding from the file, not one line at a time
Some byte strings parse both ways. cp1251 `Р°` is D0 B0, which is also valid
UTF-8 for `а`, so a UTF-8-first parse quietly showed the wrong text instead of
migrating it.
A line now yields both readings, and the file decides. Any line that parses
under the codepage but not as UTF-8 is unambiguous evidence, and ambiguous lines
then follow that verdict, which is enough for any real shard: ordinary Cyrillic
or Japanese prose is invalid UTF-8 several times per line. Keys for ambiguous
lines are re-derived from the legacy reading during the rewrite.
A shard is undecidable only if every line is ambiguous, and nothing can tell
those apart.
latin-1 is also tried after the locale codepage, so a scrape carried from
Windows to a UTF-8 machine still has a reading rather than none. Requiring valid
JSON, not just a decode, keeps that from claiming torn lines.
* Weigh the whole shard, and never lose a record on the fallback path
One structurally valid JSON line carrying a stray 0x96 parses as cp1252, so a
single-line verdict let it relabel a healthy shard and mojibake every good
record in it. Each line with non-ASCII bytes now votes: parsing only under the
codepage is evidence for legacy, parsing as UTF-8 is evidence against, since
codepage text rarely forms valid multibyte UTF-8. Ties leave the file alone.
When the migration cannot be written the append handle uses the legacy codepage,
and errors = "replace" quietly turned characters it cannot hold into question
marks while write() still reported success. That path now escapes to \uXXXX
instead, which is ASCII, so every codepage holds it and json.loads returns the
exact characters. Nothing needs replacing, so errors = "strict" is safe.
stream_installer runs sys.executable, so its output is now decoded as UTF-8 by
utf8_child_env rather than read as the ANSI codepage.
* Only rewrite a shard we can attribute, and append ASCII when we cannot
latin-1 was doing too much work. It reads any byte, so it gave a moved shard a
reading, but it is the right text only for cp1252: cp1251 Привет came back as
Ïðèâåò and the rewrite made that permanent. The codepage is now trusted only
when it is the locale's, and an untrusted reading is never written back.
That leaves three cases where the file holds bytes UTF-8 cannot read and we are
not converting it: no codepage to attribute it to, ambiguous lines outvoting the
unambiguous ones, and a preload that could not read the file at all. All three
used to append UTF-8 into it. They now append pure ASCII, which every
ASCII-compatible codepage stores identically, so the file keeps decoding exactly
as it did and no record is lost.
Keys from the two readings are also kept apart. A damaged line in a healthy
shard was marked seen through its codepage reading, so the retry that would have
replaced the unreadable record was refused as a duplicate.
* Let the flash-attn install stub take the kwargs the installer now passes
_run_kwargs gained encoding and errors, so the one stub in this file that
spelled its signature out rejected the call. The other four here already take
**kwargs; this one now matches.
* Do not let a stuck temp file mask the migration failure
unlink() on the failure path could raise in its own right, on a stale
.utf8.tmp directory or a temp another process holds. That escaped the
constructor instead of returning False, so the caller never reached the ASCII
append fallback that keeps the shard single-encoding.
The pip fallback in install_wheel also spawns a Python child, so it gets
utf8_child_env like the probe above it already had. The uv and nvidia-smi
children are native binaries, where PYTHONIOENCODING would do nothing.
* Stop converting legacy shards; the encoding that wrote them is unknowable
trusted only ever meant that the bytes parse under this machine's codepage,
which for a single-byte codepage is nearly always true. A cp1251 shard opened on
a cp1252 Windows box decodes cleanly and would have been rewritten with Привет
as Ïðèâåò. That is the fourth way this rewrite could corrupt a shard, and the
common cause is that a file's encoding cannot be recovered from its bytes.
So the rewrite is gone. The shard is left exactly as found, and appends are pure
ASCII whenever it holds bytes UTF-8 cannot read, which is what actually
delivered the no-mixed-encoding guarantee the rewrite was added for. Dedup keys
still come from whichever reading parses, since ids are ASCII either way.
This also removes the temp file, so there is no longer any file mode or ACL to
carry across.
* Scan the sandbox shim; it is shipped code, not a build artifact
sandbox_site is on the sandboxed child's PYTHONPATH for every Python run
(tools.py:332, 2660), so excluding it let two unannotated text calls through in
code we ship. Both read and write the remap sidecar, which holds file paths.
The exclusion list is meant for build output only, so the directory comes off
it and the two calls name their encoding.
* Force the worker's pip children to UTF-8, and read DBCS keys with a DBCS codec
The three installer calls run sys.executable -m pip with an inherited
environment, so the parent decoded UTF-8 while the child emitted the ANSI
codepage. They now go through utf8_child_env like the other Python children.
Two tests asserted no env kwarg was passed as a stand-in for no HIP flag being
injected. They now assert the flag itself, which is the guarantee they were
written for and does not depend on how the env is delivered.
Separately, latin-1 cannot stand in for a double-byte codepage while recovering
dedup keys: cp932 表 is 95 5C, and the trail byte reads as a JSON backslash, so
the record failed to parse and its id was forgotten, appending a duplicate on
resume. cp932, cp936, cp949 and cp950 are tried too. The reading is still only
ever used for keys, which are ASCII and identical whichever codec parses.
* Require more than one legacy line before trusting its dedup keys
A shard whose valid records are all ASCII casts no UTF-8 votes, so a single
damaged line won the vote by itself, its key was remembered, and the retry that
would have replaced the unreadable record was refused.
One such line is genuinely undecidable: a legacy record with one accented
character and an ASCII record with one stray byte are the same shape. Reading it
as damage costs a duplicate; reading it as legacy loses the record for good.
Only one of those is recoverable, so it is now read as damage.
A real legacy shard has a legacy line for every record carrying an umlaut, so
its dedup is unaffected.
* Append ASCII whenever the shard already holds non-ASCII bytes
The gate asked whether any line was undecodable as UTF-8, which misses a shard
where every legacy line happens to be valid UTF-8 too. A cp1251 shard of Р°
records is bytes D0 B0 throughout, so appending 世界 as UTF-8 left a file where
cp1251 reads the old records correctly and the new one as mojibake, and UTF-8
does the reverse. No single decoding recovered the whole scrape.
The gate is now simply whether the shard holds any non-ASCII byte at all, which
covers both cases and is easier to reason about: if what is already there reads
differently under different encodings, do not add more bytes that do.
Appending ASCII costs only \uXXXX escapes, which json.loads turns back into the
exact characters, and it leaves the new record correct under either reading.
* Skip the two Linux-gated flash-attn tests off Linux
_should_try_runtime_flash_attn_install ends in sys.platform.startswith(
"linux"), and the threshold test one line above already asserts exactly that,
so the two tests that drive _ensure_flash_attn_for_long_context past the gate
cannot pass anywhere else: the call returns before it reports a status. They
were written on Linux and only surface once the suite actually runs on Windows
or macOS, where both fail on an empty status list. This PR is about making the
backend behave on Windows, so its own suite should be runnable there.
* Fail closed when a KFD topology node does not decode
This PR pins that read to utf-8, which turns an undecodable byte into
UnicodeDecodeError. That is a ValueError, not an OSError, so it slips past the
handler one line below and escapes a helper whose docstring promises to fail
closed on any unreadable node. The caller would then lose the whole HIP-order
map on a machine that has AMD GPUs, and the reason the helper fails closed is
that dropping a node shifts every later ordinal and lets a similar-capacity GPU
pass the total-size guard while showing another card's usage.
Widening the handler is the same one-line change main already made in #7487, so
the two agree and the eventual merge is clean.
* Tighten the comments added in this branch
* Treat an undecodable marker and undecodable metadata as malformed, not fatal
Two more places where pinning the decode changed the failure mode. A
UnicodeDecodeError is a ValueError, so neither `except OSError` nor
`except (JSONDecodeError, OSError)` catches it, and both sites had a documented
fallback that stopped being reached.
An undecodable .transport marker used to read as an unknown value, and the
caller then safely purged and restarted the partial download. It now aborts
prepare_cache_for_transport instead, so the transfer fails rather than retrying.
Undecodable .meta.json used to fall back to the file's own name, the same way
invalid JSON does. It now aborts URI construction for the entire unstructured
seed, so one corrupt byte in original_filename takes out the whole dataset.
Both handlers are widened, matching the KFD fix earlier on this branch.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Widen two more decode guards, and pin the kernel installer's pipe
Same shape as the ones already fixed here: the read was pinned to UTF-8 while
the handler around it still only catches OSError, and UnicodeDecodeError is a
ValueError.
hf_cache_snapshot_dir answers whether a model is already on disk, and the
offline embedding checks turn a raise into a 500. A torn refs/main used to
decode into a nonsense commit and miss the snapshot dir; it now skips that cache
root and keeps looking. _remove_pid_file runs first in _graceful_shutdown, so a
corrupt studio.pid raising there abandoned the inference, export, training and
tunnel children the rest of that function exists to kill.
ssm_runtime's source-build path builds its subprocess kwargs in a dict and
splats them through _run_with_heartbeat, so neither the encoding guard nor the
earlier sweep saw the text = True in it: pip's output was still decoded with the
Windows ANSI codepage, where a non-ASCII path or a compiler diagnostic mojibakes
or raises over an install that was going fine. It now pins the same
utf-8/replace pair install_wheel uses, and the HIP branch extends that env
rather than replacing it. The guard learned the dict-literal shape and reddens
on the old code (ssm_runtime.py:253).
* Tighten the comments around the UTF-8 text I/O pins
Collapse the multi-line rationales added with the encoding pins down to a
line or two each, drop what the code already says, and use one wording for
the repeated child-env note.
* Do not let an unreadable bootstrap password stop startup, and narrow the kwargs guard
ensure_default_admin calls _load_bootstrap_password for every existing admin and
the lifespan calls that with no handler, so pinning the decode turned a damaged
or pre-pin .bootstrap_password file into a backend that will not start. We write
that file ourselves in UTF-8, so a byte that will not decode belongs to a file
whose plaintext is worthless anyway; it now reads as no bootstrap password, the
same answer as an absent file. A readable one still loads.
The new kwargs check also judged every dict literal in the tree, so an unrelated
payload carrying "text": True would have been reported as subprocess
configuration with a misleading message, and a dict that fills in its encoding on
a later line would have been reported too. It now only judges a dict that
actually reaches a call, either splatted through a name or written at the call
site, and treats a later kw["encoding"] assignment as satisfying it. The
ssm_runtime shape it was written for is still caught, and a test pins both
directions.
* Stop reading a UTF-8 record a second time
_read_line always parsed the line under the codepage as well, even when it had
already read as UTF-8. Both callers take the UTF-8 reading when there is one and
never look at the other, so on a healthy shard the second parse is pure waste,
and this file reads all of one on every resume of a scrape it expects to reach
gigabytes. Measured on 200,000 records, 76 MB: 1.96s before, 0.81s after, so the
double reading was costing 2.8x.
The early return is limited to a record, since the key lookup deliberately falls
through to the codepage reading when UTF-8 yields something that is not one. A
line UTF-8 cannot read still tries the codepage, latin-1 and the double-byte
encodings as before, which is what the second reading is for.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Pin the scanned source fixture's line endings
test_remote_code_scan_reads_non_ascii_sources compared a file's contents against
the string it wrote, but wrote it in text mode, so Windows translated the line
ends on the way out and the read back differed by a carriage return. That is the
writer's doing, not the encoding the test is about, and it was the one failure on
the Windows runner that belonged to this branch. The fixture now writes with
newline = "" so the bytes on disk are the string on every platform.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Trim the newer comments to their point
Shorten the widened-guard and state store notes added since the last pass,
and collapse the line-ending note on the scanned source fixture.
* Read the scraper checkpoint as UTF-8 only, never as a codepage
A checkpoint holds nothing but base64 cursors and booleans, so one written by
an older locale-encoded release is byte-identical to a UTF-8 one and already
reads back. The codepage fallback can therefore only ever contribute non-ASCII:
if a single-byte reading of the file were all ASCII, the UTF-8 read would have
succeeded first.
So the only file it changes the answer for is a damaged one, and there it turns
a safe reset into a resume on a mojibaked cursor. GitHub answers that with
INVALID_CURSOR_ARGUMENTS at HTTP 200, gh_client returns the partial document,
and the scraper reads zero nodes and an empty pageInfo, which marks the stream
done. Every later resume then skips it entirely.
Reading UTF-8 only restores the earlier behaviour of dropping a checkpoint that
will not decode, which re-scrapes from the first page while the writers dedup
the replay. The shard scan below keeps its codepage reading; those records do
carry non-ASCII.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Gate the remaining tilelang install tests to Linux
_tilelang_platform_supported() returns False off Linux, so _ensure_tilelang_backend
returns before the install and the subprocess mock these six assert on is never
called. They fail on macOS runners for that reason alone. The rest of the file
already carries this marker; these were missed.
* Gate the Windows-incompatible worker and ROCm tests
Two different gates, because the production code has two. The causal-conv1d and
flash-linear-attention installers bail out on sys.platform == 'win32' alone and
run everywhere else including macOS, so those cases get not_on_windows; marking
them linux_only would skip tests that legitimately pass off Linux. The DRM and
KFD readers return early unless platform.system() is Linux, and their fixtures
build a fake sysfs tree needing PCI addresses like 0000:00:02.0 as directory
names, which Windows cannot represent, so those get linux_only.
The two visible-utilization cases failed for a different reason: on Windows
get_visible_gpu_utilization takes the AMD adapter branch ahead of the torch
fallback under test, and probing it imports torch, which the runner lacks.
Stubbing that branch empty leaves every other platform unchanged.
* Treat unparseable JSON nesting as a parse failure, and guard os.fdopen
json.loads answers nesting it cannot descend with RecursionError, a
RuntimeError, so _parse let it escape where the catch-all it replaced
discarded the record. Both callers run _parse outside any further handler,
so one damaged checkpoint or shard line aborted the scraper at startup.
The encoding guard also missed os.fdopen, which is open() on a descriptor
and takes the same locale default in text mode. It flags exactly the two
text-mode calls that were left unencoded; the swap lock file's reader was
already pinned to UTF-8 while its writer still used the codepage.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Write the non-ASCII source fixture without a 3.10-only argument
Path.write_text() only grew newline in 3.10, and pyproject declares
requires-python >=3.9, so this raised TypeError there. open() takes the same
argument on every supported version and pins the bytes on disk the same way.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Tighten encoding comments
* Follow subprocess calls through callable aliases in the encoding guard
---------
Co-authored-by: Unsloth <michaelhan@Michaels-MacBook-Pro.local>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
---------
Co-authored-by: Unsloth <michaelhan@Michaels-MacBook-Pro.local>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: danielhanchen <unslothshared@gmail.com>
* Let a decode failure degrade instead of escaping a fail-closed helper
Pinning utf-8 makes a read that used to return mojibake on Windows raise
instead. 33 of those reads sit under a handler catching OSError or
json.JSONDecodeError but not UnicodeDecodeError, which subclasses
ValueError, so a corrupt file would now escape a helper written to return
a default. Adds UnicodeDecodeError to those tuples only.
* Treat an undecodable install lock as stale instead of retrying forever
* Pin utf-8 on shipping-code text I/O instead of the operator locale
113 read_text/write_text/open call sites across unsloth, studio and
unsloth_cli let locale.getencoding() decide the encoding. That is utf-8 on
the Linux and macOS runners and cp1252 on a stock Windows install, so the
same file decodes differently for a Windows user and silently produces
mojibake or raises UnicodeDecodeError.
Adds tests/test_runtime_text_encoding.py to keep it that way. It resolves
openers through each file's own imports rather than a fixed list of module
names, so an aliased tarfile.open or a local from PIL.Image import open is
not asked for an encoding it does not take.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Scan tracked files only and resolve the unbound Path calling forms
* Honour PEP 263 when scanning sources and migrate a legacy JSONL before appending
* Scope guard imports lexically and only migrate a legacy file when it round-trips
* Leave a legacy JSONL untouched and resolve path aliases in the foreign-opener check
* Tighten comments
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
* Replace standalone Studio wording with Unsloth
Replace the single word Studio with Unsloth wherever it is used as
shorthand for Unsloth Studio in docs, CLI output, UI strings, i18n
locales, workflow display names, comments and docstrings.
Kept unchanged: the full name Unsloth Studio, third party product
names (LM Studio, Visual Studio, Mac Studio), feature names
(Recipe Studio, Fine-tuning Studio and its translations), and all
identifiers such as env vars, commands, paths and filenames.
* Address review feedback on the Studio wording rename
Use "an" before Unsloth where the rename left the article as "a".
Restore the split brand where Unsloth and Studio render as two halves
of the full product name: the onboarding sidebar subtitle and the
IPv6 localhost warning. Scope two messages to the full name Unsloth
Studio where plain Unsloth was misleading: the AMD README bullet and
the CLI studio setup error.
Trim and tighten code comments and docstrings across the repository. Comment-only: every changed file verified code-identical to main via AST/token comparison.
Trim and tighten code comments and docstrings across studio/ Python. Comment-only: every changed file verified code-identical to main via AST/token comparison.
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.
* fix(gh_client): fail fast on 401/403 auth errors instead of retrying forever (#5325)
Fixes#5325. The Studio data-recipe GitHub Crawler swallows 401 Unauthorized
(and 403 Forbidden without rate-limit headers) into the generic
"network error" retry path, so a job with a stale or wrong-scoped GitHub
token spins indefinitely emitting "Retry." lines until the user cancels.
Changes:
- Add GitHubAuthError. Raised on 401, and on 403 unless the response carries
a clear rate-limit signal (Retry-After header for secondary limits, or
X-RateLimit-Remaining: 0 for primary limits).
- Track which token source resolved at construction time: explicit argument
(recipe-level field), GH_TOKEN, or GITHUB_TOKEN. Surfaced in the error
message so the user knows which credential to rotate.
- Insert the auth-failure check before the existing 403/429 rate-limit branch
in both .graphql() and .rest() so auth failures bypass the sleep-and-retry
loop and abort the recipe immediately.
Genuine rate limiting still retries via the existing path. requests.RequestException
handling is unchanged because GitHubAuthError does not inherit from it.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
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* style: apply black formatting per pre-commit.ci
* [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
* Fix GitHub auth failure handling
Preserve GitHub token source through the repo seed scraper and fail fast on non-rate-limit auth errors while keeping genuine rate-limit retries.
---------
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Wasim Yousef Said <wasimysdev@gmail.com>
* Studio: add github_repo seed reader and GitHub Support Bot recipe
Adds a first-party Data Designer seed reader that scrapes GitHub issues,
pull requests, and commits from one or more repositories via the GraphQL
API, and a learning recipe (GitHub Support Bot) that turns those rows into
synthetic support Q&A pairs for fine-tuning.
Backend (new plugin studio/backend/plugins/data-designer-github-repo-seed):
* GitHubRepoSeedSource config: repos, token (falls back to GH_TOKEN /
GITHUB_TOKEN env var), item_types (issues / pulls / commits),
per-resource limit (0 means all), max_comments_per_item.
* Rate-limit-aware GraphQL client (GitHubClient + RepoScraper) shared
across repos; flattens each item into a uniform row with columns
item_type, repo, number, title, body, state, author, created_at,
closed_at, url, labels, comments.
* Registered via the data_designer.plugins entry point.
Frontend:
* New seed_github block variant so the seed node card shows
"GitHub repositories" instead of the generic "Document file"
placeholder, with its own icon and inline summary (repo count +
item-type list).
* Rewritten seed dialog github_repo form: repos textarea pre-filled with
unslothai/unsloth + unslothai/unsloth-zoo, password input for the GH
token, items-per-repo number with an "All" toggle, and the noisier
options (item types, max comments, include comments) tucked under an
Advanced collapsible.
* Local model auto-load on Run: if a recipe uses an is_local provider
and the inference server is not already serving that model, the
executions hook calls /api/inference/load first. Removes the "open
/chat to load a model" prerequisite that users kept tripping on.
* Honor the recipe's run.rows value in the Run dialog (previously the
store reset to 5 regardless of what the template shipped).
Recipe (studio/frontend/src/features/data-recipes/learning-recipes/
github-support-bot.json):
* Defaults to the Local Model provider + unsloth/gemma-4-E2B-it-GGUF.
* Scrapes unslothai/unsloth and unslothai/unsloth-zoo, issues and pulls,
up to 100 items per resource.
* Two LLM blocks: normalized_question (llm-text) rewrites each thread
into a clean support question, support_answer (llm-structured)
produces JSON with answer / diagnosis_questions / cites / confidence.
* Run defaults to 10 rows for a quick smoke test.
Verified end-to-end on a running Studio: card renders, source-data
dialog is pre-populated, All toggle disables the limit input, the
recipe executes and produces rows against a loaded local GGUF.
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* fix: improve GitHub recipe support
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* Studio: speed up GitHub scraper and harden the support-bot recipe
Addresses a perf issue found while demoing the github_repo seed reader:
Scraper is too slow at scale. The PRs GraphQL query pulls deeply nested
fields (reviewThreads, reviews, commits, timelineItems, etc.) so the
page size was pinned at 3 to stay under GitHub's node-count ceiling. 100
PRs meant 34 serial round trips. Added lighter query variants
(PRS_PAGE_QUERY_LIGHT, ISSUES_PAGE_QUERY_LIGHT) that drop the fields the
Studio flatten layer does not use (it only reads title, body, state,
author, labels, comments). With the light query PR pages can safely go
to 25 per page and issues to 50. The plugin scraper now passes
light=True to RepoScraper so Studio always uses the fast path; the heavy
query remains available for other callers.
Recipe defaults are now demo-ready with production knobs called out:
- max_parallel_requests: 1 and max_tokens: 800 so small local models
stay stable when running the support_answer structured column.
- support_answer prompt trimmed to 80-200 words so gemma-4-E2B GGUF can
actually comply with the schema. The canonical 150-300 word codex
prompt is still documented in the node3 markdown note for
production upgrades.
* Studio: rename GitHub recipe to 'GitHub Scraper' and add Easy mode
Changes the recipe framing from a single-purpose 'Support Bot' pipeline
to a general-purpose scraper that produces {user_request,
grounded_response} training pairs. Aligns with the canonical
github_data_gatherer dataset (11 enrichment tasks mirrored in pr_requests_20
/ issue_requests_20 on the input side and explain_pr / issue_fix_plan /
issue_solution on the output side).
Recipe JSON changes:
- columns[0] renamed normalized_question -> user_request, prompt now
inverts a GitHub thread into a realistic user ask instead of
normalising it.
- columns[1] renamed support_answer -> coauthor_response, emits
{response, followups, cites, task, confidence} and branches on
issue vs PR thread type.
- Notes rewritten to document the 11-task catalog and the canonical
production prompt to paste in for a full dataset backfill.
Frontend: Easy mode for github_repo recipes. The drag-and-drop canvas is
hidden behind an 'Advanced' tab; Easy mode is the default for any recipe
whose seed_source_type is github_repo. The Easy form reuses the existing
GithubRepoSeedForm (promoted to exported), adds a rows input bound to
previewRows, a model field bound to the model_config, and a single Run
button that calls runPreview() directly (no modal). Non-github recipes
see the same Editor / Runs tabs as before.
View mode persists per-recipe-id in localStorage under
recipe-studio:view-mode:<recipeId>.
* Studio: auto-detect server GH_TOKEN and widen Easy-mode detection
The GitHub seed form now fetches /api/data-recipe/seed/github/env-token
on mount and, when the server exposes a GH_TOKEN / GITHUB_TOKEN env var
and the token field is blank, shows a small 'Using server env var' badge
and swaps the placeholder text. The token value itself is never returned
to the UI.
Widens Easy-mode detection in recipe-studio-page.tsx so that recipes
saved before ui.seed_source_type was persisted also get the Easy tab:
falls back to recipe.seed_config.source.seed_type, which is always
present for github_repo seeds.
* fix: polish GitHub recipe UI
* Studio: default llama-server --threads to -1 (auto)
Previously we passed --threads only when the caller set an explicit
value, which meant llama-server fell back to its internal default.
That default has varied across llama.cpp builds (some versions use
hardware concurrency including hyperthreads, which hurts throughput on
CPU-heavy inference). Always passing --threads -1 pins the behaviour
to llama.cpp's auto-detect (physical cores).
Caller-supplied n_threads still wins when non-None.
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* Studio: auto-switch Easy mode to Runs pane on run start
Easy mode had no progress island or canvas overlay, so after clicking Run
the only visible state was the button label flipping to "Running..." while
the screen otherwise stayed identical. This reads as stuck even though the
job is progressing.
Wire an onExecutionStart callback from recipe-studio-page.tsx through to
useRecipeExecutions so that when a run is kicked off from easy mode, the
page flips to the executions view where the Runs sidebar, progress bar,
rate/ETA panel, and live log are rendered. Advanced/editor mode keeps its
existing behavior and stays on the canvas (it already has the floating
ExecutionProgressIsland).
* fix: clean up GitHub scraper layout
* Studio: forward llm-structured output_format as llama-server response_format
Local GGUF runs of llm-structured columns used to generate the full
max_tokens budget before the prompt-level "return JSON in a ```json
fence" instruction got parsed. Small models (e.g. gemma-4-E2B-it)
routinely broke format, so each row took ~65s and frequently failed
with "No parsable JSON structure within ```json markdown fence".
For any local-provider model_config referenced by an llm-structured
column, clone the model_config and inject response_format into the
clone's inference_parameters. Uses llama.cpp server's flat shape
(tools/server/README.md):
{"type": "json_schema", "schema": <output_format>}
Not the OpenAI-nested form; data_designer's OpenAI adapter forwards
response_format verbatim via facade._COMPLETION_REQUEST_FIELDS, and
llama-server's documented schema path expects the flat variant.
The clone is per (model_alias, column) so:
- llm-text / llm-judge columns that share the same alias keep
free-form sampling.
- Each structured column gets its own schema, so columns with
different output_formats don't collide.
Effect on gemma-4-E2B-it demos: every row parses cleanly, and the
model terminates immediately after the closing brace instead of
running to max_tokens. Net wall-clock is usually faster even though
grammar-constrained sampling is slightly slower per token.
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* Studio: flip Easy to Runs pane before validation scrape, not after
Previously onExecutionStart fired inside runExecution, which runs AFTER
validateRecipe() -- and validation re-invokes the seed reader. For the
github_repo reader that is a full GraphQL scrape, so the user sat on a
"Running..." button with an otherwise unchanged Easy form for 10-15s
before anything moved.
Call onExecutionStart at the top of runWithValidation, right after we
have a payload to send. The view flips immediately; ensureLocalModelLoaded
+ validateRecipe now run against the Runs pane instead of a frozen Easy
form. runExecution still calls onExecutionStart downstream, but the
callback is idempotent (the page's easy -> executions guard skips the
second call), so no behaviour change for runs that pass validation.
If validation fails the toast + runErrors path still fires; the Easy
form's error banner still reads runErrors when the user switches back.
* Studio: unify data-recipe workflow auth on sk-unsloth-* keys
The previous commit (a61b4cc9) assumed storage.create_api_key(..., internal=True)
and storage.revoke_internal_api_key(key_id) existed, but those helpers were
only in the working tree, never committed. Recipe runs in local-model mode
were therefore crashing with 500 when _inject_local_providers tried to mint
a workflow key. This commit ships the missing pieces.
auth/storage.py:
- api_keys schema gains is_internal INTEGER DEFAULT 0 (with a guarded
ALTER TABLE migration so existing auth.db files upgrade in place).
- create_api_key takes an internal=False kwarg; internal keys are flagged
so they can be hidden from user-facing listings.
- list_api_keys takes include_internal=False so UIs never see workflow keys.
- New revoke_internal_api_key(key_id): id-only revoke for keys minted by
non-user subjects (the JobManager does not know a username).
core/data_recipe/jobs/manager.py:
- JobManager.start accepts internal_api_key_id and stores it on Job so
lifecycle handlers can revoke eagerly.
- _handle_event revokes on EVENT_JOB_COMPLETED / _ERROR / _CANCELLED.
- _pump_loop subprocess-died fallback also retires the key so a crashed
worker cannot leak a live sk-unsloth-* beyond its TTL.
- Revocation is best-effort (swallow exceptions) -- the 24h TTL is the
safety net if storage hiccups.
core/data_recipe/jobs/types.py:
- Job dataclass gains internal_api_key_id: int | None = None.
Replaces the bespoke 24h JWT path that jobs.py used to mint for local
providers. One mint/revoke/verify surface for every API key the server
issues, and revocation is now eager (seconds, not 24h) instead of TTL-only.
* Studio: plug workflow-key leak on unexpected create_job errors
Review follow-up on the sk-unsloth-* workflow-key lifecycle in
create_job. Previously the revoke handlers wrapped mgr.start(...) but
only caught RuntimeError and ValueError, and get_job_manager() sat
outside the try block entirely. Any other exception type (TypeError
from a mismatched kwarg, OSError from the queue write, etc.) would
bubble up to FastAPI and leave the minted key live until its 24h TTL.
Fix: one try block covers both get_job_manager() and mgr.start(), with
a trailing except Exception that revokes and re-raises. The
RuntimeError -> 409 and ValueError -> 400 paths are unchanged so
specific client-facing status codes still surface. Revocation is still
best-effort (_revoke_internal_api_key_safe swallows errors) because we
never want revoke failures to mask the original crash.
Severity is low -- the key can't bootstrap longer access and the 24h
TTL bounds the window -- but the reviewer's point stands: eager revoke
on every failure path is the right invariant.
* Studio: nest response_format under extra_body so pydantic accepts it
The previous commit dropped response_format at the top level of a cloned
model_config's inference_parameters, which BuilderConfig rejected with:
ValidationError: Extra inputs are not permitted [type=extra_forbidden]
data_designer.model_configs.1.inference_parameters.response_format
data_designer's BaseInferenceParams is a pydantic model with extra=forbid
and only a fixed set of fields (temperature, top_p, max_tokens,
max_parallel_requests, timeout, extra_body). The pass-through path for
anything the schema doesn't know about is `extra_body`, which the
OpenAI SDK spreads into the chat-completions request body at the top
level -- which is exactly where llama-server reads response_format from.
Inject under extra_body (merging with any existing extra_body contents)
so the clone validates. llama-server still receives
{"type": "json_schema", "schema": <output_format>} at the top level of
the request body, which is the flat shape llama.cpp's server expects.
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* Studio: forward response_format to llama-server and fence-wrap the reply
Two-part fix for the llm-structured data-recipe path:
(1) The /v1/chat/completions proxy was dropping response_format. The
route's passthrough branch only triggered on tools / tool messages, so
requests carrying a JSON schema fell into the non-passthrough GGUF path
which calls generate_chat_completion (no response_format kwarg). The
schema never reached llama-server, so guided decoding was a no-op and
the model emitted free-form text that happened to parse a fraction of
the time. Widen the passthrough trigger and teach _build_passthrough_payload
to forward response_format so llama-server's GBNF grammar actually runs.
Guided decoding does not require supports_tools, so split the condition:
a request is now passthrough-routed if it carries tools/tool messages
(existing behavior) OR carries response_format (new). The vision guard,
streaming fork, and tools-choice defaulting are unchanged.
(2) data_designer's llm-structured parser looks for a ```json ... ```
markdown fence and discards anything else. Guided decoding emits only
the JSON object (the GBNF grammar has no fence tokens), so a
100%-valid schema-constrained run still ended up 0 ok / N failed with
"No parsable JSON structure within ```json markdown fence". In
_openai_passthrough_non_streaming, wrap each choice's content in the
expected fence when the caller asked for guided decoding. Already-fenced
content is left alone so other clients that prefer raw JSON are not
affected; the wrap is scoped to requests that carried response_format.
Net effect on the GitHub Support Bot recipe on a local GGUF: schema
actually binds during sampling, content arrives wrapped in the fence
data_designer expects, and generation terminates immediately after the
closing brace instead of running out to max_tokens.
* Studio: Easy mode runs a full run, capped at the user's row count
Easy mode used to call runPreview, which produces a test run: no
artifact persisted, reduced progress tracking, and framed in the Runs
pane as "Test run". The whole point of the form is to let a user kick
off a real dataset build with one click, so wire it to runFull instead
and bind the Rows input to fullRows (not previewRows).
runFull requires a non-empty fullRunName. The Easy form has no run-name
input, so seed a default on mount whenever Easy is active and
fullRunName is still empty. Uses `<recipe name> <iso-timestamp>` so
each Easy run gets a stable-ish default that still sorts chronologically
in the Runs pane. User can override it from the Advanced run dialog
before clicking Run.
Rename GithubScraperEasyView's rows props from previewRows/setPreviewRows
to rows/setRows so the view stays agnostic to which hook state the page
chooses to bind. Loading indicator now follows fullLoading.
* Studio: clamp GitHub scrape page size and memoize the materialization
Two wins for the "before Generating fires" gap on small previews:
(1) scrape_{issues,prs,commits} hardcoded per_page (50 / 25 / 100) and
only checked the trial limit AFTER the page was written, so a 1-row
Easy run still asked GitHub for a full 50-issue + 25-PR page, wrote
them all to JSONL, and then stopped because total_new already exceeded
the trial cap. Cap per_page at min(page_cap, trial_limit) so
github_limit=1 actually asks for first:1.
(2) GitHubRepoSeedReader.get_dataset_uri used to scrape fresh on every
invocation. data_designer calls the seed reader multiple times per
recipe job (validation, preview, per-column sampling), so a 2-repo
Easy preview ran the full GraphQL scrape three times back-to-back,
burning ~15s of dead air before any LLM generation began.
Added a module-level in-process cache keyed on
(repos, item_types, limit, include_comments, max_comments_per_item,
sha256(token)[:16]) that stores the JSONL path of the first
materialization. Subsequent calls with the same signature return the
cached path, guarded by a staleness check that drops the entry if the
file was tmp-cleaned. Raw token values never land in the key.
Net effect on a 1-row Easy run, 2 repos, limit=1: 2 GraphQL round
trips instead of ~12, and the first-to-Generating gap collapses from
~15s to roughly 2-3s.
* Studio: make Easy mode Rows input editable instead of snapping to 1
The Rows to generate input used type="number" with value bound directly
to the rows state and an onChange that coerced any non-positive parse
result back to 1. The moment the user pressed backspace to clear the
field, the parent re-rendered with value=1 and the caret jumped, making
it impossible to change the value without arrowing the browser's +/-
spinner.
Switch to a text input with inputMode="numeric" and pattern="[0-9]*"
(so mobile still shows a numeric keyboard, and the browser drops the
spinner buttons the user did not want). Add a local rowsText buffer so
the field can hold transient empty / partial digit strings while
editing without fighting the parent state; the canonical rows value
only advances when the buffer parses to a valid integer in [1, 10000],
and onBlur clamps back to 1 or 10000 if the user left it out of range.
No behavior change for valid numeric edits - the downstream runFull()
still sees a clean positive integer.
* Studio: expand dataset cells horizontally by column on click
Click a long cell to expand that whole column. Click again to collapse.
Replaces the prior row-level vertical expansion which made it hard to
compare cells across columns. State is scoped per execution and per
column; the row itself is no longer a click target.
* Studio: force expanded dataset column to grow wide enough to read
* Studio: disable thinking for local recipe inference and plumb the kwarg
Reasoning-capable models (gemma-3n, qwen3.5, etc.) emit a
<think>...</think> preamble ahead of the answer by default, which
roughly doubles the generated token count per row on a local GGUF
and pushes the actual answer past data_designer's json-fence regex
on llm-structured columns. Recipes want the terse answer, not the
scratchpad.
Two halves of the fix:
(1) routes/data_recipe/jobs.py: when _inject_local_providers walks
the recipe's model_configs to point them at the local endpoint, also
stash chat_template_kwargs={"enable_thinking": false} under each
config's inference_parameters.extra_body. OpenAI SDK spreads
extra_body into the top-level request body, so llama-server and the
Studio /v1/chat/completions route both see it.
(2) routes/inference.py: the chat-completions route previously
dropped chat_template_kwargs on the floor because the whitelist
body builder only forwarded known fields.
- At the top of openai_chat_completions, lift
chat_template_kwargs.enable_thinking from payload.model_extra
onto the typed payload.enable_thinking field when the caller
did not set the latter, so the non-passthrough GGUF path's
generate_chat_completion(...) call honors the override.
- Teach _build_passthrough_payload to forward a
chat_template_kwargs dict, and have _build_openai_passthrough_body
derive that dict from payload.enable_thinking so
response_format requests (structured columns) also land at
llama-server with the reasoning preamble suppressed.
Net effect on a 10-row support-bot run with gemma-4-E2B-it-GGUF:
responses arrive without <think> tags, wall-clock per call drops
roughly in half, and structured columns stop leaking reasoning
tokens through the GBNF-constrained output.
* Studio: update GitHub Support Bot learning recipe with maintainer layout
Replace the template with the hand-laid-out export from the maintainer
so note nodes ship with real x/y positions (scattered around the
graph instead of all stacked at x=480) and the edges / canvas pan look
correct on first load. Also picks up the maintainer's prompt tweaks and
output schema names (coauthor_response / user_request / followups / task /
cites / confidence).
Diff is mostly ui.nodes positions and prompt bodies; runtime shape is
unchanged (seed_config / columns still target model_1 against the Local
Model provider).
* Studio: auto-size dataset sample columns; wide text gets a wide column
Drop the per-column click-to-expand toggle and the 180-char truncation.
Every column now renders its full value. Columns with long text get a
min-w of 48rem so the text is readable without wrapping into a tall
block; narrow-content columns get a 12rem min-w. The table wrapper
already has overflow-x-auto, so wide-column totals cause a horizontal
scrollbar instead of cramming everything into the viewport.
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* fix GitHub scrape progress
* [pre-commit.ci] auto fixes from pre-commit.com hooks
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* add resetApiBase export for test setup
* Studio: rename github-support-bot output columns to User / Assistant
Previously emitted user_request and coauthor_response, which did not
match the canonical User / Assistant chat-pair shape that downstream
SFT consumers expect. Renamed the columns in the recipe JSON (columns,
UI node ids, edges, notes, prompt Jinja refs) and the matching copy in
the learning-recipes index, data-recipes-page, and easy view.
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* Bump Data Designer to 0.5.4 (removes litellm dependency)
NVIDIA Data Designer v0.5.4 removes litellm entirely and replaces it
with native OpenAI and Anthropic adapters. This follows the litellm
supply chain incident where versions 1.82.7 and 1.82.8 were compromised
with a credential stealer.
Release notes: https://github.com/NVIDIA-NeMo/DataDesigner/releases/tag/v0.5.4
Changes:
- Bump data-designer, data-designer-config, data-designer-engine to 0.5.4
- Sync data-designer-deps.txt with 0.5.4 engine requirements:
- Added: chardet, fsspec, mcp
- Removed: python-json-logger, pymupdf, pymupdf4llm, mammoth
(these remain in the unstructured-seed plugin which still needs them)
- duckdb constraint relaxed from <1.5 to <2 (upstream fixed record_batch)
- Bump plugin lower bound to >=0.5.4
* Keep pymupdf, pymupdf4llm, mammoth in data-designer-deps
The unstructured-seed plugin is installed with --no-deps, so its
pyproject.toml dependencies are not auto-resolved. These three
packages are needed by the seed route (studio/backend/routes/
data_recipe/seed.py) and must remain in the explicit deps list.
* fix(recipe-studio): prevent fitView from zooming to wrong location on recipe load
* feat: add pymupdf/python-docx deps and unstructured uploads storage root
* feat: add POST /seed/upload-unstructured-file endpoint
* feat: add multi-file chunking with source_file column
* feat: update frontend types and API layer for multi-file upload
* feat: round-robin preview rows across source files
Ensures every uploaded file is represented in the preview table
by cycling through sources instead of just taking the first N rows.
* fix: disable OCR, fix auto-load timing, fix persistence on reload
- Disable pymupdf4llm OCR with write_images=False, show_progress=False
- Replace onAllUploaded callback with useEffect that detects uploading→done
transition (avoids stale closure reading empty file IDs)
- Fix importer to preserve file IDs from saved recipes instead of clearing
(clearing only happens at share time via sanitizeSeedForShare)
* fix: harden unstructured upload with input validation and state fixes
Validate block_id/file_id with alphanumeric regex to prevent path
traversal, use exact stem match for file deletion, add error handling
for metadata writes and empty files, fix React stale closures and
object mutations in upload loop, and correct validation logic for
unstructured seed resolved_paths.
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* fix: address PR review - legacy path import, share sanitizer, sync effect
Promote legacy source.path into resolved_paths for old unstructured
recipes, clear source.paths in share sanitizer to prevent leaking local
filesystem paths, and gate file sync effect to dialog open transition
so users can actually delete all uploaded files.
* fix: CSV column fix (BOM + whitespace + unnamed index re-save) for #4470
* fix: harden unstructured upload flow and polish dialog UX
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