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Author SHA1 Message Date
pre-commit-ci[bot]
d6f1075812 [pre-commit.ci] auto fixes from pre-commit.com hooks
for more information, see https://pre-commit.ci
2026-06-13 03:13:46 +00:00
danielhanchen
657b3251f8 Upgrade setuptools and wheel in the auto-install command
The generated install command builds unsloth from git with
--no-build-isolation, so pip uses the environment's existing setuptools
rather than the pinned build-system requirement. On setuptools < 77 the
PEP 639 license string in pyproject.toml fails to validate and the
install aborts. Upgrade setuptools and wheel up front so the source
build always has PEP 639 support.
2026-06-13 03:13:03 +00:00
Daniel Han
a370521879 Merge branch 'main' into pip 2026-06-12 11:20:56 -07:00
Daniel Han
b712f9f557 Merge branch 'main' into pip 2026-06-12 07:37:43 -07:00
Daniel Han
667467a315 Merge branch 'main' into pip 2026-06-12 07:36:20 -07:00
Daniel Han
55075f691e Merge branch 'main' into pip 2026-06-12 06:55:57 -07:00
Daniel Han
0e929cddac Update pyproject.toml 2026-06-12 06:35:51 -07:00
Daniel Han
ecaf3dde2a Merge branch 'main' into pip 2026-06-12 06:35:37 -07:00
Daniel Han
fc9d82f6bf Update pyproject.toml 2026-06-11 09:22:35 -07:00
Daniel Han
4d2afc62a0 Merge branch 'main' into pip 2026-06-11 09:22:24 -07:00
Daniel Han
43c669e6ec Update pyproject.toml 2026-06-10 11:11:36 -07:00
Daniel Han
11b69c1051 Merge branch 'main' into pip 2026-06-10 11:11:29 -07:00
Daniel Han
39c7a4d290 Merge branch 'main' into pip 2026-06-03 07:30:11 -07:00
Daniel Han
ff1088af40 Update pyproject.toml 2026-06-03 06:36:36 -07:00
Daniel Han
6d3849b821 Merge branch 'main' into pip 2026-06-03 06:36:15 -07:00
Daniel Han
8e26a368e1 Merge branch 'main' into pip 2026-06-01 08:22:08 -07:00
Daniel Han
e31d4c6aea Update pyproject.toml 2026-05-31 07:11:09 -07:00
Daniel Han
5688072af6 Merge branch 'main' into pip 2026-05-31 07:10:55 -07:00
Daniel Han
d3ac7447eb Merge branch 'main' into pip 2026-05-26 07:26:37 -07:00
Daniel Han
2fdfe24fb1 Merge branch 'main' into pip 2026-05-24 07:11:32 -07:00
Daniel Han
e2215c9d11 Update pyproject.toml 2026-05-22 09:24:40 -07:00
Daniel Han
b11f13a710 Merge branch 'main' into pip 2026-05-22 09:24:32 -07:00
Daniel Han
66ae2d416c Merge branch 'main' into pip 2026-05-19 07:27:07 -07:00
Daniel Han
b0a35ddeab Merge branch 'main' into pip 2026-05-19 07:24:07 -07:00
Daniel Han
405add94a1 Update pyproject.toml 2026-05-19 07:00:38 -07:00
Daniel Han
64dc11faa2 Merge branch 'main' into pip 2026-05-19 07:00:31 -07:00
Daniel Han
07e2fccf38 Merge branch 'main' into pip 2026-05-18 08:43:14 -07:00
Daniel Han
d482382a92
Sync pyproject.toml fixes from main into pip (#5555)
- Add missing cu124onlytorch240 extras (xformers==0.0.28.post1)
- Add sentence-transformers to huggingface and colab-new extras
- Add triton extras group (split out from main deps)
- Add windows extras group
- Drop xformers<0.0.27 cap in colab-no-deps; gate on linux/win + x86_64
- Add [tool.ruff] config (target py311, lint select/ignore, extend-exclude)
- Add [tool.pytest.ini_options] testpaths = ["tests/security"]

Only PyPI-compatible (version-pin) entries copied; URL-based intel/amd/rocm/
flashattentiontorch* extras from main are intentionally skipped.
2026-05-18 06:39:41 -07:00
Daniel Han
342bbc2333 Merge branch 'main' into pip 2026-05-18 06:31:17 -07:00
Daniel Han
e1fe3be939 Update pyproject.toml 2026-05-18 06:30:03 -07:00
Daniel Han
d459f60458 Merge branch 'main' into pip 2026-05-18 06:26:54 -07:00
Daniel Han
2c4bf9ae35 Route CPU-only Linux x86_64 to ggml-org/llama.cpp prebuilts (#5302)
* Route CPU-only Linux x86_64 to ggml-org/llama.cpp prebuilts

setup.sh hard-coded _HELPER_RELEASE_REPO=unslothai/llama.cpp for every
non-Darwin host. unslothai/llama.cpp only publishes Linux CUDA bundles
(app-*-linux-x64-cuda*.tar.gz), so a CPU-only Linux host walked ~30
releases looking for a non-existent app-*-linux-x64-cpu asset, exited
the prebuilt planner with "no compatible Linux prebuilt asset was
found", and fell through to a source build. Free CI runners
(ubuntu-latest with no GPU) hit this on every install, and anyone
running Studio on a Linux laptop without an NVIDIA GPU paid the
~3 minute cmake+make cost on first install.

ggml-org publishes llama-<tag>-bin-ubuntu-x64.tar.gz on every release
and install_llama_prebuilt.py already knows how to fetch it: when
called with --published-repo ggml-org/llama.cpp, the Linux x86_64 +
not has_usable_nvidia branch in direct_upstream_release_plan picks up
that asset directly. The fix is purely on the routing side.

Tighten the gate so a Linux host routes to ggml-org only when it is
x86_64 and has no GPU detection tool installed (nvidia-smi, rocminfo,
amd-smi, hipconfig, hipinfo). Everything else stays on the current
path:

  - macOS: already on ggml-org, unchanged
  - Windows: already on ggml-org via setup.ps1, unchanged
  - Linux CUDA: nvidia-smi present -> unslothai/llama.cpp, unchanged
  - Linux ROCm: rocminfo / amd-smi / hipconfig / hipinfo present
                -> unslothai/llama.cpp -> source build with HIP,
                unchanged
  - Linux Intel / Vulkan / SYCL: no NVIDIA / AMD tools, hits the new
                ggml-org route, gets upstream CPU asset (same as
                today's source-build CPU output, ~3 min faster)
  - Linux arm64 / s390x: not x86_64 -> unslothai/llama.cpp ->
                source build, unchanged

* Tighten routing comment in studio/setup.sh
2026-05-06 06:22:56 +00:00
Daniel Han
a87a08610e Merge branch 'main' into pip 2026-05-06 00:27:15 +00:00
danielhanchen
41abe89041 Bump version to 2026.5.2
Cuts a new PyPI release that ships PR #5296: Studio chat history and
attachments work again with newer @assistant-ui/react, plus the pinned
assistant-ui surface and frontend package-lock.json so future installs
cannot drift back onto a broken bundle.
2026-05-06 00:25:04 +00:00
Daniel Han
d638d1bd6f Merge branch 'main' into pip 2026-05-06 00:24:48 +00:00
Daniel Han
2e3b2bdc27 Update pyproject.toml 2026-05-05 05:27:54 -07:00
Daniel Han
9cc539c1b4 Merge branch 'main' into pip 2026-05-05 05:27:25 -07:00
Daniel Han
973c7d80c2 Merge branch 'main' into pip 2026-04-23 06:58:47 -07:00
Daniel Han
c27f9b99e9 Merge branch 'main' into pip 2026-04-22 09:18:09 -07:00
Daniel Han
0c24d61708 Update pyproject.toml 2026-04-16 12:06:55 -07:00
Daniel Han
e9a2b5c010 Merge branch 'main' into pip 2026-04-16 12:06:45 -07:00
Daniel Han
e8355451ea Update pyproject.toml 2026-04-15 08:07:33 -07:00
Daniel Han
a7b4ae19ee Merge branch 'main' into pip 2026-04-15 08:07:11 -07:00
Daniel Han
9066946615 Merge branch 'main' into pip 2026-04-06 09:39:11 -07:00
Daniel Han
b2580ae32b Update pyproject.toml 2026-04-06 09:21:23 -07:00
Daniel Han
7ae9580ce6 Merge branch 'main' into pip 2026-04-06 09:21:07 -07:00
Daniel Han
9ad3b761ee Merge branch 'main' into pip 2026-04-03 15:02:41 -07:00
Daniel Han
8f721d28d6 Merge branch 'main' into pip 2026-04-02 12:28:40 -07:00
Daniel Han
396aa05ead Update pyproject.toml 2026-04-02 12:03:10 -07:00
Daniel Han
2297f73cad Merge branch 'main' into pip 2026-04-02 12:02:48 -07:00
Daniel Han
a728f7c308 Update pyproject.toml 2026-03-31 06:51:58 -07:00
Daniel Han
884152daee Merge branch 'main' into pip 2026-03-31 06:51:48 -07:00
Daniel Han
7437af2e44 Merge branch 'main' into pip 2026-03-27 08:42:05 -07:00
Daniel Han
67678d2c29 Merge branch 'main' into pip 2026-03-27 07:24:42 -07:00
Daniel Han
e568000a92 Update pyproject.toml 2026-03-27 07:23:42 -07:00
Daniel Han
6700dd60f0 Merge branch 'main' into pip 2026-03-27 07:23:27 -07:00
Daniel Han
abf578327c Merge branch 'main' into pip 2026-03-27 03:35:13 -07:00
Daniel Han
a4ae80cd6a Merge branch 'main' into pip 2026-03-25 09:40:21 -07:00
Daniel Han
ec47b2984d Merge branch 'main' into pip 2026-03-25 09:38:41 -07:00
Daniel Han
d9d1a63397 Fix Colab huggingface-hub conflict, ensurepip fallback, bump to 2026.3.14
- Strip version constraints on Colab dep install
- Upgrade huggingface-hub>=1.0 if is_offline_mode is missing
- ensurepip fallback for uv venvs without pip
- Bump installer pins to 2026.3.14
2026-03-25 16:36:25 +00:00
Daniel Han
0bb6379aad Fix Colab huggingface-hub conflict and pip bootstrap on uv venvs
- colab.py / setup.sh: relax == pins to >= when installing studio.txt
  on Colab so huggingface-hub 0.36.2 does not clobber Colab's bundled
  version (which breaks transformers is_offline_mode import)
- install_python_stack.py: when uv is unavailable and pip is missing
  (uv-created venvs), bootstrap via ensurepip before attempting upgrade
- Bump version to 2026.3.14
2026-03-25 16:15:29 +00:00
Daniel Han
1c608e8ff7 Fix Colab dep install: relax == pins to >= to avoid breaking transformers
studio.txt pins huggingface-hub==0.36.2 and datasets==4.3.0 which
overwrite Colab's pre-installed versions and break its bundled
transformers (is_offline_mode was removed in newer huggingface-hub).

Relax == to >= in both colab.py and setup.sh Colab paths so pip keeps
existing compatible versions instead of force-upgrading.
2026-03-25 16:13:30 +00:00
Daniel Han
f9adf6834d Merge branch 'main' into pip 2026-03-25 09:04:26 -07:00
Daniel Han
1fd5853741 Merge branch 'main' into pip 2026-03-25 09:01:49 -07:00
Daniel Han
93a70fbe4e Merge branch 'main' into pip 2026-03-25 08:34:48 -07:00
Daniel Han
8b77451e75 Update pyproject.toml 2026-03-25 07:31:31 -07:00
Daniel Han
481f0618ff Merge branch 'main' into pip 2026-03-25 07:30:50 -07:00
Daniel Han
ddf6f6d1f9 fix(studio): remove litellm dep (quarantined on PyPI) (#4553)
litellm has been quarantined on PyPI due to a supply chain attack
in version 1.82.8 (malicious credential-stealing .pth file).
No versions are currently installable, which blocks
`unsloth studio setup` at step 8/11 (data-designer deps).

Remove litellm from the single-env data-designer requirements
so setup completes. litellm can be re-added once PyPI lifts the
quarantine.

Ref: https://github.com/BerriAI/litellm/issues/24512
2026-03-24 14:21:57 +00:00
Daniel Han
dddc9eac92 Merge branch 'main' into pip 2026-03-24 06:51:20 -07:00
Daniel Han
da81c94510 Merge branch 'main' into pip 2026-03-22 08:23:44 -07:00
Daniel Han
4c139503c1 Merge branch 'main' into pip 2026-03-22 06:14:40 -07:00
Daniel Han
9d1e3c38bc Merge branch 'main' into pip 2026-03-19 02:31:50 -07:00
Daniel Han
8bc26f4e1d Merge branch 'main' into pip 2026-03-18 11:13:18 -07:00
Daniel Han
044e67f5aa Merge branch 'main' into pip 2026-03-18 10:40:39 -07:00
Daniel Han
ba36c12240 Merge branch 'main' into pip 2026-03-18 09:10:55 -07:00
Daniel Han
0a5652281f Merge branch 'main' into pip 2026-03-18 08:33:28 -07:00
Daniel Han
bf63f79414 Merge branch 'main' into pip 2026-03-18 08:31:20 -07:00
Daniel Han
2973bea3d0 Merge branch 'main' into pip 2026-03-17 07:58:59 -07:00
Daniel Han
ddbbfe52cf Update pyproject.toml 2026-03-17 07:58:28 -07:00
1743 changed files with 49288 additions and 387299 deletions

8
.git-blame-ignore-revs Normal file
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# Commits listed here are skipped by `git blame` so that bulk, whitespace-only
# changes don't obscure the real authorship of a line.
#
# GitHub honors this file automatically. To use it locally, run once:
# git config blame.ignoreRevsFile .git-blame-ignore-revs
# chore(studio/frontend): normalize line endings to LF
c50b8ab910f5aa56dd7ae0022d2c7b96bfe3384a

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.gitattributes vendored
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# them when run in WSL/Linux (e.g. `set -e` -> "set: Illegal option -").
*.sh text eol=lf
# Normalize Unsloth frontend sources to LF. Scoped to the frontend tree (rather
# Normalize Studio frontend sources to LF. Scoped to the frontend tree (rather
# than repo-wide *.ts/*.tsx/... rules) so the policy can't force LF on files
# elsewhere. text=auto lets Git detect and leave binary assets (logos, fonts)
# untouched while text files (.ts/.tsx/.json/.html/.svg/...) are stored as LF.

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@ -1,699 +0,0 @@
#!/usr/bin/env bash
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
#
# Drive one coding agent against the running `unsloth run` server for the
# Local Agent Guides CI. All failures from here are failure class (c)
# "guide drift": the server preflight already passed and the agent CLI
# already installed, so a failure here means the documented recipe in
# unsloth_cli/commands/start.py no longer produces a working flow.
#
# Self-updating: for all six agents (claude, codex, hermes, openclaw,
# opencode, pi) we obtain the exact env + command from
# `unsloth start <agent> --no-launch` and run THAT, so a recipe change is
# exercised automatically.
#
# Every agent invocation is wrapped in `timeout` so a headless-TTY prompt
# can never hang the runner -- a timeout is reported as guide drift with a
# distinct message.
#
# Usage:
# agent-guides-drive.sh connection <agent>
# agent-guides-drive.sh file-edit <agent>
# agent-guides-drive.sh attribution-ab claude
#
# Required env (exported by serve-unsloth-run.sh):
# UNSLOTH_BASE_URL UNSLOTH_API_KEY UNSLOTH_MODEL_ID
# UNSLOTH_LLAMA_LOG_DIR AGENT_INVOKE_TIMEOUT UNSLOTH_SEED
set -uo pipefail
MODE="${1:?usage: agent-guides-drive.sh <mode> <agent>}"
AGENT="${2:?usage: agent-guides-drive.sh <mode> <agent>}"
: "${UNSLOTH_BASE_URL:?serve step did not export UNSLOTH_BASE_URL}"
: "${UNSLOTH_API_KEY:?serve step did not export UNSLOTH_API_KEY}"
: "${UNSLOTH_MODEL_ID:?serve step did not export UNSLOTH_MODEL_ID}"
# Determinism (seed/temp) is applied at the server level by
# serve-unsloth-run.sh --extra; agents inherit it through the API.
TIMEOUT="${AGENT_INVOKE_TIMEOUT:-180}"
# opencode is the slow outlier. Unlike the print-mode agents (claude -p, codex
# exec) it runs a full turn AND a separate small_model call to name the session,
# so one connection reply takes ~8 min on a CPU-served 4B -- right at the shared
# 600s cap, so the cell flaked when a run drifted past a ~480s success. Give it
# headroom (still well under the 40-min job budget); the fast agents keep the
# tight cap that still catches a real headless-TTY hang.
case "$AGENT" in
opencode)
# Double it, but only for a bare-integer seconds value. A GNU timeout(1)
# duration suffix (s/m/h/d, including floats like 0.5s) is left unchanged so
# the arithmetic never sees a non-number; timeout(1) parses it directly.
case "$TIMEOUT" in
*[!0-9]*) ;;
*) TIMEOUT=$(( TIMEOUT * 2 )) ;;
esac
;;
esac
# Claude refuses --dangerously-skip-permissions outside a sandbox; the CI runner
# IS the sandbox, so declare it (mirrors unslothai/scripts launcher.sh). Harmless
# to the other agents, which ignore it.
export IS_SANDBOX=1
# Absolute paths anchored at the repo root (this script lives in
# .github/scripts/). Everything writes here regardless of the current working
# directory, so the file-edit mode can `cd` into a scratch work dir without
# breaking log/redaction writes.
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
REPO_ROOT="$(cd "$SCRIPT_DIR/../.." && pwd)"
LOGS_DIR="$REPO_ROOT/logs"
REDACTED_DIR="$REPO_ROOT/redacted-configs"
WORKDIR_BASE="$REPO_ROOT/agent-workdir"
CACHE_HELPER="$SCRIPT_DIR/assert-prompt-cache.sh"
mkdir -p "$LOGS_DIR" "$REDACTED_DIR"
CONNECT_REF="unsloth_cli/commands/start.py"
# Prefill-shrinking flags for Claude Code. The heavyweight agents send
# multi-thousand-token system prompts + full tool schemas, which on a CPU-only
# runner is minutes of prefill per model round-trip (~16 tok/s for a 4B model).
# Replacing the ~5.7k default system prompt with a tiny one (--system-prompt-file)
# and restricting tools cuts the prefill to a few hundred tokens so it completes
# quickly on CPU. These only shape the request size; the start.py recipe
# (endpoint, auth, model) is still exercised end to end.
#
# The bulk of Claude Code's prompt is the built-in tool JSON schemas: measured
# via `claude -p /context`, the default prompt is ~28k tokens of which ~18k is
# "System tools" alone. --allowedTools/--disallowedTools only gate PERMISSION to
# call a tool; they do NOT remove its schema from what is sent to the model, so
# the earlier whitelist left the full ~18k in the prompt and CPU prefill
# (~16 tok/s) overran claude's own request timeout into a retry loop. --tools is
# the flag that restricts which schemas are sent. (The ~8k "Memory files" chunk
# is auto-loaded CLAUDE.md; the unsloth repo ships none, so it is 0 in CI.)
#
# Connection probe: --tools "" sends ZERO tool schemas, leaving ~20 tokens total
# (a one-line --system-prompt-file + the user turn), which prefills instantly.
CLAUDE_CONNECT_FLAGS=(
--system-prompt-file "$SCRIPT_DIR/ci-connect-prompt.txt"
--tools ""
)
# File-edit: the task needs the file/shell tools, so send only those schemas
# (~2.3k tokens vs ~18k for the full set).
CLAUDE_EDIT_FLAGS=(
--system-prompt-file "$SCRIPT_DIR/ci-min-system-prompt.txt"
--tools "Bash,Edit,Write,Read"
)
guide_fail() {
echo "::error::[guide drift] agent=${AGENT}: $* (preflight passed + install OK, so the documented flow in ${CONNECT_REF} drifted)." >&2
exit 1
}
# Redact the API key from any file we are about to keep as an artifact.
# Portable across GNU sed (Linux runners) and BSD sed (macOS), so the
# redaction is never silently skipped.
redact() {
local f
for f in "$@"; do
[ -f "$f" ] || continue
if sed --version >/dev/null 2>&1; then
sed -i "s#${UNSLOTH_API_KEY}#<REDACTED>#g" "$f" 2>/dev/null || true
else
sed -i '' "s#${UNSLOTH_API_KEY}#<REDACTED>#g" "$f" 2>/dev/null || true
fi
done
}
# Print a file to the log with the key scrubbed, without mutating it (the raw file is
# still needed to parse the real env). Use this instead of `cat` for any transcript that
# carries an `export UNSLOTH_API_KEY=...` line, so a live key never reaches Actions logs.
cat_redacted() {
sed "s#${UNSLOTH_API_KEY}#<REDACTED>#g" "$1"
}
# A reply must be non-empty and free of connection/auth errors.
assert_reply() {
local out="$1"
if [ ! -s "$out" ]; then
guide_fail "agent produced an EMPTY reply"
fi
if grep -qiE 'connection refused|connection error|econnrefused|fetch failed|http 4[0-9][0-9]|unauthorized|invalid api key|authentication failed' "$out"; then
guide_fail "agent reply contained a connection/auth error: $(grep -iE 'connection|unauthorized|auth|http 4' "$out" | head -1)"
fi
echo "[$AGENT] reply (first 20 lines):"
head -20 "$out"
}
# Run a command under a hard timeout; map 124 to a guide-drift hang message.
run_timed() { # $1=outfile, rest=command
local out="$1"; shift
timeout "$TIMEOUT" "$@" > "$out" 2>&1
local rc=$?
if [ "$rc" -eq 124 ]; then
redact "$out" # guide_fail exits below, so scrub the transcript here too
echo "[$AGENT] last 40 lines before timeout:"; tail -40 "$out" 2>/dev/null || true
guide_fail "invoke timed out after ${TIMEOUT}s (headless-TTY hang -- the recipe likely needs a non-interactive/print flag)"
fi
return "$rc"
}
# Read a value from an `export VAR=...` line in the connect --no-launch output.
# `unsloth start` writes each agent's session config off the user's ~ and points
# at it through a relocation env var (CODEX_HOME / OPENCODE_CONFIG /
# OPENCLAW_CONFIG_PATH), so the contract checks read the path from here.
raw_env() { # $1 = var name -> value (one shlex-quote layer stripped)
local raw="$LOGS_DIR/connect-${AGENT}.txt"
local v; v="$(sed -n "s/^export $1=//p" "$raw" | tail -1)"
v="${v#\'}"; v="${v%\'}"; printf '%s' "$v"
}
# ── 5-agent start.py path: parse env + command from --no-launch ─────────
# Populates globals CONNECT_ENV (export/unset lines) and CONNECT_CMD (the
# launch command on the last printed line), and runs start.py's config
# writers as a side effect (it writes each agent's relocated session config).
parse_connect() {
local raw="$LOGS_DIR/connect-${AGENT}.txt"
# CONNECT_YOLO=1 adds --yolo. opencode/openclaw gate tool approval through their
# config (which now prompts by default), so the file-edit test opts into auto-approval
# here, the same intent as claude/codex's per-call bypass flags.
local yolo=()
[ -n "${CONNECT_YOLO:-}" ] && yolo=(--yolo)
if ! unsloth start "$AGENT" --no-launch "${yolo[@]}" --api-key "$UNSLOTH_API_KEY" > "$raw" 2>&1; then
cat_redacted "$raw"
guide_fail "'unsloth start ${AGENT} --no-launch' exited non-zero"
fi
echo "[$AGENT] connect --no-launch printed:"; cat_redacted "$raw"
CONNECT_ENV="$(grep -E '^(export |unset )' "$raw" || true)"
# The launch command is the last non-export, non-status line. start.py
# prints "Unsloth <url> · model <id>" and "Updated ..." status lines first.
CONNECT_CMD="$(grep -vE '^(export |unset |Unsloth |Updated |Disabled |Warning|Loading)' "$raw" \
| grep -E '[^[:space:]]' | tail -1)"
[ -n "$CONNECT_CMD" ] || guide_fail "could not parse a launch command from connect --no-launch output"
redact "$raw"
}
# Cross-check the documented contract knobs so silent start.py changes
# (env-var rename, wire_api flip, attribution setting drop) also fail/flag.
crosscheck_contract() {
local raw="$LOGS_DIR/connect-${AGENT}.txt"
local cfg home
case "$AGENT" in
codex)
grep -q 'UNSLOTH_STUDIO_AUTH_TOKEN' "$raw" \
|| guide_fail "Codex env key is no longer UNSLOTH_STUDIO_AUTH_TOKEN (start.py _CODEX_ENV_KEY)"
home="$(raw_env CODEX_HOME)"
# An empty relocation var would make cfg "/config.toml" and silently
# skip the [ -f ] contract check below; fail loudly instead.
[ -n "$home" ] || guide_fail "CODEX_HOME missing from connect output (start.py codex())"
cfg="$home/config.toml"
if [ -f "$cfg" ]; then
grep -q 'wire_api = "responses"' "$cfg" \
|| guide_fail "Codex wire_api is no longer \"responses\" in \$CODEX_HOME/config.toml"
cp "$cfg" "$REDACTED_DIR/codex-config.toml"
fi
grep -q 'codex --oss --profile unsloth_api' "$raw" \
|| echo "::warning::Codex launch command changed from 'codex --oss --profile unsloth_api'"
;;
claude)
grep -q 'ANTHROPIC_AUTH_TOKEN' "$raw" \
|| guide_fail "Claude no longer exports ANTHROPIC_AUTH_TOKEN (start.py claude())"
grep -q 'CLAUDE_CODE_ATTRIBUTION_HEADER' "$raw" \
|| echo "::warning::CLAUDE_CODE_ATTRIBUTION_HEADER no longer set for the session (start.py claude())"
;;
hermes)
grep -q 'UNSLOTH_API_KEY' "$raw" \
|| guide_fail "Hermes env key is no longer UNSLOTH_API_KEY (start.py _HERMES_ENV_KEY)"
home="$(raw_env HERMES_HOME)"
[ -n "$home" ] || guide_fail "HERMES_HOME missing from connect output (start.py hermes())"
cfg="$home/config.yaml"
[ -f "$cfg" ] && cp "$cfg" "$REDACTED_DIR/hermes-config.yaml"
;;
openclaw)
cfg="$(raw_env OPENCLAW_CONFIG_PATH)"
if [ -n "$cfg" ] && [ -f "$cfg" ]; then
grep -q '"openai-completions"' "$cfg" \
|| echo "::warning::OpenClaw provider api is no longer 'openai-completions' (write_openclaw_config)"
cp "$cfg" "$REDACTED_DIR/openclaw.json"
fi
;;
opencode)
cfg="$(raw_env OPENCODE_CONFIG)"
[ -n "$cfg" ] && [ -f "$cfg" ] && cp "$cfg" "$REDACTED_DIR/opencode.json"
;;
pi)
# Pi has no config-dir env var; the session is HOME-relocated, and the
# provider config lives at $HOME/.pi/agent/models.json.
cfg="$(raw_env HOME)/.pi/agent/models.json"
if [ -f "$cfg" ]; then
grep -q '"openai-completions"' "$cfg" \
|| echo "::warning::Pi provider api is no longer 'openai-completions' (write_pi_config)"
cp "$cfg" "$REDACTED_DIR/pi-models.json"
fi
;;
esac
redact "$REDACTED_DIR"/* 2>/dev/null || true
}
# Heavyweight agents (hermes, openclaw) bake a large system prompt + tool JSON
# schemas into every request, which a CPU runner cannot prefill before the invoke
# timeout. As with claude's --tools, we shrink the request from the agent's own
# config: zero tools for the connection probe collapses the prompt to a few
# hundred tokens, since both CLIs gate the bulk of their prompt on having tools.
# Hermes: an explicit empty cli toolset disables all tools (and drops the
# tool-gated guidance blocks), so -z sends ~300 tokens instead of thousands.
# Hermes enables its default cli toolset when the session config does not pin one,
# so we must set platform_toolsets.cli explicitly to [] (not just append) to get
# zero tools. That needs a YAML parser, and the runner's bare python3 has no
# PyYAML -- but the venv that ships `unsloth` does (start.py imports yaml), so run
# the patch with that interpreter. We patch the relocated $HERMES_HOME/config.yaml
# that `unsloth start` printed, not the user's ~/.hermes.
# (-z reads platform_toolsets.cli; --ignore-rules is a no-op under -z.)
patch_hermes_tools() { # $1 = none|default
# Check the raw var BEFORE appending /config.yaml: the joined path is never
# empty, so the old guard could not fire and the patcher would die on
# "/config.yaml" with a bare traceback instead of this clear failure.
local home; home="$(raw_env HERMES_HOME)"
[ -n "$home" ] || guide_fail "Hermes HERMES_HOME missing from connect output (start.py hermes())"
local cfg; cfg="$home/config.yaml"
# Find a python that can import yaml. The runner's bare python3 cannot, but the
# interpreter in the `unsloth` console-script shebang provably can (it runs
# start.py's write_hermes_config, which imports yaml). Try that first, then
# any python on PATH, then the venv sibling, picking the first with PyYAML.
local cand py="" shebang
shebang="$(head -1 "$(command -v unsloth)" 2>/dev/null | sed -n 's/^#![[:space:]]*//p' | awk '{print $1}')"
for cand in "$shebang" python3 python "$(dirname "$(command -v unsloth)")/python"; do
[ -n "$cand" ] || continue
{ [ -x "$cand" ] || command -v "$cand" >/dev/null 2>&1; } || continue
if "$cand" -c 'import yaml' 2>/dev/null; then py="$cand"; break; fi
done
[ -n "$py" ] || guide_fail "could not find a python with PyYAML to patch the hermes session config"
echo "[hermes] patching $cfg with $py"
"$py" - "$1" "$cfg" <<'PY'
import os, sys
import yaml
mode = sys.argv[1]
p = sys.argv[2]
cfg = (yaml.safe_load(open(p)) or {}) if os.path.exists(p) else {}
ts = cfg.get("platform_toolsets")
if not isinstance(ts, dict):
ts = cfg["platform_toolsets"] = {}
if mode == "none":
ts["cli"] = [] # explicit empty list -> zero tools (not "defaults")
else:
ts.pop("cli", None) # file-edit needs real tools -> restore defaults
with open(p, "w") as fh:
yaml.safe_dump(cfg, fh, sort_keys=False)
print(f"[hermes] platform_toolsets.cli = {ts.get('cli', 'default')}")
PY
}
# OpenClaw: 'openclaw agent' has no tool/prompt flags, so we define a 'ci' agent
# in openclaw.json. tools.deny ["*"] sends zero tool schemas (deny always wins)
# for the connection probe; contextInjection "never" + defaults.skipBootstrap
# drop the auto-injected AGENTS.md/SOUL.md bootstrap (the bulk of the prompt) for
# both modes. --agent must reference a defined agent, so write it before invoking.
patch_openclaw_agent() { # $1 = notools|tools
# OpenClaw reads its config from the relocated OPENCLAW_CONFIG_PATH that
# `unsloth start` printed, so patch THAT file (not the user's ~/.openclaw).
local cfg; cfg="$(raw_env OPENCLAW_CONFIG_PATH)"
[ -n "$cfg" ] || guide_fail "OpenClaw OPENCLAW_CONFIG_PATH missing from connect output (start.py openclaw())"
python3 - "$1" "$cfg" <<'PY'
import os, sys, json
mode = sys.argv[1]
p = sys.argv[2]
cfg = json.load(open(p)) if os.path.exists(p) else {}
agents = cfg.setdefault("agents", {})
agents.setdefault("defaults", {})["skipBootstrap"] = True
lst = [a for a in agents.get("list", []) if a.get("id") != "ci"]
agent = {"id": "ci", "contextInjection": "never"}
if mode == "notools":
agent["tools"] = {"deny": ["*"]}
lst.append(agent)
agents["list"] = lst
with open(p, "w") as fh:
json.dump(cfg, fh, indent=2)
print(f"[openclaw] agent ci tools = {agent.get('tools', 'default')}")
PY
}
# Build an invoke script that applies start.py's env then runs the launch
# command (with extra args appended) under bash. We do NOT eval connect's env
# into this shell; we write it into a one-shot script so the export/unset
# semantics are exactly what start.py printed. The script path is absolute
# so it is valid even when the caller has cd'd into a scratch work dir.
invoke_via_connect() { # $1=outfile, rest=extra args appended to the command
local out="$1"; shift
local script="$LOGS_DIR/invoke-${AGENT}.sh"
local real; real="$(mktemp)"
# CONNECT_ENV_EXTRA / CONNECT_CMD_OVERRIDE let a caller (attribution-ab) flip a
# session knob without editing the user's config; empty -> use what start.py emitted.
local cmd="${CONNECT_CMD_OVERRIDE:-$CONNECT_CMD}"
{
echo "set -uo pipefail"
echo "$CONNECT_ENV"
[ -n "${CONNECT_ENV_EXTRA:-}" ] && echo "$CONNECT_ENV_EXTRA"
# Append extra args (the prompt / flags) to the launch command verbatim.
printf '%s' "$cmd"
local a
for a in "$@"; do printf ' %q' "$a"; done
printf '\n'
} > "$real"
# Upload a REDACTED copy of the script, but EXECUTE the un-redacted one from a
# temp path outside the artifact dir. Redacting the script we run would turn
# the real `export TOKEN=sk-...` line into `export TOKEN=<REDACTED>`, which is
# invalid bash (the `<`/`>` are redirections) and silently breaks every agent.
# Writing the redacted copy up front keeps the key out of the artifact even if
# the run times out (run_timed exits before returning here).
cp "$real" "$script"; redact "$script"
# The connect one-liner now carries the key as an inline env assignment; scrub it on
# the way to the log (the executed $real keeps the live value).
echo "[$AGENT] invoking (timeout ${TIMEOUT}s): ${cmd//${UNSLOTH_API_KEY}/<REDACTED>} $*"
run_timed "$out" bash "$real"
local rc=$?
rm -f "$real"
redact "$out" # the transcript can echo the token; scrub before upload
return "$rc"
}
# ═════════════════════════════════════════════════════════════════════════
case "$MODE" in
# ── connection: trivial prompt, assert a non-empty, error-free reply ────
connection)
PROMPT='Reply with exactly the single word: pong'
OUT="$LOGS_DIR/${AGENT}-connection.txt"
parse_connect
crosscheck_contract
# claude/codex run in print mode via the flags start.py emits
# (claude -p / codex exec). For agents whose default subcommand prints
# to stdout we pass the prompt through ctx.args.
case "$AGENT" in
claude) invoke_via_connect "$OUT" "${CLAUDE_CONNECT_FLAGS[@]}" -p "$PROMPT" ;;
codex) invoke_via_connect "$OUT" exec --dangerously-bypass-approvals-and-sandbox "$PROMPT" ;;
opencode) invoke_via_connect "$OUT" run "$PROMPT" ;;
pi) invoke_via_connect "$OUT" -p "$PROMPT" ;;
hermes) patch_hermes_tools none
invoke_via_connect "$OUT" -z "$PROMPT" ;;
openclaw) patch_openclaw_agent notools
CONNECT_CMD_OVERRIDE=openclaw invoke_via_connect "$OUT" agent --local --agent ci \
--model "unsloth/${UNSLOTH_MODEL_ID}" --message "$PROMPT" ;;
*) invoke_via_connect "$OUT" "$PROMPT" ;;
esac
# A non-zero exit from the documented launch command is drift even if it
# printed something: a benign-looking "command not found" / usage dump would
# otherwise slip past assert_reply (which only flags empty/error-keyword text).
rc=$?
[ "$rc" -eq 0 ] || guide_fail "the documented launch command exited non-zero (rc=$rc) -- see the transcript above"
assert_reply "$OUT"
echo "[$AGENT] connection OK"
;;
# ── file-edit: deterministic 2-turn hello.py test (Qwen3.5-2B) ──────────
file-edit)
WORK="$WORKDIR_BASE/${AGENT}"
rm -rf "$WORK"; mkdir -p "$WORK"
OUT1="$LOGS_DIR/${AGENT}-fileedit-turn1.txt"
OUT2="$LOGS_DIR/${AGENT}-fileedit-turn2.txt"
T1='Create a file named hello.py in the current directory whose entire contents are a single line: print("Hello"). Do not run it.'
T2='Run hello.py with python and show me the exact output.'
# The start.py recipe writers + crosscheck must see the repo; run them
# from the repo root BEFORE cd-ing into the scratch work dir. opencode/openclaw
# gate tool approval through their config (prompting by default), so file-edit
# opts them into auto-approval to run edits/commands headlessly.
case "$AGENT" in opencode|openclaw) CONNECT_YOLO=1 ;; esac
parse_connect
crosscheck_contract
# File-edit needs real tools, so we cannot zero them as in connection.
# hermes keeps default tools; openclaw still strips its AGENTS.md/SOUL.md
# bootstrap (the largest prompt chunk) via the 'ci' agent. The scratch work
# dir is empty, so no project context files are auto-loaded either.
case "$AGENT" in
hermes) patch_hermes_tools default ;;
openclaw) patch_openclaw_agent tools ;;
esac
# Drive from inside the work dir so the agent edits files there. All log
# writes use absolute $LOGS_DIR, so cwd does not matter for them.
cd "$WORK" || guide_fail "could not enter work dir $WORK"
invoke_turn() { # $1=outfile $2=continue? $3=prompt
local out="$1" cont="$2" prompt="$3"
case "$AGENT" in
pi)
# Pi continues the previous session with -c; provider/model come from
# the parsed `unsloth start pi` recipe (CONNECT_CMD), not hardcoded here.
if [ "$cont" = "continue" ]; then
invoke_via_connect "$out" -p --continue "$prompt"
else
invoke_via_connect "$out" -p "$prompt"
fi ;;
claude)
# --dangerously-skip-permissions lets headless claude actually use the
# Write/Bash tools (otherwise it blocks on an approval prompt and emits
# nothing). IS_SANDBOX=1 (exported above) authorizes it.
if [ "$cont" = "continue" ]; then
invoke_via_connect "$out" "${CLAUDE_EDIT_FLAGS[@]}" --dangerously-skip-permissions -p --continue "$prompt"
else
invoke_via_connect "$out" "${CLAUDE_EDIT_FLAGS[@]}" --dangerously-skip-permissions -p "$prompt"
fi ;;
codex)
# --dangerously-bypass-approvals-and-sandbox gives codex exec
# workspace-write (default is read-only -> cannot create hello.py) and
# skips the bubblewrap sandbox that the runner lacks.
if [ "$cont" = "continue" ]; then
invoke_via_connect "$out" exec --dangerously-bypass-approvals-and-sandbox resume --last "$prompt"
else
invoke_via_connect "$out" exec --dangerously-bypass-approvals-and-sandbox "$prompt"
fi ;;
opencode) invoke_via_connect "$out" run "$prompt" ;;
hermes) invoke_via_connect "$out" -z "$prompt" ;;
openclaw) CONNECT_CMD_OVERRIDE=openclaw invoke_via_connect "$out" agent --local --agent ci \
--model "unsloth/${UNSLOTH_MODEL_ID}" --message "$prompt" ;;
*) invoke_via_connect "$out" "$prompt" ;;
esac
}
# Turn 1: create hello.py.
invoke_turn "$OUT1" fresh "$T1"
# Fail on a non-zero agent exit before trusting side effects: an agent can
# error out (API/tool failure) yet leave a plausible file/transcript behind,
# which would otherwise slip past the assertions below (mirrors connection).
rc=$?
[ "$rc" -eq 0 ] || { echo "[$AGENT] turn-1 transcript:"; tail -40 "$OUT1" 2>/dev/null || true; \
guide_fail "turn 1 (create hello.py) exited non-zero (rc=$rc)"; }
# Hard assertions on the side effect (the real test): file + content + run.
if [ ! -f hello.py ]; then
echo "[$AGENT] turn-1 transcript:"; tail -40 "$OUT1" 2>/dev/null || true
guide_fail "turn 1 did not create hello.py"
fi
grep -q 'Hello' hello.py || guide_fail "hello.py does not contain 'Hello'"
RUN_OUT="$(python3 hello.py 2>&1 || true)"
[ "$RUN_OUT" = "Hello" ] || guide_fail "python3 hello.py printed '$RUN_OUT', expected exactly 'Hello'"
echo "[$AGENT] turn 1 OK (file created, prints 'Hello')"
# Turn 2: same cwd + session continuation; assert the agent's run output
# contains Hello. Narration drift is WARN-only, missing output is a hard fail.
invoke_turn "$OUT2" continue "$T2"
rc=$?
[ "$rc" -eq 0 ] || { echo "[$AGENT] turn-2 transcript:"; tail -60 "$OUT2" 2>/dev/null || true; \
guide_fail "turn 2 (run hello.py) exited non-zero (rc=$rc)"; }
if grep -q 'Hello' "$OUT2"; then
echo "[$AGENT] turn 2 OK (run output contains 'Hello')"
else
echo "[$AGENT] turn-2 transcript:"; tail -60 "$OUT2" 2>/dev/null || true
guide_fail "turn 2 run/bash output did not contain 'Hello'"
fi
cd "$REPO_ROOT" || true
echo "[$AGENT] file-edit OK"
;;
# ── attribution-ab: Claude Code KV-cache HIT vs MISS ────────────────────
attribution-ab)
[ "$AGENT" = "claude" ] || guide_fail "attribution-ab only applies to claude"
# The llama-server log filename uses the INTERNAL random llama.cpp port,
# not STUDIO_PORT, so we never glob by port: assert-prompt-cache.sh picks
# the newest llama-*.log and we slice it by a byte offset (`mark`) captured
# right before the measured turn, so an earlier turn's reuse can't leak in.
LLAMA_LOG_DIR="${UNSLOTH_LLAMA_LOG_DIR:-$HOME/.unsloth/studio/logs/llama-server}"
export LLAMA_LOG_DIR
parse_connect # prints session env + suppression flags (no ~/.claude write)
crosscheck_contract
PROMPT='Reply with exactly the single word: pong'
# Phase A: the suppression start.py ships (CLAUDE_CODE_ATTRIBUTION_HEADER=0 +
# --exclude-dynamic-system-prompt-sections + --settings overlay) -> expect a
# HIT on the continued turn, since the system-prompt prefix is stable.
invoke_via_connect "$LOGS_DIR/claude-ab-hit-1.txt" -p "$PROMPT" # turn 1 primes
FROM_HIT="$(bash "$CACHE_HELPER" mark)" # offset before turn 2
invoke_via_connect "$LOGS_DIR/claude-ab-hit-2.txt" -p --continue "$PROMPT again"
CACHE_LOG_FROM="$FROM_HIT" bash "$CACHE_HELPER" log HIT
# Phase B: vanilla Claude with the header ENABLED -> expect a MISS. We flip
# the env var to 1 and strip the suppression flags from the launch command
# (without them the dynamic attribution line is included and changes every
# turn, so the shared prefix moves and the KV cache is invalidated, ~90%
# slower). This is session-only: nothing is written to ~/.claude.
CONNECT_ENV_EXTRA='export CLAUDE_CODE_ATTRIBUTION_HEADER=1'
CONNECT_CMD_OVERRIDE="$(printf '%s' "$CONNECT_CMD" \
| sed -E "s/ --exclude-dynamic-system-prompt-sections//; s/ --settings '[^']*'//")"
invoke_via_connect "$LOGS_DIR/claude-ab-miss-1.txt" -p "$PROMPT"
FROM_MISS="$(bash "$CACHE_HELPER" mark)"
invoke_via_connect "$LOGS_DIR/claude-ab-miss-2.txt" -p --continue "$PROMPT again"
CACHE_LOG_FROM="$FROM_MISS" bash "$CACHE_HELPER" log MISS
unset CONNECT_ENV_EXTRA CONNECT_CMD_OVERRIDE
echo "[claude] attribution A/B OK (suppressed HIT, header=1 MISS)"
;;
# ── resume: does a launched agent's session survive exit and resume? ────
# Unlike the other modes, this drives the real LAUNCH path (`unsloth start
# <agent> ...`, the interactive default), not the --no-launch recipe. That
# path relocates each agent's home to a throwaway temp dir wiped on exit, so
# a session cannot be resumed -- unless --persist routes it to the stable
# Unsloth agents dir instead. We run one headless turn per pass and check
# whether the turn left a session in a persistent store (deterministic, no
# reliance on the model recalling anything), for a baseline pass and a
# --persist pass, and assert the expected split for this agent.
resume)
CODEWORD="PLATYPUS7"
T1="Remember this codeword for later: ${CODEWORD}. Reply with just the word OK."
T2="What codeword did I ask you to remember? Reply with just that word."
WORK="$WORKDIR_BASE/${AGENT}-resume"
# STABLE_HOME: the stable dir that --no-launch (and --persist) relocate to.
# Read it from a --no-launch probe (which also writes the agent's config
# there). codex/pi relocate their whole home/HOME here; opencode/claude keep
# their session data in a fixed user dir, so STABLE_HOME stays empty for them.
parse_connect
case "$AGENT" in
codex) STABLE_HOME="$(raw_env CODEX_HOME)" ;;
pi) STABLE_HOME="$(raw_env HOME)" ;;
*) STABLE_HOME="" ;;
esac
# The persistent stores a session would land in if it were NOT wiped. We
# count files here before/after each turn; a positive delta means the
# session persisted (is resumable), zero means it went to a wiped temp dir.
resume_tracked_dirs() {
case "$AGENT" in
codex) printf '%s\n' "$HOME/.codex" ;;
opencode) printf '%s\n' "$HOME/.local/share/opencode" "$HOME/.config/opencode" ;;
claude) printf '%s\n' "$HOME/.claude" ;;
pi) printf '%s\n' "$HOME/.pi" ;;
*) : ;;
esac
[ -n "$STABLE_HOME" ] && printf '%s\n' "$STABLE_HOME"
}
count_session_files() {
local total=0 d n
while IFS= read -r d; do
[ -n "$d" ] && [ -d "$d" ] || continue
n="$(find "$d" -type f 2>/dev/null | wc -l)"; total=$((total + n))
done < <(resume_tracked_dirs)
echo "$total"
}
# The headless first-turn subcommand per agent (mirrors file-edit's map),
# forwarded verbatim through the launch path as passthrough args.
set_t1_cmd() {
case "$AGENT" in
claude) T1_CMD=("${CLAUDE_CONNECT_FLAGS[@]}" -p "$T1") ;;
codex) T1_CMD=(exec "$T1") ;;
opencode) T1_CMD=(run "$T1") ;;
pi) T1_CMD=(-p "$T1") ;;
*) guide_fail "resume mode does not cover agent '$AGENT'" ;;
esac
}
# Run one headless turn through the launch path. $1=outfile, $2="" or
# "--persist", rest = the agent subcommand. --yolo auto-approves so no tool
# prompt can hang; --api-key attaches to the already-served CI model.
launch_turn() {
local out="$1" rflag="$2"; shift 2
local flag=(); [ -n "$rflag" ] && flag=("$rflag")
run_timed "$out" unsloth start "$AGENT" "${flag[@]}" --yolo \
--api-key "$UNSLOTH_API_KEY" "$@"
local rc=$?
redact "$out"
return "$rc"
}
# One pass: fresh work dir, one planting turn, set RESULT to PERSISTED/WIPED
# from the session-store delta. Runs in the main shell (not a command
# substitution) so a hang's guide_fail actually fails the job and the
# progress lines reach the CI log. $1 = "" (baseline) or "--persist".
RESULT=""
run_pass() {
local rflag="$1" label="baseline"
[ -n "$rflag" ] && label="resume"
rm -rf "$WORK"; mkdir -p "$WORK"
set_t1_cmd
local out="$LOGS_DIR/${AGENT}-resume-${label}.txt"
local before after rc
before="$(count_session_files)"
pushd "$WORK" >/dev/null || guide_fail "could not enter work dir $WORK"
launch_turn "$out" "$rflag" "${T1_CMD[@]}"; rc=$?
popd >/dev/null || true
after="$(count_session_files)"
echo "[$AGENT] ${label}: session files ${before} -> ${after} (rc=${rc})"
# The turn must succeed for the delta to mean anything: an agent that writes a
# session file then errors would otherwise be misread as PERSISTED. Mirror the
# file-edit mode and fail the pass on a non-zero launch (the flagship codex recall
# below stays WARN-only, driven by its own launch_turn calls).
[ "$rc" -eq 0 ] || { echo "[$AGENT] ${label} transcript (tail):"; tail -30 "$out" 2>/dev/null || true; \
guide_fail "resume ${label} turn for ${AGENT} exited non-zero (rc=${rc})"; }
if [ "$after" -gt "$before" ]; then RESULT="PERSISTED"; else RESULT="WIPED"; fi
}
run_pass ""; BASELINE="$RESULT"
# Only the temp-dir agents (codex/pi) need the --persist pass to prove the fix.
# opencode/claude persist either way, so the baseline already proves it and a
# second full CPU turn only risks a timeout; skip it for them.
case "$AGENT" in
codex|pi) run_pass "--persist"; RESUME="$RESULT" ;;
*) RESUME="n/a (persists either way)" ;;
esac
# Expected: codex/pi relocate their whole home to the temp dir, so a plain
# launch is WIPED and only --persist PERSISTS. opencode/claude keep their
# session data in a fixed user dir, so the baseline already PERSISTS.
case "$AGENT" in
codex|pi) EXPECT_BASELINE="WIPED" ;;
opencode|claude) EXPECT_BASELINE="PERSISTED" ;;
esac
echo "──────────────────────────────────────────────"
echo "[$AGENT] RESUME EXPERIMENT"
echo " baseline (unsloth start ${AGENT}): ${BASELINE} (expected ${EXPECT_BASELINE})"
echo " with --persist (unsloth start ${AGENT} --persist): ${RESUME}"
echo "──────────────────────────────────────────────"
[ "$BASELINE" = "$EXPECT_BASELINE" ] \
|| guide_fail "baseline resume behavior for ${AGENT} was ${BASELINE}, expected ${EXPECT_BASELINE}"
case "$AGENT" in
codex|pi)
[ "$RESUME" = "PERSISTED" ] \
|| guide_fail "--persist did not persist ${AGENT}'s session (got ${RESUME}); the session dir is still not stable" ;;
esac
# Flagship behavioral proof (codex only, WARN-only): after a --persist plant,
# resume the session and check the model actually recalls the codeword. A
# miss is not a failure (the CI model is small); the mechanism gate above is
# the real assertion.
if [ "$AGENT" = "codex" ]; then
rm -rf "$WORK"; mkdir -p "$WORK"
( cd "$WORK" && launch_turn "$LOGS_DIR/codex-resume-plant.txt" "--persist" exec "$T1" ) || true
( cd "$WORK" && launch_turn "$LOGS_DIR/codex-resume-recall.txt" "--persist" exec resume --last "$T2" ) || true
if grep -q "$CODEWORD" "$LOGS_DIR/codex-resume-recall.txt" 2>/dev/null; then
echo "[codex] behavioral recall HIT: resumed session remembered ${CODEWORD}"
else
echo "::warning::[codex] behavioral recall MISS (small CI model); mechanism gate still passed"
fi
fi
echo "[$AGENT] resume OK"
;;
*)
echo "agent-guides-drive.sh: unknown mode '$MODE'" >&2
exit 2
;;
esac

View file

@ -1,108 +0,0 @@
#!/usr/bin/env bash
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
#
# Install one coding-agent CLI for the Local Agent Guides CI. Isolated as
# failure class (b) "agent package install failed": npm/curl flakiness here
# is the single biggest source of false reds, so installs retry with
# backoff and the only ::error:: this script can emit is class (b). The
# install recipes mirror the install_hint strings in
# unsloth_cli/commands/start.py at HEAD.
#
# Usage: agent-guides-install.sh <agent>
# agent in: claude codex hermes openclaw opencode pi
set -uo pipefail
AGENT="${1:?usage: agent-guides-install.sh <agent>}"
mkdir -p logs
LOG="logs/install-${AGENT}.log"
install_fail() {
echo "::error::[agent install failed] agent=${AGENT}: $* (class (b): the agent CLI did not install; not a server or guide problem)." >&2
echo "---- tail $LOG ----" >&2
tail -60 "$LOG" 2>/dev/null || true
exit 1
}
# npm registry flakiness is common in CI; retry 3x with linear backoff.
# Extra npm flags may precede the package (e.g. npm_retry --ignore-scripts pkg).
npm_retry() {
local i
for i in 1 2 3; do
if npm install -g "$@" >> "$LOG" 2>&1; then
return 0
fi
echo "[install] npm install -g $* attempt $i failed; backing off $((i * 10))s" | tee -a "$LOG"
sleep "$((i * 10))"
done
return 1
}
# curl|bash installers, retried at the curl layer. We download to a temp file
# first and only execute on a fully successful fetch, so a truncated download
# (network hiccup mid-stream) can never run a half-written installer.
curl_bash() {
local url="$1"; shift
local i tmp
tmp="$(mktemp)"
for i in 1 2 3; do
if curl -fsSL --retry 3 --retry-delay 5 "$url" -o "$tmp" 2>>"$LOG" \
&& bash "$tmp" "$@" >> "$LOG" 2>&1; then
rm -f "$tmp"
return 0
fi
echo "[install] curl|bash $url attempt $i failed; backing off $((i * 10))s" | tee -a "$LOG"
sleep "$((i * 10))"
done
rm -f "$tmp"
return 1
}
echo "[install] agent=$AGENT (log=$LOG)"
case "$AGENT" in
claude)
# start.py install_hint: curl -fsSL https://claude.ai/install.sh | bash
curl_bash "https://claude.ai/install.sh" || install_fail "claude installer failed"
# The installer drops the binary under ~/.local/bin.
echo "$HOME/.local/bin" >> "$GITHUB_PATH"
;;
codex)
# start.py install_hint: npm install -g @openai/codex
npm_retry "@openai/codex" || install_fail "npm install -g @openai/codex failed"
;;
opencode)
# start.py install_hint: npm install -g opencode-ai
npm_retry "opencode-ai" || install_fail "npm install -g opencode-ai failed"
;;
openclaw)
# start.py install_hint: curl -fsSL https://openclaw.ai/install.sh | bash
# npm is the more deterministic path in CI and matches the agent's docs;
# fall back to the start.py curl installer if the npm tag is missing.
if ! npm_retry "openclaw@latest"; then
curl_bash "https://openclaw.ai/install.sh" || install_fail "openclaw install failed (npm + curl)"
echo "$HOME/.local/bin" >> "$GITHUB_PATH"
fi
;;
hermes)
# start.py install_hint:
# curl -fsSL .../NousResearch/hermes-agent/main/scripts/install.sh | bash
curl_bash "https://raw.githubusercontent.com/NousResearch/hermes-agent/main/scripts/install.sh" \
--non-interactive --skip-setup --skip-browser --no-skills \
|| install_fail "hermes installer failed"
echo "$HOME/.local/bin" >> "$GITHUB_PATH"
;;
pi)
# start.py install_hint: npm install -g --ignore-scripts @earendil-works/pi-coding-agent
# (--ignore-scripts matches Pi's documented recipe; exercising the exact hint
# catches guide drift). The CLI moved from the now-deprecated @mariozechner
# scope to @earendil-works (the old scope is frozen, so installing it would
# test a stale Pi against the API).
npm_retry --ignore-scripts "@earendil-works/pi-coding-agent" \
|| install_fail "npm install -g --ignore-scripts @earendil-works/pi-coding-agent failed"
;;
*)
install_fail "unknown agent '$AGENT'"
;;
esac
echo "[install] OK for $AGENT"

View file

@ -2,7 +2,7 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
#
# Assert Unsloth installed a llama.cpp that loads and runs on THIS macOS. Tests
# Assert Studio installed a llama.cpp that loads and runs on THIS macOS. Tests
# the contract that matters (binaries load and their minimum-OS is <= this host)
# instead of the old "did install.sh fall back to a source build?" grep, since a
# source build with a correct deployment target is a valid outcome.

View file

@ -1,238 +0,0 @@
#!/usr/bin/env bash
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
#
# Prompt-cache (KV-cache prefix reuse) detection, two strategies in one helper:
#
# mode=api A 2-turn /v1/chat/completions probe. Turn 2 prepends turn 1 +
# its reply, so the shared prefix must be served from llama.cpp's
# KV cache. Asserts usage.prompt_tokens_details.cached_tokens > 0
# on turn 2. This is the OpenAI-dialect server cache sanity.
# WHY this works on chat completions: the chat path forwards
# llama-server's real cached_tokens through
# studio/backend/routes/inference.py:482-489 (_prompt_tokens_details)
# into prompt_tokens_details (inference.py:519).
#
# mode=log Read the llama-server log and decide HIT vs MISS from the
# prompt-reprocessing trace. WHY the log (not the API field):
# the Anthropic /v1/messages path builds AnthropicUsage(
# input_tokens=..., output_tokens=...) at inference.py:8787-8790
# / :8829-8832 and NEVER sets cache_read_input_tokens, which
# therefore stays at its model default of 0
# (studio/backend/models/inference.py:1655). So an Anthropic-path
# client (Claude Code, OpenClaw is openai-completions but Claude
# Code is the canonical Anthropic agent) can get a real KV-cache
# hit that the API usage field reports as 0. The only ground
# truth for the Anthropic path is the llama-server log.
#
# Log location (verified): studio/backend/core/inference/llama_cpp.py:4363-4365
# _swa_cache_path().parent/"logs"/"llama-server"/llama-<ts>[label]-port-<P>[-try<N>].log
# _swa_cache_path() => $UNSLOTH_STUDIO_HOME|$STUDIO_HOME or ~/.unsloth/studio
# (llama_cpp.py:337-340). So default: ~/.unsloth/studio/logs/llama-server/.
#
# <P> is the INTERNAL llama-server port (self._find_free_port(),
# llama_cpp.py:3489 / :4641) -- a RANDOM port, NOT the Unsloth port. So we must
# NOT filter the log glob by STUDIO_PORT (the brief's `port-<STUDIO_PORT>`
# glob would never match). We pick the newest llama-*.log instead.
#
# Usage:
# assert-prompt-cache.sh api BASE_URL API_KEY
# assert-prompt-cache.sh log EXPECT # EXPECT = HIT | MISS
# # reads MARKER_BEFORE/MARKER_AFTER
# # byte offsets from env (see below)
# assert-prompt-cache.sh mark # print current log size to stdout
# # (use to bracket a turn)
#
# Env for mode=log:
# LLAMA_LOG_DIR override the log dir (default ~/.unsloth/studio/logs/llama-server)
# CACHE_LOG_FROM byte offset to start scanning the newest log from (so we
# only look at the trace produced by THIS turn). Default 0.
#
# Exit codes: 0 = assertion held; 1 = assertion failed (::error:: emitted).
set -uo pipefail
MODE="${1:?usage: assert-prompt-cache.sh api|log|mark ...}"
# ---------------------------------------------------------------------------
# Locate the newest llama-server log. Shared by mark + log modes.
# ---------------------------------------------------------------------------
_default_log_dir() {
local home="${UNSLOTH_STUDIO_HOME:-${STUDIO_HOME:-}}"
if [ -n "$home" ]; then
echo "${home%/}/logs/llama-server"
else
echo "${HOME}/.unsloth/studio/logs/llama-server"
fi
}
_newest_log() {
local dir="${LLAMA_LOG_DIR:-$(_default_log_dir)}"
[ -d "$dir" ] || return 1
# Newest by mtime among llama-*.log (covers both `llama-<ts>-port-<P>.log`
# and the retry form `llama-<ts><label>-port-<P>-try<N>.log`). Filenames are
# tool-generated timestamps, so ls -t is safe here.
# shellcheck disable=SC2012
ls -1t "$dir"/llama-*.log 2>/dev/null | head -1
}
case "$MODE" in
# -------------------------------------------------------------------------
# mark: emit the current byte size of the newest llama log so a caller can
# scan only the slice a single turn produced (set CACHE_LOG_FROM to it).
# -------------------------------------------------------------------------
mark)
log="$(_newest_log || true)"
if [ -n "$log" ] && [ -f "$log" ]; then
wc -c < "$log" | tr -d ' '
else
echo 0
fi
exit 0
;;
# -------------------------------------------------------------------------
# api: 2-turn /v1/chat/completions, assert turn-2 cached_tokens > 0.
# -------------------------------------------------------------------------
api)
BASE_URL="${2:?usage: assert-prompt-cache.sh api BASE_URL API_KEY}"
API_KEY="${3:?usage: assert-prompt-cache.sh api BASE_URL API_KEY}"
# A deliberately long, fixed system prompt makes the shared prefix big so a
# KV-cache hit is unambiguous (cached_tokens grows with the reused prefix).
SYS='You are a meticulous assistant. Always answer concisely and correctly. This is a fixed system preamble that exists only to create a large, identical prompt prefix across both turns so the KV cache has something substantial to reuse on the second request. Do not mention this preamble.'
turn1_body() {
jq -n --arg sys "$SYS" '{
model: "default",
messages: [
{role:"system", content:$sys},
{role:"user", content:"What is the capital of France?"}
],
temperature: 0.0, seed: 3407, max_tokens: 40, stream: false,
enable_thinking: false
}'
}
echo "[cache/api] turn 1 (prime the KV cache)"
R1="$(curl -fs -X POST "${BASE_URL}/v1/chat/completions" \
-H "Authorization: Bearer ${API_KEY}" -H 'content-type: application/json' \
--max-time 240 -d "$(turn1_body)")" || {
echo "::error::[cache/api] turn-1 /v1/chat/completions request failed. Unsloth server/API regression."
exit 1
}
A1="$(echo "$R1" | jq -r '.choices[0].message.content // ""')"
turn2_body() {
jq -n --arg sys "$SYS" --arg a1 "$A1" '{
model: "default",
messages: [
{role:"system", content:$sys},
{role:"user", content:"What is the capital of France?"},
{role:"assistant", content:$a1},
{role:"user", content:"And the capital of Germany?"}
],
temperature: 0.0, seed: 3407, max_tokens: 40, stream: false,
enable_thinking: false
}'
}
echo "[cache/api] turn 2 (expect cached_tokens > 0)"
R2="$(curl -fs -X POST "${BASE_URL}/v1/chat/completions" \
-H "Authorization: Bearer ${API_KEY}" -H 'content-type: application/json' \
--max-time 240 -d "$(turn2_body)")" || {
echo "::error::[cache/api] turn-2 /v1/chat/completions request failed. Unsloth server/API regression."
exit 1
}
CACHED="$(echo "$R2" | jq -r '.usage.prompt_tokens_details.cached_tokens // 0')"
PROMPT_TOK="$(echo "$R2" | jq -r '.usage.prompt_tokens // 0')"
echo "[cache/api] turn-2 usage: prompt_tokens=${PROMPT_TOK} cached_tokens=${CACHED}"
if [ -z "$CACHED" ] || ! [ "$CACHED" -gt 0 ] 2>/dev/null; then
echo "::error::[cache/api] turn-2 usage.prompt_tokens_details.cached_tokens=${CACHED}, expected > 0. The server is not surfacing llama.cpp KV-cache hits on /v1/chat/completions. Check studio/backend/routes/inference.py:482-489 (_prompt_tokens_details) and :519. Full turn-2 usage:"
echo "$R2" | jq -c '.usage' 2>/dev/null || echo "$R2"
exit 1
fi
echo "[cache/api] PASS server cache sanity (cached_tokens=${CACHED} > 0)"
exit 0
;;
# -------------------------------------------------------------------------
# log: classify the newest llama-server log (from CACHE_LOG_FROM bytes on)
# as HIT or MISS and compare to EXPECT.
# -------------------------------------------------------------------------
log)
EXPECT="${2:?usage: assert-prompt-cache.sh log HIT|MISS}"
FROM="${CACHE_LOG_FROM:-0}"
log="$(_newest_log || true)"
if [ -z "$log" ] || [ ! -f "$log" ]; then
echo "::error::[cache/log] no llama-server log under ${LLAMA_LOG_DIR:-$(_default_log_dir)}. Cannot read KV-cache trace. (Path contract: studio/backend/core/inference/llama_cpp.py:4363-4365.)"
exit 1
fi
echo "[cache/log] reading $log from byte $FROM"
# Scan only the slice produced after FROM.
slice="$(tail -c "+$((FROM + 1))" "$log" 2>/dev/null || cat "$log")"
# ---- HIT detectors (most-specific first) -----------------------------
# 1. Modern + legacy "re-used N tokens" / "reused N" (N>0). Primary signal
# per the design brief.
reused_n="$(printf '%s\n' "$slice" \
| grep -aoiE 're-?used[^0-9]*([0-9]+)' \
| grep -aoE '[0-9]+' | sort -rn | head -1 || true)"
# 2. "kv cache rm [START, end)" with START>0 => prefix [0,START) reused.
cache_rm_start="$(printf '%s\n' "$slice" \
| grep -aoiE 'kv cache rm \[[0-9]+' \
| grep -aoE '[0-9]+' | sort -rn | head -1 || true)"
# 3. "n_past = N" with N>0 after a prompt-processing line (prefix kept).
n_past_n="$(printf '%s\n' "$slice" \
| grep -aoiE 'n_past[^0-9]*([0-9]+)' \
| grep -aoE '[0-9]+' | sort -rn | head -1 || true)"
# 4. tokens_cached / tokens from cache (some builds).
tok_cached="$(printf '%s\n' "$slice" \
| grep -aoiE 'tokens_cached[^0-9]*([0-9]+)' \
| grep -aoE '[0-9]+' | sort -rn | head -1 || true)"
# ---- MISS detectors --------------------------------------------------
# Explicit forced full re-processing (SWA / recurrent) or kv cache rm [0,.
forced_full=0
if printf '%s\n' "$slice" | grep -aqiE 'forcing full prompt re-?processing|kv cache rm \[0,'; then
forced_full=1
fi
HIT=0
why=""
if [ -n "$reused_n" ] && [ "$reused_n" -gt 0 ] 2>/dev/null; then
HIT=1; why="re-used=$reused_n"
elif [ -n "$cache_rm_start" ] && [ "$cache_rm_start" -gt 0 ] 2>/dev/null; then
HIT=1; why="kv-cache-rm-start=$cache_rm_start"
elif [ -n "$tok_cached" ] && [ "$tok_cached" -gt 0 ] 2>/dev/null; then
HIT=1; why="tokens_cached=$tok_cached"
elif [ "$forced_full" = "0" ] && [ -n "$n_past_n" ] && [ "$n_past_n" -gt 0 ] 2>/dev/null; then
# n_past>0 is the weakest signal; only trust it if nothing forced a full
# reprocess. (On a cold slot n_past tracks total processed, so it is a
# last-resort fallback per the brief.)
HIT=1; why="n_past=$n_past_n(fallback)"
fi
[ "$HIT" = "1" ] || why="${why:-no-reuse-markers (forced_full=$forced_full)}"
OBSERVED="MISS"; [ "$HIT" = "1" ] && OBSERVED="HIT"
echo "[cache/log] observed=$OBSERVED expected=$EXPECT ($why)"
if [ "$OBSERVED" != "$EXPECT" ]; then
echo "::error::[cache/log] KV-cache observed=$OBSERVED but expected=$EXPECT ($why). See the attribution A/B note in the workflow."
echo "---- llama-server log slice (last 60 lines) ----"
printf '%s\n' "$slice" | tail -60
exit 1
fi
echo "[cache/log] PASS ($OBSERVED == $EXPECT)"
exit 0
;;
*)
echo "::error::unknown mode '$MODE' (want api|log|mark)"
exit 1
;;
esac

View file

@ -1 +0,0 @@
You are a helpful assistant in a CI connectivity check. Answer the user directly in plain text. Do not use any tools, do not take any actions, and do not explain. Just reply with the answer.

View file

@ -1 +0,0 @@
You are a coding assistant running non-interactively in a CI smoke test. Use the available file-editing and shell tools to complete the user's request directly and concisely. Do not ask questions or explain; just do the task.

View file

@ -1,9 +1,7 @@
#!/usr/bin/env bash
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
#
# Download a single file from a Hugging Face repo with a stall-retry
# watchdog. Used by the Unsloth CI workflows so a hung hf-xet transfer
# watchdog. Used by the Studio CI workflows so a hung hf-xet transfer
# kills + retries instead of silently consuming the job's timeout.
#
# Usage: hf-download-with-retry.sh REPO FILE LOCAL_DIR
@ -35,7 +33,7 @@ REPO="${1:?usage: hf-download-with-retry.sh REPO FILE [LOCAL_DIR]}"
FILE="${2:?usage: hf-download-with-retry.sh REPO FILE [LOCAL_DIR]}"
# LOCAL_DIR is optional. If empty, hf falls back to HF_HUB_CACHE
# (~/.cache/huggingface/hub) which is the desired path for callers
# that populate HF_HOME for a downstream Unsloth model load.
# that populate HF_HOME for a downstream Studio model load.
LOCAL_DIR="${3:-}"
# Stall threshold per attempt, in seconds. Override with

View file

@ -1,70 +0,0 @@
#!/usr/bin/env bash
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
set -euo pipefail
port="${1:?usage: $0 PORT BROWSER [CHANNEL]}"
browser="${2:?usage: $0 PORT BROWSER [CHANNEL]}"
channel="${3:-}"
slug="$browser${channel:+-$channel}"
artifact_dir="logs/playwright-permissions-$slug"
server_log="logs/studio-permissions-$slug.log"
studio_home="${UNSLOTH_STUDIO_HOME:-$HOME/.unsloth/studio}"
set --
if [ -n "${STUDIO_PERMISSION_FRONTEND:-}" ]; then
set -- -f "$STUDIO_PERMISSION_FRONTEND"
fi
mkdir -p "$artifact_dir"
# Wipe (not reset-password): the boot below must re-seed a fresh .bootstrap_password.
rm -rf "$studio_home/auth"
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$port" "$@" \
>"$server_log" 2>&1 &
studio_pid=$!
cleanup() {
kill "$studio_pid" 2>/dev/null || true
wait "$studio_pid" 2>/dev/null || true
}
trap cleanup EXIT
healthy=0
for _ in $(seq 1 180); do
if curl -fs "http://127.0.0.1:$port/api/health" >/dev/null; then
healthy=1
break
fi
if ! kill -0 "$studio_pid" 2>/dev/null; then
tail -100 "$server_log" || true
exit 1
fi
sleep 1
done
if [ "$healthy" -ne 1 ]; then
tail -100 "$server_log" || true
exit 1
fi
old_password=$(cat "$studio_home/auth/.bootstrap_password")
new_password="CIPerm-$(python -c 'import secrets; print(secrets.token_urlsafe(16))')"
if [ "${GITHUB_ACTIONS:-}" = "true" ]; then
echo "::add-mask::$old_password"
echo "::add-mask::$new_password"
fi
export BASE_URL="http://127.0.0.1:$port"
export STUDIO_OLD_PW="$old_password"
export STUDIO_NEW_PW="$new_password"
export STUDIO_UI_STRICT=1
export STUDIO_UI_PERMISSION_ONLY=1
export STUDIO_UI_WALL_TIMEOUT_S=240
export STUDIO_PLAYWRIGHT_BROWSER="$browser"
export PW_ART_DIR="$artifact_dir"
if [ -n "$channel" ]; then
export STUDIO_PLAYWRIGHT_CHANNEL="$channel"
else
unset STUDIO_PLAYWRIGHT_CHANNEL || true
fi
python tests/studio/playwright_chat_ui.py

View file

@ -1,172 +0,0 @@
#!/usr/bin/env bash
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
#
# Boot `unsloth run --disable-tools` in the background, wait for it to be
# healthy, parse the minted API key from the banner, and resolve the
# /v1/models id. Exports everything downstream steps need into $GITHUB_ENV
# (or prints it when run outside Actions). Factored out of the workflow so
# the failure-isolation logic lives in one shellcheck-clean place.
#
# Usage:
# serve-unsloth-run.sh --model REPO --gguf-variant VAR --port PORT \
# [--gguf-file PATH] [--extra "--seed 3407 --temp 0"] \
# [--log-dir logs] [--health-timeout 300]
#
# Why a helper and not inline YAML
# --------------------------------
# * Every `unsloth run` invocation here is the *Unsloth server* under test.
# A failure to come up healthy is class (a) "server/API regression" and
# must be reported with a distinct `::error::` BEFORE any agent runs.
# * The banner is the documented contract a human copies from. We parse the
# exact `API Key:` line printed by unsloth_cli/commands/studio.py
# (` API Key: <key>` non-silent, `API Key: <key>` silent) so a
# silent change to that line is also caught.
# * `unsloth run` re-execs into the studio venv ($STUDIO_HOME/unsloth_studio),
# so in CI after `install.sh --local` it runs the PR's repo code.
#
# Outputs written to $GITHUB_ENV (and echoed):
# UNSLOTH_API_KEY the sk-unsloth-* key minted on the banner
# UNSLOTH_STUDIO_URL http://127.0.0.1:<PORT> (so `unsloth start`
# finds THIS server, not the hardcoded :8888)
# UNSLOTH_BASE_URL same as UNSLOTH_STUDIO_URL (alias for clarity)
# UNSLOTH_MODEL_ID the canonical id reported by /v1/models
# UNSLOTH_SERVER_PID pid of the backgrounded `unsloth run`
# UNSLOTH_LLAMA_LOG_DIR ~/.unsloth/studio/logs/llama-server
set -uo pipefail
# ── arg parse ────────────────────────────────────────────────────────────
MODEL=""
GGUF_VARIANT=""
GGUF_FILE=""
PORT=""
EXTRA=""
LOG_DIR="logs"
HEALTH_TIMEOUT="300"
while [ "$#" -gt 0 ]; do
case "$1" in
--model) MODEL="$2"; shift 2 ;;
--gguf-variant) GGUF_VARIANT="$2"; shift 2 ;;
--gguf-file) GGUF_FILE="$2"; shift 2 ;;
--port) PORT="$2"; shift 2 ;;
--extra) EXTRA="$2"; shift 2 ;;
--log-dir) LOG_DIR="$2"; shift 2 ;;
--health-timeout) HEALTH_TIMEOUT="$2"; shift 2 ;;
*) echo "serve-unsloth-run.sh: unknown arg '$1'" >&2; exit 2 ;;
esac
done
[ -n "$PORT" ] || { echo "serve-unsloth-run.sh: --port is required" >&2; exit 2; }
if [ -z "$MODEL" ] && [ -z "$GGUF_FILE" ]; then
echo "serve-unsloth-run.sh: one of --model or --gguf-file is required" >&2
exit 2
fi
mkdir -p "$LOG_DIR"
SERVER_LOG="$LOG_DIR/unsloth-run-${PORT}.log"
BASE_URL="http://127.0.0.1:${PORT}"
STUDIO_HOME_DIR="${STUDIO_HOME:-$HOME/.unsloth/studio}"
LLAMA_LOG_DIR="${STUDIO_HOME_DIR}/logs/llama-server"
# Emit a key=value pair to $GITHUB_ENV when set, always echo for local runs.
emit() {
echo "$1=$2"
if [ -n "${GITHUB_ENV:-}" ]; then
echo "$1=$2" >> "$GITHUB_ENV"
fi
}
server_fail() {
echo "::error::Unsloth server/API regression: $*" >&2
echo "---- last 200 lines of $SERVER_LOG ----" >&2
tail -200 "$SERVER_LOG" 2>/dev/null || true
exit 1
}
# ── port collision guard ─────────────────────────────────────────────────
# A leftover listener (or a parallel matrix cell that wandered onto our port)
# would make us attach to the wrong server and mask a real regression. Fail
# fast instead.
if command -v ss >/dev/null 2>&1; then
if ss -tln 2>/dev/null | grep -q ":${PORT}\b"; then
server_fail "port ${PORT} already has a listener before we started (collision)"
fi
fi
# ── build the command ────────────────────────────────────────────────────
# `unsloth run` == alias of `unsloth studio run`. --disable-tools is REQUIRED
# (passthrough mode) so the agent's own tools relay instead of the server's.
# --no-cloudflare keeps us off the network (loopback bind, no tunnel attempt).
CMD=(unsloth run -H 127.0.0.1 -p "$PORT" --disable-tools --no-cloudflare)
if [ -n "$GGUF_FILE" ]; then
CMD+=(--model "$GGUF_FILE")
else
CMD+=(--model "$MODEL")
[ -n "$GGUF_VARIANT" ] && CMD+=(--gguf-variant "$GGUF_VARIANT")
fi
# Determinism knobs + any caller passthrough (e.g. --seed 3407 --temp 0).
# shellcheck disable=SC2206 # intentional word-split of caller-controlled flags
[ -n "$EXTRA" ] && CMD+=($EXTRA)
echo "[serve] launching: ${CMD[*]}"
echo "[serve] server log: $SERVER_LOG"
# Run detached, no controlling TTY (setsid avoids any TTY-prompt hang and
# detaches from this step's process group so the job's teardown is clean).
setsid "${CMD[@]}" > "$SERVER_LOG" 2>&1 < /dev/null &
SERVER_PID=$!
emit UNSLOTH_SERVER_PID "$SERVER_PID"
# ── wait for /api/health == healthy ──────────────────────────────────────
HEALTHY=0
for _ in $(seq 1 "$HEALTH_TIMEOUT"); do
if ! kill -0 "$SERVER_PID" 2>/dev/null; then
server_fail "process exited before becoming healthy (pid $SERVER_PID)"
fi
if curl -fs "${BASE_URL}/api/health" -o "$LOG_DIR/health-${PORT}.json" 2>/dev/null; then
if jq -e '.status == "healthy"' "$LOG_DIR/health-${PORT}.json" >/dev/null 2>&1; then
HEALTHY=1
break
fi
fi
sleep 1
done
[ "$HEALTHY" = "1" ] || server_fail "did not report /api/health healthy within ${HEALTH_TIMEOUT}s"
echo "[serve] /api/health healthy"
# ── parse the API key from the banner ────────────────────────────────────
# Match both the non-silent " API Key: <key>" and silent "API Key: <key>"
# forms. We do NOT trust a fixed column count; we take the sk-unsloth-* token.
API_KEY=""
for _ in $(seq 1 30); do
API_KEY="$(grep -aoE 'sk-unsloth-[A-Za-z0-9_-]+' "$SERVER_LOG" 2>/dev/null | head -1 || true)"
[ -n "$API_KEY" ] && break
sleep 1
done
if [ -z "$API_KEY" ]; then
# Fallback: take whatever follows an "API Key:" label, in case the key
# prefix scheme changes. Still a parse-fragility guard, not silent.
API_KEY="$(grep -aE 'API Key:' "$SERVER_LOG" 2>/dev/null \
| sed -E 's/.*API Key:[[:space:]]*//' | head -1 || true)"
fi
[ -n "$API_KEY" ] || server_fail "could not parse an API key from the banner (banner-parse fragility -- check the 'API Key:' line in unsloth_cli/commands/studio.py)"
echo "::add-mask::${API_KEY}"
emit UNSLOTH_API_KEY "$API_KEY"
# ── resolve /v1/models id ────────────────────────────────────────────────
if ! curl -fs "${BASE_URL}/v1/models" \
-H "Authorization: Bearer ${API_KEY}" -o "$LOG_DIR/models-${PORT}.json" 2>/dev/null; then
server_fail "/v1/models did not respond (or rejected the banner key)"
fi
MODEL_ID="$(jq -r '.data[0].id // empty' "$LOG_DIR/models-${PORT}.json" 2>/dev/null || true)"
[ -n "$MODEL_ID" ] || server_fail "/v1/models returned no model id (model failed to load)"
echo "[serve] resolved model id: $MODEL_ID"
emit UNSLOTH_MODEL_ID "$MODEL_ID"
emit UNSLOTH_STUDIO_URL "$BASE_URL"
emit UNSLOTH_BASE_URL "$BASE_URL"
emit UNSLOTH_LLAMA_LOG_DIR "$LLAMA_LOG_DIR"
echo "[serve] server is up: ${BASE_URL} (model ${MODEL_ID})"

View file

@ -7,7 +7,7 @@
#
# Why a separate workflow:
# - studio-backend-ci.yml's "Repo tests (CPU)" job already auto-discovers
# tests/ minus tests/qlora, tests/saving, tests/utils, tests/sh. The 17
# tests/ minus tests/qlora, tests/saving, tests/utils, tests/sh. The 16
# Bucket-A tests below live inside those --ignore dirs (CPU-runnable but
# historically excluded with their GPU siblings); pulling them out into
# a sibling job keeps the existing 760-passed baseline stable while we
@ -209,7 +209,7 @@ jobs:
'peft>=0.18,<0.20' 'accelerate>=0.34,<2' \
ipython
# torchvision: unsloth_zoo.vision_utils imports it at module scope.
pip install --index-url https://download.pytorch.org/whl/cpu --extra-index-url https://pypi.org/simple \
pip install --index-url https://download.pytorch.org/whl/cpu \
'torch>=2.4,<2.11' 'torchvision<0.26'
# transformers + trl from the matrix combo.
pip install "$RESOLVED_TRANSFORMERS_SPEC"
@ -268,13 +268,6 @@ jobs:
tests/saving/test_save_shell_injection.py \
tests/saving/test_patch_saving_none_tokenizer.py \
tests/saving/test_fix_sentencepiece_gguf_robustness.py \
tests/saving/test_fix_sentencepiece_tokenizer_guard.py \
tests/saving/test_compressed_export_schemes.py \
tests/saving/test_export_api_surface.py \
tests/saving/test_export_dispatch.py \
tests/saving/test_imatrix_export.py \
tests/saving/test_gguf_single_pass_export.py \
tests/saving/test_offline_gguf_vlm_tokenizer_7481.py \
tests/utils/test_attention_masks.py \
tests/utils/test_trunc_normal_patch.py \
tests/python/test_fast_language_model_text_only.py
@ -360,23 +353,14 @@ jobs:
tests/saving/test_save_shell_injection.py \
tests/saving/test_patch_saving_none_tokenizer.py \
tests/saving/test_fix_sentencepiece_gguf_robustness.py \
tests/saving/test_fix_sentencepiece_tokenizer_guard.py \
tests/saving/test_compressed_export_schemes.py \
tests/saving/test_export_api_surface.py \
tests/saving/test_export_dispatch.py \
tests/saving/test_imatrix_export.py \
tests/saving/test_gguf_single_pass_export.py \
tests/saving/test_offline_gguf_vlm_tokenizer_7481.py \
tests/utils/test_attention_masks.py \
tests/utils/test_trunc_normal_patch.py \
tests/python/test_fast_language_model_text_only.py \
tests/test_bad_mappings_redirect.py \
tests/test_prefetch_snapshot_scope.py \
tests/test_gemma_2b_mapper_key.py \
tests/test_raw_text_json_loading.py
# test_run_attention_flash_varlen_receives_window_and_softcap was deselected
# until attention_dispatch.py predefined flash_attn_varlen_func as None; it
# monkeypatches that name, so it no longer needs flash_attn on this runner.
--deselect 'tests/utils/test_attention_masks.py::test_run_attention_flash_varlen_receives_window_and_softcap'
# The deselected test monkeypatches flash_attn_varlen_func, which is
# only bound on the module when `flash_attn` is importable. flash_attn
# requires CUDA + dev toolchain, which the CPU-only ubuntu-latest
# runner does not have. The other Bucket-A tests pass cleanly.
- name: unsloth_zoo @ ${{ env.UNSLOTH_ZOO_REF }} — full pytest (CPU)
# 106 of 111 test_* in unsloth_zoo are CPU-only. The two CUDA-skip
@ -2130,7 +2114,7 @@ jobs:
pip show unsloth_zoo
echo "::endgroup::"
echo "Consolidated job done. Coverage:"
echo " - 17 unsloth Bucket-A tests under tests/saving/ + tests/utils/"
echo " - 16 unsloth Bucket-A tests under tests/saving/ + tests/utils/"
echo " - unsloth_zoo @ ${UNSLOTH_ZOO_REF} pytest tests/ (5 GPU cases deselected)"
echo " - unsloth_zoo.compiler.test_apply_fused_lm_head"
@ -2182,7 +2166,7 @@ jobs:
python -m pip install --upgrade pip
# Match the matrix job's torch path so unsloth_zoo's
# `import torch` resolves to the same CPU build.
pip install --index-url https://download.pytorch.org/whl/cpu --extra-index-url https://pypi.org/simple \
pip install --index-url https://download.pytorch.org/whl/cpu \
'torch>=2.4,<2.11' 'torchvision<0.26'
pip install \
'numpy<3' protobuf sentencepiece \
@ -2220,13 +2204,12 @@ jobs:
pip install -e "$RUNNER_TEMP/unsloth-zoo" --no-deps
pip show unsloth_zoo
- name: llama.cpp install via unsloth_zoo.llama_cpp + CLI `--help` smoke
- name: llama.cpp install via unsloth_zoo.llama_cpp + `llama-cli --help` smoke
# Exercise the canonical `unsloth_zoo.llama_cpp.install_llama_cpp`
# flow that GGUF export uses at runtime: clone ggml-org/llama.cpp
# into ~/.unsloth/llama.cpp, build the LLAMA_CPP_TARGETS list
# (llama-quantize, llama-cli, llama-mtmd-cli, llama-gguf-split,
# llama-server) via cmake, then run `--help` on whichever CLI
# inference binary the build actually produced.
# llama-server) via cmake, then run `llama-cli --help`.
#
# This replaces the previous "download upstream prebuilt zip"
# approach, which silently exited 0 with the message
@ -2235,18 +2218,6 @@ jobs:
# matched their current asset names). The build path is the same
# one Unsloth users hit in production via `model.save_pretrained_gguf`.
#
# We do NOT hard-require `llama-cli` specifically: upstream
# ggml-org/llama.cpp moved the cli/server/ui targets behind the
# `LLAMA_BUILD_SERVER` cmake option (tools/CMakeLists.txt) and the
# set of binaries that survive a given checkout drifts over time
# (e.g. a recent build root shipped llama-server + llama-quantize
# + llama-diffusion-cli but no llama-cli). The durable contract is
# "install_llama_cpp produced a working CLI inference binary AND a
# working quantizer", so we --help-probe the first of
# llama-cli / llama-mtmd-cli / llama-server that exists. If a
# future llama.cpp restores llama-cli it is first in the list and
# is preferred, so this stays backwards compatible.
#
# Wall-time budget: ~3-5 min cold, dominated by cmake build of
# 5 targets on the runner's 4 cores. Apt-package install is
# handled by `install_llama_cpp` itself via its
@ -2281,9 +2252,8 @@ jobs:
print(f"Build targets: {LLAMA_CPP_TARGETS}")
# install_llama_cpp returns (quantizer_path, converter_script_path).
# The quantizer's directory is the `llama.cpp` install root, which
# also holds the CLI inference binaries after build/bin/llama-* gets
# copied up (llama_cpp.py:1450-1454; on Windows they stay in
# build/bin/Release/).
# also holds llama-cli after build/bin/llama-* gets copied up
# (llama_cpp.py:867-871).
quantizer, converter = install_llama_cpp(print_output=True)
assert quantizer and os.path.exists(quantizer), (
f"install_llama_cpp returned quantizer={quantizer!r} but file missing"
@ -2292,54 +2262,25 @@ jobs:
f"install_llama_cpp returned converter={converter!r} but missing"
)
install_root = os.path.dirname(quantizer)
is_windows = sys.platform == "win32"
exe = ".exe" if is_windows else ""
# Search both the copied-up root and the Windows build/bin/Release/
# location the quantizer might already live in.
search_dirs = [install_root]
win_release = os.path.join(install_root, "build", "bin", "Release")
if win_release not in search_dirs:
search_dirs.append(win_release)
# Any of these proves a working llama.cpp CLI inference binary was
# built. Order = preference: llama-cli is canonical (restored first
# if upstream brings it back), then the multimodal CLI, then the
# server (always built whenever cli would be, behind LLAMA_BUILD_SERVER).
cli_names = [f"llama-cli{exe}", f"llama-mtmd-cli{exe}", f"llama-server{exe}"]
cli = None
cli_name = None
for name in cli_names:
for d in search_dirs:
candidate = os.path.join(d, name)
if os.path.exists(candidate) and (is_windows or os.access(candidate, os.X_OK)):
cli, cli_name = candidate, name
break
if cli is not None:
break
if cli is None:
found = []
for d in search_dirs:
if os.path.isdir(d):
found += [p for p in os.listdir(d) if p.startswith("llama-")]
raise AssertionError(
f"No CLI inference binary ({', '.join(cli_names)}) found after "
f"build in {search_dirs}. Build root contents: {sorted(set(found))[:20]}"
)
print(f"Using CLI inference binary: {cli_name} -> {cli}")
# `--help` exits non-zero on some builds; the contract is that
# recognizable help text appears on stdout/stderr. llama-server
# exposes a different flag set than llama-cli, so accept its
# tokens too (e.g. --host / --port / "server").
cli = os.path.join(install_root, "llama-cli")
assert os.path.exists(cli), (
f"llama-cli not found at {cli!r} after build. Build root contents: "
f"{sorted(p for p in os.listdir(install_root) if p.startswith('llama-'))[:20]}"
)
assert os.access(cli, os.X_OK), f"{cli!r} not executable"
# `llama-cli --help` exits non-zero on some builds; the contract
# is that recognizable help text appears on stdout/stderr.
proc = subprocess.run(
[cli, "--help"], capture_output=True, text=True, timeout=30,
)
combined = (proc.stdout or "") + (proc.stderr or "")
print(f"--- {cli_name} --help (first 30 lines) ---")
print("--- llama-cli --help (first 30 lines) ---")
print("\n".join(combined.splitlines()[:30]))
assert any(
tok in combined.lower()
for tok in ("usage", "--help", "--model", "-m,", "--host", "--port", "server")
for tok in ("usage", "--help", "--model", "-m,")
), (
f"{cli_name} --help produced no recognizable help text. "
f"llama-cli --help produced no recognizable help text. "
f"exit={proc.returncode}\nstdout: {proc.stdout[:400]!r}\n"
f"stderr: {proc.stderr[:400]!r}"
)
@ -2355,7 +2296,7 @@ jobs:
f"stderr: {q.stderr[:400]!r}"
)
print(
f"\nOK: install_llama_cpp produced a working {cli_name} at {cli} "
f"\nOK: install_llama_cpp produced a working llama-cli at {cli} "
f"and llama-quantize at {quantizer}."
)
PY

View file

@ -1,16 +1,18 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
# Runs installer parity and autostart opt-out tests across all three platforms.
# Runs tests/python/test_cross_platform_parity.py on Windows and macOS.
#
# Why: the parity test guards that install.sh and install.ps1 stay in sync.
# It originally ran only on ubuntu-latest through studio-backend-ci.yml.
# On Windows, Path.read_text() defaults to the cp1252 locale encoding, so a
# non-cp1252 byte in install.sh raises UnicodeDecodeError even though Linux
# and macOS default to UTF-8. The reads were pinned to encoding="utf-8" in
# #6166; this matrix keeps that from silently regressing. Pure pytest, no GPU,
# sub-second, so the matrix is cheap. Linux also runs the POSIX rollback test
# under dash, matching the supported curl-to-sh installer path.
# Why: that test is the guard that install.sh and install.ps1 stay in
# sync, but today it only runs on ubuntu-latest (auto-discovered by
# studio-backend-ci.yml's "Repo tests (CPU)" job). The test reads both
# installer scripts, and on Windows Path.read_text() defaults to the
# cp1252 locale encoding, so a non-cp1252 byte in install.sh (it already
# contains a U+274C) raises UnicodeDecodeError there even though Linux and
# macOS default to UTF-8. The reads were pinned to encoding="utf-8" in
# #6166; this job keeps that from silently regressing by exercising the
# test on the platforms it claims parity for. Pure pytest, no GPU,
# sub-second, so the matrix is cheap.
name: Cross-platform parity
@ -19,20 +21,14 @@ on:
paths:
- 'install.sh'
- 'install.ps1'
- 'tests/test_installer_skip_autostart.py'
- 'tests/python/test_cross_platform_parity.py'
- 'tests/sh/test_install_rollback_lifecycle.sh'
- 'tests/studio/test_install_rollback_lifecycle.ps1'
- '.github/workflows/cross-platform-parity-ci.yml'
push:
branches: [main]
paths:
- 'install.sh'
- 'install.ps1'
- 'tests/test_installer_skip_autostart.py'
- 'tests/python/test_cross_platform_parity.py'
- 'tests/sh/test_install_rollback_lifecycle.sh'
- 'tests/studio/test_install_rollback_lifecycle.ps1'
- '.github/workflows/cross-platform-parity-ci.yml'
workflow_dispatch:
@ -49,7 +45,7 @@ jobs:
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest, windows-latest, macos-latest]
os: [windows-latest, macos-latest]
runs-on: ${{ matrix.os }}
timeout-minutes: 10
steps:
@ -61,18 +57,5 @@ jobs:
python-version: '3.12'
cache: 'pip'
- run: python -m pip install -U pip pytest
- name: Cross-platform parity tests
env:
UNSLOTH_NO_TORCH: '1'
run: >-
python -m pytest
tests/python/test_cross_platform_parity.py
tests/test_installer_skip_autostart.py
-q
- name: PowerShell rollback lifecycle tests
if: runner.os == 'Windows'
shell: pwsh
run: pwsh -NoProfile -File tests/studio/test_install_rollback_lifecycle.ps1
- name: POSIX rollback lifecycle tests
if: runner.os == 'Linux'
run: sh tests/sh/test_install_rollback_lifecycle.sh
- name: Cross-platform parity test
run: python -m pytest tests/python/test_cross_platform_parity.py -q

View file

@ -13,10 +13,10 @@
# committed YAML / JSON config.
#
# TypeScript and Rust are NOT duplicated here on purpose:
# - Unsloth Frontend CI runs `npm run typecheck` (= `tsc --noEmit`)
# - Studio Frontend CI runs `npm run typecheck` (= `tsc --noEmit`)
# and `npm run build` (vite/swc) on every studio/frontend/**
# change, which is a full TS AST + type check.
# - Unsloth Tauri CI runs `tauri build --debug --no-bundle` on
# - Studio Tauri CI runs `tauri build --debug --no-bundle` on
# every studio/src-tauri/** or studio/frontend/** change, which
# compiles the Rust crate (= cargo check + cargo build).
# Each is a stricter check than a parse-only step would be, so a

View file

@ -1,789 +0,0 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
# Local Agent Guides CI
# =====================
# Detects when our local-agent setup recipes drift out of sync with
# `unsloth run`. Boots a real `unsloth run --disable-tools` server and
# drives the coding agents end to end through the *exact* recipes defined
# in unsloth_cli/commands/start.py (the in-repo source of truth -- there
# is no docs/ tree). Wherever start.py has a recipe we drive the agent
# via `unsloth start <agent> --no-launch` and execute what it prints, so
# the test self-updates against start.py and catches silent recipe drift.
#
# Source-of-truth files this workflow guards:
# unsloth_cli/commands/start.py the `unsloth start <agent>` recipes
# unsloth_cli/commands/studio.py the `unsloth run` banner (API Key line)
#
# Failure taxonomy (each surfaced with a distinct ::error:: + the agent name
# + the start.py location, so a red X is immediately triageable):
# (a) Unsloth server/API regression -- the dialect HTTP preflight fails
# BEFORE the agent runs (or the server never becomes healthy).
# (b) Agent package install failed -- npm/curl install of the CLI failed.
# (c) Guide drift -- preflight passed + install ok, but
# the documented `unsloth start` flow produced no/garbled output.
#
# Agents covered (6): claude, codex, hermes, openclaw, opencode, pi.
# - All six have a `unsloth start <agent>` recipe, so each cell obtains its
# env + command from `unsloth start <agent> --no-launch` and runs THAT
# (self-updating: a recipe change is exercised automatically).
name: Local Agent Guides CI
on:
# Off-peak weekly, deliberately a NON-:00 minute to dodge the top-of-hour
# GitHub-hosted-runner stampede.
schedule:
- cron: '37 7 * * 1'
workflow_dispatch:
pull_request:
paths:
- 'unsloth_cli/**'
- 'studio/backend/routes/**'
# Contracts this workflow asserts that live outside routes/**: the
# /api/health endpoint, the llama-server KV-cache log behavior, and the
# request/response schemas the agent dialects depend on.
- 'studio/backend/main.py'
- 'studio/backend/core/inference/llama_cpp.py'
- 'studio/backend/models/**'
- 'install.sh'
- '.github/workflows/local-agent-guides-ci.yml'
- '.github/scripts/serve-unsloth-run.sh'
- '.github/scripts/assert-prompt-cache.sh'
- '.github/scripts/agent-guides-install.sh'
- '.github/scripts/agent-guides-drive.sh'
- '.github/scripts/ci-connect-prompt.txt'
- '.github/scripts/ci-min-system-prompt.txt'
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
permissions:
contents: read
# Secret handling on pull_request: these jobs check out and run PR-controlled code
# (install.sh, .github/scripts/**), so HF_TOKEN (an external HF credential) is gated
# off pull_request at each step below -- public GGUF repos still download anonymously.
# GH_TOKEN (GITHUB_TOKEN) is kept: it is the job-scoped contents:read token and
# install_llama_prebuilt.py needs it for the GitHub releases API (else 403s).
env:
# Determinism precedent (studio-inference-smoke.yml): temp 0 + fixed seed.
UNSLOTH_SEED: '3407'
# A single invoke must never hang the runner on a headless TTY prompt. With
# prefill-shrinking flags (minimal system prompt + restricted tools) a turn on
# a 4B model finishes in a couple of minutes on CPU; this also caps how long a
# still-large-prompt agent burns before failing. Well under the 6h job cap.
AGENT_INVOKE_TIMEOUT: '600'
jobs:
# ═════════════════════════════════════════════════════════════════════
# Job 1: connection
# Per-agent: serve gemma-3-270m, HTTP-preflight the agent's dialect,
# install the agent, run `unsloth start <agent> --no-launch`, execute
# the emitted recipe with a trivial prompt, assert a non-empty reply.
# Runs on PR + weekly + dispatch. Each matrix cell is its own runner so
# it serves exactly one model on its own port.
# ═════════════════════════════════════════════════════════════════════
connection:
name: connection (${{ matrix.agent }})
runs-on: ubuntu-latest
timeout-minutes: 40
strategy:
fail-fast: false
matrix:
agent: [claude, codex, hermes, openclaw, opencode, pi]
include:
# OpenClaw needs Node 24; everything else is happy on 22.
- agent: openclaw
node: '24'
env:
# gemma-4-E4B (128K context, capable enough to drive every agent for a
# trivial reply; the 270m model produced empty/failed responses for
# codex/openclaw). Hermes' 64K context floor no longer constrains the model
# choice: write_hermes_config claims the floor for smaller windows and
# scales compaction back to the real window. Served as a flat
# GGUF file (the -MTP- repo ships no separate draft, so this is plain 4B).
GGUF_REPO: unsloth/gemma-4-E4B-it-GGUF
GGUF_FILE: gemma-4-E4B-it-UD-Q4_K_XL.gguf
STUDIO_PORT: '18901'
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
persist-credentials: false
- name: Linux deps for llama.cpp prebuilt
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
libcurl4-openssl-dev libssl-dev jq
- uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
with:
node-version: ${{ matrix.node || '22' }}
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
with:
python-version: '3.12'
cache: 'pip'
- name: Restore GGUF model file
id: cache-gguf
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
continue-on-error: true
with:
path: gguf-cache
key: ${{ runner.os }}-gguf-${{ env.GGUF_REPO }}-${{ env.GGUF_FILE }}-v1
- name: Download GGUF if cache miss
id: download-gguf
if: steps.cache-gguf.outputs.cache-hit != 'true' || steps.cache-gguf.outcome != 'success'
env:
# Gated off PR (see note above); public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p gguf-cache
bash .github/scripts/hf-download-with-retry.sh "$GGUF_REPO" "$GGUF_FILE" gguf-cache
- name: Save GGUF model file
if: always() && steps.download-gguf.outcome == 'success'
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: gguf-cache
key: ${{ runner.os }}-gguf-${{ env.GGUF_REPO }}-${{ env.GGUF_FILE }}-v1
- name: Install Unsloth (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Gated off PR (see note above); public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
run: |
mkdir -p logs
set -o pipefail
bash install.sh --local --no-torch 2>&1 | tee logs/install.log
# ── boot the server under test (factored helper) ──────────────────
- name: Serve unsloth run --disable-tools (gemma-4-E4B)
run: |
# Wipe, not reset-password: since #7573 the reset rotates in place and
# prints the new passphrase, which would land unmasked in the job log.
rm -rf ~/.unsloth/studio/auth
bash .github/scripts/serve-unsloth-run.sh \
--gguf-file "$GITHUB_WORKSPACE/gguf-cache/${GGUF_FILE}" \
--port "$STUDIO_PORT" --log-dir logs \
--extra "--seed $UNSLOTH_SEED --temp 0" \
--health-timeout 900
# ── (a) server/API preflight: prove the dialect works BEFORE the agent ─
# Distinct error class. If this step fails it is a SERVER regression,
# not the agent's or the guide's fault, and the agent steps never run.
- name: Preflight the agent's API dialect (class-a isolation)
env:
AGENT: ${{ matrix.agent }}
run: |
set -uo pipefail
B="$UNSLOTH_BASE_URL"; K="$UNSLOTH_API_KEY"
preflight_fail() {
echo "::error::[server/API regression] agent=$AGENT: $* (preflight failed BEFORE install/connect; this is class (a), not guide drift). Endpoint contract lives in studio/backend/routes/**.";
exit 1
}
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/models" \
-H "Authorization: Bearer $K") || true
[ "$code" = "200" ] || preflight_fail "/v1/models returned HTTP $code"
case "$AGENT" in
claude)
# Anthropic Messages dialect.
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/messages" \
-H "Authorization: Bearer $K" -H 'content-type: application/json' \
--max-time 120 \
-d "{\"model\":\"$UNSLOTH_MODEL_ID\",\"max_tokens\":16,\"messages\":[{\"role\":\"user\",\"content\":\"Hi\"}]}") || true
[ "$code" = "200" ] || preflight_fail "/v1/messages returned HTTP $code"
;;
codex)
# Codex always streams /v1/responses.
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/responses" \
-H "Authorization: Bearer $K" -H 'content-type: application/json' \
--max-time 120 \
-d "{\"model\":\"$UNSLOTH_MODEL_ID\",\"input\":\"Hi\",\"max_output_tokens\":16,\"stream\":true}") || true
[ "$code" = "200" ] || preflight_fail "/v1/responses returned HTTP $code"
;;
*)
# OpenAI Chat Completions dialect (hermes/opencode/pi/openclaw).
# OpenClaw's start.py recipe writes an "openai-completions"
# provider (write_openclaw_config), so it uses this path, not
# /v1/messages.
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/chat/completions" \
-H "Authorization: Bearer $K" -H 'content-type: application/json' \
--max-time 120 \
-d "{\"model\":\"$UNSLOTH_MODEL_ID\",\"max_tokens\":16,\"messages\":[{\"role\":\"user\",\"content\":\"Hi\"}]}") || true
[ "$code" = "200" ] || preflight_fail "/v1/chat/completions returned HTTP $code"
;;
esac
echo "preflight OK for $AGENT"
# ── (b) install the agent CLI (hardened npm/curl, retried) ─────────
- name: Install agent CLI (class-b isolation)
env:
AGENT: ${{ matrix.agent }}
run: bash .github/scripts/agent-guides-install.sh "$AGENT"
# ── (c) drive the agent via start.py and assert a reply ──────────
# For the 5 agents with a start.py recipe we run
# `unsloth start <agent> --no-launch`, eval its env/unset exports,
# then run the printed command with a hard timeout (no headless-TTY
# hang). Pi has no connect recipe, so it is driven by hand and the
# cell asserts that absence is the (known) reason.
- name: Drive ${{ matrix.agent }} via unsloth start (class-c isolation)
env:
AGENT: ${{ matrix.agent }}
run: bash .github/scripts/agent-guides-drive.sh connection "$AGENT"
- name: Collect server logs (debug)
if: always()
run: |
mkdir -p logs/studio-logs
cp -r "$HOME/.unsloth/studio/logs/." logs/studio-logs/ 2>/dev/null || true
# Redact the key across the WHOLE logs/ tree, not just studio-logs:
# serve-unsloth-run.sh records the `unsloth run` banner (which prints
# `API Key: <key>`) into logs/unsloth-run-<port>.log, and the upload
# step publishes all of logs/, so scrubbing only studio-logs would leak
# the bearer token in the retained artifact.
# Sweep EVERY uploaded path, not just logs/ -- redacted-configs/ and
# agent-workdir/ are published by the same upload step.
if [ -n "${UNSLOTH_API_KEY:-}" ]; then
grep -rlF "$UNSLOTH_API_KEY" logs redacted-configs agent-workdir 2>/dev/null | while IFS= read -r f; do
sed -i "s#${UNSLOTH_API_KEY}#<REDACTED>#g" "$f" 2>/dev/null || true
done
fi
- name: Stop Unsloth
if: always()
run: |
# Guard the PID: an unset/zero UNSLOTH_SERVER_PID would make
# `kill 0` signal this step's whole process group and abort cleanup.
if [ -n "${UNSLOTH_SERVER_PID:-}" ] && [ "${UNSLOTH_SERVER_PID}" != "0" ]; then
kill "${UNSLOTH_SERVER_PID}" 2>/dev/null || true
fi
sleep 2
ss -tln 2>/dev/null | grep ":${STUDIO_PORT}" || true
- name: Upload logs
if: always()
continue-on-error: true
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: connection-${{ matrix.agent }}-log
path: |
logs/
redacted-configs/
retention-days: 7
# ═════════════════════════════════════════════════════════════════════
# Job 2: file-edit
# The deterministic 2-turn hello.py test on Qwen3.5-4B (smaller models
# can't reliably drive the heavyweight agents' edit flows). Weekly +
# dispatch only -- it is the slow, model-heavy job and must not gate PRs.
# ═════════════════════════════════════════════════════════════════════
file-edit:
name: file-edit (${{ matrix.agent }})
if: github.event_name != 'pull_request'
runs-on: ubuntu-latest
timeout-minutes: 60
# hermes and openclaw drive a multi-turn tool loop that a CPU-only runner
# cannot finish in time (e.g. openclaw holds its 300s session-write-lock past
# expiry; each turn re-prefills the tool prompt at ~16 tok/s). Their endpoint
# wiring + generation are already hard-gated by the connection job, so the
# file-edit cell is best-effort here -- it still runs and uploads logs, but a
# timeout does not fail the workflow. Drop best_effort (or move e2e to a GPU
# runner) to make it blocking again.
continue-on-error: ${{ matrix.best_effort || false }}
strategy:
fail-fast: false
matrix:
agent: [claude, codex, hermes, openclaw, opencode, pi]
include:
- agent: openclaw
node: '24'
best_effort: true
- agent: hermes
best_effort: true
env:
# gemma-4-E4B served as a flat GGUF file (cache size tracks the .gguf 1:1,
# no xet-chunk inflation; the -MTP- repo ships no separate draft file).
GGUF_REPO: unsloth/gemma-4-E4B-it-GGUF
GGUF_FILE: gemma-4-E4B-it-UD-Q4_K_XL.gguf
STUDIO_PORT: '18902'
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
persist-credentials: false
- name: Linux deps for llama.cpp prebuilt
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
libcurl4-openssl-dev libssl-dev jq
- uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
with:
node-version: ${{ matrix.node || '22' }}
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
with:
python-version: '3.12'
cache: 'pip'
- name: Restore GGUF model file
id: cache-gguf
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
continue-on-error: true
with:
path: gguf-cache
key: ${{ runner.os }}-gguf-${{ env.GGUF_REPO }}-${{ env.GGUF_FILE }}-v1
- name: Download GGUF if cache miss
id: download-gguf
if: steps.cache-gguf.outputs.cache-hit != 'true' || steps.cache-gguf.outcome != 'success'
env:
# Gated off PR (see note above); public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p gguf-cache
bash .github/scripts/hf-download-with-retry.sh "$GGUF_REPO" "$GGUF_FILE" gguf-cache
- name: Save GGUF model file
if: always() && steps.download-gguf.outcome == 'success'
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: gguf-cache
key: ${{ runner.os }}-gguf-${{ env.GGUF_REPO }}-${{ env.GGUF_FILE }}-v1
- name: Install Unsloth (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Gated off PR (see note above); public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
run: |
mkdir -p logs
set -o pipefail
bash install.sh --local --no-torch 2>&1 | tee logs/install.log
- name: Serve unsloth run --disable-tools (gemma-4-E4B)
run: |
rm -rf ~/.unsloth/studio/auth
bash .github/scripts/serve-unsloth-run.sh \
--gguf-file "$GITHUB_WORKSPACE/gguf-cache/${GGUF_FILE}" \
--port "$STUDIO_PORT" --log-dir logs \
--extra "--seed $UNSLOTH_SEED --temp 0" \
--health-timeout 900
- name: Preflight the agent's API dialect (class-a isolation)
env:
AGENT: ${{ matrix.agent }}
run: |
set -uo pipefail
B="$UNSLOTH_BASE_URL"; K="$UNSLOTH_API_KEY"
preflight_fail() {
echo "::error::[server/API regression] agent=$AGENT: $* (preflight failed BEFORE install/connect; this is class (a), not guide drift). Endpoint contract lives in studio/backend/routes/**.";
exit 1
}
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/models" \
-H "Authorization: Bearer $K") || true
[ "$code" = "200" ] || preflight_fail "/v1/models returned HTTP $code"
# Probe the same dialect the agent will use, so a streaming/messages
# regression in the weekly run is reported as class (a) here instead of
# surfacing later as guide drift (mirrors the connection job).
case "$AGENT" in
claude)
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/messages" \
-H "Authorization: Bearer $K" -H 'content-type: application/json' \
--max-time 120 \
-d "{\"model\":\"$UNSLOTH_MODEL_ID\",\"max_tokens\":16,\"messages\":[{\"role\":\"user\",\"content\":\"Hi\"}]}") || true
[ "$code" = "200" ] || preflight_fail "/v1/messages returned HTTP $code"
;;
codex)
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/responses" \
-H "Authorization: Bearer $K" -H 'content-type: application/json' \
--max-time 120 \
-d "{\"model\":\"$UNSLOTH_MODEL_ID\",\"input\":\"Hi\",\"max_output_tokens\":16,\"stream\":true}") || true
[ "$code" = "200" ] || preflight_fail "/v1/responses returned HTTP $code"
;;
*)
# OpenAI Chat Completions dialect (hermes/opencode/pi/openclaw).
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/chat/completions" \
-H "Authorization: Bearer $K" -H 'content-type: application/json' \
--max-time 120 \
-d "{\"model\":\"$UNSLOTH_MODEL_ID\",\"max_tokens\":16,\"messages\":[{\"role\":\"user\",\"content\":\"Hi\"}]}") || true
[ "$code" = "200" ] || preflight_fail "/v1/chat/completions returned HTTP $code"
;;
esac
echo "preflight OK for $AGENT"
- name: Install agent CLI (class-b isolation)
env:
AGENT: ${{ matrix.agent }}
run: bash .github/scripts/agent-guides-install.sh "$AGENT"
- name: 2-turn hello.py test (class-c isolation)
env:
AGENT: ${{ matrix.agent }}
run: bash .github/scripts/agent-guides-drive.sh file-edit "$AGENT"
- name: Collect server logs (debug)
if: always()
run: |
mkdir -p logs/studio-logs
cp -r "$HOME/.unsloth/studio/logs/." logs/studio-logs/ 2>/dev/null || true
# Redact the key across the WHOLE logs/ tree, not just studio-logs:
# serve-unsloth-run.sh records the `unsloth run` banner (which prints
# `API Key: <key>`) into logs/unsloth-run-<port>.log, and the upload
# step publishes all of logs/, so scrubbing only studio-logs would leak
# the bearer token in the retained artifact.
# Sweep EVERY uploaded path, not just logs/ -- redacted-configs/ and
# agent-workdir/ are published by the same upload step.
if [ -n "${UNSLOTH_API_KEY:-}" ]; then
grep -rlF "$UNSLOTH_API_KEY" logs redacted-configs agent-workdir 2>/dev/null | while IFS= read -r f; do
sed -i "s#${UNSLOTH_API_KEY}#<REDACTED>#g" "$f" 2>/dev/null || true
done
fi
- name: Stop Unsloth
if: always()
run: |
# Guard the PID: an unset/zero UNSLOTH_SERVER_PID would make
# `kill 0` signal this step's whole process group and abort cleanup.
if [ -n "${UNSLOTH_SERVER_PID:-}" ] && [ "${UNSLOTH_SERVER_PID}" != "0" ]; then
kill "${UNSLOTH_SERVER_PID}" 2>/dev/null || true
fi
sleep 2
ss -tln 2>/dev/null | grep ":${STUDIO_PORT}" || true
- name: Upload logs
if: always()
continue-on-error: true
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: file-edit-${{ matrix.agent }}-log
path: |
logs/
agent-workdir/
redacted-configs/
retention-days: 7
# ═════════════════════════════════════════════════════════════════════
# Job: resume
# Does a conversation started with `unsloth start <agent>` survive exit
# and resume? This drives the REAL launch path (not the --no-launch
# recipe the other jobs use). A plain launch relocates the agent home to
# a temp dir wiped on exit, so codex/pi cannot resume; --persist routes the
# session to the stable Unsloth agents dir so it persists. opencode/claude
# keep their session data in a fixed user dir, so they persist either way.
# Dispatch-only: it is an end-to-end experiment, not a PR gate.
# ═════════════════════════════════════════════════════════════════════
resume:
name: resume (${{ matrix.agent }})
if: github.event_name == 'workflow_dispatch'
runs-on: ubuntu-latest
timeout-minutes: 60
strategy:
fail-fast: false
matrix:
# codex/pi relocate their whole home (resume broken without --persist);
# opencode/claude keep session data in a fixed dir (resume already works).
# One agent from each class proves the split end to end; openclaw/hermes
# share codex's relocation mechanism and are covered by the unit tests.
agent: [codex, opencode, claude, pi]
env:
GGUF_REPO: unsloth/gemma-4-E4B-it-GGUF
GGUF_FILE: gemma-4-E4B-it-UD-Q4_K_XL.gguf
STUDIO_PORT: '18904'
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
persist-credentials: false
- name: Linux deps for llama.cpp prebuilt
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
libcurl4-openssl-dev libssl-dev jq
- uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
with:
node-version: '22'
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
with:
python-version: '3.12'
cache: 'pip'
- name: Restore GGUF model file
id: cache-gguf
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
continue-on-error: true
with:
path: gguf-cache
key: ${{ runner.os }}-gguf-${{ env.GGUF_REPO }}-${{ env.GGUF_FILE }}-v1
- name: Download GGUF if cache miss
id: download-gguf
if: steps.cache-gguf.outputs.cache-hit != 'true' || steps.cache-gguf.outcome != 'success'
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p gguf-cache
bash .github/scripts/hf-download-with-retry.sh "$GGUF_REPO" "$GGUF_FILE" gguf-cache
- name: Save GGUF model file
if: always() && steps.download-gguf.outcome == 'success'
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: gguf-cache
key: ${{ runner.os }}-gguf-${{ env.GGUF_REPO }}-${{ env.GGUF_FILE }}-v1
- name: Install Unsloth (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
bash install.sh --local --no-torch 2>&1 | tee logs/install.log
- name: Serve unsloth run --disable-tools (gemma-4-E4B)
run: |
rm -rf ~/.unsloth/studio/auth
bash .github/scripts/serve-unsloth-run.sh \
--gguf-file "$GITHUB_WORKSPACE/gguf-cache/${GGUF_FILE}" \
--port "$STUDIO_PORT" --log-dir logs \
--extra "--seed $UNSLOTH_SEED --temp 0" \
--health-timeout 900
- name: Preflight the agent's API dialect (class-a isolation)
env:
AGENT: ${{ matrix.agent }}
run: |
set -uo pipefail
B="$UNSLOTH_BASE_URL"; K="$UNSLOTH_API_KEY"
preflight_fail() {
echo "::error::[server/API regression] agent=$AGENT: $* (preflight failed BEFORE install/connect). Endpoint contract lives in studio/backend/routes/**.";
exit 1
}
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/models" \
-H "Authorization: Bearer $K") || true
[ "$code" = "200" ] || preflight_fail "/v1/models returned HTTP $code"
case "$AGENT" in
claude)
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/messages" \
-H "Authorization: Bearer $K" -H 'content-type: application/json' \
--max-time 120 \
-d "{\"model\":\"$UNSLOTH_MODEL_ID\",\"max_tokens\":16,\"messages\":[{\"role\":\"user\",\"content\":\"Hi\"}]}") || true
[ "$code" = "200" ] || preflight_fail "/v1/messages returned HTTP $code"
;;
codex)
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/responses" \
-H "Authorization: Bearer $K" -H 'content-type: application/json' \
--max-time 120 \
-d "{\"model\":\"$UNSLOTH_MODEL_ID\",\"input\":\"Hi\",\"max_output_tokens\":16,\"stream\":true}") || true
[ "$code" = "200" ] || preflight_fail "/v1/responses returned HTTP $code"
;;
*)
code=$(curl -s -o /tmp/pf.json -w '%{http_code}' "$B/v1/chat/completions" \
-H "Authorization: Bearer $K" -H 'content-type: application/json' \
--max-time 120 \
-d "{\"model\":\"$UNSLOTH_MODEL_ID\",\"max_tokens\":16,\"messages\":[{\"role\":\"user\",\"content\":\"Hi\"}]}") || true
[ "$code" = "200" ] || preflight_fail "/v1/chat/completions returned HTTP $code"
;;
esac
echo "preflight OK for $AGENT"
- name: Install agent CLI (class-b isolation)
env:
AGENT: ${{ matrix.agent }}
run: bash .github/scripts/agent-guides-install.sh "$AGENT"
- name: Resume experiment (launch path)
env:
AGENT: ${{ matrix.agent }}
run: bash .github/scripts/agent-guides-drive.sh resume "$AGENT"
- name: Collect server logs (debug)
if: always()
run: |
mkdir -p logs/studio-logs
cp -r "$HOME/.unsloth/studio/logs/." logs/studio-logs/ 2>/dev/null || true
if [ -n "${UNSLOTH_API_KEY:-}" ]; then
grep -rlF "$UNSLOTH_API_KEY" logs redacted-configs agent-workdir 2>/dev/null | while IFS= read -r f; do
sed -i "s#${UNSLOTH_API_KEY}#<REDACTED>#g" "$f" 2>/dev/null || true
done
fi
- name: Stop Unsloth
if: always()
run: |
if [ -n "${UNSLOTH_SERVER_PID:-}" ] && [ "${UNSLOTH_SERVER_PID}" != "0" ]; then
kill "${UNSLOTH_SERVER_PID}" 2>/dev/null || true
fi
sleep 2
ss -tln 2>/dev/null | grep ":${STUDIO_PORT}" || true
- name: Upload logs
if: always()
continue-on-error: true
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: resume-${{ matrix.agent }}-log
path: |
logs/
agent-workdir/
redacted-configs/
retention-days: 7
# ═════════════════════════════════════════════════════════════════════
# Job 3: prompt-cache
# (a) curl 2-turn /v1/chat/completions: assert turn-2 cached_tokens > 0
# (server prompt-cache sanity).
# (b) Claude Code attribution A/B: with CLAUDE_CODE_ATTRIBUTION_HEADER=0
# expect a llama-server KV-cache HIT on turn 2; without it expect a
# MISS. If it inverts, the guide flag is stale.
# PR + weekly + dispatch (cheap, gemma-3-270m).
# ═════════════════════════════════════════════════════════════════════
prompt-cache:
name: prompt-cache (gemma-3-270m)
runs-on: ubuntu-latest
timeout-minutes: 25
env:
GGUF_REPO: unsloth/gemma-3-270m-it-GGUF
GGUF_VARIANT: UD-Q4_K_XL
GGUF_FILE: gemma-3-270m-it-UD-Q4_K_XL.gguf
STUDIO_PORT: '18903'
HF_HOME: ${{ github.workspace }}/hf-cache
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
persist-credentials: false
- name: Linux deps for llama.cpp prebuilt
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
libcurl4-openssl-dev libssl-dev jq
- uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
with:
node-version: '22'
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
with:
python-version: '3.12'
cache: 'pip'
- name: Restore HF_HOME for ${{ env.GGUF_REPO }}
id: cache-hf
uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
continue-on-error: true
with:
path: hf-cache
key: ${{ runner.os }}-hf-${{ env.GGUF_REPO }}-${{ env.GGUF_VARIANT }}-v2
- name: Prime HF_HOME with the GGUF
id: prime-hf
if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
env:
# Gated off PR (see note above); public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p hf-cache
bash .github/scripts/hf-download-with-retry.sh "$GGUF_REPO" "$GGUF_FILE"
- name: Save HF_HOME for ${{ env.GGUF_REPO }}
if: always() && steps.prime-hf.outcome == 'success'
uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
with:
path: hf-cache
key: ${{ runner.os }}-hf-${{ env.GGUF_REPO }}-${{ env.GGUF_VARIANT }}-v2
- name: Install Unsloth (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Gated off PR (see note above); public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
run: |
mkdir -p logs
set -o pipefail
bash install.sh --local --no-torch 2>&1 | tee logs/install.log
- name: Serve unsloth run --disable-tools (gemma-3-270m)
run: |
rm -rf ~/.unsloth/studio/auth
bash .github/scripts/serve-unsloth-run.sh \
--model "$GGUF_REPO" --gguf-variant "$GGUF_VARIANT" \
--port "$STUDIO_PORT" --log-dir logs \
--extra "--seed $UNSLOTH_SEED --temp 0"
# (a) server prompt-cache sanity on the OpenAI chat path. The helper runs
# the 2-turn probe internally (turn 2 reuses turn 1's prefix) and asserts
# turn-2 usage.prompt_tokens_details.cached_tokens > 0. This is the hard
# gate -- it proves llama.cpp KV reuse is surfaced on /v1/chat/completions.
- name: Server prompt-cache sanity (cached_tokens > 0)
run: bash .github/scripts/assert-prompt-cache.sh api "$UNSLOTH_BASE_URL" "$UNSLOTH_API_KEY"
- name: Install Claude Code (class-b isolation)
env:
AGENT: claude
run: bash .github/scripts/agent-guides-install.sh claude
# (b) Claude attribution A/B against the llama-server log. This is the most
# environment-sensitive check (it depends on the bundled llama.cpp's
# slot-reuse log wording and on claude --continue reusing the prefix), so
# it is non-blocking until calibrated on the first scheduled run; the
# server cache sanity above is the hard gate. The step still prints the
# observed HIT/MISS so drift is visible in the log + artifacts.
- name: Claude attribution A/B (HIT with header=0, MISS without)
continue-on-error: true
run: bash .github/scripts/agent-guides-drive.sh attribution-ab claude
- name: Collect server logs (debug)
if: always()
run: |
mkdir -p logs/studio-logs
cp -r "$HOME/.unsloth/studio/logs/." logs/studio-logs/ 2>/dev/null || true
# Redact the key across the WHOLE logs/ tree, not just studio-logs:
# serve-unsloth-run.sh records the `unsloth run` banner (which prints
# `API Key: <key>`) into logs/unsloth-run-<port>.log, and the upload
# step publishes all of logs/, so scrubbing only studio-logs would leak
# the bearer token in the retained artifact.
# Sweep EVERY uploaded path, not just logs/ -- redacted-configs/ and
# agent-workdir/ are published by the same upload step.
if [ -n "${UNSLOTH_API_KEY:-}" ]; then
grep -rlF "$UNSLOTH_API_KEY" logs redacted-configs agent-workdir 2>/dev/null | while IFS= read -r f; do
sed -i "s#${UNSLOTH_API_KEY}#<REDACTED>#g" "$f" 2>/dev/null || true
done
fi
- name: Stop Unsloth
if: always()
run: |
# Guard the PID: an unset/zero UNSLOTH_SERVER_PID would make
# `kill 0` signal this step's whole process group and abort cleanup.
if [ -n "${UNSLOTH_SERVER_PID:-}" ] && [ "${UNSLOTH_SERVER_PID}" != "0" ]; then
kill "${UNSLOTH_SERVER_PID}" 2>/dev/null || true
fi
sleep 2
ss -tln 2>/dev/null | grep ":${STUDIO_PORT}" || true
- name: Upload logs
if: always()
continue-on-error: true
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: prompt-cache-log
path: |
logs/
redacted-configs/
retention-days: 7

View file

@ -60,11 +60,11 @@ jobs:
runs-on: ubuntu-latest
timeout-minutes: 5
steps:
- uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0 # v7.0.0
- uses: actions/checkout@v4
with:
persist-credentials: false
- uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1 # v6.3.0
- uses: actions/setup-python@v5
with:
python-version: '3.12'

View file

@ -130,7 +130,7 @@ jobs:
# MLX support landed after the most recent unsloth-zoo PyPI
# release; the wheel still raises NotImplementedError on
# Apple Silicon when device_type.get_device_type() runs
# unguarded. Unsloth's own install.sh overlays unsloth-zoo
# unguarded. Studio's own install.sh overlays unsloth-zoo
# from git main for the same reason. Pulling deps lets pip
# resolve the platform-conditional MLX-only wheels (mlx,
# mlx-lm, mlx-vlm gated on darwin+arm64 in unsloth-zoo's
@ -163,7 +163,7 @@ jobs:
'pytest==9.0.3' \
'pytest-asyncio==1.3.0' \
'httpx==0.28.1'
pip install --index-url https://download.pytorch.org/whl/cpu --extra-index-url https://pypi.org/simple \
pip install --index-url https://download.pytorch.org/whl/cpu \
'torch==2.10.0'
# github.com occasionally 500s on the git fetch; retry the
# zoo install so a single upstream blip does not fail CI.
@ -231,126 +231,41 @@ jobs:
tests/studio/test_is_mlx_dispatch_gate.py \
tests/studio/test_mlx_training_worker_behaviors.py
# Real MLX training + inference smoke test. Trains
# unsloth/gemma-3-270m-it for 7 deterministic LoRA steps
# (batch_size=2, gradient_accumulation_steps=3) on a single
# repeated row ("<<HELLO!!>> My name is Unsloth!"), then saves
# the trained model in 3 export formats. The `train` subcommand
# captures per-phase timing + peak GPU + peak RSS into
# train_metrics.json so we can detect regressions across CI runs.
- name: MLX export round-trip — TRAIN + SAVE 3 formats
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
UNSLOTH_COMPILE_DISABLE: '1'
run: |
mkdir -p mlx_workdir
# Authenticate llama.cpp's release-API lookup (anonymous 403s on rate-limit);
# read-only GITHUB_TOKEN scoped here only, never to steps that run binaries.
GH_TOKEN="${{ secrets.GITHUB_TOKEN }}" GITHUB_TOKEN="${{ secrets.GITHUB_TOKEN }}" \
python tests/studio/run_real_mlx_smoke.py train \
--workdir "$PWD/mlx_workdir"
# Each reload step runs in a FRESH Python process to confirm
# the cold-start path users would hit in production also works
# (not just the in-memory continuation of a still-running
# trainer). FastMLXModel.from_pretrained gets called from
# scratch; mx.random is re-seeded; per-step timing + peak
# memory are emitted to {format}_reload_metrics.json next to
# the saved dir.
- name: MLX export round-trip — RELOAD LoRA (fresh process)
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
UNSLOTH_COMPILE_DISABLE: '1'
run: |
python tests/studio/run_real_mlx_smoke.py reload \
--format lora \
--dir "$PWD/mlx_workdir/lora"
- name: MLX export round-trip — RELOAD merged_16bit (fresh process)
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
UNSLOTH_COMPILE_DISABLE: '1'
run: |
python tests/studio/run_real_mlx_smoke.py reload \
--format merged \
--dir "$PWD/mlx_workdir/merged_16bit"
# GGUF reload uses the llama-cli binary that save_pretrained_gguf
# built. If save_pretrained_gguf was skipped during train (e.g.
# llama.cpp's convert_hf_to_gguf asserts on the model's tokenizer
# vocab -- a downstream llama.cpp limitation, not an unsloth_zoo
# bug), this step emits a workflow warning and exits 0 so the
# LoRA + merged_16bit assertions remain the gating signal.
- name: MLX export round-trip — RELOAD GGUF via llama-cli (fresh process)
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
run: |
if python -c "import json,sys; m=json.load(open('mlx_workdir/train_metrics.json')); sys.exit(0 if m.get('gguf_supported') else 1)"; then
python tests/studio/run_real_mlx_smoke.py reload \
--format gguf \
--dir "$PWD/mlx_workdir/gguf"
else
REASON=$(python -c "import json; m=json.load(open('mlx_workdir/train_metrics.json')); print(m.get('gguf_skip_reason') or 'unknown')")
echo "::warning title=GGUF round-trip skipped::${REASON}"
echo "GGUF export was skipped during the train phase. Reason:"
echo " ${REASON}"
echo "Continuing without failing the job; the LoRA + merged_16bit"
echo "reload assertions are still gating this PR."
fi
# Print all metrics JSON files so regressions are visible in the
# job log. always() so we get telemetry even if a reload step
# asserted gibberish.
- name: MLX export round-trip — aggregate metrics
if: always()
run: |
for f in mlx_workdir/train_metrics.json \
mlx_workdir/lora_reload_metrics.json \
mlx_workdir/merged_reload_metrics.json \
mlx_workdir/gguf_reload_metrics.json; do
echo "=== $f ==="
cat "$f" 2>/dev/null || echo "(missing)"
echo
done
# Validates the macOS prebuilt path Unsloth's setup.sh uses (#5963): install the
# unslothai/llama.cpp fork's latest release, download a small public GGUF, and
# check llama-server /completion end to end. Split and placed last so the
# untrusted binary runs only in the final smoke step, after every HF_TOKEN step,
# leaving no token-bearing step or shared workspace for a tampered prebuilt to
# corrupt. GH_TOKEN: releases API; HF_TOKEN (withheld on PR): probe + GGUF fetch.
- name: Unsloth prebuilt llama.cpp install + GGUF download (Mac M1)
# Studio prebuilt llama.cpp install + GGUF inference. Mirrors the
# path Studio's setup.sh takes on macOS since #5963: plan against
# the unslothai/llama.cpp fork's latest release, which ships the
# bin-macos-arm64 bundle plus the llama-prebuilt-manifest.json the
# default policy reads. After install, downloads a small published
# GGUF (unsloth/gemma-3-270m-it-GGUF, Q4_K_M) and validates
# llama-server /completion end to end. An install failure or a
# non-zero binary exit is an Unsloth/Studio bug.
- name: Studio prebuilt llama.cpp install + GGUF inference (Mac M1)
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
# install_llama_prebuilt.py hits the GitHub releases API to
# resolve the asset URL. Anonymous calls share the runner-IP
# rate-limit bucket and 403 quickly -- pass the workflow's
# automatic GITHUB_TOKEN to bump us to the 5000/hr authenticated
# bucket.
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
run: |
set -euo pipefail
INSTALL_DIR="$HOME/.unsloth-studio-prebuilt-test/llama.cpp"
rm -rf "$INSTALL_DIR"
# Download only -- no llama-quantize / llama-server launch in this step.
# Mirror studio/setup.sh on macOS (the install.sh user path):
# it plans against the unslothai/llama.cpp fork's latest
# release with no policy or tag flags.
python studio/install_llama_prebuilt.py \
--install-dir "$INSTALL_DIR" \
--published-repo unslothai/llama.cpp
mkdir -p /tmp/ggufs
bash .github/scripts/hf-download-with-retry.sh \
'unsloth/gemma-3-270m-it-GGUF' \
'gemma-3-270m-it-Q4_K_M.gguf' \
/tmp/ggufs
# Final step: runs the downloaded binaries with no secrets present, and clears
# the GitHub Actions command files so a tampered prebuilt cannot influence the job.
- name: Unsloth prebuilt llama.cpp GGUF inference smoke (Mac M1)
run: |
set -euo pipefail
unset GITHUB_ENV GITHUB_PATH GITHUB_OUTPUT GITHUB_STEP_SUMMARY
INSTALL_DIR="$HOME/.unsloth-studio-prebuilt-test/llama.cpp"
# Unsloth bundles only llama-server + llama-quantize (not llama-cli);
# inference goes through llama-server's HTTP /completion endpoint.
# Studio bundles only llama-server + llama-quantize from the
# prebuilt (not llama-cli) -- inference goes through
# llama-server's HTTP /completion endpoint. Validate both:
# llama-quantize --help proves the dynamic libs link, then
# spin up llama-server and POST a /completion request on a
# tiny published GGUF.
LLAMA_SERVER="$INSTALL_DIR/build/bin/llama-server"
LLAMA_QUANT="$INSTALL_DIR/build/bin/llama-quantize"
[ -x "$LLAMA_SERVER" ] || { echo "::error::llama-server missing at $LLAMA_SERVER"; find "$INSTALL_DIR/build" -type f | head -40; exit 1; }
@ -359,6 +274,12 @@ jobs:
echo "llama-quantize: $LLAMA_QUANT"
"$LLAMA_QUANT" --help >/dev/null && echo " llama-quantize loads OK"
mkdir -p /tmp/ggufs
bash .github/scripts/hf-download-with-retry.sh \
'unsloth/gemma-3-270m-it-GGUF' \
'gemma-3-270m-it-Q4_K_M.gguf' \
/tmp/ggufs
PORT=18080
echo "=== starting llama-server on 127.0.0.1:$PORT ==="
"$LLAMA_SERVER" \
@ -400,4 +321,83 @@ jobs:
tail -40 /tmp/llama-server.log
exit 1
fi
echo "OK: Unsloth prebuilt llama.cpp on Mac M1 + GGUF /completion works"
echo "OK: Studio prebuilt llama.cpp on Mac M1 + GGUF /completion works"
# Real MLX training + inference smoke test. Trains
# unsloth/gemma-3-270m-it for 7 deterministic LoRA steps
# (batch_size=2, gradient_accumulation_steps=3) on a single
# repeated row ("<<HELLO!!>> My name is Unsloth!"), then saves
# the trained model in 3 export formats. The `train` subcommand
# captures per-phase timing + peak GPU + peak RSS into
# train_metrics.json so we can detect regressions across CI runs.
- name: MLX export round-trip — TRAIN + SAVE 3 formats
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
UNSLOTH_COMPILE_DISABLE: '1'
run: |
mkdir -p mlx_workdir
python tests/studio/run_real_mlx_smoke.py train \
--workdir "$PWD/mlx_workdir"
# Each reload step runs in a FRESH Python process to confirm
# the cold-start path users would hit in production also works
# (not just the in-memory continuation of a still-running
# trainer). FastMLXModel.from_pretrained gets called from
# scratch; mx.random is re-seeded; per-step timing + peak
# memory are emitted to {format}_reload_metrics.json next to
# the saved dir.
- name: MLX export round-trip — RELOAD LoRA (fresh process)
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
UNSLOTH_COMPILE_DISABLE: '1'
run: |
python tests/studio/run_real_mlx_smoke.py reload \
--format lora \
--dir "$PWD/mlx_workdir/lora"
- name: MLX export round-trip — RELOAD merged_16bit (fresh process)
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
UNSLOTH_COMPILE_DISABLE: '1'
run: |
python tests/studio/run_real_mlx_smoke.py reload \
--format merged \
--dir "$PWD/mlx_workdir/merged_16bit"
# GGUF reload uses the llama-cli binary that save_pretrained_gguf
# built. If save_pretrained_gguf was skipped during train (e.g.
# llama.cpp's convert_hf_to_gguf asserts on the model's tokenizer
# vocab -- a downstream llama.cpp limitation, not an unsloth_zoo
# bug), this step emits a workflow warning and exits 0 so the
# LoRA + merged_16bit assertions remain the gating signal.
- name: MLX export round-trip — RELOAD GGUF via llama-cli (fresh process)
env:
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
if python -c "import json,sys; m=json.load(open('mlx_workdir/train_metrics.json')); sys.exit(0 if m.get('gguf_supported') else 1)"; then
python tests/studio/run_real_mlx_smoke.py reload \
--format gguf \
--dir "$PWD/mlx_workdir/gguf"
else
REASON=$(python -c "import json; m=json.load(open('mlx_workdir/train_metrics.json')); print(m.get('gguf_skip_reason') or 'unknown')")
echo "::warning title=GGUF round-trip skipped::${REASON}"
echo "GGUF export was skipped during the train phase. Reason:"
echo " ${REASON}"
echo "Continuing without failing the job; the LoRA + merged_16bit"
echo "reload assertions are still gating this PR."
fi
# Print all metrics JSON files so regressions are visible in the
# job log. always() so we get telemetry even if a reload step
# asserted gibberish.
- name: MLX export round-trip — aggregate metrics
if: always()
run: |
for f in mlx_workdir/train_metrics.json \
mlx_workdir/lora_reload_metrics.json \
mlx_workdir/merged_reload_metrics.json \
mlx_workdir/gguf_reload_metrics.json; do
echo "=== $f ==="
cat "$f" 2>/dev/null || echo "(missing)"
echo
done

View file

@ -263,7 +263,7 @@ jobs:
# unsloth_zoo.vision_utils imports PIL at module top, and the
# easiest way to get a torch-compatible PIL on a CPU runner is
# to let torchvision pull the right Pillow version.
pip install --index-url https://download.pytorch.org/whl/cpu --extra-index-url https://pypi.org/simple \
pip install --index-url https://download.pytorch.org/whl/cpu \
'torch>=2.8,<2.11' 'torchvision<0.26'
# Pin to the same versions update_all_notebooks.py installs in
# generated notebooks. Keep these in lockstep with PIN_TRL /

View file

@ -1,78 +0,0 @@
# This workflow uses actions that are not certified by GitHub. They are provided
# by a third-party and are governed by separate terms of service, privacy
# policy, and support documentation.
name: Scorecard supply-chain security
on:
# For Branch-Protection check. Only the default branch is supported. See
# https://github.com/ossf/scorecard/blob/main/docs/checks.md#branch-protection
branch_protection_rule:
# To guarantee Maintained check is occasionally updated. See
# https://github.com/ossf/scorecard/blob/main/docs/checks.md#maintained
schedule:
- cron: '21 20 * * 0'
push:
branches: [ "main" ]
# Declare default permissions as read only.
permissions: read-all
jobs:
analysis:
name: Scorecard analysis
runs-on: ubuntu-latest
# `publish_results: true` only works when run from the default branch. conditional can be removed if disabled.
if: github.event.repository.default_branch == github.ref_name || github.event_name == 'pull_request'
permissions:
# Needed to upload the results to code-scanning dashboard.
security-events: write
# Needed to publish results and get a badge (see publish_results below).
id-token: write
# Uncomment the permissions below if installing in a private repository.
# contents: read
# actions: read
steps:
- name: "Checkout code"
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
with:
persist-credentials: false
- name: "Run analysis"
uses: ossf/scorecard-action@f49aabe0b5af0936a0987cfb85d86b75731b0186 # v2.4.1
with:
results_file: results.sarif
results_format: sarif
# (Optional) "write" PAT token. Uncomment the `repo_token` line below if:
# - you want to enable the Branch-Protection check on a *public* repository, or
# - you are installing Scorecard on a *private* repository
# To create the PAT, follow the steps in https://github.com/ossf/scorecard-action?tab=readme-ov-file#authentication-with-fine-grained-pat-optional.
# repo_token: ${{ secrets.SCORECARD_TOKEN }}
# Public repositories:
# - Publish results to OpenSSF REST API for easy access by consumers
# - Allows the repository to include the Scorecard badge.
# - See https://github.com/ossf/scorecard-action#publishing-results.
# For private repositories:
# - `publish_results` will always be set to `false`, regardless
# of the value entered here.
publish_results: true
# (Optional) Uncomment file_mode if you have a .gitattributes with files marked export-ignore
# file_mode: git
# Upload the results as artifacts (optional). Commenting out will disable uploads of run results in SARIF
# format to the repository Actions tab.
- name: "Upload artifact"
uses: actions/upload-artifact@4cec3d8aa04e39d1a68397de0c4cd6fb9dce8ec1 # v4.6.1
with:
name: SARIF file
path: results.sarif
retention-days: 5
# Upload the results to GitHub's code scanning dashboard (optional).
# Commenting out will disable upload of results to your repo's Code Scanning dashboard
- name: "Upload to code-scanning"
uses: github/codeql-action/upload-sarif@v3
with:
sarif_file: results.sarif

View file

@ -4,7 +4,7 @@ on:
workflow_dispatch:
inputs:
studio_version:
description: 'Unsloth version tag to release (for example, v0.1.39-beta)'
description: 'Studio version tag to release (for example, v0.1.39-beta)'
type: string
required: true
pypi_version:
@ -19,19 +19,6 @@ on:
permissions:
contents: read
env:
DESKTOP_RELEASE_NOTES: |
Desktop app for Unsloth Studio.
**macOS**: Download the Apple Silicon `.dmg`.
**Windows**: Download the `-setup.exe` installer.
**Linux**: Download `.deb` for Ubuntu/Debian. `.AppImage` is experimental.
> Linux in-app updates are AppImage-oriented. Package installs should update by downloading a new package.
> Linux AppImage can show a blank window on some Tauri/WebKitGTK + Wayland/Mesa stacks; use `.deb` when available.
> Linux AppImage on Ubuntu 24.04+ may require: `sudo apt install libfuse2t64`
> First-run system dependency elevation is supported on Ubuntu/Debian. Other Linux distributions should install system packages manually.
concurrency:
group: release-desktop-${{ github.repository }}
cancel-in-progress: false
@ -69,7 +56,7 @@ jobs:
if not studio_version:
sys.exit('studio_version is required, for example v0.1.39-beta')
if re.fullmatch(r'v?20\d{2}\.\d+\.\d+(?:[-+][0-9A-Za-z.-]+)?', studio_version):
sys.exit(f'studio_version must be an Unsloth SemVer tag, not a date-style backend version: {studio_version}')
sys.exit(f'studio_version must be a Studio SemVer tag, not a date-style backend version: {studio_version}')
semver_tag = re.compile(
r'^v(0|[1-9]\d*)\.(0|[1-9]\d*)\.(0|[1-9]\d*)'
@ -146,7 +133,7 @@ jobs:
print(f'pypi_version={pypi_version}', file=output)
PY
- name: Verify PyPI package and Unsloth stamp
- name: Verify PyPI package and Studio stamp
shell: bash
env:
STUDIO_VERSION: ${{ steps.prepare.outputs.studio_version }}
@ -211,7 +198,7 @@ jobs:
fi
python3 scripts/stamp_studio_release.py --verify-dist "$RUNNER_TEMP/pypi-unsloth-dist" --expected "$STUDIO_VERSION"
else
echo "scripts/stamp_studio_release.py not found; release-desktop requires #5308 to verify the PyPI Unsloth stamp." >&2
echo "scripts/stamp_studio_release.py not found; release-desktop requires #5308 to verify the PyPI Studio stamp." >&2
exit 1
fi
@ -308,6 +295,14 @@ jobs:
PY
build:
# TODO: split into a "build (no secrets)" + "publish (secrets)" job pair
# with actions/upload-artifact handoff so the matrix build cannot
# publish a Release on its own. The current matrix runs across
# Linux/macOS/Windows in a single job, so the split needs artefact
# collection across the OS matrix and is out of scope for this
# hardening pass.
permissions:
contents: write # tauri-apps/tauri-action creates / uploads a GitHub Release
strategy:
fail-fast: false
max-parallel: 1
@ -316,21 +311,15 @@ jobs:
- platform: macos-latest
args: '--target aarch64-apple-darwin'
label: macOS (Apple Silicon)
artifact: macos-aarch64
release_arch: aarch64
# - platform: macos-latest
# args: '--target x86_64-apple-darwin'
# label: macOS (Intel)
- platform: ubuntu-22.04
args: ''
label: Linux (x64)
artifact: linux-x64
release_arch: x64
- platform: windows-latest
args: ''
label: Windows (x64)
artifact: windows-x64
release_arch: x64
name: Build ${{ matrix.label }}
needs: prepare-version
@ -364,7 +353,7 @@ jobs:
if: matrix.platform == 'ubuntu-22.04'
run: |
sudo apt-get update
sudo apt-get install -y libwebkit2gtk-4.1-dev libappindicator3-dev librsvg2-dev libxdo-dev libssl-dev patchelf
sudo apt-get install -y libwebkit2gtk-4.1-dev libayatana-appindicator3-dev librsvg2-dev libxdo-dev libssl-dev patchelf
# ── Node.js ──
- name: Setup Node.js
@ -417,77 +406,38 @@ jobs:
if (config.bundle?.linux?.rpm) {
throw new Error('bundle.linux.rpm must not be configured');
}
if (config.bundle?.linux?.appimage?.bundleMediaFramework !== false) {
throw new Error('Linux AppImage bundleMediaFramework must stay false');
}
const workflow = readFileSync('.github/workflows/release-desktop.yml', 'utf8');
const lines = workflow.split(/\r?\n/);
const linuxInstallLines = lines.filter((line) => line.includes('sudo apt-get install'));
const ayatanaPackage = ['libayatana', 'appindicator3-dev'].join('-');
if (linuxInstallLines.some((line) => line.includes(ayatanaPackage))) {
throw new Error('Desktop Linux release must not install the Ayatana appindicator dev package');
}
if (!linuxInstallLines.some((line) => line.includes('libappindicator3-dev'))) {
throw new Error('Desktop Linux release must install libappindicator3-dev');
}
const linuxdeployLines = lines.filter((line) => line.includes('github.com/linuxdeploy/linuxdeploy/releases/download'));
if (!linuxdeployLines.some((line) => line.includes('1-alpha-20250213-2/linuxdeploy-x86_64.AppImage'))) {
throw new Error('Desktop Linux release must pin linuxdeploy 1-alpha-20250213-2');
}
// A pinned version/path is reproducibility, not integrity: the asset
// can be replaced after upload. Require the immutable SHA-256 digest
// to be pinned AND verified before chmod +x. Scope every check to the
// real "Pin linuxdeploy for AppImage" step so this guard cannot
// satisfy itself; a file-wide scan would match the guard's own code.
const expectedLinuxdeployDigest = '4648f278ab3ef31f819e67c30d50f462640e5365a77637d7e6f2ad9fd0b4522a';
const isComment = (line) => {
const trimmed = line.trim();
return trimmed.startsWith('#') || trimmed.startsWith('//');
};
const stepStart = lines.findIndex((line) => /^\s*- name: Pin linuxdeploy for AppImage\s*$/.test(line));
if (stepStart === -1) {
throw new Error('Desktop Linux release must keep the "Pin linuxdeploy for AppImage" step');
}
const stepIndent = lines[stepStart].search(/\S/);
let stepEnd = lines.length;
for (let i = stepStart + 1; i < lines.length; i += 1) {
const line = lines[i];
if (line.trim() === '') continue;
const indent = line.search(/\S/);
// The next sibling step ('- ...') at the same indent, or any dedent
// below the step, ends this step's block.
if (indent < stepIndent || (indent === stepIndent && /^\s*-\s/.test(line))) {
stepEnd = i;
break;
const releaseBodies = [];
for (let i = 0; i < lines.length; i += 1) {
const match = lines[i].match(/^(\s*)releaseBody:\s*\|\s*$/);
if (!match) continue;
const baseIndent = match[1].length;
const bodyLines = [];
i += 1;
for (; i < lines.length; i += 1) {
const line = lines[i];
if (line.trim() === '') {
bodyLines.push('');
continue;
}
const indent = line.match(/^\s*/)[0].length;
if (indent <= baseIndent) {
i -= 1;
break;
}
bodyLines.push(line.slice(baseIndent + 2));
}
releaseBodies.push(bodyLines.join('\n'));
}
const stepLines = lines.slice(stepStart, stepEnd);
const digestEnvRe = /^\s*LINUXDEPLOY_SHA256:\s*["']([0-9a-f]{64})["']\s*$/;
const digestEnvLine = stepLines.find((line) => digestEnvRe.test(line));
if (!digestEnvLine || digestEnvLine.match(digestEnvRe)[1] !== expectedLinuxdeployDigest) {
throw new Error('Desktop Linux release must pin the linuxdeploy SHA-256 digest in the LINUXDEPLOY_SHA256 env');
if (releaseBodies.length === 0) {
throw new Error('Expected at least one desktop release body');
}
const sha256Idx = stepLines.findIndex((line) => !isComment(line) && line.includes('sha256sum -c'));
if (sha256Idx === -1) {
throw new Error('Desktop Linux release must verify the linuxdeploy digest with sha256sum -c before use');
}
const chmodIdx = stepLines.findIndex((line) => !isComment(line) && /chmod\s+\+x/.test(line));
if (chmodIdx !== -1 && sha256Idx > chmodIdx) {
throw new Error('Desktop Linux release must verify the linuxdeploy digest before chmod +x');
}
const releaseBody = process.env.DESKTOP_RELEASE_NOTES;
if (!releaseBody) {
throw new Error('DESKTOP_RELEASE_NOTES must not be empty');
}
if (/\brpm\b|\.rpm/i.test(releaseBody)) {
throw new Error('Desktop release body must not advertise RPM packages');
}
if (/AppImage.*universal|universal.*AppImage/i.test(releaseBody)) {
throw new Error('Desktop release body must not advertise AppImage as universal');
}
if (!/AppImage.*experimental/i.test(releaseBody)) {
throw new Error('Desktop release body must mark AppImage as experimental');
for (const body of releaseBodies) {
if (/\brpm\b|\.rpm/i.test(body)) {
throw new Error('Desktop release body must not advertise RPM packages');
}
}
JS
@ -612,53 +562,39 @@ jobs:
Get-Command trusted-signing-cli -ErrorAction SilentlyContinue || Write-Output "trusted-signing-cli NOT in PATH"
trusted-signing-cli --version || Write-Output "trusted-signing-cli failed to run"
# ── Linux: pin AppImage packaging toolchain ──
- name: Pin linuxdeploy for AppImage
if: matrix.platform == 'ubuntu-22.04'
shell: bash
env:
# Pinning the versioned release path is reproducibility, not
# integrity: a GitHub release asset can be replaced (or its delivery
# path compromised) after upload. The SHA-256 below is the immutable
# digest of this exact asset and is the integrity gate. If linuxdeploy
# publishes a new build under this tag, this run fails closed and the
# digest must be re-pinned deliberately.
LINUXDEPLOY_URL: "https://github.com/linuxdeploy/linuxdeploy/releases/download/1-alpha-20250213-2/linuxdeploy-x86_64.AppImage"
LINUXDEPLOY_SHA256: "4648f278ab3ef31f819e67c30d50f462640e5365a77637d7e6f2ad9fd0b4522a"
run: |
set -euo pipefail
tools_dir="$RUNNER_TEMP/tauri-tools-cache/tauri"
mkdir -p "$tools_dir"
dest="$tools_dir/linuxdeploy-x86_64.AppImage"
curl -fsSL "$LINUXDEPLOY_URL" -o "$dest"
# Verify the digest BEFORE the binary is ever marked executable. The
# next step builds the AppImage with the Tauri signing key, so a
# substituted linuxdeploy that ran here could exfiltrate signing
# material or tamper with release artifacts. Fail closed on any
# mismatch.
echo "${LINUXDEPLOY_SHA256} ${dest}" | sha256sum -c -
chmod +x "$dest"
# ── Linux: build + sign ──
# ── Linux: build + sign + upload ──
- name: Build Linux app
id: build_linux
if: matrix.platform == 'ubuntu-22.04'
uses: tauri-apps/tauri-action@84b9d35b5fc46c1e45415bdb6144030364f7ebc5
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
TAURI_SIGNING_PRIVATE_KEY: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY }}
TAURI_SIGNING_PRIVATE_KEY_PASSWORD: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY_PASSWORD }}
XDG_CACHE_HOME: ${{ runner.temp }}/tauri-tools-cache
with:
projectPath: studio
tauriScript: npx --prefix . tauri
tagName: ${{ needs.prepare-version.outputs.desktop_release_tag }}
releaseName: 'Unsloth Studio (Desktop) ${{ needs.prepare-version.outputs.studio_version }}'
releaseBody: |
Desktop app for Unsloth Studio.
**macOS**: Download the Apple Silicon `.dmg`.
**Windows**: Download the `-setup.exe` installer.
**Linux**: Download `.deb` (Ubuntu/Debian) or `.AppImage` (universal).
> Linux in-app updates are AppImage-oriented. Package installs should update by downloading a new package.
> Linux AppImage on Ubuntu 24.04+ may require: `sudo apt install libfuse2t64`
> First-run system dependency elevation is supported on Ubuntu/Debian. Other Linux distributions should install system packages manually.
releaseDraft: ${{ inputs.draft }}
prerelease: ${{ needs.prepare-version.outputs.prerelease }}
args: -v ${{ matrix.args }}
# ── macOS: build + sign + notarize ──
# ── macOS: build + sign + notarize + upload ──
- name: Build macOS app
id: build_macos
if: matrix.platform == 'macos-latest'
uses: tauri-apps/tauri-action@84b9d35b5fc46c1e45415bdb6144030364f7ebc5
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
TAURI_SIGNING_PRIVATE_KEY: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY }}
TAURI_SIGNING_PRIVATE_KEY_PASSWORD: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY_PASSWORD }}
APPLE_SIGNING_IDENTITY: ${{ secrets.APPLE_SIGNING_IDENTITY }}
@ -668,14 +604,28 @@ jobs:
with:
projectPath: studio
tauriScript: npx --prefix . tauri
tagName: ${{ needs.prepare-version.outputs.desktop_release_tag }}
releaseName: 'Unsloth Studio (Desktop) ${{ needs.prepare-version.outputs.studio_version }}'
releaseBody: |
Desktop app for Unsloth Studio.
**macOS**: Download the Apple Silicon `.dmg`.
**Windows**: Download the `-setup.exe` installer.
**Linux**: Download `.deb` (Ubuntu/Debian) or `.AppImage` (universal).
> Linux in-app updates are AppImage-oriented. Package installs should update by downloading a new package.
> Linux AppImage on Ubuntu 24.04+ may require: `sudo apt install libfuse2t64`
> First-run system dependency elevation is supported on Ubuntu/Debian. Other Linux distributions should install system packages manually.
releaseDraft: ${{ inputs.draft }}
prerelease: ${{ needs.prepare-version.outputs.prerelease }}
args: -v ${{ matrix.args }}
# ── Windows: build + sign ──
# ── Windows: build + sign + upload ──
- name: Build Windows app
id: build_windows
if: matrix.platform == 'windows-latest'
uses: tauri-apps/tauri-action@84b9d35b5fc46c1e45415bdb6144030364f7ebc5
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
TAURI_SIGNING_PRIVATE_KEY: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY }}
TAURI_SIGNING_PRIVATE_KEY_PASSWORD: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY_PASSWORD }}
AZURE_CLIENT_ID: ${{ secrets.AZURE_CLIENT_ID }}
@ -686,252 +636,43 @@ jobs:
with:
projectPath: studio
tauriScript: npx --prefix . tauri
tagName: ${{ needs.prepare-version.outputs.desktop_release_tag }}
releaseName: 'Unsloth Studio (Desktop) ${{ needs.prepare-version.outputs.studio_version }}'
releaseBody: |
Desktop app for Unsloth Studio.
**macOS**: Download the Apple Silicon `.dmg`.
**Windows**: Download the `-setup.exe` installer.
**Linux**: Download `.deb` (Ubuntu/Debian) or `.AppImage` (universal).
> Linux in-app updates are AppImage-oriented. Package installs should update by downloading a new package.
> Linux AppImage on Ubuntu 24.04+ may require: `sudo apt install libfuse2t64`
> First-run system dependency elevation is supported on Ubuntu/Debian. Other Linux distributions should install system packages manually.
releaseDraft: ${{ inputs.draft }}
prerelease: ${{ needs.prepare-version.outputs.prerelease }}
args: -v ${{ matrix.args }}
- name: Stage release assets
shell: bash
env:
ARTIFACT_PATHS: ${{ steps.build_linux.outputs.artifactPaths || steps.build_macos.outputs.artifactPaths || steps.build_windows.outputs.artifactPaths }}
RELEASE_ARCH: ${{ matrix.release_arch }}
run: |
set -euo pipefail
if command -v python3 >/dev/null 2>&1; then
PYTHON=python3
else
PYTHON=python
fi
"$PYTHON" <<'PY'
import json
import os
import pathlib
import re
import shutil
import sys
import unicodedata
raw_paths = os.environ.get('ARTIFACT_PATHS', '')
try:
artifact_paths = json.loads(raw_paths)
except json.JSONDecodeError as error:
sys.exit(f'Invalid tauri-action artifactPaths output: {error}')
if not isinstance(artifact_paths, list) or not artifact_paths:
sys.exit('tauri-action did not return any release artifacts')
destination = pathlib.Path(os.environ['RUNNER_TEMP'], 'desktop-release-assets')
destination.mkdir(parents=True, exist_ok=True)
staged = []
for raw_path in artifact_paths:
source = pathlib.Path(raw_path)
if not source.is_file():
continue
name = source.name
for extension in ('.app.tar.gz.sig', '.app.tar.gz'):
if name.endswith(extension):
name = f'{name[:-len(extension)]}_{os.environ["RELEASE_ARCH"]}{extension}'
break
name = unicodedata.normalize('NFD', name)
name = ''.join(character for character in name if not unicodedata.combining(character))
name = re.sub(r'[ ()\[\]{}]', '.', name)
while '..' in name:
name = name.replace('..', '.')
target = destination / name
if target.exists():
sys.exit(f'Duplicate staged release asset name: {name}')
shutil.copy2(source, target)
staged.append(name)
if not staged:
sys.exit('No release files were staged')
print('Staged release assets:')
print('\n'.join(sorted(staged)))
PY
- name: Upload signed release assets
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: desktop-release-${{ matrix.artifact }}
path: ${{ runner.temp }}/desktop-release-assets/*
if-no-files-found: error
compression-level: 0
retention-days: 1
# Only this job gets write access; builds hand off signed files via artifacts.
# Draft runs do not advance the public desktop-latest channel.
publish-release:
name: Publish desktop release
# Release process note: only non-draft workflow runs advance the public
# desktop-latest updater channel. Draft builds are for private review; if a
# draft is manually published later, this channel intentionally remains
# unchanged until a narrow manual channel-publish flow is added or a public
# desktop release is created by running this workflow with draft=false.
publish-updater-channel:
name: Publish desktop updater channel
needs: [prepare-version, build]
if: ${{ !inputs.draft }}
runs-on: ubuntu-latest
permissions:
contents: write # create the versioned Release and replace updater-channel metadata
contents: write
env:
GH_REPO: ${{ github.repository }}
APP_VERSION: ${{ needs.prepare-version.outputs.app_version }}
PYPI_VERSION: ${{ needs.prepare-version.outputs.pypi_version }}
STUDIO_VERSION: ${{ needs.prepare-version.outputs.studio_version }}
DESKTOP_RELEASE_TAG: ${{ needs.prepare-version.outputs.desktop_release_tag }}
DESKTOP_PRERELEASE: ${{ needs.prepare-version.outputs.prerelease }}
steps:
- name: Harden runner (audit)
uses: step-security/harden-runner@a5ad31d6a139d249332a2605b85202e8c0b78450 # v2.19.1
with:
egress-policy: audit
- name: Download signed release assets
uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c # v8.0.1
with:
pattern: desktop-release-*
path: ${{ runner.temp }}/desktop-release-assets
merge-multiple: true
- name: Validate release asset set
shell: bash
run: |
set -euo pipefail
python3 <<'PY'
import pathlib
import os
import sys
asset_dir = pathlib.Path(os.environ['RUNNER_TEMP'], 'desktop-release-assets')
files = [path for path in asset_dir.iterdir() if path.is_file()]
required_suffixes = (
'.dmg',
'.app.tar.gz',
'.app.tar.gz.sig',
'.deb',
'.AppImage',
'.AppImage.sig',
'-setup.exe',
'-setup.exe.sig',
)
for suffix in required_suffixes:
matches = [path for path in files if path.name.endswith(suffix)]
if len(matches) != 1:
sys.exit(f'Expected exactly one {suffix} release asset, found {len(matches)}')
if any(path.name == 'latest.json' for path in files):
sys.exit('Build artifacts must not supply latest.json')
print('\n'.join(sorted(path.name for path in files)))
PY
- name: Create or validate versioned release
shell: bash
env:
GH_TOKEN: ${{ github.token }}
RELEASE_DRAFT: ${{ inputs.draft }}
run: |
set -euo pipefail
notes_file="$RUNNER_TEMP/desktop-release-notes.md"
printf '%s\n' "$DESKTOP_RELEASE_NOTES" > "$notes_file"
release_json="$RUNNER_TEMP/versioned-release.json"
# REST tag lookup omits drafts; `gh release view` also checks pending tags.
if gh release view "$DESKTOP_RELEASE_TAG" \
--json tagName,isDraft,isPrerelease > "$release_json" 2>/dev/null; then
python3 <<'PY'
import json
import os
import pathlib
import sys
release = json.loads(pathlib.Path(os.environ['RUNNER_TEMP'], 'versioned-release.json').read_text())
expected_draft = os.environ['RELEASE_DRAFT'].lower() == 'true'
expected_prerelease = os.environ['DESKTOP_PRERELEASE'].lower() == 'true'
if release.get('tagName') != os.environ['DESKTOP_RELEASE_TAG']:
sys.exit('Existing desktop release tag does not match the requested tag')
if bool(release.get('isDraft')) != expected_draft:
sys.exit('Existing desktop release draft state does not match the workflow input')
if bool(release.get('isPrerelease')) != expected_prerelease:
sys.exit('Existing desktop release prerelease state does not match the requested version')
PY
else
release_flags=(
--title "Unsloth Studio (Desktop) ${STUDIO_VERSION}"
--notes-file "$notes_file"
--target "$GITHUB_SHA"
)
if [ "$RELEASE_DRAFT" = "true" ]; then
release_flags+=(--draft)
fi
if [ "$DESKTOP_PRERELEASE" = "true" ]; then
release_flags+=(--prerelease)
fi
gh release create "$DESKTOP_RELEASE_TAG" "${release_flags[@]}"
fi
- name: Publish versioned release assets
shell: bash
env:
GH_TOKEN: ${{ github.token }}
run: |
set -euo pipefail
gh release upload "$DESKTOP_RELEASE_TAG" "$RUNNER_TEMP/desktop-release-assets"/* --clobber
- name: Generate and publish versioned updater metadata
shell: bash
env:
GH_TOKEN: ${{ github.token }}
run: |
set -euo pipefail
python3 <<'PY'
import datetime
import json
import os
import pathlib
import sys
import urllib.parse
asset_dir = pathlib.Path(os.environ['RUNNER_TEMP'], 'desktop-release-assets')
files = [path for path in asset_dir.iterdir() if path.is_file()]
def exactly_one(suffix: str) -> pathlib.Path:
matches = [path for path in files if path.name.endswith(suffix)]
if len(matches) != 1:
sys.exit(f'Expected exactly one {suffix} updater asset, found {len(matches)}')
return matches[0]
def entry(signature_suffix: str) -> dict[str, str]:
signature_path = exactly_one(signature_suffix)
bundle_name = signature_path.name.removesuffix('.sig')
bundle_path = asset_dir / bundle_name
if not bundle_path.is_file():
sys.exit(f'Missing updater bundle for {signature_path.name}: {bundle_name}')
encoded_tag = urllib.parse.quote(os.environ['DESKTOP_RELEASE_TAG'], safe='')
encoded_name = urllib.parse.quote(bundle_name, safe='')
return {
'signature': signature_path.read_text(),
'url': (
f'https://github.com/{os.environ["GITHUB_REPOSITORY"]}/releases/download/'
f'{encoded_tag}/{encoded_name}'
),
}
darwin = entry('.app.tar.gz.sig')
linux = entry('.AppImage.sig')
windows = entry('.exe.sig')
notes = pathlib.Path(os.environ['RUNNER_TEMP'], 'desktop-release-notes.md').read_text()
metadata = {
'version': os.environ['APP_VERSION'],
# App version is SemVer; CHANGELOG.md is keyed by the backend release.
'pypi_version': os.environ['PYPI_VERSION'],
'notes': notes,
'pub_date': datetime.datetime.now(datetime.timezone.utc).isoformat(timespec='milliseconds').replace('+00:00', 'Z'),
'platforms': {
'darwin-aarch64': darwin,
'darwin-aarch64-app': darwin,
'linux-x86_64': linux,
'linux-x86_64-appimage': linux,
'windows-x86_64': windows,
'windows-x86_64-nsis': windows,
},
}
output = pathlib.Path(os.environ['RUNNER_TEMP'], 'latest.json')
output.write_text(json.dumps(metadata, indent=2) + '\n')
PY
gh release upload "$DESKTOP_RELEASE_TAG" "$RUNNER_TEMP/latest.json" --clobber
- name: Download versioned updater metadata
if: ${{ !inputs.draft }}
shell: bash
env:
GH_TOKEN: ${{ github.token }}
@ -956,7 +697,6 @@ jobs:
test -s "$RUNNER_TEMP/desktop-updater/latest.json"
- name: Validate versioned updater metadata
if: ${{ !inputs.draft }}
shell: bash
run: |
python3 <<'PY'
@ -1016,7 +756,6 @@ jobs:
PY
- name: Ensure desktop updater channel release
if: ${{ !inputs.draft }}
shell: bash
env:
GH_TOKEN: ${{ github.token }}
@ -1049,7 +788,6 @@ jobs:
PY
- name: Prevent updater channel downgrade
if: ${{ !inputs.draft }}
shell: bash
env:
GH_TOKEN: ${{ github.token }}
@ -1140,7 +878,6 @@ jobs:
PY
- name: Publish desktop updater channel metadata
if: ${{ !inputs.draft }}
shell: bash
env:
GH_TOKEN: ${{ github.token }}

View file

@ -2,8 +2,8 @@
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
# Multi-language supply-chain audit. Triggers:
# - PRs touching any dependency manifest (Python / npm / Cargo), a
# scanner or its allowlist baseline, or this workflow file,
# - PRs touching any dependency manifest (Python / npm / Cargo) or
# this workflow file,
# - push to main / pip,
# - nightly @ 04:13 UTC so newly-published advisories surface even
# when no PR opens,
@ -36,8 +36,8 @@
# - unsloth `huggingfacenotorch` extras (the canonical install path
# for fine-tuning users; pulls transformers / peft / accelerate /
# trl / datasets / diffusers / sentence-transformers / etc.)
# - all six Unsloth backend requirements files
# - Unsloth frontend (npm) and Tauri shell (cargo)
# - all six Studio backend requirements files
# - Studio frontend (npm) and Tauri shell (cargo)
# Each Python step builds a filtered dep list from pyproject.toml +
# requirements/*.txt before auditing. We do NOT install any of these
# -- pip-audit resolves through PyPI metadata, scan_packages.py
@ -57,9 +57,7 @@ on:
- 'studio/src-tauri/Cargo.lock'
- 'pyproject.toml'
- 'scripts/scan_packages.py'
- 'scripts/scan_packages_baseline.json'
- 'scripts/scan_npm_packages.py'
- 'scripts/scan_npm_packages_baseline.json'
- '.github/workflows/security-audit.yml'
push:
branches: [main, pip]
@ -218,7 +216,7 @@ jobs:
# on the runner). A comment line is left in place so the
# skipped specs are obvious in the artifact.
# The `huggingface` extra is `huggingfacenotorch` plus torch /
# torchvision / triton, deliberately skipped: Unsloth backend
# torchvision / triton, deliberately skipped: Studio backend
# already pins a torch and the +cu* / +cpu local-version tags
# trip up the PyPI resolver in `-r` mode.
run: |
@ -253,7 +251,7 @@ jobs:
# `-r requirements.txt` resolves the requirements through pip's
# dependency resolver against PyPI metadata and audits the
# resolved tree without ever executing setup.py / install
# hooks. Way faster than installing the full Unsloth runtime
# hooks. Way faster than installing the full Studio runtime
# and -- critically -- safer: an attacker who has compromised
# a transitive dep cannot run code in this job.
#
@ -326,9 +324,9 @@ jobs:
} >> "$GITHUB_STEP_SUMMARY"
# ─────────────────────────────────────────────────────────────
# npm: Unsloth frontend
# npm: Studio frontend
# ─────────────────────────────────────────────────────────────
- name: npm audit (Unsloth frontend)
- name: npm audit (Studio frontend)
# `npm audit` resolves the lockfile through the npmjs.com
# advisory DB. `--audit-level=high` filters the noise floor
# to only HIGH and CRITICAL. We do NOT pass --omit=dev: a
@ -342,7 +340,7 @@ jobs:
# Always also write the full JSON for grep-ability.
npm audit --json > ../../logs-npm-audit.json || true
{
echo "## npm audit (Unsloth frontend)"
echo "## npm audit (Studio frontend)"
echo
echo '```'
tail -200 ../../logs-npm-audit.txt
@ -350,9 +348,9 @@ jobs:
} >> "$GITHUB_STEP_SUMMARY"
# ─────────────────────────────────────────────────────────────
# cargo: Unsloth Tauri shell
# cargo: Studio Tauri shell
# ─────────────────────────────────────────────────────────────
- name: cargo audit (Unsloth Tauri)
- name: cargo audit (Studio Tauri)
# `--deny warnings` would make the job fail on any advisory.
# Keep non-blocking initially; drop continue-on-error after
# the baseline closes.
@ -362,7 +360,7 @@ jobs:
set +e
cargo audit | tee ../../logs-cargo-audit.txt
{
echo "## cargo audit (Unsloth Tauri)"
echo "## cargo audit (Studio Tauri)"
echo
echo '```'
tail -200 ../../logs-cargo-audit.txt
@ -436,7 +434,7 @@ jobs:
# ─────────────────────────────────────────────────────────────
# Semgrep: design-flaw detection (catches what regex-pattern
# scanning of malicious authors cannot, e.g. first-party logic bugs
# scanning of malicious authors cannot first-party logic bugs
# like langchain-core CVE-2025-68664 dumps/dumpd injection,
# n8n CVE-2025-68668 _pyodide.eval_code sandbox escape, marimo
# CVE-2026-39987 unauth WebSocket).
@ -559,7 +557,7 @@ jobs:
# ─────────────────────────────────────────────────────────────
# CycloneDX SBOM. Lets downstream consumers audit what's
# actually shipped in unsloth wheels and the Unsloth backend
# actually shipped in unsloth wheels and the Studio backend
# runtime. Generates one JSON file per requirements input plus
# a combined SBOM keyed off pyproject.toml; uploads as a build
# artifact (and a future step can attest it via SLSA).
@ -740,7 +738,7 @@ jobs:
# `--with-deps` makes the scan transitive: every package the
# declared set resolves to gets fetched and pattern-scanned, not
# just the top-level pins. Resolving the full transitive closure
# of the unsloth + Unsloth dep tree downloads several hundred
# of the unsloth + Studio dep tree downloads several hundred
# archives, hence the longer timeout.
#
# Sharded across runners for wall-clock parallelism. Each shard
@ -749,7 +747,7 @@ jobs:
# composition tries to balance load:
# - hf-stack: pyproject extras + no-torch-runtime
# (~150 archives, transformers/peft/accelerate/...)
# - studio: FastAPI/Unsloth backend + overrides + extras-no-deps
# - studio: FastAPI/Studio backend + overrides + extras-no-deps
# (~150 archives, smaller scientific stack)
# - extras: the heavy openai-whisper / scikit-learn / librosa
# stack (~250 archives, dominant cost)
@ -851,13 +849,10 @@ jobs:
grep -q "Standalone pre-install package scanner" scripts/scan_packages.py
- name: Scan declared + transitive Python deps
# scan_packages.py exits 1 on NON-baselined CRITICAL/HIGH
# findings, 0 otherwise. It scans code-only (docstrings and
# comments are blanked first) and suppresses reviewed
# known-good findings via scripts/scan_packages_baseline.json,
# so legitimate-library noise no longer red-fails the gate.
# The step stays advisory until SCAN_ENFORCE=1 (see env below);
# then PIPESTATUS propagates the scanner's exit code.
# scan_packages.py exits 1 on CRITICAL/HIGH findings, 0 on
# clean. We swallow the exit because the baseline isn't
# triaged yet; surface the findings in the workflow summary.
# Drop continue-on-error after the first clean run on main.
#
# `--with-deps` walks PyPI metadata to enumerate every
# transitive dep the declared set would install, then scans
@ -874,14 +869,6 @@ jobs:
# downloads in exchange for wall-clock parallelism.
env:
SHARD_FILES: ${{ matrix.shard.files }}
# Enforcement switch. "1" = blocking: a non-baselined CRITICAL/HIGH
# fails the build. scan_packages.py scans code-only (docstrings/comments
# stripped), fetches sdist-only packages directly from PyPI (no build)
# so every shard resolves, and honors the reviewed allowlist at
# scripts/scan_packages_baseline.json, so only NON-baselined
# CRITICAL/HIGH cause its exit 1. The committed baseline makes all three
# shards exit 0 today; set this back to "0" to return to advisory.
SCAN_ENFORCE: "1"
run: |
set +e
mkdir -p logs
@ -897,14 +884,12 @@ jobs:
fi
done
echo "::endgroup::"
rc=0
if [ ${#REQ_ARGS[@]} -eq 0 ]; then
echo "[security-audit] shard ${{ matrix.shard.id }}: no PyPI specs, nothing to scan" \
| tee "$LOG"
else
python scripts/scan_packages.py --with-deps "${REQ_ARGS[@]}" \
2>&1 | tee "$LOG"
rc=${PIPESTATUS[0]}
fi
{
echo "## scan_packages :: shard ${{ matrix.shard.id }}"
@ -912,19 +897,11 @@ jobs:
echo "### Files in this shard"
for f in $SHARD_FILES; do echo "- audit-reqs/$f.txt"; done
echo
echo "scan_packages.py exit code: $rc (enforce=$SCAN_ENFORCE)"
echo
echo '### Findings (tail)'
echo '```'
tail -200 "$LOG"
echo '```'
} >> "$GITHUB_STEP_SUMMARY"
# Advisory by default; blocking once SCAN_ENFORCE=1 and the baseline
# is committed. PIPESTATUS is captured above so `tee` does not mask the
# scanner's exit code.
if [ "$SCAN_ENFORCE" = "1" ]; then
exit "$rc"
fi
- uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
if: always()
@ -964,7 +941,7 @@ jobs:
# documented at scripts/scan_npm_packages.py top-of-file. The
# script is stdlib-only so adding it does not increase the
# transitive supply-chain surface.
name: npm scan-packages (Unsloth frontend tarballs)
name: npm scan-packages (Studio frontend tarballs)
runs-on: ubuntu-latest
timeout-minutes: 30
needs: []
@ -998,37 +975,24 @@ jobs:
python3 -c "import ast; ast.parse(open('scripts/scan_npm_packages.py').read())"
- name: Scan npm tarballs (declared + transitive, no install)
# scan_npm_packages.py exits 1 on NON-baselined HIGH/CRITICAL
# findings, 0 otherwise. It scans code-only (JS/TS comments are
# blanked first) and honors a reviewed allowlist at
# scripts/scan_npm_packages_baseline.json. It never runs
# `npm install`, never executes anything from a downloaded
# tarball, and only fetches from registry.npmjs.org. The npm
# corpus is clean (the baseline is empty), so the gate is
# enforcing (SCAN_ENFORCE=1) and any new finding fails the build.
env:
SCAN_ENFORCE: "1"
# The script exits 1 on HIGH/CRITICAL findings; we capture the
# full log and surface it in the step summary either way. It
# never runs `npm install`, never executes anything from a
# downloaded tarball, and only fetches from registry.npmjs.org.
# Initially non-blocking so the baseline can settle; drop
# continue-on-error once the baseline is clean for a week.
run: |
set +e
set -o pipefail
LOG=logs-scan-npm.txt
python3 scripts/scan_npm_packages.py 2>&1 | tee "$LOG"
rc=${PIPESTATUS[0]}
{
echo "## scan_npm_packages"
echo
echo "scan_npm_packages.py exit code: $rc (enforce=$SCAN_ENFORCE)"
echo
echo '### Findings (tail)'
echo '```'
tail -300 "$LOG"
echo '```'
} >> "$GITHUB_STEP_SUMMARY"
# Blocking: the npm corpus is clean, so any non-baselined
# HIGH/CRITICAL is new and should fail the build. PIPESTATUS is
# captured above so `tee` does not mask the scanner's exit code.
if [ "$SCAN_ENFORCE" = "1" ]; then
exit "$rc"
fi
- uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
if: always()
@ -1173,7 +1137,7 @@ jobs:
with:
python-version: '3.12'
- name: Install Unsloth frontend deps (--ignore-scripts)
- name: Install Studio frontend deps (--ignore-scripts)
# `npm audit signatures` requires node_modules to be populated.
# `--ignore-scripts` is mandatory: this is exactly the lever the
# new-install-script gate below protects against, and we must

View file

@ -1,156 +0,0 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
# Measures where Studio's startup time goes, on each platform.
#
# Nothing recorded a number before: main.py logs "lifespan startup completed in X ms"
# and studio_test_kit polls /healthz, but both throw the elapsed time away. A first
# local run (Linux, warm cache, 18-core server) put `import main` at 5.7-6.6s BEFORE
# the server can bind, dominated by eager module-level imports pulled in by routes:
# torch ~1.9s self, unsloth_zoo ~0.8s, routes ~0.6s, transformers ~0.5s.
#
# Not a gate yet: --max-healthz-seconds exists, but a budget should come from
# observed numbers rather than a guess.
name: Startup profile
on:
pull_request:
paths:
# The measured import graph is the whole backend tree: main.py imports auth,
# core, hub, loggers, models, picker, routes and utils at module scope.
- 'studio/backend/**'
- '!studio/backend/tests/**'
# The launch phase spawns `unsloth studio --api-only`, so the CLI counts too.
- 'unsloth_cli/**'
- 'studio/src-tauri/src/preflight**'
# The profiler hardcodes the desktop argv that process.rs::backend_args builds,
# so a change there must schedule a run or the two silently diverge.
- 'studio/src-tauri/src/process.rs'
- 'scripts/profile_startup.py'
- '.github/workflows/startup-profile-ci.yml'
# The job profiles whatever `install.sh --local` built: the installers pick the
# venv's Python and the dependency specs, and pyproject's include list is what
# makes --local overlay studio.backend*.
- 'install.sh'
- 'install.ps1'
- 'pyproject.toml'
# --local also runs the checkout's setup scripts (install.sh picks
# $_REPO_ROOT/studio/setup.sh, the editable install resolves setup.ps1 to the
# repo), and both call install_python_stack.py, which picks the dependencies.
- 'studio/setup.sh'
- 'studio/setup.ps1'
- 'studio/install_python_stack.py'
workflow_dispatch:
inputs:
repeats:
description: 'launch repeats per OS (median reported)'
type: string
default: '3'
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
permissions:
contents: read
jobs:
profile:
name: startup ${{ matrix.os }}
runs-on: ${{ matrix.os }}
timeout-minutes: 60
continue-on-error: true
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest, macos-14, windows-latest]
env:
UNSLOTH_STUDIO_HOME: ${{ github.workspace }}/.studio-home
# A wildcard bind calls ifconfig.me on the startup path; loopback times our code.
UNSLOTH_STUDIO_DISABLE_PUBLIC_CHECK: '1'
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
persist-credentials: false
- name: Install Studio
shell: bash
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
set -o pipefail
mkdir -p logs
# --local is load-bearing: it overlays the checkout, so the profiled server
# is this diff. Without it install.sh resolves unsloth from PyPI.
if [ "${{ runner.os }}" = "Windows" ]; then
pwsh -NoProfile -File ./install.ps1 --local 2>&1 | tee logs/install.log
else
bash install.sh --local 2>&1 | tee logs/install.log
fi
- name: Profile startup
shell: bash
run: |
BIN="$UNSLOTH_STUDIO_HOME/unsloth_studio/bin/unsloth"
[ -x "$BIN" ] || BIN="$UNSLOTH_STUDIO_HOME/unsloth_studio/Scripts/unsloth.exe"
[ -x "$BIN" ] || BIN=""
# Profile imports with the INSTALLED interpreter: that venv is what launches.
PY="$UNSLOTH_STUDIO_HOME/unsloth_studio/bin/python"
[ -x "$PY" ] || PY="$UNSLOTH_STUDIO_HOME/unsloth_studio/Scripts/python.exe"
[ -x "$PY" ] || PY="$(command -v python3 || command -v python)"
python3 scripts/profile_startup.py \
--python "$PY" \
${BIN:+--bin "$BIN"} \
--repeats "${{ inputs.repeats || '3' }}" \
--json "startup-${{ matrix.os }}.json" 2>&1 | tee logs/profile.log
- name: Summary
if: always()
shell: bash
run: |
f="startup-${{ matrix.os }}.json"
[ -f "$f" ] || { echo "no profile produced"; exit 0; }
python3 - "$f" >> "$GITHUB_STEP_SUMMARY" <<'PY'
import json, sys
d = json.load(open(sys.argv[1]))
print(f"### {d['platform']} / {d['machine']} (py {d['python']}, {d['cpu_count']} cpu)\n")
imp = d.get("imports", {})
# Gate on ok: a failed `import main` still leaves rows, so a total can lie.
if imp.get("ok"):
print(f"**`import main`: {imp['total_seconds']}s**\n")
print("| package | self ms |")
print("|---|---:|")
for k, v in list(imp.get("self_by_package_ms", {}).items())[:8]:
print(f"| {k} | {v} |")
print()
else:
print("**`import main` failed - no valid import profile**\n")
print("```\n" + (imp.get("error") or "")[-1500:] + "\n```\n")
lau = d.get("launch") or {}
runs = len(lau.get("runs") or [])
failed = lau.get("failed_runs") or 0
if lau.get("healthz_median_seconds") is not None:
# The aggregates cover only the runs that reached healthz, so flag the
# failures: bare numbers would read as a normal fast startup.
note = f" _({runs - failed} of {runs} launches; {failed} never became healthy)_" if failed else ""
print(f"**time to a healthy port: {lau['healthz_median_seconds']}s median, "
f"{lau['healthz_max_seconds']}s max**{note}\n")
elif lau.get("skipped"):
print(f"_launch phase skipped: {lau['skipped']}_\n")
elif runs:
print(f"**no launch measurement: all {runs} launches failed to become healthy**\n")
PY
- name: Upload profile
if: always()
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
with:
name: startup-profile-${{ matrix.os }}
path: |
startup-*.json
logs/
retention-days: 14
if-no-files-found: warn

View file

@ -1,7 +1,7 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
# Unsloth API & Auth Tests -- HTTP-level integration tests for the
# Studio API & Auth Tests -- HTTP-level integration tests for the
# FastAPI surface. No Playwright, no model UI; tests/studio/test_studio_api_smoke.py
# runs ~30 s and asserts:
# - CORS hardening (no wildcard + credentials, no bootstrap leak)
@ -15,7 +15,7 @@
# Reuses the GGUF cache key from studio-ui-smoke.yml so the model
# download is one cache-hit on the second job.
name: Unsloth API CI
name: Studio API CI
on:
pull_request:
@ -40,7 +40,7 @@ permissions:
jobs:
api-smoke:
name: Unsloth API & Auth Tests
name: Studio API & Auth Tests
runs-on: ubuntu-latest
timeout-minutes: 12
env:
@ -83,8 +83,7 @@ jobs:
id: prime-hf
if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p hf-cache
@ -98,11 +97,10 @@ jobs:
path: hf-cache
key: ${{ runner.os }}-hf-${{ env.GGUF_REPO }}-${{ env.GGUF_VARIANT }}-v2
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
@ -111,10 +109,9 @@ jobs:
- name: Install pyjwt for the JWT-expiry forge test
run: pip install 'pyjwt>=2.6'
- name: Reset auth + boot Unsloth (API-only)
- name: Reset auth + boot Studio (API-only)
run: |
# Wipe (not reset-password): the boot below must re-seed a fresh .bootstrap_password.
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -145,7 +142,7 @@ jobs:
echo "STUDIO_NEW_PW=$NEW" >> "$GITHUB_ENV"
echo "STUDIO_NEW2_PW=$NEW2" >> "$GITHUB_ENV"
- name: Run Unsloth API & Auth tests
- name: Run Studio API & Auth tests
# The script is named WITHOUT a `test_` prefix so it isn't
# auto-collected by pytest in Backend CI's `tests/` walk
# (which doesn't set BASE_URL and would crash at import).
@ -154,7 +151,7 @@ jobs:
STUDIO_AUTH_DIR: /home/runner/.unsloth/studio/auth
run: python tests/studio/studio_api_smoke.py
- name: Stop Unsloth
- name: Stop Studio
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true

View file

@ -30,13 +30,6 @@ on:
- 'unsloth/**'
- 'unsloth_cli/**'
- 'tests/**'
# The root installers: tests/sh/*.sh and tests/studio/install/* assert
# against these two files, so a change here must run the suite that
# covers it. Without them an install-only edit (the shape most AMD/ROCm
# routing fixes take) skipped Backend CI entirely.
- 'install.sh'
- 'install.ps1'
- 'scripts/**'
- 'pyproject.toml'
- '.github/workflows/studio-backend-ci.yml'
push:
@ -71,20 +64,19 @@ jobs:
- name: Install backend test dependencies (CPU only)
run: |
python -m pip install --upgrade pip
# Unsloth's declared backend deps:
# Studio's declared backend deps:
pip install -r studio/backend/requirements/studio.txt
# Extras that studio.txt does not list but the import chain needs
# (python-multipart for FastAPI form/file uploads, sqlalchemy/cryptography
# for the auth DB, yaml/jinja2 for utils.models.model_config, psutil for
# the orphan-cleanup process scan, etc.):
# for the auth DB, yaml/jinja2 for utils.models.model_config, etc.):
pip install \
python-multipart aiofiles sqlalchemy cryptography psutil \
python-multipart aiofiles sqlalchemy cryptography \
pyyaml jinja2 mammoth unpdf requests \
'numpy<3' pytest pytest-asyncio httpx
# Torch CPU + transformers are required by a chunk of the backend test
# suite (gpu_selection, kv_cache_estimation, utils). CPU-only torch
# keeps the install ~250 MB / ~1 min on a clean runner.
pip install --index-url https://download.pytorch.org/whl/cpu --extra-index-url https://pypi.org/simple 'torch>=2.4,<2.11'
pip install --index-url https://download.pytorch.org/whl/cpu 'torch>=2.4,<2.11'
pip install 'transformers>=4.51,<5.5'
- name: Backend tests
@ -141,11 +133,11 @@ jobs:
python -m pip install --upgrade pip
pip install -r studio/backend/requirements/studio.txt
pip install \
python-multipart aiofiles sqlalchemy cryptography psutil \
python-multipart aiofiles sqlalchemy cryptography \
pyyaml jinja2 mammoth unpdf requests typer \
'numpy<3' pytest pytest-asyncio httpx
# torchvision: unsloth_zoo.vision_utils imports it at module scope.
pip install --index-url https://download.pytorch.org/whl/cpu --extra-index-url https://pypi.org/simple \
pip install --index-url https://download.pytorch.org/whl/cpu \
'torch>=2.4,<2.11' 'torchvision<0.26'
pip install 'transformers>=4.51,<5.5'
# bitsandbytes: hard import in unsloth/models/_utils.py. Recent
@ -200,7 +192,6 @@ jobs:
--ignore=tests/sh \
--ignore=tests/studio/test_hardware_dispatch_matrix.py \
--ignore=tests/studio/test_is_mlx_dispatch_gate.py \
--ignore=tests/studio/test_xpu_spoof_pipeline.py \
--ignore=tests/vllm_compat \
--ignore=tests/version_compat \
-m 'not server and not e2e' \
@ -213,53 +204,29 @@ jobs:
env:
PYTHONPATH: ${{ github.workspace }}/studio
UNSLOTH_COMPILE_DISABLE: '1'
# These files mutate hardware.py module globals at runtime via the
# spoof fixtures (CUDA/ROCm/XPU/MLX/CPU), which leaks state into any
# other test that imports hardware. Run them in their own pytest
# invocation so the leak does not cross file boundaries.
# These two files mutate hardware.py module globals at runtime
# via the spoof fixtures, which leaks state into any other test
# that imports hardware. Run them in their own pytest invocation
# so the leak does not cross file boundaries.
run: |
python -m pytest -q --tb=short \
tests/studio/test_hardware_dispatch_matrix.py \
tests/studio/test_is_mlx_dispatch_gate.py \
tests/studio/test_xpu_spoof_pipeline.py
- name: CLI tests (unsloth_cli)
# unsloth_cli/tests had no CI at all: `unsloth_cli/**` was only a paths
# trigger and a ruff target, so 673 tests covering the studio launcher,
# the pre-exposure gate and the auth secret writers ran nowhere, and
# four of them had been failing on main unnoticed.
# Own step, not folded into the tests/ discovery above: pyproject's
# testpaths is tests/, and this suite needs no PYTHONPATH or CUDA spoof
# (it self-bootstraps sys.path and imports neither unsloth nor torch).
run: python -m pytest unsloth_cli/tests -q --tb=short
tests/studio/test_is_mlx_dispatch_gate.py
- name: Shell installer tests
# Auto-discovered rather than allowlisted. The old hardcoded list had
# silently fallen seven files behind tests/run_all.sh, including
# test_strixhalo_wsl_reroute.sh -- the only shell coverage of the ROCm
# WSL reroute -- so that suite never ran on a PR. Skips are explicit,
# each with a reason, and tests/studio/test_ci_shell_suite_coverage.py
# fails if this step stops discovering the directory or the skip list
# grows without one.
#
# Skipped:
# test_install_host_defaults.sh: asserts an install.ps1 layout that
# has drifted (separate followup).
# test_install_rollback_lifecycle.sh: already runs on both platforms
# in cross-platform-parity-ci.yml.
# Subset that does not depend on a writable / pristine install.sh
# tree; test_install_host_defaults.sh checks install.ps1 layout
# which has drifted (separate followup).
run: |
set -e
skip="test_install_host_defaults.sh test_install_rollback_lifecycle.sh"
found=0
for s in tests/sh/test_*.sh; do
case " $skip " in
*" $(basename "$s") "*) echo "skipping $s (see workflow comment)"; continue ;;
esac
found=$((found + 1))
for s in \
tests/sh/test_get_torch_index_url.sh \
tests/sh/test_mac_intel_compat.sh \
tests/sh/test_nvcc_meets_llama_minimum.sh \
tests/sh/test_tauri_install_exit_order.sh \
tests/sh/test_torch_constraint.sh; do
echo "::group::$s"
bash "$s"
echo "::endgroup::"
done
[ "$found" -gt 0 ] || { echo "::error::no shell tests discovered under tests/sh"; exit 1; }
echo "ran $found shell installer test files"

View file

@ -1,76 +0,0 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
# Runs studio/backend/tests/test_export_capability.py on Linux, Windows and macOS.
#
# export_capability() is per-OS (is_apple_silicon() and the PyTorch-import probe differ per
# platform) and the export backend must import without PyTorch, so this confirms the gating and
# import-safety on hosted Windows/macOS. Hosted runners have no GPU/MLX, so a real accelerator
# export is validated separately. No GPU / model / llama.cpp: the tests mock the probes and block
# torch/unsloth, so the job installs only a CPU PyTorch plus import deps.
name: Unsloth export capability
on:
pull_request:
paths:
- 'studio/backend/utils/hardware/hardware.py'
- 'studio/backend/core/export/export.py'
- 'studio/backend/routes/export.py'
- 'studio/backend/main.py'
- 'studio/backend/tests/test_export_capability.py'
- '.github/workflows/studio-export-capability-ci.yml'
push:
branches: [main]
paths:
- 'studio/backend/utils/hardware/hardware.py'
- 'studio/backend/core/export/export.py'
- 'studio/backend/routes/export.py'
- 'studio/backend/main.py'
- 'studio/backend/tests/test_export_capability.py'
- '.github/workflows/studio-export-capability-ci.yml'
workflow_dispatch:
concurrency:
group: ${{ github.workflow }}-${{ github.ref }}
cancel-in-progress: true
permissions:
contents: read
jobs:
capability:
name: capability (${{ matrix.os }})
strategy:
fail-fast: false
matrix:
os: [ubuntu-latest, windows-latest, macos-latest]
runs-on: ${{ matrix.os }}
timeout-minutes: 20
env:
# No accelerator on hosted runners; keep detection on the CPU path.
CUDA_VISIBLE_DEVICES: ""
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
persist-credentials: false
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
with:
python-version: '3.12'
cache: 'pip'
- name: Upgrade pip
run: python -m pip install --upgrade pip
- name: Install CPU PyTorch
# CPU wheel index so every OS gets a CPU build; keep PyPI as an extra index so torch's
# transitive deps still resolve (matching the other workflows in this repo).
run: python -m pip install --index-url https://download.pytorch.org/whl/cpu --extra-index-url https://pypi.org/simple "torch>=2.4,<2.13"
- name: Install backend import deps
# Enough to import utils.hardware and core.export.export; NOT unsloth (needs a GPU, and
# the import-safety test blocks it) or triton/llama.cpp (Linux-only / native builds).
run: python -m pip install
transformers peft accelerate safetensors huggingface_hub datasets
sentencepiece protobuf fastapi starlette structlog psutil
python-multipart pydantic httpx "numpy<3" pytest
- name: Export capability + import-safety tests
working-directory: studio/backend
run: python -m pytest tests/test_export_capability.py -q

View file

@ -133,13 +133,10 @@ jobs:
- name: Typecheck
run: npm run typecheck
- name: Unit tests
run: npm test
- name: Build
run: npm run build
- name: Built bundle must not contain Unsloth's unstable_Provider call site
- name: Built bundle must not contain Studio's unstable_Provider call site
run: |
set -e
JS=$(ls dist/assets/index-*.js | head -1)
@ -147,7 +144,7 @@ jobs:
echo "main bundle: $JS"
echo "unstable_Provider: hits=$HITS (assistant-ui internals contribute up to 3)"
if [ "$HITS" -gt 3 ]; then
echo "::error file=studio/frontend/src/features/chat/runtime-provider.tsx::Unsloth bundle still passes unstable_Provider through useRemoteThreadListRuntime; this is the 2026.5.1 chat-history regression. Pass adapters directly into useLocalRuntime instead."
echo "::error file=studio/frontend/src/features/chat/runtime-provider.tsx::Studio bundle still passes unstable_Provider through useRemoteThreadListRuntime; this is the 2026.5.1 chat-history regression. Pass adapters directly into useLocalRuntime instead."
exit 1
fi

View file

@ -1,7 +1,7 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
# Three end-to-end smoke jobs that boot a freshly-installed Unsloth and
# Three end-to-end smoke jobs that boot a freshly-installed Studio and
# exercise the surfaces real users hit through the OpenAI / Anthropic
# SDKs and curl. Each job picks the smallest model that exercises the
# behaviour under test, primes HF_HOME via actions/cache, and shares
@ -27,7 +27,7 @@
# All three jobs run in parallel. Total wall time is dominated by job 3
# on a cold cache; warm cache cuts that to ~3 min.
name: Unsloth GGUF CI
name: Studio GGUF CI
on:
pull_request:
@ -97,8 +97,7 @@ jobs:
id: prime-hf
if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p hf-cache
@ -112,11 +111,10 @@ jobs:
path: hf-cache
key: ${{ runner.os }}-hf-${{ env.GGUF_REPO }}-${{ env.GGUF_VARIANT }}-v2
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
@ -125,10 +123,9 @@ jobs:
- name: Install OpenAI + Anthropic Python SDKs
run: pip install 'openai>=1.50' 'anthropic>=0.40'
- name: Reset auth + boot Unsloth (API-only)
- name: Reset auth + boot Studio (API-only)
run: |
# Wipe (not reset-password): the boot below must re-seed a fresh .bootstrap_password.
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -143,7 +140,7 @@ jobs:
fi
sleep 1
done
echo "Unsloth did not become healthy in 180s"
echo "Studio did not become healthy in 180s"
tail -200 logs/studio.log
exit 1
@ -230,11 +227,11 @@ jobs:
return replies
def run_anthropic():
# Two SDK quirks vs. Unsloth:
# Two SDK quirks vs. Studio:
# 1. base_url must NOT include /v1 -- the SDK appends
# /v1/messages itself; otherwise the request hits
# /v1/v1/messages and 405s.
# 2. The SDK sends `x-api-key` by default, but Unsloth's
# 2. The SDK sends `x-api-key` by default, but Studio's
# auth layer is HTTPBearer-only. Override via
# default_headers so Authorization: Bearer ... is
# sent instead.
@ -277,7 +274,7 @@ jobs:
print(
f"[{label}] WARN non-determinism at temperature=0.0 across "
f"{len(determinism_failures)} of {len(first)} turn(s); "
f"small-quant model drift, not an Unsloth regression. "
f"small-quant model drift, not a Studio regression. "
f"Details: " + " | ".join(determinism_failures)
)
# Sanity: turn-2 reply should mention the earlier question, and
@ -291,7 +288,7 @@ jobs:
print(f"[{label}] {status_word} -- 4 turns, history grounded ('paris' present)")
PY
- name: Stop Unsloth
- name: Stop Studio
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true
@ -320,20 +317,17 @@ jobs:
timeout-minutes: 25
env:
# Tool calling is the highest-volume GGUF in this workflow
# (Qwen3.5-2B at Q4_K_XL = ~1.28 GiB). Caching HF_HOME would
# (Qwen3.5-2B at IQ3_XXS = ~890 MiB). Caching HF_HOME would
# store xet chunks + blobs + snapshots = ~4 GiB compressed --
# 4-5x file-size inflation, dominated by xet chunks. Use main's
# `--local-dir gguf-cache` pattern to cache the flat .gguf only.
# Unsloth's /api/inference/load accepts either a HF repo (which
# Studio's /api/inference/load accepts either a HF repo (which
# uses HF_HOME) or an absolute file path; passing the absolute
# path keeps the test off HF_HOME entirely so the cache size
# tracks the GGUF file 1:1. The OpenAI/Anth and JSON+images
# jobs still cover the gguf_variant resolution path.
# Q4_K_XL, not IQ3_XXS: at IQ3_XXS this model emits malformed
# tool calls that llama-server's peg-native parser rejects with a
# 500. Mac/Windows already use Q4_K_XL for the same reason.
GGUF_REPO: unsloth/Qwen3.5-2B-GGUF
GGUF_FILE: Qwen3.5-2B-UD-Q4_K_XL.gguf
GGUF_FILE: Qwen3.5-2B-UD-IQ3_XXS.gguf
STUDIO_PORT: '18889'
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
@ -367,8 +361,7 @@ jobs:
id: download-gguf
if: steps.cache-gguf.outputs.cache-hit != 'true' || steps.cache-gguf.outcome != 'success'
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p gguf-cache
@ -381,17 +374,16 @@ jobs:
path: gguf-cache
key: ${{ runner.os }}-gguf-${{ env.GGUF_REPO }}-${{ env.GGUF_FILE }}-v1
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
bash install.sh --local --no-torch 2>&1 | tee logs/install.log
- name: Reset auth + boot Unsloth (API-only, default tool policy)
- name: Reset auth + boot Studio (API-only, default tool policy)
# We deliberately use the API-only mode rather than
# `unsloth studio run` because the latter calls
# `set_tool_policy(...)` with a resolved bool: on loopback the
@ -401,7 +393,7 @@ jobs:
# tool_policy=None so each request's `enable_tools` field is
# honoured.
run: |
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -445,8 +437,6 @@ jobs:
python - <<'PY'
import json
import os
import time
import urllib.error
import urllib.request
BASE = os.environ["BASE_URL"]
@ -467,26 +457,10 @@ jobs:
"Content-Type": "application/json",
},
)
# Shared CI runners stall sporadically, so retry transport-level
# failures only; HTTP status errors surface immediately. Bounded
# to fit the job's timeout-minutes: short probes get 3 full
# attempts, long probes one retry capped at 300s (a healthy
# server answers a retry quickly; a stalled one never does).
attempts = 3 if timeout <= 300 else 2
for attempt in range(attempts):
try:
t = timeout if attempt == 0 else min(timeout, 300)
with urllib.request.urlopen(req, timeout = t) as resp:
return resp.status, json.loads(resp.read().decode())
except urllib.error.HTTPError:
raise
except (TimeoutError, ConnectionError, urllib.error.URLError) as exc:
if attempt == attempts - 1:
raise
print(f"[retry] {path}: {exc!r}", flush = True)
time.sleep(15)
with urllib.request.urlopen(req, timeout = timeout) as resp:
return resp.status, json.loads(resp.read().decode())
def post_sse(path, body, *, timeout = 600, retries = 1, complete_on = None):
def post_sse(path, body, *, timeout = 600):
"""POST a streaming request and accumulate the assistant
text deltas. The server-side agentic loop ALWAYS returns
SSE regardless of the request's `stream` field, so any
@ -502,22 +476,6 @@ jobs:
invocation markers / tool output, since
`delta.content` alone is not evidence
that the tool path executed.
A shared CI runner can stall the stream transport (the
connection opening, or a mid-stream read) even when Unsloth
is healthy, so retry a stall once with a fresh request
capped at 300s. A stall means the stream did NOT complete,
so partial events are normally NOT returned (an early
tool_start with no tool_end is not proof the tool loop
finished). The one exception is `complete_on`: an optional
predicate over the events collected so far -- when a stall
happens after it is already satisfied (the tool ran and
produced its result before the trailing read timed out),
those events are returned rather than discarded, so the
stall-after-answer case still counts. HTTP status errors
surface immediately; a stall that yields no completed result
across all attempts re-raises so the caller can rotate to
the next seed.
"""
body = {**body, "stream": True}
data = json.dumps(body).encode()
@ -530,45 +488,26 @@ jobs:
"Content-Type": "application/json",
},
)
for attempt in range(retries + 1):
parts = []
events = []
t = timeout if attempt == 0 else min(timeout, 300)
try:
with urllib.request.urlopen(req, timeout = t) as resp:
for raw in resp:
line = raw.decode().strip()
if not line.startswith("data: "):
continue
payload = line[6:]
if payload == "[DONE]":
break
events.append(payload)
try:
chunk = json.loads(payload)
except json.JSONDecodeError:
continue
for choice in chunk.get("choices", []):
delta = choice.get("delta", {}) or {}
if delta.get("content"):
parts.append(delta["content"])
return "".join(parts), events
except urllib.error.HTTPError:
raise
except (TimeoutError, ConnectionError, urllib.error.URLError) as exc:
# A stall after the tool already produced its result is
# the case this probe exists to tolerate: keep those
# events. But a stall with only an early tool_start (no
# completed output) is not proof the tool loop finished,
# so it must not pass -- retry once, then raise so
# _run_tool_probe rotates to the next seed.
if complete_on is not None and complete_on(events):
print(f"[retry-sse] {path}: {exc!r}; keeping {len(events)} completed events", flush = True)
return "".join(parts), events
if attempt == retries:
raise
print(f"[retry-sse] {path}: {exc!r}", flush = True)
time.sleep(15)
parts = []
events = []
with urllib.request.urlopen(req, timeout = timeout) as resp:
for raw in resp:
line = raw.decode().strip()
if not line.startswith("data: "):
continue
payload = line[6:]
if payload == "[DONE]":
break
events.append(payload)
try:
chunk = json.loads(payload)
except json.JSONDecodeError:
continue
for choice in chunk.get("choices", []):
delta = choice.get("delta", {}) or {}
if delta.get("content"):
parts.append(delta["content"])
return "".join(parts), events
_STUDIO_TOOL_TYPES = {
"tool_start", "tool_end", "tool_use", "tool_result",
@ -576,11 +515,11 @@ jobs:
def _tool_invoked(events):
"""Structural check: True iff some SSE payload is a real
tool envelope (Unsloth tool_start/tool_end, Anthropic
tool envelope (Studio tool_start/tool_end, Anthropic
tool_use/tool_result, OpenAI non-empty delta.tool_calls /
message.tool_calls / finish_reason='tool_calls' /
role:'tool' / function_call). tool_status is NOT
evidence: Unsloth emits empty tool_status events on
evidence: Studio emits empty tool_status events on
iteration boundaries even when no tool ran.
"""
for raw in events:
@ -699,61 +638,23 @@ jobs:
attempt has structural invocation evidence. WARN (not
FAIL) if invoked but no attempt produces the expected
literal in tool_end.result -- small-quant Qwen3.5-2B can
emit OpenAI tool_calls deltas without Unsloth's GGUF
emit OpenAI tool_calls deltas without Studio's GGUF
agentic loop intercepting them, and that GGUF-vs-OpenAI
format mismatch is out of scope for #5642.
"""
attempts_log = []
best = None
# Cap the wall-clock spent rotating through stalled seeds so a
# persistent no-data wedge fails fast (clean assertion) instead
# of being killed by the job's timeout-minutes. A healthy or
# merely degenerate round answers in seconds, so all seeds still
# run in the normal case; only stalls consume the budget.
probe_deadline = time.monotonic() + 300
for attempt_i in range(max_attempts):
# Cap each read by the budget still remaining (not just a flat
# 180s) and skip an attempt too small to finish, so the whole
# rotation stays within ~300s -- two probes then fit the job's
# timeout-minutes even if every seed stalls.
remaining = int(probe_deadline - time.monotonic())
if attempt_i and remaining < 30:
print(f"[tools] {label}: seed-rotation budget spent after {attempt_i} attempts", flush = True)
break
attempt_seed = SEED + attempt_i
try:
# Bounded per-attempt timeout, no inner retry -- the seed
# loop IS the retry, so a stall raises quickly and rotates
# rather than spending post_sse's full 600+300s. complete_on
# keeps a stall that already produced the tool result (only
# the trailing read timed out) instead of discarding it.
content, events = post_sse("/v1/chat/completions", {
"messages": [{"role": "user", "content": prompt}],
"enable_tools": True,
"permission_mode": "full",
"enabled_tools": enabled,
"session_id": f"{session}-att{attempt_i}",
"temperature": TOOL_PROBE_TEMP,
"seed": attempt_seed,
"max_tokens": 600,
}, timeout = min(180, remaining), retries = 0,
complete_on = lambda ev: _tool_invoked(ev) and _tool_output_contains(ev, *needles))
except urllib.error.HTTPError:
# HTTPError subclasses URLError, so re-raise a real 4xx/5xx
# here instead of letting the transport-stall handler below
# swallow it and rotate seeds -- an endpoint status failure
# must surface, not be masked as missing tool evidence.
raise
except (TimeoutError, ConnectionError, urllib.error.URLError) as exc:
# A transport stall that outlived post_sse's own retry:
# log it as a failed attempt and rotate to the next seed
# rather than sinking the whole probe on one bad stream.
attempts_log.append({
"attempt": attempt_i, "seed": attempt_seed,
"transport_error": repr(exc),
})
print(f"[tools] retry {label} attempt {attempt_i}: transport {exc!r}", flush = True)
continue
content, events = post_sse("/v1/chat/completions", {
"messages": [{"role": "user", "content": prompt}],
"enable_tools": True,
"enabled_tools": enabled,
"session_id": f"{session}-att{attempt_i}",
"temperature": TOOL_PROBE_TEMP,
"seed": attempt_seed,
"max_tokens": 600,
})
invoked = _tool_invoked(events)
produced = _tool_output_contains(events, *needles)
attempts_log.append({
@ -812,21 +713,17 @@ jobs:
# because (a) the search may legitimately return no results,
# and (b) DuckDuckGo upstream blocks GHA IP ranges often
# enough that requiring a tool_call marker would create
# red-herring failures from infra rather than from Unsloth.
# red-herring failures from infra rather than from Studio.
try:
# Best-effort and bounded: a single 180s attempt keeps a stall
# from eating the job's timeout-minutes (it already WARNs, so a
# retry buys nothing).
content, events = post_sse("/v1/chat/completions", {
"messages": [{"role": "user", "content": "Search the web for 'unsloth ai github' and summarise."}],
"enable_tools": True,
"permission_mode": "full",
"enabled_tools": ["web_search"],
"session_id": "ci-tool-calling-web",
"temperature": 0.0,
"seed": SEED,
"max_tokens": 400,
}, timeout = 180, retries = 0)
})
print(
f"[tools] PASS web_search stream ({len(content)} chars in content, "
f"{len(events)} raw events)"
@ -835,7 +732,7 @@ jobs:
print(f"[tools] WARN web_search probe failed (non-blocking): {exc}")
# ── 5. Thinking on / off ─────────────────────────────────────
# Unsloth strips think blocks from message.content for tools-mode
# Studio strips think blocks from message.content for tools-mode
# responses, so we toggle plain chat (no enable_tools) and look
# at the surfaced reasoning_content / message.thinking field.
def thinking_call(enable):
@ -849,7 +746,7 @@ jobs:
})
assert status == 200
msg = data["choices"][0]["message"]
# Unsloth surfaces thinking via reasoning_content (OpenAI
# Studio surfaces thinking via reasoning_content (OpenAI
# extension). Fall back to inline <think> markers for
# robustness across template versions.
raw = (msg.get("content") or "") + (msg.get("reasoning_content") or "")
@ -869,15 +766,12 @@ jobs:
print(f"[tools] PASS thinking on/off (on={len(on_text)} chars, off={len(off_text)} chars)")
PY
- name: Stop Unsloth
- name: Stop Studio
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true
sleep 2
ss -tln | grep ":${STUDIO_PORT}" || true
# Capture backend + llama-server logs so a 500 has a server-side traceback.
mkdir -p logs/server-logs
cp -r ~/.unsloth/studio/logs/. logs/server-logs/ 2>/dev/null || true
- name: Upload logs
# Always upload so green runs are still reviewable.
@ -890,7 +784,6 @@ jobs:
path: |
logs/studio.log
logs/install.log
logs/server-logs/
retention-days: 7
# ─────────────────────────────────────────────────────────────────────
@ -945,8 +838,7 @@ jobs:
id: prime-hf
if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p hf-cache
@ -961,11 +853,10 @@ jobs:
path: hf-cache
key: ${{ runner.os }}-hf-${{ env.GGUF_REPO }}-${{ env.GGUF_VARIANT }}-${{ env.MMPROJ_FILE }}-v2
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
@ -974,12 +865,12 @@ jobs:
- name: Install OpenAI + Anthropic Python SDKs
run: pip install 'openai>=1.50' 'anthropic>=0.40'
- name: Reset auth + boot Unsloth (API-only)
- name: Reset auth + boot Studio (API-only)
# See Job 2's comment: API-only mode keeps tool_policy=None so
# response_format requests aren't routed through the agentic
# tool loop.
run: |
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -1034,8 +925,6 @@ jobs:
import base64
import json
import os
import time
import urllib.error
import urllib.request
from openai import OpenAI
from anthropic import Anthropic
@ -1054,36 +943,20 @@ jobs:
"Content-Type": "application/json",
},
)
# Shared CI runners stall sporadically, so retry transport-level
# failures only; HTTP status errors surface immediately. Bounded
# to fit the job's timeout-minutes: short probes get 3 full
# attempts, long probes one retry capped at 300s (a healthy
# server answers a retry quickly; a stalled one never does).
attempts = 3 if timeout <= 300 else 2
for attempt in range(attempts):
try:
t = timeout if attempt == 0 else min(timeout, 300)
with urllib.request.urlopen(req, timeout = t) as resp:
return resp.status, json.loads(resp.read().decode())
except urllib.error.HTTPError:
raise
except (TimeoutError, ConnectionError, urllib.error.URLError) as exc:
if attempt == attempts - 1:
raise
print(f"[retry] {path}: {exc!r}", flush = True)
time.sleep(15)
with urllib.request.urlopen(req, timeout = timeout) as resp:
return resp.status, json.loads(resp.read().decode())
# ── 1. response_format = json_object (JSON mode) ─────────────
# llama.cpp's HTTP server supports OpenAI-compatible JSON
# mode: `response_format: {"type": "json_object"}` constrains
# the model to emit syntactically-valid JSON. We use raw HTTP
# rather than the OpenAI SDK so that the field shape Unsloth
# rather than the OpenAI SDK so that the field shape Studio
# forwards to llama-server is unambiguous (the SDK rewrites
# response_format depending on which variant it recognises).
# We deliberately do NOT pass a strict JSON schema -- on
# small Gemma-4 quants the GBNF-from-schema path occasionally
# produces empty output, and JSON mode is the surface we care
# about exposing through Unsloth.
# about exposing through Studio.
status, data = post("/v1/chat/completions", {
"model": "default",
"messages": [
@ -1113,7 +986,7 @@ jobs:
print(f"[json] PASS json_object -> {parsed}")
# ── 2. OpenAI image_url (data URI base64) ───────────────────
# 64x64 solid-red PNG. stb_image (used by Unsloth's image
# 64x64 solid-red PNG. stb_image (used by Studio's image
# normaliser at routes/inference.py:3410) rejects 4x4 or
# smaller PNGs as truncated, so we go up to 64x64 -- still
# tiny in token cost. The assertion is loose: any non-empty
@ -1149,9 +1022,9 @@ jobs:
print("[image/openai] PASS image_url accepted, non-empty response")
# ── 3. Anthropic source/base64 image ────────────────────────
# Two SDK quirks vs. Unsloth: base_url must NOT include /v1
# Two SDK quirks vs. Studio: base_url must NOT include /v1
# (the SDK appends it itself; otherwise /v1/v1/messages -> 405),
# and Unsloth's auth is HTTPBearer-only so the SDK's default
# and Studio's auth is HTTPBearer-only so the SDK's default
# x-api-key header is ignored -- send Authorization: Bearer
# via default_headers.
anthropic = Anthropic(
@ -1185,7 +1058,7 @@ jobs:
print("[image/anthropic] PASS source/base64 accepted, non-empty response")
PY
- name: Stop Unsloth
- name: Stop Studio
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true

View file

@ -1,7 +1,7 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
#
# Event-loop regression test for the Unsloth model-load orchestrator.
# Event-loop regression test for the Studio model-load orchestrator.
# Pins down issue #5642 (Win10 UI freeze on model load): the /load
# route calls LlamaCppBackend.detect_audio_type synchronously, blocking
# the FastAPI event loop on a chain of sync httpx.Client.post() probes.
@ -14,7 +14,7 @@
# danielhanchen/unsloth-staging-2 (Ubuntu / macOS / Windows all
# green at PR time).
name: Unsloth load-orchestrator CI
name: Studio load-orchestrator CI
on:
pull_request:

View file

@ -33,7 +33,7 @@ permissions:
jobs:
api-smoke:
name: Unsloth API & Auth Tests
name: Studio API & Auth Tests
runs-on: macos-14
timeout-minutes: 25
env:
@ -68,8 +68,7 @@ jobs:
id: prime-hf
if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p hf-cache
@ -83,11 +82,10 @@ jobs:
path: hf-cache
key: ${{ runner.os }}-hf-${{ env.GGUF_REPO }}-${{ env.GGUF_VARIANT }}-v2
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
@ -99,10 +97,9 @@ jobs:
- name: Install pyjwt for the JWT-expiry forge test
run: pip install 'pyjwt>=2.6'
- name: Reset auth + boot Unsloth (API-only)
- name: Reset auth + boot Studio (API-only)
run: |
# Wipe (not reset-password): the boot below must re-seed a fresh .bootstrap_password.
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -130,13 +127,13 @@ jobs:
echo "STUDIO_NEW_PW=$NEW" >> "$GITHUB_ENV"
echo "STUDIO_NEW2_PW=$NEW2" >> "$GITHUB_ENV"
- name: Run Unsloth API & Auth tests
- name: Run Studio API & Auth tests
env:
BASE_URL: http://127.0.0.1:18895
STUDIO_AUTH_DIR: /Users/runner/.unsloth/studio/auth
run: python tests/studio/studio_api_smoke.py
- name: Stop Unsloth
- name: Stop Studio
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true

View file

@ -1,7 +1,7 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
# Three end-to-end smoke jobs that boot a freshly-installed Unsloth and
# Three end-to-end smoke jobs that boot a freshly-installed Studio and
# exercise the surfaces real users hit through the OpenAI / Anthropic
# SDKs and curl. Each job picks the smallest model that exercises the
# behaviour under test, primes a model cache via actions/cache, and
@ -91,8 +91,7 @@ jobs:
id: prime-hf
if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p hf-cache
@ -108,11 +107,10 @@ jobs:
path: hf-cache
key: ${{ runner.os }}-hf-${{ env.GGUF_REPO }}-${{ env.GGUF_VARIANT }}-v2
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
@ -124,10 +122,9 @@ jobs:
- name: Install OpenAI + Anthropic Python SDKs
run: pip install 'openai>=1.50' 'anthropic>=0.40'
- name: Reset auth + boot Unsloth (API-only)
- name: Reset auth + boot Studio (API-only)
run: |
# Wipe (not reset-password): the boot below must re-seed a fresh .bootstrap_password.
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -142,7 +139,7 @@ jobs:
fi
sleep 1
done
echo "Unsloth did not become healthy in 180s"
echo "Studio did not become healthy in 180s"
tail -200 logs/studio.log
exit 1
@ -229,11 +226,11 @@ jobs:
return replies
def run_anthropic():
# Two SDK quirks vs. Unsloth:
# Two SDK quirks vs. Studio:
# 1. base_url must NOT include /v1 -- the SDK appends
# /v1/messages itself; otherwise the request hits
# /v1/v1/messages and 405s.
# 2. The SDK sends `x-api-key` by default, but Unsloth's
# 2. The SDK sends `x-api-key` by default, but Studio's
# auth layer is HTTPBearer-only. Override via
# default_headers so Authorization: Bearer ... is
# sent instead.
@ -284,7 +281,7 @@ jobs:
print(f"[{label}] OK -- 4 turns, run1 == run2, history grounded")
PY
- name: Stop Unsloth
- name: Stop Studio
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true
@ -349,8 +346,7 @@ jobs:
id: download-gguf
if: steps.cache-gguf.outputs.cache-hit != 'true' || steps.cache-gguf.outcome != 'success'
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p gguf-cache
@ -364,11 +360,10 @@ jobs:
path: gguf-cache
key: ${{ runner.os }}-gguf-${{ env.GGUF_REPO }}-${{ env.GGUF_FILE }}-v1
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
@ -377,7 +372,7 @@ jobs:
- name: Assert llama.cpp loads on this macOS
run: bash .github/scripts/assert-llama-loads.sh
- name: Reset auth + boot Unsloth (API-only, default tool policy)
- name: Reset auth + boot Studio (API-only, default tool policy)
# We deliberately use the API-only mode rather than
# `unsloth studio run` because the latter calls
# `set_tool_policy(...)` with a resolved bool: on loopback the
@ -387,7 +382,7 @@ jobs:
# tool_policy=None so each request's `enable_tools` field is
# honoured.
run: |
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -431,8 +426,6 @@ jobs:
python - <<'PY'
import json
import os
import time
import urllib.error
import urllib.request
BASE = os.environ["BASE_URL"]
@ -453,41 +446,14 @@ jobs:
"Content-Type": "application/json",
},
)
# Shared CI runners stall sporadically, so retry transport-level
# failures only; HTTP status errors surface immediately. Bounded
# to fit the job's timeout-minutes: short probes get 3 full
# attempts, long probes one retry capped at 300s (a healthy
# server answers a retry quickly; a stalled one never does).
attempts = 3 if timeout <= 300 else 2
for attempt in range(attempts):
try:
t = timeout if attempt == 0 else min(timeout, 300)
with urllib.request.urlopen(req, timeout = t) as resp:
return resp.status, json.loads(resp.read().decode())
except urllib.error.HTTPError:
raise
except (TimeoutError, ConnectionError, urllib.error.URLError) as exc:
if attempt == attempts - 1:
raise
print(f"[retry] {path}: {exc!r}", flush = True)
time.sleep(15)
with urllib.request.urlopen(req, timeout = timeout) as resp:
return resp.status, json.loads(resp.read().decode())
def post_sse(path, body, *, timeout = 600, retries = 1, soft = False):
def post_sse(path, body, *, timeout = 600):
"""POST a streaming request and accumulate the assistant
text deltas. The server-side agentic loop ALWAYS returns
SSE regardless of the request's `stream` field, so any
call with enable_tools=true must use this helper.
A shared CI runner can stall the stream transport (the
connection opening, or a mid-stream read) even when Unsloth
is healthy, so harden the read three ways: retry a stall
once with a fresh request capped at 300s; return any text
already streamed before a stall (a stall on the trailing
tokens, after the answer arrived, still counts); and when
every attempt yields nothing, a hard call re-raises while a
soft call (the best-effort server-side tool probes) returns
None so the caller can WARN instead of sinking the whole
job. HTTP status errors always surface immediately."""
call with enable_tools=true must use this helper."""
body = {**body, "stream": True}
data = json.dumps(body).encode()
req = urllib.request.Request(
@ -499,43 +465,24 @@ jobs:
"Content-Type": "application/json",
},
)
for attempt in range(retries + 1):
parts = []
t = timeout if attempt == 0 else min(timeout, 300)
try:
with urllib.request.urlopen(req, timeout = t) as resp:
for raw in resp:
line = raw.decode().strip()
if not line.startswith("data: "):
continue
payload = line[6:]
if payload == "[DONE]":
break
try:
chunk = json.loads(payload)
except json.JSONDecodeError:
continue
for choice in chunk.get("choices", []):
delta = choice.get("delta", {}) or {}
if delta.get("content"):
parts.append(delta["content"])
return "".join(parts)
except urllib.error.HTTPError:
raise
except (TimeoutError, ConnectionError, urllib.error.URLError) as exc:
# Text already streamed is a valid signal -- keep it
# rather than re-running a heavy generation.
if parts:
joined = "".join(parts)
print(f"[retry-sse] {path}: {exc!r}; keeping {len(joined)} partial chars", flush = True)
return joined
if attempt == retries:
if soft:
print(f"[tools] WARN {path}: SSE transport stalled with no data ({exc!r}) -- non-blocking", flush = True)
return None
raise
print(f"[retry-sse] {path}: {exc!r}", flush = True)
time.sleep(15)
parts = []
with urllib.request.urlopen(req, timeout = timeout) as resp:
for raw in resp:
line = raw.decode().strip()
if not line.startswith("data: "):
continue
payload = line[6:]
if payload == "[DONE]":
break
try:
chunk = json.loads(payload)
except json.JSONDecodeError:
continue
for choice in chunk.get("choices", []):
delta = choice.get("delta", {}) or {}
if delta.get("content"):
parts.append(delta["content"])
return "".join(parts)
# ── 1. Standard OpenAI function calling ──────────────────────
weather_tool = {
@ -575,11 +522,11 @@ jobs:
assert status == 200, f"tool call status {status}: {data}"
choice = data["choices"][0]
tool_calls = (choice.get("message") or {}).get("tool_calls") or []
# Unsloth's contract: when tool_choice='required', llama.cpp's
# Studio's contract: when tool_choice='required', llama.cpp's
# grammar should force a tool_calls payload. On Mac that
# contract is sometimes broken by the underlying quant; the
# PASS path is "tool_calls present + correct schema", the
# WARN path documents Unsloth still returned 200 with a
# WARN path documents Studio still returned 200 with a
# well-formed choices[] envelope.
if tool_calls:
tc = tool_calls[0]
@ -606,23 +553,16 @@ jobs:
# macos-14 free runner is ~10 tok/s on Qwen3.5-2B Q4_K_XL;
# cap max_tokens tightly so each SSE round stays under ~30s
# even when the model stalls in a degenerate output state.
# retries=0 on the best-effort probes: this job's 25-minute cap
# allows a 10-minute model load, so a no-data stall must be a
# single 180s attempt (not 180+15+180s) to leave room for the
# thinking checks. A soft/best-effort probe only WARNs anyway.
content = post_sse("/v1/chat/completions", {
"messages": [{"role": "user", "content": "What is 123 * 456? Use the python tool to compute it and tell me the number."}],
"enable_tools": True,
"permission_mode": "full",
"enabled_tools": ["python"],
"session_id": "ci-tool-calling-py",
"temperature": TEMP,
"seed": SEED,
"max_tokens": 128,
}, timeout = 180, retries = 0, soft = True)
if content is None:
print("[tools] WARN python tool: SSE transport stalled after retries -- non-blocking")
elif "56088" in content or "56,088" in content:
}, timeout = 180)
if "56088" in content or "56,088" in content:
print(f"[tools] PASS python tool ({len(content)} chars, found 56088)")
else:
# Empty stream is a known Mac-quant degeneracy too; log
@ -649,19 +589,18 @@ jobs:
content = post_sse("/v1/chat/completions", {
"messages": [{"role": "user", "content": "Search the web for 'unsloth ai github' and summarise."}],
"enable_tools": True,
"permission_mode": "full",
"enabled_tools": ["web_search"],
"session_id": "ci-tool-calling-web",
"temperature": TEMP,
"seed": SEED,
"max_tokens": 96,
}, timeout = 180, retries = 0)
}, timeout = 180)
print(f"[tools] PASS web_search stream ({len(content)} chars)")
except Exception as exc:
print(f"[tools] WARN web_search probe failed (non-blocking): {exc}")
# ── 4. Thinking on / off ─────────────────────────────────────
# Unsloth strips think blocks from message.content for tools-mode
# Studio strips think blocks from message.content for tools-mode
# responses, so we toggle plain chat (no enable_tools) and look
# at the surfaced reasoning_content / message.thinking field.
def thinking_call(enable):
@ -679,7 +618,7 @@ jobs:
}, timeout = 180)
assert status == 200
msg = data["choices"][0]["message"]
# Unsloth surfaces thinking via reasoning_content (OpenAI
# Studio surfaces thinking via reasoning_content (OpenAI
# extension). Fall back to inline <think> markers for
# robustness across template versions.
raw = (msg.get("content") or "") + (msg.get("reasoning_content") or "")
@ -705,7 +644,7 @@ jobs:
print(f"[tools] PASS thinking on/off (on={len(on_text)} chars, off={len(off_text)} chars)")
PY
- name: Stop Unsloth
- name: Stop Studio
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true
@ -786,8 +725,7 @@ jobs:
# Authenticated + parallel: shared macos-14 NAT egress stalls
# multi-GB anonymous downloads.
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p gguf-cache
@ -811,11 +749,10 @@ jobs:
path: gguf-cache
key: ${{ runner.os }}-gguf-${{ env.GGUF_REPO }}-${{ env.GGUF_FILE }}-${{ env.MMPROJ_FILE }}-v2
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
@ -827,12 +764,12 @@ jobs:
- name: Install OpenAI + Anthropic Python SDKs
run: pip install 'openai>=1.50' 'anthropic>=0.40'
- name: Reset auth + boot Unsloth (API-only)
- name: Reset auth + boot Studio (API-only)
# See Job 2's comment: API-only mode keeps tool_policy=None so
# response_format requests aren't routed through the agentic
# tool loop.
run: |
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -882,8 +819,6 @@ jobs:
import base64
import json
import os
import time
import urllib.error
import urllib.request
from openai import OpenAI
from anthropic import Anthropic
@ -907,36 +842,20 @@ jobs:
"Content-Type": "application/json",
},
)
# Shared CI runners stall sporadically, so retry transport-level
# failures only; HTTP status errors surface immediately. Bounded
# to fit the job's timeout-minutes: short probes get 3 full
# attempts, long probes one retry capped at 300s (a healthy
# server answers a retry quickly; a stalled one never does).
attempts = 3 if timeout <= 300 else 2
for attempt in range(attempts):
try:
t = timeout if attempt == 0 else min(timeout, 300)
with urllib.request.urlopen(req, timeout = t) as resp:
return resp.status, json.loads(resp.read().decode())
except urllib.error.HTTPError:
raise
except (TimeoutError, ConnectionError, urllib.error.URLError) as exc:
if attempt == attempts - 1:
raise
print(f"[retry] {path}: {exc!r}", flush = True)
time.sleep(15)
with urllib.request.urlopen(req, timeout = timeout) as resp:
return resp.status, json.loads(resp.read().decode())
# ── 1. response_format = json_object (JSON mode) ─────────────
# llama.cpp's HTTP server supports OpenAI-compatible JSON
# mode: `response_format: {"type": "json_object"}` constrains
# the model to emit syntactically-valid JSON. We use raw HTTP
# rather than the OpenAI SDK so that the field shape Unsloth
# rather than the OpenAI SDK so that the field shape Studio
# forwards to llama-server is unambiguous (the SDK rewrites
# response_format depending on which variant it recognises).
# We deliberately do NOT pass a strict JSON schema -- on
# small Gemma-4 quants the GBNF-from-schema path occasionally
# produces empty output, and JSON mode is the surface we care
# about exposing through Unsloth.
# about exposing through Studio.
status, data = post("/v1/chat/completions", {
"model": "default",
"messages": [
@ -1008,7 +927,7 @@ jobs:
)
# ── 2. OpenAI image_url (data URI base64) ───────────────────
# 64x64 solid-red PNG. stb_image (used by Unsloth's image
# 64x64 solid-red PNG. stb_image (used by Studio's image
# normaliser at routes/inference.py:3410) rejects 4x4 or
# smaller PNGs as truncated, so we go up to 64x64 -- still
# tiny in token cost. The assertion is loose: any non-empty
@ -1024,11 +943,11 @@ jobs:
# The Mac prebuilt llama.cpp server has a known crash when
# processing image inputs alongside the gemma-4-E2B mmproj
# (server disconnects mid-completion). This is upstream
# llama.cpp behaviour, not Unsloth. Wrap both SDK calls in
# llama.cpp behaviour, not Studio. Wrap both SDK calls in
# try/except so an upstream crash registers as a WARN rather
# than failing the whole job. Unsloth's contract (OpenAI/
# than failing the whole job. Studio's contract (OpenAI/
# Anthropic image fields are accepted and forwarded) is
# validated by the request body Unsloth constructs, not by
# validated by the request body Studio constructs, not by
# whether llama.cpp can decode it on Mac Metal.
client = OpenAI(base_url = f"{BASE}/v1", api_key = KEY)
try:
@ -1054,14 +973,14 @@ jobs:
except Exception as exc:
print(
f"[image/openai] WARN image_url SDK call raised: {type(exc).__name__}: "
f"{exc}. Likely upstream llama.cpp Mac+vision crash, NOT an Unsloth "
f"regression. Unsloth successfully forwarded the request."
f"{exc}. Likely upstream llama.cpp Mac+vision crash, NOT a Studio "
f"regression. Studio successfully forwarded the request."
)
# ── 3. Anthropic source/base64 image ────────────────────────
# Two SDK quirks vs. Unsloth: base_url must NOT include /v1
# Two SDK quirks vs. Studio: base_url must NOT include /v1
# (the SDK appends it itself; otherwise /v1/v1/messages -> 405),
# and Unsloth's auth is HTTPBearer-only so the SDK's default
# and Studio's auth is HTTPBearer-only so the SDK's default
# x-api-key header is ignored -- send Authorization: Bearer
# via default_headers.
anthropic = Anthropic(
@ -1100,11 +1019,11 @@ jobs:
print(
f"[image/anthropic] WARN anthropic image SDK call raised: "
f"{type(exc).__name__}: {exc}. Likely upstream llama.cpp Mac+vision "
f"crash, NOT an Unsloth regression."
f"crash, NOT a Studio regression."
)
PY
- name: Stop Unsloth
- name: Stop Studio
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true

View file

@ -1,7 +1,7 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
# Proves Unsloth's llama.cpp install loads on every supported macOS. The heavy
# Proves Studio's llama.cpp install loads on every supported macOS. The heavy
# app smokes stay single-OS; this matrix covers the OS-version dimension cheaply
# (install.sh + binary-load assert). Regression guard for the macOS-version
# selection in studio/install_llama_prebuilt.py.
@ -60,11 +60,10 @@ jobs:
with:
python-version: '3.12'
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail

View file

@ -19,7 +19,6 @@ on:
- 'install.sh'
- 'pyproject.toml'
- 'tests/studio/**'
- '.github/scripts/run-studio-permission-browser.sh'
- '.github/workflows/studio-mac-ui-smoke.yml'
push:
branches: [main, pip]
@ -69,8 +68,7 @@ jobs:
id: prime-hf
if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p hf-cache
@ -84,11 +82,10 @@ jobs:
path: hf-cache
key: ${{ runner.os }}-hf-${{ env.GGUF_REPO }}-${{ env.GGUF_VARIANT }}-v2
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
@ -97,7 +94,7 @@ jobs:
- name: Assert llama.cpp loads on this macOS
run: bash .github/scripts/assert-llama-loads.sh
- name: Install Playwright browsers
- name: Install Playwright + Chromium
# No --with-deps on Mac: that flag installs Linux apt packages.
# GitHub-hosted macos-14 ships the system frameworks Chromium
# needs already.
@ -113,7 +110,7 @@ jobs:
# in-script retry recover from any residual flakes.
run: |
pip install 'playwright>=1.55,<1.58'
python -m playwright install chromium webkit
python -m playwright install chromium
- name: Patch Playwright pipeTransport.js to tolerate malformed JSON
# In Playwright 1.55-1.58, pipeTransport.js does
@ -144,10 +141,9 @@ jobs:
print(f"pipeTransport.js: patched JSON.parse calls in {path}")
PY
- name: Reset auth + boot Unsloth
- name: Reset auth + boot Studio
run: |
# Wipe (not reset-password): the boot below must re-seed a fresh .bootstrap_password.
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -187,14 +183,13 @@ jobs:
# Retry up to 3 times to absorb known macos-14 free-runner
# flakes: (1) Playwright Node 24 pipeTransport.js 'Unexpected
# end of JSON input' crash when the Chromium browser process
# dies mid-test, (2) Chromium net::ERR_NO_BUFFER_SPACE when the
# runner's kernel briefly runs out of socket buffers, and (3) a
# goto 'interrupted by another navigation' when the SPA auth
# guard redirects mid-navigation. The retry FULLY resets Unsloth
# (kill, wipe auth, reboot, wait /api/health, re-export
# bootstrap pw) before re-running the script. A real test failure
# (assertion / timeout) does NOT match any pattern so it bypasses
# retry and surfaces immediately.
# dies mid-test, and (2) Chromium net::ERR_NO_BUFFER_SPACE
# when the runner's kernel briefly runs out of socket buffers.
# The retry FULLY resets Studio (kill, reset-password, reboot,
# wait /api/health, re-export bootstrap pw) before re-running
# the script. A real test failure (assertion / timeout) does
# NOT match either pattern so it bypasses retry and surfaces
# immediately.
run: |
mkdir -p logs/playwright
attempt=1
@ -207,14 +202,13 @@ jobs:
if [ "$rc" -eq 0 ]; then
break
fi
if { grep -q "Unexpected end of JSON input" logs/playwright_attempt_${attempt}.log \
|| grep -q "ERR_NO_BUFFER_SPACE" logs/playwright_attempt_${attempt}.log \
|| grep -q "interrupted by another navigation" logs/playwright_attempt_${attempt}.log; } \
if { grep -q "Unexpected end of JSON input" logs/playwright_attempt_${attempt}.log \
|| grep -q "ERR_NO_BUFFER_SPACE" logs/playwright_attempt_${attempt}.log; } \
&& [ "$attempt" -lt "$max_attempts" ]; then
echo "::warning::Playwright flake on attempt ${attempt}; resetting Unsloth and retrying..."
echo "::warning::Playwright flake on attempt ${attempt}; resetting Studio and retrying..."
kill "${STUDIO_PID}" 2>/dev/null || true
sleep 2
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> "logs/studio_retry_${attempt}.log" 2>&1 &
STUDIO_PID=$!
@ -240,19 +234,15 @@ jobs:
exit "$rc"
done
- name: Stop Unsloth (chat-ui ends with Shutdown click; this is belt-and-suspenders)
- name: Stop Studio (chat-ui ends with Shutdown click; this is belt-and-suspenders)
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true
sleep 2
- name: Cross-browser permission controls
- name: Reset auth + boot Studio for extra UI tests (port 18897)
run: |
bash .github/scripts/run-studio-permission-browser.sh 18895 webkit
- name: Reset auth + boot Unsloth for extra UI tests (port 18897)
run: |
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p 18897 \
> logs/studio_extra.log 2>&1 &
@ -277,7 +267,7 @@ jobs:
echo "STUDIO_EXTRA_OLD_PW=$OLD" >> "$GITHUB_ENV"
echo "STUDIO_EXTRA_NEW_PW=$NEW" >> "$GITHUB_ENV"
- name: Drive Compare/Recipes/Export/Unsloth/Settings with Playwright
- name: Drive Compare/Recipes/Export/Studio/Settings with Playwright
env:
BASE_URL: http://127.0.0.1:18897
STUDIO_OLD_PW: ${{ env.STUDIO_EXTRA_OLD_PW }}
@ -288,8 +278,8 @@ jobs:
STUDIO_UI_TURN_TIMEOUT_MS: '540000'
GGUF_REPO: ${{ env.GGUF_REPO }}
GGUF_VARIANT: ${{ env.GGUF_VARIANT }}
# Same flake-retry shape as "Drive the chat UI with Playwright" -- catches
# pipeTransport JSON crash, ERR_NO_BUFFER_SPACE, and nav interrupts.
# Same flake-retry shape as "Drive the chat UI with Playwright"
# -- catches pipeTransport JSON crash and ERR_NO_BUFFER_SPACE.
run: |
mkdir -p logs/playwright_extra
attempt=1
@ -302,14 +292,13 @@ jobs:
if [ "$rc" -eq 0 ]; then
break
fi
if { grep -q "Unexpected end of JSON input" logs/playwright_extra_attempt_${attempt}.log \
|| grep -q "ERR_NO_BUFFER_SPACE" logs/playwright_extra_attempt_${attempt}.log \
|| grep -q "interrupted by another navigation" logs/playwright_extra_attempt_${attempt}.log; } \
if { grep -q "Unexpected end of JSON input" logs/playwright_extra_attempt_${attempt}.log \
|| grep -q "ERR_NO_BUFFER_SPACE" logs/playwright_extra_attempt_${attempt}.log; } \
&& [ "$attempt" -lt "$max_attempts" ]; then
echo "::warning::Playwright flake on attempt ${attempt}; resetting Unsloth and retrying..."
echo "::warning::Playwright flake on attempt ${attempt}; resetting Studio and retrying..."
kill "${STUDIO_EXTRA_PID}" 2>/dev/null || true
sleep 2
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p 18897 \
> "logs/studio_extra_retry_${attempt}.log" 2>&1 &
STUDIO_EXTRA_PID=$!
@ -333,7 +322,7 @@ jobs:
exit "$rc"
done
- name: Stop second Unsloth
- name: Stop second Studio
if: always()
run: |
kill "${STUDIO_EXTRA_PID}" 2>/dev/null || true
@ -349,7 +338,5 @@ jobs:
logs/studio_extra.log
logs/install.log
logs/playwright
logs/playwright-permissions-*
logs/playwright_extra
logs/studio-permissions-*.log
retention-days: 7

View file

@ -4,15 +4,15 @@
# Mac counterpart to studio-update-smoke.yml. Verifies that on a real
# Apple Silicon (macos-14, M1) runner:
#
# 1. install.sh --local --no-torch installs Unsloth AND auto-fetches
# 1. install.sh --local --no-torch installs Studio AND auto-fetches
# the prebuilt llama.cpp Mac binary (llama-bNNNN-bin-macos-arm64
# from ggml-org/llama.cpp). Hitting the source-build fallback is
# treated as an Unsloth bug -- Unsloth must always pick the
# treated as an Unsloth bug -- Studio must always pick the
# prebuilt on Mac.
# 2. unsloth studio update --local is idempotent. Two consecutive
# runs both report "prebuilt up to date and validated", no
# source-build fallback.
# 3. The installed Unsloth still boots and /api/health returns
# 3. The installed Studio still boots and /api/health returns
# healthy after the update path.
name: Mac Studio Update CI
@ -42,7 +42,7 @@ permissions:
jobs:
update-idempotency:
name: Unsloth Updating Tests
name: Studio Updating Tests
runs-on: macos-14
timeout-minutes: 30
steps:
@ -59,11 +59,10 @@ jobs:
python-version: '3.12'
cache: 'pip'
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
@ -75,8 +74,7 @@ jobs:
- name: First update should be a no-op (prebuilt already validated)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
set -o pipefail
unsloth studio update --local 2>&1 | tee logs/update.log
@ -95,8 +93,7 @@ jobs:
- name: Second update must also be a no-op
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
set -o pipefail
unsloth studio update --local 2>&1 | tee logs/update2.log
@ -106,7 +103,7 @@ jobs:
grep -qE "prebuilt up to date and validated|prebuilt installed and validated" logs/update2.log
echo "second update was clean"
- name: Boot Unsloth briefly to confirm the install is still usable
- name: Boot Studio briefly to confirm the install is still usable
run: |
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p 18891 \
@ -123,13 +120,13 @@ jobs:
sleep 1
done
if [ -z "$HEALTHY" ]; then
echo "Unsloth failed to come up after \`update\`"
echo "Studio failed to come up after \`update\`"
tail -200 logs/studio.log
kill "$PID" 2>/dev/null || true
exit 1
fi
kill "$PID" 2>/dev/null || true
echo "post-update Unsloth /api/health OK"
echo "post-update Studio /api/health OK"
- name: Uninstall and verify clean
# Round-trip through scripts/uninstall.sh on real macOS. As a side

View file

@ -12,7 +12,7 @@
# stay in release-desktop.yml (manual `workflow_dispatch`) because they need
# code-signing secrets and ~30 min of runner time each.
name: Unsloth Tauri CI
name: Studio Tauri CI
on:
pull_request:
@ -47,7 +47,7 @@ jobs:
run: |
sudo apt-get update
sudo apt-get install -y \
libwebkit2gtk-4.1-dev libappindicator3-dev \
libwebkit2gtk-4.1-dev libayatana-appindicator3-dev \
librsvg2-dev libxdo-dev libssl-dev patchelf
- uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
@ -91,16 +91,6 @@ jobs:
npm run build
test -f dist/index.html
# The crate carries ~100 unit tests (native_file_dialogs, preflight,
# install, desktop_auth, ...) that nothing ran until now: this workflow
# only ever built. Run them here, where the toolchain and the WebKit dev
# packages are already installed, so a broken assertion fails the PR
# instead of sitting unnoticed. `--no-fail-fast` reports every failing
# test in one run rather than stopping at the first.
- name: Rust unit tests (studio/src-tauri)
working-directory: studio/src-tauri
run: cargo test --no-fail-fast
- name: Tauri debug build (Linux, no bundle, no codesign)
# `--debug` + `--no-bundle` keeps this lean: compiles the Rust crate,
# confirms the frontend dist is wired into Tauri, but skips the AppImage

View file

@ -1,8 +1,8 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
# End-to-end Unsloth chat UI smoke via Playwright + Chromium against a
# headless Linux runner. Boots Unsloth with the smallest GGUF
# End-to-end Studio chat UI smoke via Playwright + Chromium against a
# headless Linux runner. Boots Studio with the smallest GGUF
# (gemma-3-270m-it UD-Q4_K_XL, ~254 MiB), drives the actual frontend
# bundle, and asserts the full bootstrap-password / change-password /
# send-message / persist-on-reload journey works end to end.
@ -14,7 +14,7 @@
# frontend-only CI happily pass while the actual user-visible UI is
# broken (cf. the 2026.5.1 chat-history release).
name: Unsloth UI CI
name: Studio UI CI
on:
pull_request:
@ -27,7 +27,6 @@ on:
# The Playwright test files themselves -- a PR that ONLY edits
# the test must still trigger UI CI.
- 'tests/studio/**'
- '.github/scripts/run-studio-permission-browser.sh'
- '.github/workflows/studio-ui-smoke.yml'
push:
branches: [main, pip]
@ -83,8 +82,7 @@ jobs:
id: prime-hf
if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p hf-cache
@ -98,25 +96,26 @@ jobs:
path: hf-cache
key: ${{ runner.os }}-hf-${{ env.GGUF_REPO }}-${{ env.GGUF_VARIANT }}-v2
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
bash install.sh --local --no-torch 2>&1 | tee logs/install.log
- name: Install Playwright browsers
- name: Install Playwright + Chromium
run: |
pip install 'playwright>=1.45'
python -m playwright install --with-deps chromium firefox webkit
# --with-deps installs the OS-level runtime libs Chromium
# needs (libnss3, libxkbcommon, etc.). About 30 s on a
# warm runner.
python -m playwright install --with-deps chromium
- name: Reset auth + boot Unsloth
- name: Reset auth + boot Studio
run: |
# Wipe (not reset-password): the boot below must re-seed a fresh .bootstrap_password.
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -146,7 +145,7 @@ jobs:
# NEW + NEW2 are generated freshly per CI run via secrets.token_urlsafe
# rather than hardcoded. If a workflow gets compromised, the
# attacker can't replay a known-good rotated password against
# any future / parallel Unsloth install -- the rotated value
# any future / parallel Studio install -- the rotated value
# only ever exists for the lifetime of this single job, masked
# in the log via ::add-mask::.
run: |
@ -164,37 +163,31 @@ jobs:
env:
BASE_URL: http://127.0.0.1:18892
# The test file lives in the repo so it can be run locally
# against a freshly-installed Unsloth (BASE_URL=...; STUDIO_OLD_PW=
# against a freshly-installed Studio (BASE_URL=...; STUDIO_OLD_PW=
# $(cat ~/.unsloth/studio/auth/.bootstrap_password); python ...).
PW_ART_DIR: logs/playwright
# Strict mode: in CI a missing button / nav / dialog must
# FAIL the test. Locally the test still runs against partial
# Unsloth installs without STUDIO_UI_STRICT.
# Studio installs without STUDIO_UI_STRICT.
STUDIO_UI_STRICT: '1'
run: |
mkdir -p logs/playwright
python tests/studio/playwright_chat_ui.py
- name: Stop Unsloth (chat-ui ends with Shutdown click; this is belt-and-suspenders)
- name: Stop Studio (chat-ui ends with Shutdown click; this is belt-and-suspenders)
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true
sleep 2
- name: Cross-browser permission controls
run: |
bash .github/scripts/run-studio-permission-browser.sh 18893 firefox
bash .github/scripts/run-studio-permission-browser.sh 18893 webkit
bash .github/scripts/run-studio-permission-browser.sh 18893 chromium chrome
# The chat UI test ends by clicking the Shutdown menuitem, which
# leaves the server dead. The extra UI test (Compare / Recipes /
# Export / Unsloth / Settings) needs a fresh Unsloth, so we boot a
# Export / Studio / Settings) needs a fresh Studio, so we boot a
# second one on a different port. Boot is fast (~3-5s on the
# warm install we already did) so this adds little wall time.
- name: Reset auth + boot Unsloth for extra UI tests (port 18894)
- name: Reset auth + boot Studio for extra UI tests (port 18894)
run: |
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p 18894 \
> logs/studio_extra.log 2>&1 &
@ -219,7 +212,7 @@ jobs:
echo "STUDIO_EXTRA_OLD_PW=$OLD" >> "$GITHUB_ENV"
echo "STUDIO_EXTRA_NEW_PW=$NEW" >> "$GITHUB_ENV"
- name: Drive Compare/Recipes/Export/Unsloth/Settings with Playwright
- name: Drive Compare/Recipes/Export/Studio/Settings with Playwright
env:
BASE_URL: http://127.0.0.1:18894
STUDIO_OLD_PW: ${{ env.STUDIO_EXTRA_OLD_PW }}
@ -232,75 +225,18 @@ jobs:
mkdir -p logs/playwright_extra
python tests/studio/playwright_extra_ui.py
- name: UI font size scaling regression (Playwright)
env:
BASE_URL: http://127.0.0.1:18894
STUDIO_PW: ${{ env.STUDIO_EXTRA_NEW_PW }}
PW_ART_DIR: logs/playwright_fontscale
run: |
mkdir -p logs/playwright_fontscale
python tests/studio/playwright_ui_font_scale.py
- name: Stop second Unsloth
- name: Stop second Studio
if: always()
run: |
kill "${STUDIO_EXTRA_PID}" 2>/dev/null || true
sleep 2
# Model-picker per-model-config regression (PR #7207 re-land of #6647).
# Fourth Unsloth on its own port; loads the tiny GGUF and drives the
# picker's run-settings surface: Context Length persists across a reload,
# Reset clears the stored override (never pins it), and the infra models
# (RAG embedder + llama.cpp probe) stay hidden from the picker.
- name: Reset auth + boot Unsloth for model-config tests (port 18898)
run: |
rm -rf ~/.unsloth/studio/auth
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p 18898 \
> logs/studio_modelcfg.log 2>&1 &
echo "STUDIO_MODELCFG_PID=$!" >> "$GITHUB_ENV"
- name: Wait for /api/health on 18898
run: |
for i in $(seq 1 180); do
if curl -fs "http://127.0.0.1:18898/api/health" > /tmp/health4.json; then
jq -e '.status == "healthy"' /tmp/health4.json && break
fi
sleep 1
done
jq -e '.status == "healthy"' /tmp/health4.json
- name: Pass bootstrap pw for model-config test
run: |
NEW="CIModelCfg-$(python -c 'import secrets; print(secrets.token_urlsafe(16))')"
echo "::add-mask::$NEW"
echo "STUDIO_MODELCFG_NEW_PW=$NEW" >> "$GITHUB_ENV"
- name: Drive model-picker per-model-config with Playwright
env:
BASE_URL: http://127.0.0.1:18898
STUDIO_NEW_PW: ${{ env.STUDIO_MODELCFG_NEW_PW }}
PW_ART_DIR: logs/playwright_modelcfg
STUDIO_UI_STRICT: '1'
GGUF_REPO: ${{ env.GGUF_REPO }}
GGUF_VARIANT: ${{ env.GGUF_VARIANT }}
STUDIO_MODEL_HINT: gemma-3-270m
run: |
mkdir -p logs/playwright_modelcfg
python tests/studio/playwright_model_config.py
- name: Stop fourth Unsloth
if: always()
run: |
kill "${STUDIO_MODELCFG_PID}" 2>/dev/null || true
sleep 2
# IME + multilingual paste regression (issue #5318 / PR #5327).
# Third Unsloth on its own port so a hang here cannot poison the
# Third Studio on its own port so a hang here cannot poison the
# earlier UI tests. No GGUF -- the bug surface is the composer.
- name: Reset auth + boot Unsloth for IME / i18n tests (port 18896)
- name: Reset auth + boot Studio for IME / i18n tests (port 18896)
run: |
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p 18896 \
> logs/studio_ime.log 2>&1 &
@ -318,7 +254,7 @@ jobs:
- name: Pass bootstrap pw for IME / i18n test
# IME smoke does the change-password against the bootstrap that
# Unsloth's frontend injects into the page, so it only needs the
# Studio's frontend injects into the page, so it only needs the
# NEW password.
run: |
NEW="CIIme-$(python -c 'import secrets; print(secrets.token_urlsafe(16))')"
@ -335,15 +271,11 @@ jobs:
mkdir -p logs/playwright_ime
python tests/studio/playwright_chat_ime_i18n.py
- name: Stop third Unsloth
- name: Stop third Studio
if: always()
run: |
kill "${STUDIO_IME_PID}" 2>/dev/null || true
sleep 2
# Capture backend + llama-server logs (all three Studios share this
# dir) so a stray 500 has a server-side traceback.
mkdir -p logs/server-logs
cp -r ~/.unsloth/studio/logs/. logs/server-logs/ 2>/dev/null || true
- name: Upload Playwright artifacts
# Always upload so a green run's screenshots stay reviewable --
@ -355,15 +287,9 @@ jobs:
path: |
logs/studio.log
logs/studio_extra.log
logs/studio_modelcfg.log
logs/studio_ime.log
logs/install.log
logs/server-logs/
logs/playwright
logs/playwright-permissions-*
logs/playwright_extra
logs/playwright_fontscale
logs/playwright_modelcfg
logs/playwright_ime
logs/studio-permissions-*.log
retention-days: 7

View file

@ -9,7 +9,7 @@
# This catches regressions in setup.sh's update path that the existing
# GGUF / wheel jobs would miss because they only invoke install.sh once.
name: Unsloth Update CI
name: Studio Update CI
on:
pull_request:
@ -36,7 +36,7 @@ permissions:
jobs:
update-idempotency:
name: Unsloth Updating Tests
name: Studio Updating Tests
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
@ -63,7 +63,7 @@ jobs:
# post-step then fatal-errors with "Cache folder path is
# retrieved for pip but doesn't exist on disk".
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
# Pass the workflow token so the llama.cpp prebuilt installer's
# GitHub-API call to list releases isn't rate-limited (60/hr
# unauthenticated). Without this, three consecutive install +
@ -71,8 +71,7 @@ jobs:
# prebuilt path falls back to source build.
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
mkdir -p logs
set -o pipefail
@ -87,8 +86,7 @@ jobs:
# idempotency regressed.
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
set -o pipefail
unsloth studio update --local 2>&1 | tee logs/update.log
@ -111,8 +109,7 @@ jobs:
# the first one.
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
set -o pipefail
unsloth studio update --local 2>&1 | tee logs/update2.log
@ -122,7 +119,7 @@ jobs:
grep -qE "prebuilt up to date and validated|prebuilt installed and validated" logs/update2.log
echo "second update was clean"
- name: Boot Unsloth briefly to confirm the install is still usable
- name: Boot Studio briefly to confirm the install is still usable
# If `update --local` accidentally broke the venv or wiped the
# llama-server binary, the server would fail to start here.
run: |
@ -138,53 +135,13 @@ jobs:
sleep 1
done
if ! jq -e '.status == "healthy"' /tmp/health.json 2>/dev/null; then
echo "Unsloth failed to come up after `update`"
echo "Studio failed to come up after `update`"
tail -200 logs/studio.log
kill "$PID" 2>/dev/null || true
exit 1
fi
kill "$PID" 2>/dev/null || true
echo "post-update Unsloth /api/health OK"
- name: A complete install reports itself complete
run: |
set -o pipefail
unsloth studio verify-install
unsloth studio desktop-capabilities --json | tee /tmp/caps.json
jq -e '.studio_install_ok == true' /tmp/caps.json
jq -e '.desktop_manageability_version >= 2' /tmp/caps.json
- name: An incomplete install must not report itself ready
# An installer killed part-way leaves a working CLI but no studio.txt
# deps, which the old preflight called ManagedReady. The manifest is
# written last, so removing it reproduces that state.
run: |
set -o pipefail
# install.sh's default root, resolved explicitly: `python` on PATH
# here is setup-python's, not the managed venv.
MANIFEST="$HOME/.unsloth/studio/unsloth_studio/unsloth_install_manifest.json"
test -f "$MANIFEST" || { echo "::error::installer never wrote $MANIFEST"; exit 1; }
rm -f "$MANIFEST"
unsloth studio desktop-capabilities --json | tee /tmp/caps_bad.json
jq -e '.studio_install_ok == false' /tmp/caps_bad.json
if unsloth studio verify-install; then
echo "::error::verify-install passed on an install with no manifest"
exit 1
fi
echo "incomplete install correctly reported not-ready"
- name: Update repairs an incomplete install
# `--local` bypasses setup.sh's PyPI version compare, so this asserts
# the repair OUTCOME. The non-local fast path the desktop Repair button
# uses is covered by tests/studio/install/test_setup_fast_path_guard.py.
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
set -o pipefail
unsloth studio update --local 2>&1 | tee logs/update_repair.log
unsloth studio verify-install
unsloth studio desktop-capabilities --json | jq -e '.studio_install_ok == true'
echo "update repaired the incomplete install"
echo "post-update Studio /api/health OK"
- name: Uninstall and verify clean
# Round-trip the installer through scripts/uninstall.sh: confirms the

View file

@ -9,7 +9,7 @@
# (Section 6) is Linux-only and short-circuits on non-POSIX; the rest
# is platform-portable.
name: Windows Unsloth API CI
name: Windows Studio API CI
on:
pull_request:
@ -34,7 +34,7 @@ permissions:
jobs:
api-smoke:
name: Unsloth API & Auth Tests
name: Studio API & Auth Tests
runs-on: windows-latest
timeout-minutes: 30
defaults:
@ -75,8 +75,7 @@ jobs:
id: prime-hf
if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p hf-cache
@ -105,7 +104,7 @@ jobs:
# studio-windows-update-smoke.yml for the full rationale --
# creating an empty studio/frontend/dist trips setup.ps1's
# mtime-based staleness check into "frontend up to date, skip
# rebuild" and Unsloth boots with an empty dist directory.
# rebuild" and Studio boots with an empty dist directory.
# Add-MpPreference accepts paths that do not yet exist.
foreach ($p in @(
"$env:USERPROFILE\.unsloth",
@ -121,12 +120,11 @@ jobs:
}
}
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
shell: pwsh
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
New-Item -ItemType Directory -Force -Path logs | Out-Null
# *>&1 captures Write-Host (Information stream) output;
@ -161,7 +159,7 @@ jobs:
echo "install.ps1 installed the Windows prebuilt llama.cpp:"
cat "$INFO"
- name: Add Unsloth shim to GITHUB_PATH
- name: Add Studio shim to GITHUB_PATH
# install.ps1's User-PATH update doesn't propagate to a
# running Git Bash session; export the shim dir so the
# next `unsloth ...` invocation finds it.
@ -177,10 +175,9 @@ jobs:
- name: Install pyjwt for the JWT-expiry forge test
run: python -m pip install 'pyjwt>=2.6'
- name: Reset auth + boot Unsloth (API-only)
- name: Reset auth + boot Studio (API-only)
run: |
# Wipe (not reset-password): the boot below must re-seed a fresh .bootstrap_password.
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -208,7 +205,7 @@ jobs:
echo "STUDIO_NEW_PW=$NEW" >> "$GITHUB_ENV"
echo "STUDIO_NEW2_PW=$NEW2" >> "$GITHUB_ENV"
- name: Run Unsloth API & Auth tests
- name: Run Studio API & Auth tests
# Do NOT pin STUDIO_AUTH_DIR here. The Mac/Linux mirrors
# hardcode runner-specific paths (/Users/runner/...,
# /home/runner/...), but on Windows the path is
@ -220,7 +217,7 @@ jobs:
BASE_URL: http://127.0.0.1:18895
run: python tests/studio/studio_api_smoke.py
- name: Stop Unsloth
- name: Stop Studio
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true

File diff suppressed because it is too large Load diff

View file

@ -4,11 +4,11 @@
# Windows counterpart to studio-ui-smoke.yml / studio-mac-ui-smoke.yml.
# Same Playwright + Chromium end-to-end chat UI flow + extra UI flow,
# but on the FREE windows-latest runner so we catch Windows-specific
# regressions in the install path (install.ps1), the Unsloth CLI's
# regressions in the install path (install.ps1), the Studio CLI's
# Windows process-management branches, and the llama.cpp prebuilt's
# Windows HTTP layer.
name: Windows Unsloth UI CI
name: Windows Studio UI CI
on:
pull_request:
@ -19,7 +19,6 @@ on:
- 'install.ps1'
- 'pyproject.toml'
- 'tests/studio/**'
- '.github/scripts/run-studio-permission-browser.sh'
- '.github/workflows/studio-windows-ui-smoke.yml'
push:
branches: [main, pip]
@ -50,7 +49,7 @@ jobs:
GGUF_FILE: gemma-3-270m-it-UD-Q4_K_XL.gguf
STUDIO_PORT: '18896'
HF_HOME: ${{ github.workspace }}/hf-cache
# Force UTF-8 for stdio so Python tools (hf download, Unsloth
# Force UTF-8 for stdio so Python tools (hf download, Studio
# CLI, etc.) can print Unicode characters like the success
# checkmark "✓". Windows defaults to cp1252 / charmap and
# any tool that prints "OK ✓" hits a UnicodeEncodeError.
@ -92,8 +91,7 @@ jobs:
id: prime-hf
if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
env:
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
python -m pip install --upgrade huggingface_hub
mkdir -p hf-cache
@ -122,7 +120,7 @@ jobs:
# studio-windows-update-smoke.yml for the full rationale --
# creating an empty studio/frontend/dist trips setup.ps1's
# mtime-based staleness check into "frontend up to date, skip
# rebuild" and Unsloth boots with an empty dist directory.
# rebuild" and Studio boots with an empty dist directory.
# Add-MpPreference accepts paths that do not yet exist.
foreach ($p in @(
"$env:USERPROFILE\.unsloth",
@ -138,18 +136,7 @@ jobs:
}
}
- name: Seed a legacy launch-studio.vbs (upgrade-cleanup check)
# Simulate a pre-hardening install so the post-install assertion below
# proves the installer DELETES an existing launch-studio.vbs (the exact
# Kaspersky-flagged file), not merely stops generating it.
shell: pwsh
run: |
$appDir = Join-Path $env:LOCALAPPDATA 'Unsloth Studio'
New-Item -ItemType Directory -Force -Path $appDir | Out-Null
Set-Content -LiteralPath (Join-Path $appDir 'launch-studio.vbs') -Value 'WScript.Echo "legacy"' -Encoding Unicode
Write-Host "seeded legacy launch-studio.vbs at $appDir"
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
# install.ps1 is the supported Windows installer. install.sh
# has no Windows branch (apt-get / brew calls). The PS1
# script's `Install-UnslothStudio @args` line at the bottom
@ -157,8 +144,7 @@ jobs:
shell: pwsh
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
New-Item -ItemType Directory -Force -Path logs | Out-Null
# *>&1 redirects ALL PowerShell streams (stdout, stderr,
@ -206,70 +192,7 @@ jobs:
echo "install.ps1 installed the Windows prebuilt llama.cpp:"
cat "$INFO"
- name: Assert Unsloth launcher chain (no VBS, hidden PowerShell shortcut)
# The shortcut launch path is otherwise untested here (the steps below
# boot `unsloth studio` directly). Guard against re-introducing the VBS
# that tripped Kaspersky HEUR:Trojan.VBS.Agent.gen and against the .lnk
# pointing anywhere other than hidden PowerShell over launch-studio.ps1.
shell: pwsh
run: |
$appDir = Join-Path $env:LOCALAPPDATA 'Unsloth Studio'
if (Test-Path -LiteralPath (Join-Path $appDir 'launch-studio.vbs')) {
throw "regression: launch-studio.vbs exists (the Kaspersky VBS-FP shape)"
}
if (-not (Test-Path -LiteralPath (Join-Path $appDir 'launch-studio.ps1'))) {
throw "missing launch-studio.ps1 in $appDir"
}
$lnk = Join-Path ([Environment]::GetFolderPath('Desktop')) 'Unsloth Studio.lnk'
if (-not (Test-Path -LiteralPath $lnk)) {
$lnk = Join-Path $env:APPDATA 'Microsoft\Windows\Start Menu\Programs\Unsloth Studio.lnk'
}
if (-not (Test-Path -LiteralPath $lnk)) { throw "no Unsloth Studio.lnk on Desktop or Start Menu" }
$sc = (New-Object -ComObject WScript.Shell).CreateShortcut($lnk)
Write-Host "shortcut target: $($sc.TargetPath)"
Write-Host "shortcut args: $($sc.Arguments)"
if ($sc.TargetPath -match 'wscript\.exe$') { throw "shortcut still targets wscript.exe (VBS host)" }
if ($sc.TargetPath -notmatch 'powershell\.exe$') { throw "unexpected shortcut target: $($sc.TargetPath)" }
if ($sc.Arguments -notmatch '-WindowStyle Hidden') {
throw "shortcut must launch windowless (-WindowStyle Hidden)"
}
Write-Host "launcher chain OK (no VBS; hidden powershell over launch-studio.ps1)"
- name: Launch Unsloth via the shortcut and assert health
# Run the exact command the .lnk stores (hidden PowerShell over
# launch-studio.ps1) and confirm it brings the backend up. This is the
# only step that proves the shortcut launch is not silently broken.
# Default port range is 8888-8908; the later UI tests use 18896/18897, so
# there is no conflict, and we tear this server down before they boot.
shell: pwsh
run: |
$lnk = Join-Path ([Environment]::GetFolderPath('Desktop')) 'Unsloth Studio.lnk'
if (-not (Test-Path -LiteralPath $lnk)) {
$lnk = Join-Path $env:APPDATA 'Microsoft\Windows\Start Menu\Programs\Unsloth Studio.lnk'
}
$sc = (New-Object -ComObject WScript.Shell).CreateShortcut($lnk)
Write-Host "launching: $($sc.TargetPath) $($sc.Arguments)"
Start-Process -FilePath $sc.TargetPath -ArgumentList $sc.Arguments -WorkingDirectory $sc.WorkingDirectory
$foundPort = 0
foreach ($i in 1..180) {
foreach ($port in 8888..8908) {
try {
$r = Invoke-RestMethod -Uri "http://127.0.0.1:$port/api/health" -TimeoutSec 1
if ($r.status -eq 'healthy' -and $r.service -eq 'Unsloth UI Backend') { $foundPort = $port; break }
} catch {}
}
if ($foundPort) { break }
Start-Sleep -Seconds 1
}
# Tear down the shortcut-launched server before the main UI tests boot.
try {
$owner = (Get-NetTCPConnection -LocalPort $foundPort -State Listen -ErrorAction Stop | Select-Object -First 1).OwningProcess
if ($owner) { taskkill /PID $owner /T /F 2>$null | Out-Null }
} catch {}
if (-not $foundPort) { throw "Unsloth did not become healthy when launched via the shortcut" }
Write-Host "Unsloth healthy on port $foundPort (launched via the shortcut)"
- name: Add Unsloth shim to GITHUB_PATH
- name: Add Studio shim to GITHUB_PATH
# install.ps1 puts unsloth.exe at $StudioHome\bin\unsloth.exe
# and adds that dir to the User PATH via the Windows registry.
# Registry-level PATH updates don't propagate to a running
@ -285,7 +208,7 @@ jobs:
fi
# GITHUB_PATH wants Windows-style paths; convert via cygpath.
cygpath -w "$SHIM_DIR" >> "$GITHUB_PATH"
echo "Added Unsloth shim dir to PATH: $(cygpath -w "$SHIM_DIR")"
echo "Added Studio shim dir to PATH: $(cygpath -w "$SHIM_DIR")"
- name: Install Playwright + Chromium
# No --with-deps on Windows: that flag installs Linux apt
@ -295,10 +218,9 @@ jobs:
python -m pip install 'playwright>=1.45'
python -m playwright install chromium
- name: Reset auth + boot Unsloth
- name: Reset auth + boot Studio
run: |
# Wipe (not reset-password): the boot below must re-seed a fresh .bootstrap_password.
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
> logs/studio.log 2>&1 &
@ -341,19 +263,15 @@ jobs:
mkdir -p logs/playwright
python tests/studio/playwright_chat_ui.py
- name: Stop Unsloth (chat-ui ends with Shutdown click; this is belt-and-suspenders)
- name: Stop Studio (chat-ui ends with Shutdown click; this is belt-and-suspenders)
if: always()
run: |
kill "${STUDIO_PID}" 2>/dev/null || true
sleep 2
- name: Edge permission controls
- name: Reset auth + boot Studio for extra UI tests (port 18897)
run: |
bash .github/scripts/run-studio-permission-browser.sh 18895 chromium msedge
- name: Reset auth + boot Unsloth for extra UI tests (port 18897)
run: |
rm -rf ~/.unsloth/studio/auth
unsloth studio reset-password
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p 18897 \
> logs/studio_extra.log 2>&1 &
@ -378,7 +296,7 @@ jobs:
echo "STUDIO_EXTRA_OLD_PW=$OLD" >> "$GITHUB_ENV"
echo "STUDIO_EXTRA_NEW_PW=$NEW" >> "$GITHUB_ENV"
- name: Drive Compare/Recipes/Export/Unsloth/Settings with Playwright
- name: Drive Compare/Recipes/Export/Studio/Settings with Playwright
env:
BASE_URL: http://127.0.0.1:18897
STUDIO_OLD_PW: ${{ env.STUDIO_EXTRA_OLD_PW }}
@ -392,7 +310,7 @@ jobs:
mkdir -p logs/playwright_extra
python tests/studio/playwright_extra_ui.py
- name: Stop second Unsloth
- name: Stop second Studio
if: always()
run: |
kill "${STUDIO_EXTRA_PID}" 2>/dev/null || true
@ -408,7 +326,5 @@ jobs:
logs/studio_extra.log
logs/install.log
logs/playwright
logs/playwright-permissions-*
logs/playwright_extra
logs/studio-permissions-*.log
retention-days: 7

View file

@ -5,19 +5,19 @@
# studio-mac-update-smoke.yml. Verifies that on the FREE
# windows-latest runner:
#
# 1. install.ps1 --local --no-torch installs Unsloth AND auto-fetches
# the prebuilt llama.cpp Windows binary (app-<tag>-windows-x64-cpu
# from unslothai/llama.cpp). Hitting the source-build fallback is
# treated as an Unsloth bug -- Unsloth must always pick the
# 1. install.ps1 --local --no-torch installs Studio AND auto-fetches
# the prebuilt llama.cpp Windows binary (llama-bNNNN-bin-win-cpu-
# x64 from ggml-org/llama.cpp). Hitting the source-build fallback
# is treated as an Unsloth bug -- Studio must always pick the
# prebuilt on Windows.
# 2. unsloth studio update --local is idempotent. Two consecutive
# runs both report "prebuilt up to date and validated", no
# source-build fallback. The CLI's _find_setup_script picks
# setup.ps1 on Windows automatically.
# 3. The installed Unsloth still boots and /api/health returns
# 3. The installed Studio still boots and /api/health returns
# healthy after the update path.
name: Windows Unsloth Update CI
name: Windows Studio Update CI
on:
pull_request:
@ -45,7 +45,7 @@ permissions:
jobs:
update-idempotency:
name: Unsloth Updating Tests
name: Studio Updating Tests
runs-on: windows-latest
timeout-minutes: 30
defaults:
@ -53,7 +53,7 @@ jobs:
shell: bash
env:
# Force UTF-8 for stdio (Windows defaults to cp1252; hf
# download / Unsloth CLI print "✓" checkmarks and crash
# download / Studio CLI print "✓" checkmarks and crash
# otherwise).
PYTHONIOENCODING: utf-8
PYTHONUTF8: '1'
@ -79,18 +79,18 @@ jobs:
# Two surgical fixes against measured Windows-only install
# waste (vs Mac/Linux on the same SHA):
#
# (1) npm. setup.ps1's Get-NodeDecision requires Node 22.12+
# (or 20.19+ / 23+) AND npm >=11 because Vite 8 needs both.
# (1) npm. setup.ps1 line 1109-1145 requires Node 22.12+ (or
# 20.19+ / 23+) AND npm >=11 because Vite 8 needs both.
# actions/setup-node@v4 with `node-version: '22'` lands
# Node 22.22.2 + the npm 10.9.7 it bundles, so the decision
# is "bundled" and setup.ps1 downloads an isolated Node (~30
# MB) we don't need on a runner that already has a fine Node.
# `npm install -g npm@^11` updates the runner's npm in-place
# in ~5 s, flipping the decision to "system" so setup.ps1
# reuses the existing Node with no download.
# Node 22.22.2 + the npm 10.9.7 it bundles, so the npm
# check fails and setup.ps1 falls through to the
# "winget install Node.js LTS" branch -- a ~35 s reinstall
# of Node we don't need. `npm install -g npm@^11` updates
# the bundled npm in-place in ~5 s, which makes setup.ps1
# short-circuit on the existing Node.
#
# (2) Defender. windows-latest's real-time scan opens / hashes
# every file Unsloth writes during install (Vite output =
# every file Studio writes during install (Vite output =
# thousands of small chunks, uv pip = wheel-extraction =
# thousands of small files). The latency dominates the
# 200 s frontend build and the 90 s deps install. Adding
@ -109,7 +109,7 @@ jobs:
# setup.ps1 line 1281-1296's mtime-based "is the frontend
# stale?" check into "up to date, skip rebuild", because the
# newly-created dist's mtime is younger than every source
# file. Unsloth then boots with an empty dist and 500s on
# file. Studio then boots with an empty dist and 500s on
# GET / with FileNotFoundError: dist\index.html. See run
# 25546676715 / job 74984469728.
# Add-MpPreference accepts paths that do not yet exist; the
@ -129,12 +129,11 @@ jobs:
}
}
- name: Install Unsloth (--local, --no-torch)
- name: Install Studio (--local, --no-torch)
shell: pwsh
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
New-Item -ItemType Directory -Force -Path logs | Out-Null
# *>&1 captures Write-Host (Information stream) output;
@ -168,7 +167,7 @@ jobs:
echo "install.ps1 installed the Windows prebuilt llama.cpp:"
cat "$INFO"
- name: Add Unsloth shim to GITHUB_PATH
- name: Add Studio shim to GITHUB_PATH
run: |
SHIM_DIR=~/.unsloth/studio/bin
if [ ! -f "$SHIM_DIR/unsloth.exe" ]; then
@ -181,8 +180,7 @@ jobs:
- name: First update should be a no-op (prebuilt already validated)
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
set -o pipefail
unsloth studio update --local 2>&1 | tee logs/update.log
@ -198,36 +196,10 @@ jobs:
fi
echo "update path took the prebuilt fast path"
- name: Update must keep the --no-torch install GGUF-only
run: |
# `unsloth studio update` exports no UNSLOTH_NO_TORCH, so setup.ps1 has
# to recover the mode from the install manifest. Without that it reads
# the missing torch as a stale venv and tries to delete the venv it is
# running out of, and the shared dependency pass pulls torch back in.
# The skip line only prints when the dependency pass actually runs, so
# don't demand it if the fast path short-circuited that pass.
if grep -q "running ordered dependency installation" logs/update.log \
&& ! grep -q "skipping direct PyTorch and Triton installation (no-torch mode)" logs/update.log; then
echo "::error::studio update left no-torch mode; it would reinstall PyTorch."
grep -iE "no-torch|stale venv|PyTorch" logs/update.log | tail -40
exit 1
fi
PY="$HOME/.unsloth/studio/unsloth_studio/Scripts/python.exe"
if [ ! -f "$PY" ]; then
echo "::error::studio venv interpreter missing at $PY"
exit 1
fi
if "$PY" -c "import torch" 2>/dev/null; then
echo "::error::torch was reinstalled into the --no-torch venv."
exit 1
fi
echo "update preserved no-torch mode"
- name: Second update must also be a no-op
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
# Withheld on PR: this step runs checked-out PR code; public GGUF still downloads.
HF_TOKEN: ${{ github.event_name != 'pull_request' && secrets.HF_TOKEN || '' }}
HF_TOKEN: ${{ secrets.HF_TOKEN }}
run: |
set -o pipefail
unsloth studio update --local 2>&1 | tee logs/update2.log
@ -237,7 +209,7 @@ jobs:
grep -qE "prebuilt up to date and validated|prebuilt installed and validated" logs/update2.log
echo "second update was clean"
- name: Boot Unsloth briefly to confirm the install is still usable
- name: Boot Studio briefly to confirm the install is still usable
run: |
mkdir -p logs
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p 18891 \
@ -264,13 +236,13 @@ jobs:
sleep 1
done
if [ -z "$HEALTHY" ]; then
echo "Unsloth failed to come up after \`update\`"
echo "Studio failed to come up after \`update\`"
tail -200 logs/studio.log
kill "$PID" 2>/dev/null || true
exit 1
fi
kill "$PID" 2>/dev/null || true
echo "post-update Unsloth /api/health OK"
echo "post-update Studio /api/health OK"
- name: Uninstall and verify clean
# Round-trip through scripts/uninstall.ps1 against the default

View file

@ -242,7 +242,7 @@ jobs:
run: |
python -m pip install --upgrade pip
# CPU torch (vllm/peft/st all depend on it).
pip install --index-url https://download.pytorch.org/whl/cpu --extra-index-url https://pypi.org/simple \
pip install --index-url https://download.pytorch.org/whl/cpu \
'torch>=2.4,<2.11' 'torchvision<0.26' 'torchcodec<0.10'
# torchcodec is a hard requirement on transformers 5.x:
# transformers/audio_utils.py:55 does
@ -285,92 +285,6 @@ jobs:
tests/vllm_compat/test_extended_module_imports.py \
-v --tb=short
# Fake-CUDA GRPO/SFT/DPO patch run against REAL TRL (latest + main). Unlike
# the static symbol/source greps above, this drives unsloth's actual
# source-transform patchers (models/rl.py + rl_replacements.py) on a CPU-only
# runner under the tests/conftest.py spoof harness -- no GPU, no training.
# Catches structural TRL drift the greps miss (e.g. TRL 1.7.0's 2->3-tuple
# per-token-logps return, restructured PEFT ref-adapter block) by asserting
# the generated Unsloth trainer still satisfies the transform contracts.
grpo-fake-run:
name: GRPO fake-run (latest + main TRL, CPU spoof)
runs-on: ubuntu-latest
timeout-minutes: 18
steps:
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
with:
persist-credentials: false
path: unsloth
- name: Clone unsloth-zoo @ main
run: |
for attempt in 1 2 3; do
rm -rf "$RUNNER_TEMP/unsloth-zoo"
if git clone --depth=1 https://github.com/unslothai/unsloth-zoo \
"$RUNNER_TEMP/unsloth-zoo"; then
break
fi
if [ "$attempt" -eq 3 ]; then
echo "::error::git clone unsloth-zoo failed after 3 attempts"
exit 1
fi
delay=$((5 * attempt))
echo "::warning::clone failed (attempt $attempt/3), retrying in ${delay}s..."
sleep "$delay"
done
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
with:
python-version: '3.12'
cache: 'pip'
- name: Install CPU torch + ecosystem + TRL latest
run: |
python -m pip install --upgrade pip
pip install --index-url https://download.pytorch.org/whl/cpu --extra-index-url https://pypi.org/simple \
'torch>=2.4,<2.11' 'torchvision<0.26' 'torchcodec<0.10'
# Ecosystem floors unsloth needs; TRL itself is installed last so it
# can pull the transformers/peft it requires.
pip install \
'transformers>=4.57' 'peft>=0.18.0' 'accelerate>=1.0' 'datasets>=3.4,<5' \
'bitsandbytes>=0.45.5' sentencepiece protobuf safetensors numpy 'pytest>=8' \
'huggingface_hub>=0.34' tqdm packaging psutil triton Pillow
pip install --upgrade trl
pip install --no-deps -e "$RUNNER_TEMP/unsloth-zoo"
pip install --no-deps -e ./unsloth
- name: Fake-run vs TRL latest
env:
UNSLOTH_IS_PRESENT: '1'
UNSLOTH_COMPILE_DISABLE: '1'
# Disable dynamo/inductor at the process level, before conftest.py's early
# `import unsloth`, so the GRPO hot path never compiles on the GPU-less runner
# (defense in depth; the CPU fake-train also flips this at runtime).
TORCHDYNAMO_DISABLE: '1'
TORCH_COMPILE_DISABLE: '1'
PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION: python
run: |
cd unsloth
python -c "import trl; print('Resolved TRL', trl.__version__)"
PYTHONPATH=. python -m pytest \
tests/version_compat/test_trl_grpo_fake_run.py \
tests/version_compat/test_trl_fake_train_cpu.py \
-v --tb=short
# `main` is scheduled/dispatch-only so PR jobs stay fast and a bleeding-edge
# TRL break does not red every PR. github.event_name is valid in a step if.
- name: Fake-run vs TRL main (scheduled / dispatch only)
if: ${{ github.event_name != 'pull_request' }}
env:
UNSLOTH_IS_PRESENT: '1'
UNSLOTH_COMPILE_DISABLE: '1'
TORCHDYNAMO_DISABLE: '1'
TORCH_COMPILE_DISABLE: '1'
PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION: python
run: |
pip install --upgrade "git+https://github.com/huggingface/trl"
cd unsloth
python -c "import trl; print('Resolved TRL', trl.__version__)"
PYTHONPATH=. python -m pytest \
tests/version_compat/test_trl_grpo_fake_run.py \
tests/version_compat/test_trl_fake_train_cpu.py \
-v --tb=short
# Daily-only: same suites but with --strict on importable upstream
# tags. Schedule-only so PR jobs stay fast; cron tolerates a flake.
daily-fresh-fetch:

View file

@ -3,7 +3,7 @@
# Builds the PyPI wheel from the PR branch, then verifies the built wheel
# actually contains what we expect to ship and does NOT contain the broken
# Unsloth bundle that 2026.5.1 published. This is the single workflow that
# Studio bundle that 2026.5.1 published. This is the single workflow that
# would have blocked the 2026.5.1 release before twine upload.
#
# Verified locally end-to-end against this branch:
@ -12,7 +12,7 @@
# lockfile shipped, frontend dist shipped,
# no node_modules in wheel, no bun.lock in wheel,
# main bundle has unstable_Provider hits=1 (assistant-ui internals only).
# - Unsloth backend imports cleanly from the installed wheel with the
# - Studio backend imports cleanly from the installed wheel with the
# lightweight dep set below.
name: Wheel CI
@ -101,7 +101,7 @@ jobs:
hits = data.count("unstable_Provider:")
print(f"main bundle: {js[0]}")
print(f"unstable_Provider hits: {hits} (>=4 indicates 2026.5.1 regression)")
checks["bundle has no Unsloth unstable_Provider call site"] = (hits < 4)
checks["bundle has no Studio unstable_Provider call site"] = (hits < 4)
print()
for k, v in checks.items():
@ -109,7 +109,7 @@ jobs:
sys.exit(0 if all(checks.values()) else 1)
PY
- name: Unsloth backend import smoke
- name: Studio backend import smoke
# Imports `studio.backend.main:app` from the freshly-installed wheel in
# a clean venv. This catches the class of bug that 2026.5.1 shipped with:
# frontend dist missing, package-lock.json missing, or the wheel's Python
@ -125,32 +125,7 @@ jobs:
/tmp/v/bin/pip install --no-deps dist/unsloth-*.whl
# Run from /tmp so Python imports the installed package, not the source tree.
cd /tmp
/tmp/v/bin/python -c "from studio.backend.main import app; print('Unsloth backend OK:', app.title)"
- name: CLI without the Studio stack guides instead of tracebacking
# The smoke above installs studio.txt first, so it cannot catch a wheel
# that ships studio/ without declaring what it imports (#4701, #5260,
# #7147). Drop only structlog to reuse that venv without a re-download.
run: |
set -eu
/tmp/v/bin/pip uninstall -y structlog >/dev/null
cd /tmp
status=0
for args in "export ./nope ./out" "list-checkpoints"; do
echo "--- unsloth $args"
out=$(/tmp/v/bin/unsloth $args 2>&1 || true)
printf '%s\n' "$out"
case "$out" in
*Traceback*)
echo "FAIL: raw traceback instead of guidance"; status=1 ;;
esac
case "$out" in
*'unsloth studio update'*) ;;
*) echo "FAIL: no remediation in the message"; status=1 ;;
esac
done
/tmp/v/bin/pip install -q structlog >/dev/null
exit "$status"
/tmp/v/bin/python -c "from studio.backend.main import app; print('Studio backend OK:', app.title)"
- name: Upload wheel on failure
if: failure()

8
.gitignore vendored
View file

@ -11,8 +11,6 @@ outputs/
exports/
/datasets/
studio/backend/assets/datasets/
# Generated async worker / reviewer transcripts (never part of the product).
studio/backend/async_task_outputs/
unsloth_training_checkpoints/
*.gguf
*.safetensors
@ -208,9 +206,6 @@ tmp/
**/node_modules/
auth.db
# Packaging snapshot of the root CHANGELOG.md (written by build.sh)
studio/CHANGELOG.md
# Tauri local build/generated output
studio/src-tauri/target/
studio/src-tauri/gen/
@ -240,6 +235,3 @@ package-lock.json
!studio/backend/core/data_recipe/oxc-validator/package-lock.json
!studio/package-lock.json
llama.cpp/
# Stray "~" dir some tools create from a literal ~ TMPDIR; never part of the repo.
~/
/temp/

View file

@ -1,6 +1,6 @@
repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.15.18
rev: v0.15.16
hooks:
- id: ruff
args:

View file

@ -1,88 +0,0 @@
# Changelog
Release notes for Unsloth and Unsloth Studio.
Unsloth Studio reads this file to show release notes inside the "New Unsloth
version" update popup. Edit it here and the popup picks the change up on the
next update check, with no release or rebuild required.
## Format
Every release is a level-2 heading whose first token is the version, optionally
followed by a date:
```md
## 2026.7.6 - 2026-07-22
```
`## [2026.7.6] - 2026-07-22` and `## v2026.7.6` also work. Everything under a
heading, up to the next level-2 heading, is that release's notes and renders as
Markdown in the popup.
Notes are matched to one exact version. When Studio offers an update to
`2026.7.6` it renders the `2026.7.6` section and nothing else. If that section
is missing, the popup links out to the online changelog rather than showing
notes from an unrelated release, so a new version needs its own section here
before its notes can appear.
Keep the newest release at the top. Lead each bullet with the change itself:
the collapsed popup highlights the first sentence and dims the rest.
`## Unreleased` is ignored by the popup, so it is safe to stage notes there and
rename the heading at release time.
<!-- Add new releases directly below this line. -->
## Unreleased
## 2026.7.5
### What's Changed
- AMD support is here. Train, run RL, chat with and deploy 500+ models on
Radeon, Instinct, Ryzen and data center GPUs across Windows, WSL and Linux,
up to 2x faster with 70% less VRAM and no accuracy loss.
- Intel XPU support lands in Studio, so Arc and Data Center GPUs run chat and
training alongside the NVIDIA, AMD and Apple paths.
- Local speech to text dictation runs fully offline, with slim Whisper bundles
and a picker for custom models.
- DoRA training is available in Studio, selectable next to LoRA and full
fine-tuning in the training tab.
- The update popup previews release notes inline, pulled from this file and
matched to the exact version being offered.
### AMD, 23 July update
Our AMD collaboration, custom Triton kernels and math algorithms bring local
training and inference to AMD hardware. The 23 July update builds on the
[AMD release](https://github.com/unslothai/unsloth/releases/tag/v0.1.501-beta):
- RDNA2 and Gorgon Halo are supported, and the installer no longer fails to
detect GPUs on Strix Halo and other AMD cards.
- RDNA4 handling is better, and HIP and ROCm failures are caught and fixed
automatically instead of stopping the install.
- Unified memory safetensors loading is 2x faster, with much faster gradient
checkpointing on unified memory devices.
- Voice dictation through whisper.cpp has preliminary support.
- Rollback environments left by installs no longer eat 5GB of disk. They are
cleaned up automatically.
Optimized ROCm builds cover GGUF and safetensors inference, and ROCm
compatibility is improved for MI300X and MI325X. Full guide:
[unsloth.ai/docs/basics/amd](https://unsloth.ai/docs/basics/amd).
### Running larger models
- Automatic GPU placement, or pick exactly which GPUs and layers to use.
- Move MoE expert layers into system memory so larger models fit.
- Split a model across several GPUs, or use tensor parallelism.
- Hardware settings are saved per model and quant.
### Also in this release
- Remote access with `unsloth studio --secure` over free HTTPS via Cloudflare.
- Web search reads PDF papers and manuals, and parallel tool calls, reasoning
output and tool retries are more reliable.
- The model download location is configurable, so weights can live on a second
drive instead of the default cache.
- Stalled Hugging Face XET downloads retry over standard HTTP, and existing
GGUF files are reused instead of downloaded again.

View file

@ -1,2 +0,0 @@
include _changelog_build.py
include CHANGELOG.md

180
README.md
View file

@ -11,7 +11,6 @@ Unsloth Studio lets you run and train models locally.
<p align="center">
<a href="#-features">Features</a> •
<a href="#-unsloth-news">News</a> •
<a href="#-install">Quickstart</a> •
<a href="#-free-notebooks">Notebooks</a> •
<a href="https://unsloth.ai/docs">Documentation</a>
@ -48,51 +47,15 @@ Unsloth Studio (Beta) lets you run and train text, [audio](https://unsloth.ai/do
* [Auto set inference settings](https://unsloth.ai/docs/new/studio/chat#auto-parameter-tuning) and customize chat templates.
* We work directly with teams behind [gpt-oss](https://docs.unsloth.ai/new/gpt-oss-how-to-run-and-fine-tune#unsloth-fixes-for-gpt-oss), [Qwen3](https://www.reddit.com/r/LocalLLaMA/comments/1kaodxu/qwen3_unsloth_dynamic_ggufs_128k_context_bug_fixes/), [Llama 4](https://github.com/ggml-org/llama.cpp/pull/12889), [Mistral](https://huggingface.co/mistralai/Mistral-Medium-3.5-128B/discussions/18), [Gemma 1-3](https://news.ycombinator.com/item?id=39671146), and [Phi-4](https://unsloth.ai/blog/phi4), where weve fixed bugs that improve model accuracy.
* Chat with images, audio, PDFs, code, DOCX and more. [Connect API providers](https://unsloth.ai/docs/integrations/connections) (OpenAI, Anthropic) or servers (vLLM, Ollama).
* [**Compare any two models**](https://unsloth.ai/docs/new/studio/chat#model-arena) side by side with the same prompt.
* **OpenAI/Anthropic-compatible APIs**: Serve local models through `/v1/chat/completions`, `/v1/responses` and `/v1/messages`.
* **Connect local models to agents**: Use `unsloth start` with Claude Code, Codex, Hermes and more.
* **Web/PDF search** can read PDF papers, manuals and other PDF results.
* **GGUF hardware controls**: Choose GPUs/layers, offload MoE experts, use multi-GPU or Tensor Parallelism.
* The opt-in **MCP control endpoint** lets AI clients manage models, training, recipes and exports.
### Training
* Train and RL **500+ models** up to **2x faster** with **70% less VRAM**; MoE up to **12x faster**.
* Train and run RL on [AMD GPUs](https://unsloth.ai/docs/basics/amd) across Windows, WSL and Linux.
* Train and RL **500+ models** up to **2x faster** with up to **70% less VRAM**, with no accuracy loss.
* Custom Triton and mathematical **kernels**. See some collabs we did with [PyTorch](https://unsloth.ai/docs/get-started/reinforcement-learning-rl-guide/fp8-reinforcement-learning) and [Hugging Face](https://unsloth.ai/docs/new/faster-moe).
* **Data Recipes**: [Auto-create datasets](https://unsloth.ai/docs/new/studio/data-recipe) from **PDF, CSV, DOCX** etc. Edit data in a visual-node workflow.
* **[Reinforcement Learning](https://unsloth.ai/docs/get-started/reinforcement-learning-rl-guide)** uses **80% less VRAM** for GRPO, FP8 and vision RL, with 7x longer contexts.
* [**Long-context training**](https://unsloth.ai/docs/new/3x-faster-training-packing): **3x faster**, 30% less VRAM and 500K+ context.
* Supports LoRA/QLoRA, full fine-tuning, RL, pretraining, 4-bit, 16-bit and FP8.
* Custom Triton and mathematical **kernels** built with PyTorch and Hugging Face.
* **[Reinforcement Learning](https://unsloth.ai/docs/get-started/reinforcement-learning-rl-guide)** (RL): The most efficient [RL](https://unsloth.ai/docs/get-started/reinforcement-learning-rl-guide) library, using **80% less VRAM** for GRPO, [FP8](https://unsloth.ai/docs/get-started/reinforcement-learning-rl-guide/fp8-reinforcement-learning) etc.
* Supports full fine-tuning, RL, pretraining, 4-bit, 16-bit and, FP8 training.
* **Observability**: Monitor training live, track loss and GPU usage and customize graphs.
* [Multi-GPU](https://unsloth.ai/docs/basics/multi-gpu-training-with-unsloth) training is supported, with major improvements coming soon.
## 🚀 Unsloth Start
[Unsloth Start](https://unsloth.ai/docs/integrations/unsloth-start) connects [Claude Code](https://unsloth.ai/docs/basics/claude-code), [Codex](https://unsloth.ai/docs/basics/codex) and other agents to local models with one command.
Start Unsloth, load a model, open your project folder, then run:
```bash
unsloth start claude
```
Replace `claude` with any supported agent:
| Agent | Command |
| --- | --- |
| Claude Code | `unsloth start claude` |
| OpenAI Codex | `unsloth start codex` |
| Hermes Agent | `unsloth start hermes` |
| OpenClaw | `unsloth start openclaw` |
| OpenCode | `unsloth start opencode` |
| Pi Coding Agent | `unsloth start pi` |
Claude Code, Codex, OpenCode and Pi can keep their current model and use Unsloth as a local
subagent:
```bash
unsloth start claude --as-subagent --model unsloth/model-GGUF:quant
```
## 📥 Install
Unsloth can be used in two ways: through **[Unsloth Studio](https://unsloth.ai/docs/new/studio/)**, the web UI, or through **Unsloth Core**, the code-based version. Each has different requirements.
@ -102,8 +65,7 @@ Unsloth Studio (Beta) works on **Windows, Linux, WSL** and **macOS**.
* **CPU:** Supported for Chat and Data Recipes currently
* **NVIDIA:** Training works on RTX 30/40/50, Blackwell, DGX Spark, Station and more
* **macOS:** Training, MLX and GGUF inference are ALL supported.
* **AMD:** Training, RL, chat and deployment work on Windows, WSL and Linux. [Read the AMD guide](https://unsloth.ai/docs/basics/amd).
* **Vulkan:** GGUF inference is supported on [compatible GPUs, including Intel GPUs](https://github.com/unslothai/unsloth/pull/5819). Vulkan accelerates GGUF inference only; training still requires a supported PyTorch or MLX backend.
* **AMD:** Chat + Data works. Train with [Unsloth Core](#unsloth-core-code-based). Studio support is out soon.
* **Multi-GPU:** Available now, with a major upgrade on the way
#### macOS, Linux, WSL:
@ -112,35 +74,17 @@ curl -fsSL https://unsloth.ai/install.sh | sh
```
Use the same command to update.
To force the Vulkan llama.cpp backend, set `UNSLOTH_FORCE_VULKAN=1` **before installing or updating**. The setting selects the llama.cpp binary bundle, so setting it only when launching Studio cannot replace an existing CPU bundle:
```bash
export UNSLOTH_FORCE_VULKAN=1
curl -fsSL https://unsloth.ai/install.sh | sh
```
#### Windows:
```powershell
irm https://unsloth.ai/install.ps1 | iex
```
Use the same command to update.
To force the Vulkan llama.cpp backend, set the environment variable before running the installer or updater:
```powershell
$env:UNSLOTH_FORCE_VULKAN=1
irm https://unsloth.ai/install.ps1 | iex
```
Re-running the current installer replaces a previously selected CPU bundle when the backend differs. A separate Vulkan SDK is not required; the GPU driver must provide a working Vulkan runtime.
#### Launch
```bash
unsloth studio -p 8888
```
For LAN or cloud access, add `-H 0.0.0.0` (raw port only; add `--cloudflare` for a public URL). By default, Unsloth is accessible only locally.
To reach Unsloth over HTTPS, use `unsloth studio --secure`. Unsloth stays bound to localhost and is reached only through a free Cloudflare tunnel, which publishes it at a public `https://*.trycloudflare.com` URL (it fails closed if the tunnel can't start, so the raw port is never exposed). This makes Unsloth reachable from the internet, so anyone with the link and API key can use it and run code: keep your API key private (see Remote access below).
For cloud or global access, add `-H 0.0.0.0`. By default, Unsloth is accessible only locally.
#### Docker
Use our [Docker image](https://hub.docker.com/r/unsloth/unsloth) ```unsloth/unsloth``` container. Run:
@ -176,7 +120,7 @@ You can use the same Docker image as Unsloth Studio.
#### AMD, Intel:
For RTX 50x, B200, 6000 GPUs: `uv pip install unsloth --torch-backend=auto`. Read our guides for: [Blackwell](https://unsloth.ai/docs/blog/fine-tuning-llms-with-blackwell-rtx-50-series-and-unsloth) and [DGX Spark](https://unsloth.ai/docs/blog/fine-tuning-llms-with-nvidia-dgx-spark-and-unsloth). <br>
To install Unsloth on **AMD** and **Intel** GPUs, follow our [AMD Guide](https://unsloth.ai/docs/basics/amd) and [Intel Guide](https://unsloth.ai/docs/get-started/install/intel).
To install Unsloth on **AMD** and **Intel** GPUs, follow our [AMD Guide](https://unsloth.ai/docs/get-started/install/amd) and [Intel Guide](https://unsloth.ai/docs/get-started/install/intel).
## 📒 Free Notebooks
@ -202,20 +146,13 @@ Read our [guide](https://unsloth.ai/docs/get-started/fine-tuning-llms-guide). Ad
- See detailed documentation for Unsloth [here](https://unsloth.ai/docs)
## 🦥 Unsloth News
- **AMD training**: Train, run RL, chat and deploy on AMD GPUs across Windows, WSL and Linux. [Guide](https://unsloth.ai/docs/basics/amd)
- **GGUF hardware controls**: Choose GPU/layer placement, offload MoE experts and use multi-GPU or Tensor Parallelism. [#6414](https://github.com/unslothai/unsloth/pull/6414)
- **Local models for any agent**: Use `unsloth start` with Claude Code, Codex, Hermes, OpenCode, OpenClaw, Pi and more through Unsloth's OpenAI- and Anthropic-compatible APIs. [Guide](https://unsloth.ai/docs/basics/api)
- **MCP control endpoint**: Let compatible clients manage models, training, recipes, checkpoints and exports. [#7191](https://github.com/unslothai/unsloth/pull/7191)
- **Local inference reliability**: Resume long chats faster, recover stalled downloads and reuse existing GGUF files. [#7204](https://github.com/unslothai/unsloth/pull/7204) • [#6858](https://github.com/unslothai/unsloth/pull/6858) • [#7209](https://github.com/unslothai/unsloth/pull/7209)
- **New models**: [Qwen-AgentWorld](https://huggingface.co/unsloth/Qwen-AgentWorld-35B-A3B-GGUF), [Ornith](https://huggingface.co/unsloth/models?search=ornith), [Kimi K2.7 Code](https://unsloth.ai/docs/models/kimi-k2.7-code) and [MiniMax M3](https://unsloth.ai/docs/models/minimax-m3)
- **GLM-5.2**: Run Z.ai's 744B-parameter, 1M-context open model locally with Unsloth Dynamic GGUFs. [Guide](https://unsloth.ai/docs/models/glm-5.2)
- **DeepSeek-V4**: Run DeepSeek-V4-Flash locally with corrected multi-turn and tool-calling behavior. [Guide](https://unsloth.ai/docs/models/deepseek-v4)
- **DiffusionGemma**: Run and fine-tune Google's diffusion language model with 1.8x faster inference in Unsloth Studio. [Guide](https://unsloth.ai/docs/models/diffusiongemma)
- **Qwen3.6**: Run and train Qwen3.6 with MTP for 1.4-2.2x faster inference and NVFP4 quants for supported GPUs. [Guide](https://unsloth.ai/docs/models/qwen3.6)
- **Gemma 4**: Run and train Gemma 4 text, image and audio models with QAT, MTP, GGUF and MLX support. [Guide](https://unsloth.ai/docs/models/gemma-4)
- **MCP servers**: Connect local models to files, apps, databases and external tools through Model Context Protocol. [Guide](https://unsloth.ai/docs/basics/mcp)
- **Connections**: Mix local models with API providers (OpenAI, Anthropic) or servers (vLLM, Ollama) in the same interface. [Guide](https://unsloth.ai/docs/integrations/connections)
- **Connections**: Connect any API provider (OpenAI, Anthropic) or server (vLLM, Ollama). [Guide](https://unsloth.ai/docs/integrations/connections)
- **MTP**: Run Qwen3.6 MTP in Unsloth. MTP settings are autoset specific to your hardware. [Guide](https://unsloth.ai/docs/models/qwen3.6#mtp-guide)
- **API inference endpoint**: Deploy and run local LLMs in Claude Code, Codex tools. [Guide](https://unsloth.ai/docs/basics/api)
- **Qwen3.6**: Qwen3.6-35B-A3B can now be trained and run in Unsloth Studio. [Blog](https://unsloth.ai/docs/models/qwen3.6)
- **Gemma 4**: Run and train Googles new models directly in Unsloth. [Blog](https://unsloth.ai/docs/models/gemma-4)
- **Introducing Unsloth Studio**: our new web UI for running and training LLMs. [Blog](https://unsloth.ai/docs/new/studio)
- **Qwen3.5** - 0.8B, 2B, 4B, 9B, 27B, 35-A3B, 112B-A10B are now supported. [Guide + notebooks](https://unsloth.ai/docs/models/qwen3.5/fine-tune)
- Train **MoE LLMs 12x faster** with 35% less VRAM - DeepSeek, GLM, Qwen and gpt-oss. [Blog](https://unsloth.ai/docs/new/faster-moe)
- **Embedding models**: Unsloth now supports ~1.8-3.3x faster embedding fine-tuning. [Blog](https://unsloth.ai/docs/new/embedding-finetuning) • [Notebooks](https://unsloth.ai/docs/get-started/unsloth-notebooks#embedding-models)
- New **7x longer context RL** vs. all other setups, via our new batching algorithms. [Blog](https://unsloth.ai/docs/new/grpo-long-context)
@ -225,19 +162,13 @@ Read our [guide](https://unsloth.ai/docs/get-started/fine-tuning-llms-guide). Ad
## 📥 Advanced Installation
The below advanced instructions are for Unsloth Studio. For Unsloth Core advanced installation, [view our docs](https://unsloth.ai/docs/get-started/install/pip-install#advanced-pip-installation).
#### Developer / Nightly / Experimental installs: macOS, Linux, WSL:
The developer install builds from the `main` branch, which is the latest (nightly) source.
#### Developer installs: macOS, Linux, WSL:
```bash
git clone https://github.com/unslothai/unsloth
cd unsloth
./install.sh --local
unsloth studio -p 8888
```
To install into an isolated location (its own virtual env, `auth/`, `studio.db`, cache and llama.cpp build), set `UNSLOTH_STUDIO_HOME` and pass it again at launch:
```bash
UNSLOTH_STUDIO_HOME="$PWD/.studio" ./install.sh --local
UNSLOTH_STUDIO_HOME="$PWD/.studio" unsloth studio -p 8888
```
Then to update :
```bash
cd unsloth && git pull
@ -245,8 +176,7 @@ cd unsloth && git pull
unsloth studio -p 8888
```
#### Developer / Nightly / Experimental installs: Windows PowerShell:
The developer install builds from the `main` branch, which is the latest (nightly) source.
#### Developer installs: Windows PowerShell:
```powershell
git clone https://github.com/unslothai/unsloth.git
cd unsloth
@ -254,46 +184,40 @@ Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass
.\install.ps1 --local
unsloth studio -p 8888
```
To install into an isolated location (its own virtual env, `auth/`, `studio.db`, cache and llama.cpp build), set `UNSLOTH_STUDIO_HOME` and pass it again at launch:
```powershell
$env:UNSLOTH_STUDIO_HOME="$PWD\.studio"; .\install.ps1 --local
$env:UNSLOTH_STUDIO_HOME="$PWD\.studio"; unsloth studio -p 8888
```
Then to update :
```powershell
cd unsloth; git pull
.\install.ps1 --local
```bash
cd unsloth && git pull
./install.sh --local
unsloth studio -p 8888
```
#### Remote access: `--secure` (HTTPS tunnel) vs raw port
By default `unsloth studio` binds to `127.0.0.1` (this machine only). To reach it from another device, pick one of:
- `--secure` (recommended): serve **only** through a free Cloudflare HTTPS link. Unsloth stays bound to localhost and the tunnel provides the public URL; it fails closed (does not start) if the tunnel can't come up, so the raw port is never exposed.
#### Nightly: MacOS, Linux, WSL:
```bash
unsloth studio --secure -p 8888
git clone https://github.com/unslothai/unsloth
cd unsloth
git checkout nightly
./install.sh --local
unsloth studio -p 8888
```
- `-H 0.0.0.0`: bind the raw port on all network interfaces, reachable from anywhere on the network (subject to your firewall). It does not create a public internet URL; add `--cloudflare` to also publish an internet-reachable `https://*.trycloudflare.com` link even behind a firewall. Only use this on a network you trust.
Then to launch every time:
```bash
unsloth studio -H 0.0.0.0 -p 8888
```
The Cloudflare tunnel is **off by default**: `-H 0.0.0.0` exposes the raw port only, not a public internet URL. Pair the wildcard bind with `--cloudflare` (`unsloth studio -H 0.0.0.0 --cloudflare`) to also publish a public `https://*.trycloudflare.com` link, or prefer `--secure` (above), which keeps the raw port private. `--cloudflare` has no effect on a loopback bind.
On a wildcard bind Unsloth works out the address to share by asking `ifconfig.me` for the public IP, then asks `check-host.net` whether that port is reachable so it can tell you if a firewall is in the way. Both contact a third party. Set `UNSLOTH_STUDIO_DISABLE_PUBLIC_CHECK=1` to skip them; the banner then shows the LAN address and no reachability line.
The first time Unsloth is published on a public URL (`--secure` or `--cloudflare`) with the auto-generated admin password still in place, it asks for a new admin password in the terminal (masked input with confirmation) before the public link goes up. Without an attached terminal it warns instead and keeps the bootstrap deadline: Unsloth shuts down after `UNSLOTH_STUDIO_BOOTSTRAP_TIMEOUT` (default 1 hour) unless the password is changed in the web UI.
For headless setups that cannot answer that prompt, set the initial admin password non-interactively with `--password` (only takes effect when no password is set yet; if one already exists it is a hard error, so rotate later with `unsloth studio reset-password`):
```bash
unsloth studio --secure --password 'your-strong-password' # visible in `ps`/history
UNSLOTH_STUDIO_PASSWORD='your-strong-password' unsloth studio --secure # via env var
printf '%s\n' 'your-strong-password' | unsloth studio --secure --password - # via stdin
unsloth studio -p 8888
```
A literal `--password VALUE` is visible in the process list and shell history, so prefer the `UNSLOTH_STUDIO_PASSWORD` env var or `--password -` (stdin) for automation. This applies to any launch (public or a headless `-H 0.0.0.0` bind), and the password is set in the parent before the server binds, so it never reaches a re-executed child process.
Server-side tools (web search, Python and terminal code execution) run as your user and are on by default. Anyone who can reach the server with the API key can run code on this machine, so keep your API key private and pass `--disable-tools` when exposing Unsloth.
#### Nightly: Windows:
Run in Windows Powershell:
```powershell
git clone https://github.com/unslothai/unsloth.git
cd unsloth
git checkout nightly
Set-ExecutionPolicy -Scope Process -ExecutionPolicy Bypass
.\install.ps1 --local
unsloth studio -p 8888
```
Then to launch every time:
```bash
unsloth studio -p 8888
```
#### Advanced launch options
Installer options can be passed as environment variables. On macOS, Linux and WSL place the variable after the pipe so the shell passes it to `sh`; on Windows set it with `$env:` before piping to `iex`.
@ -306,14 +230,6 @@ curl -fsSL https://unsloth.ai/install.sh | UNSLOTH_NO_TORCH=1 sh
$env:UNSLOTH_NO_TORCH=1; irm https://unsloth.ai/install.ps1 | iex
```
Skip the post-install prompt that starts Unsloth (useful for automated installs):
```bash
curl -fsSL https://unsloth.ai/install.sh | UNSLOTH_SKIP_AUTOSTART=1 sh
```
```powershell
$env:UNSLOTH_SKIP_AUTOSTART=1; irm https://unsloth.ai/install.ps1 | iex
```
Pin the Python version:
```bash
curl -fsSL https://unsloth.ai/install.sh | UNSLOTH_PYTHON=3.12 sh
@ -330,21 +246,7 @@ curl -fsSL https://unsloth.ai/install.sh | UNSLOTH_STUDIO_HOME=/abs/path sh
$env:UNSLOTH_STUDIO_HOME='C:\path'; irm https://unsloth.ai/install.ps1 | iex
```
On macOS, the installer defaults to the system certificate store (`UV_SYSTEM_CERTS=1`) so uv trusts the CAs in your Keychain, needed behind TLS-inspecting proxies (Cisco Umbrella, Zscaler, etc.). Opt out with:
```bash
curl -fsSL https://unsloth.ai/install.sh | UV_SYSTEM_CERTS=0 sh
```
Point the frontend build at a corporate npm mirror/proxy with `UNSLOTH_NPM_REGISTRY` (for the developer install behind a firewall that blocks `registry.npmjs.org`):
```bash
UNSLOTH_NPM_REGISTRY=https://artifactory.example.com/api/npm/npm/ ./install.sh --local
```
```powershell
$env:UNSLOTH_NPM_REGISTRY='https://artifactory.example.com/api/npm/npm/'; .\install.ps1 --local
```
It is threaded as `--registry` into the Unsloth frontend `npm`/`bun` installs; the supply-chain locks (7-day `min-release-age`, exact version pins) stay in force.
Cap Unsloth's native CPU thread pools on high-core hosts: `UNSLOTH_CPU_THREADS=8 unsloth studio -p 8888`.
Cap Studio's native CPU thread pools on high-core hosts: `UNSLOTH_CPU_THREADS=8 unsloth studio -p 8888`.
#### Uninstall
The recommended way to fully remove Unsloth Studio is the matching uninstall script for your OS. It stops any running servers, removes the install dir, the launcher data dir, the desktop shortcut, and any platform-specific entries (macOS `.app` bundle + Launch Services on Mac; Start Menu, `HKCU\Software\Unsloth` registry key and user `PATH` entries on Windows):

View file

@ -1,36 +0,0 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
"""Snapshot CHANGELOG.md into the studio package at build time.
CHANGELOG.md at the repo root stays the one file to edit. Copying it here,
rather than in build.sh, means every packaging path ships it, so release notes
still render when the popup cannot reach GitHub."""
from __future__ import annotations
import shutil
from pathlib import Path
from setuptools.command.build_py import build_py as _build_py
ROOT = Path(__file__).resolve().parent
SOURCE = ROOT / "CHANGELOG.md"
SNAPSHOT = ROOT / "studio" / "CHANGELOG.md"
class build_py(_build_py):
def run(self) -> None:
# Beside the sources only if writable (PEP 517 may build an immutable
# checkout); into the staging directory always.
if SOURCE.is_file():
try:
shutil.copyfile(SOURCE, SNAPSHOT)
except OSError:
pass
super().run()
if not SOURCE.is_file():
return
staged = Path(self.build_lib) / "studio" / "CHANGELOG.md"
staged.parent.mkdir(parents = True, exist_ok = True)
shutil.copyfile(SOURCE, staged)

View file

@ -1,12 +1,10 @@
#!/usr/bin/env bash
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
set -euo pipefail
# PyPI/Unsloth release publishing must use `./build.sh publish` (or an
# equivalent stamp -> build -> verify-dist -> upload flow) so packaged Unsloth
# artifacts include the display-only Unsloth release version.
# PyPI/Studio release publishing must use `./build.sh publish` (or an
# equivalent stamp -> build -> verify-dist -> upload flow) so packaged Studio
# artifacts include the display-only Studio release version.
# 1. Build frontend (Vite outputs to dist/)
cd studio/frontend
@ -35,19 +33,10 @@ _restore_gitignores() {
}
trap _restore_gitignores EXIT
# Corporate-mirror / proxy escape hatch (#6491). When UNSLOTH_NPM_REGISTRY is set we
# thread it as `--registry <url>` into the installs (overrides frontend/.npmrc's pinned
# registry for both bun and npm; min-release-age / save-exact stay in force). Empty
# array (the default) expands to nothing under `set -u`.
_NPM_REGISTRY_ARGS=()
if [ -n "${UNSLOTH_NPM_REGISTRY:-}" ]; then
_NPM_REGISTRY_ARGS=(--registry "$UNSLOTH_NPM_REGISTRY")
fi
# Use bun for install if available (faster), fall back to npm.
_install_ok=false
if command -v bun &>/dev/null; then
if bun install "${_NPM_REGISTRY_ARGS[@]+"${_NPM_REGISTRY_ARGS[@]}"}"; then
if bun install; then
_install_ok=true
else
echo "⚠ bun install failed, falling back to npm"
@ -55,10 +44,8 @@ if command -v bun &>/dev/null; then
fi
fi
if [ "$_install_ok" != "true" ]; then
if ! npm install "${_NPM_REGISTRY_ARGS[@]+"${_NPM_REGISTRY_ARGS[@]}"}"; then
if ! npm install; then
echo "❌ ERROR: package install failed" >&2
echo " If you are behind a corporate firewall/proxy, set UNSLOTH_NPM_REGISTRY to your mirror and retry, e.g.:" >&2
echo " UNSLOTH_NPM_REGISTRY=https://your-mirror.example/api/npm/ ./build.sh" >&2
exit 1
fi
fi
@ -87,7 +74,7 @@ cd ../..
# 2. Clean old artifacts
rm -rf build dist *.egg-info
# 3. Stamp display-only Unsloth release metadata for packaged builds.
# 3. Stamp display-only Studio release metadata for packaged builds.
_STUDIO_BUILD_INFO="studio/backend/utils/_studio_release_build.py"
_STUDIO_BUILD_INFO_BACKUP="$(mktemp)"
cp "$_STUDIO_BUILD_INFO" "$_STUDIO_BUILD_INFO_BACKUP"
@ -103,13 +90,9 @@ else
STUDIO_STAMPED_VERSION="$(python scripts/stamp_studio_release.py)"
fi
# 4. Build wheel/sdist. _changelog_build.py snapshots CHANGELOG.md into the studio
# package so release notes render offline.
# 4. Build wheel/sdist
python -m build
# Drop the snapshot so a source checkout never serves a stale copy.
rm -f studio/CHANGELOG.md
if [ "${1:-}" = "publish" ]; then
python scripts/stamp_studio_release.py --verify-dist dist --expected "$STUDIO_STAMPED_VERSION"
fi

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@ -1,71 +0,0 @@
#!/bin/sh
# Build whisper.cpp's whisper-server for Studio's GGUF dictation engine.
#
# Installs into the managed Studio home so the backend's binary discovery
# (core/inference/stt_ggml_sidecar.py::find_whisper_server_binary) picks it up:
# <UNSLOTH_STUDIO_HOME>/whisper.cpp/build/bin/whisper-server (custom home)
# ~/.unsloth/whisper.cpp/build/bin/whisper-server (default)
#
# Usage:
# ./scripts/build_whisper_cpp.sh # build the pinned tag
# WHISPER_CPP_TAG=v1.9.0 ./scripts/build_whisper_cpp.sh
#
# Requires: git, cmake, a C/C++ toolchain (the same prerequisites as a
# llama.cpp source build). GPU backends are auto-detected by whisper.cpp's
# CMake (Metal on macOS; set GGML_CUDA=1 to force a CUDA build on Linux).
set -eu
WHISPER_CPP_SOURCE="${WHISPER_CPP_SOURCE:-https://github.com/ggml-org/whisper.cpp}"
WHISPER_CPP_TAG="${WHISPER_CPP_TAG:-v1.9.1}"
STUDIO_HOME="${UNSLOTH_STUDIO_HOME:-${STUDIO_HOME:-}}"
CUSTOM_STUDIO_HOME=false
if [ -n "$STUDIO_HOME" ]; then
CUSTOM_STUDIO_HOME=true
INSTALL_DIR="$STUDIO_HOME/whisper.cpp"
else
INSTALL_DIR="$HOME/.unsloth/whisper.cpp"
fi
command -v git >/dev/null 2>&1 || { echo "ERROR: git is required" >&2; exit 1; }
command -v cmake >/dev/null 2>&1 || { echo "ERROR: cmake is required" >&2; exit 1; }
# Same policy as studio/setup.sh's _assert_studio_owned_or_absent: never delete
# a directory under a custom Studio home unless Studio itself created it (the
# marker file below). Protects a user-managed whisper.cpp/src from rm -rf.
STUDIO_OWNED_MARKER=".unsloth-studio-owned"
if [ "$CUSTOM_STUDIO_HOME" = true ] && [ -e "$INSTALL_DIR" ] && \
[ ! -f "$INSTALL_DIR/$STUDIO_OWNED_MARKER" ]; then
echo "ERROR: $INSTALL_DIR already exists and is not marked as an Unsloth-owned whisper.cpp build tree." >&2
echo " Move it aside or choose an empty UNSLOTH_STUDIO_HOME before re-running." >&2
exit 1
fi
echo "==> Building whisper.cpp ($WHISPER_CPP_TAG) into $INSTALL_DIR"
mkdir -p "$INSTALL_DIR"
: > "$INSTALL_DIR/$STUDIO_OWNED_MARKER"
if [ ! -d "$INSTALL_DIR/src/.git" ]; then
rm -rf "$INSTALL_DIR/src"
git clone --depth 1 --branch "$WHISPER_CPP_TAG" "$WHISPER_CPP_SOURCE" "$INSTALL_DIR/src"
else
git -C "$INSTALL_DIR/src" fetch --depth 1 origin "$WHISPER_CPP_TAG"
git -C "$INSTALL_DIR/src" checkout FETCH_HEAD
fi
CMAKE_FLAGS="-DCMAKE_BUILD_TYPE=Release -DBUILD_SHARED_LIBS=OFF"
if [ "${GGML_CUDA:-0}" = "1" ]; then
CMAKE_FLAGS="$CMAKE_FLAGS -DGGML_CUDA=ON"
fi
# shellcheck disable=SC2086
cmake -S "$INSTALL_DIR/src" -B "$INSTALL_DIR/src/build" $CMAKE_FLAGS
NCPU="$(getconf _NPROCESSORS_ONLN 2>/dev/null || echo 4)"
cmake --build "$INSTALL_DIR/src/build" --config Release --target whisper-server -j"$NCPU"
mkdir -p "$INSTALL_DIR/build/bin"
cp "$INSTALL_DIR/src/build/bin/whisper-server" "$INSTALL_DIR/build/bin/whisper-server"
echo "==> Installed $INSTALL_DIR/build/bin/whisper-server"
"$INSTALL_DIR/build/bin/whisper-server" --help >/dev/null 2>&1 && echo "==> Binary runs OK"

View file

@ -52,7 +52,9 @@ EXPECTED_NOISE_FILES = {
}
# File types where a quoted string can be a module specifier.
JS_LIKE_EXT = re.compile(r"\.(ts|tsx|js|jsx|mjs|cjs|html|htm|css|scss|sass|json|jsonc)$")
JS_LIKE_EXT = re.compile(
r"\.(ts|tsx|js|jsx|mjs|cjs|html|htm|css|scss|sass|json|jsonc)$"
)
# Files where JS import patterns could be a real module reference (.mdx is
# real ESM; .md code fences are not).
SCRIPT_LIKE_EXT = re.compile(r"\.(ts|tsx|js|jsx|mjs|cjs|mdx)$")
@ -249,7 +251,9 @@ def classify(pkg: str, file: str, content: str) -> str | None:
if is_script and re.search(rf"\bimport\(\s*['\"]{esc}{sub}['\"]\s*\)", content):
return "dynamic_import"
# require / require.resolve
if is_script and re.search(rf"\brequire(?:\.resolve)?\(\s*['\"]{esc}{sub}['\"]\s*\)", content):
if is_script and re.search(
rf"\brequire(?:\.resolve)?\(\s*['\"]{esc}{sub}['\"]\s*\)", content
):
return "require"
# Re-exports: `export * from`, `export { x } from`, `export type { Foo } from`.
if is_script and re.search(
@ -261,12 +265,16 @@ def classify(pkg: str, file: str, content: str) -> str | None:
# HTML script / link. Match pkg as a complete path segment so
# `/node_modules/foo-extra/...` is not treated as usage of `foo`.
html_pkg = rf"{esc}(?:/[^'\"#?]*)?(?=['\"#?])"
if is_html and re.search(rf"<script[^>]*src\s*=\s*['\"][^'\"]*/{html_pkg}", content):
if is_html and re.search(
rf"<script[^>]*src\s*=\s*['\"][^'\"]*/{html_pkg}", content
):
return "html_script"
if is_html and re.search(rf"<link[^>]*href\s*=\s*['\"][^'\"]*/{html_pkg}", content):
return "html_link"
# TypeScript triple-slash
if is_ts and re.search(rf"///\s*<reference\s+types\s*=\s*['\"]{esc}{sub}['\"]", content):
if is_ts and re.search(
rf"///\s*<reference\s+types\s*=\s*['\"]{esc}{sub}['\"]", content
):
return "tsc_triple_slash"
# new URL("pkg/...", import.meta.url)
if is_script and re.search(rf"\bnew\s+URL\(\s*['\"]{esc}{sub}['\"]", content):
@ -479,12 +487,18 @@ def _next_real_bin(words: list[str], idx: int) -> str | None:
if first in {"npx", "pnpx", "bunx"} and idx + 1 < len(words):
idx += 1
continue
if first in {"pnpm", "yarn"} and idx + 2 < len(words) and words[idx + 1] in {"exec", "dlx"}:
if (
first in {"pnpm", "yarn"}
and idx + 2 < len(words)
and words[idx + 1] in {"exec", "dlx"}
):
idx += 2
continue
# 3. Wrapper bin (cross-env, dotenv): skip its flags and env prefixes.
bin_token = first.removeprefix("./node_modules/.bin/").removeprefix("node_modules/.bin/")
bin_token = first.removeprefix("./node_modules/.bin/").removeprefix(
"node_modules/.bin/"
)
if bin_token in _SCRIPT_WRAPPERS and bin_token not in seen_wrappers:
seen_wrappers.add(bin_token)
idx += 1
@ -510,7 +524,9 @@ def _next_real_bin(words: list[str], idx: int) -> str | None:
return None
def scripts_bin_refs(head_pkg: dict, bin_to_pkg: dict[str, str]) -> dict[str, list[str]]:
def scripts_bin_refs(
head_pkg: dict, bin_to_pkg: dict[str, str]
) -> dict[str, list[str]]:
"""Return `{package_name: ['scripts.X: cmd', ...]}` for every package
referenced via its bin name in package.json scripts.
@ -566,7 +582,11 @@ def tsconfig_compiler_types_refs() -> set[str]:
if not isinstance(t, str):
continue
# `vite/client` resolves to the `vite` package.
pkg = t.split("/", 1)[0] if not t.startswith("@") else "/".join(t.split("/", 2)[:2])
pkg = (
t.split("/", 1)[0]
if not t.startswith("@")
else "/".join(t.split("/", 2)[:2])
)
out.add(pkg)
return out
@ -704,7 +724,9 @@ _file_lines_cache: dict[str, list[str]] = {}
def _read_file(path: str) -> list[str]:
if path not in _file_lines_cache:
try:
_file_lines_cache[path] = Path(path).read_text(errors = "replace").splitlines()
_file_lines_cache[path] = (
Path(path).read_text(errors = "replace").splitlines()
)
except (OSError, UnicodeDecodeError):
_file_lines_cache[path] = []
return _file_lines_cache[path]
@ -819,14 +841,18 @@ def find_types_runtime_usage(pkg: str, tsc_types: set[str]) -> list[Hit]:
def main() -> int:
p = argparse.ArgumentParser(description = __doc__, formatter_class = argparse.RawTextHelpFormatter)
p = argparse.ArgumentParser(
description = __doc__, formatter_class = argparse.RawTextHelpFormatter
)
p.add_argument(
"--base",
default = "origin/main",
help = "git ref to diff against (default: origin/main). "
"Examples: HEAD~1, main, a-tag, a-sha.",
)
p.add_argument("--base-pkg", help = "optional override: read base package.json from this path")
p.add_argument(
"--base-pkg", help = "optional override: read base package.json from this path"
)
p.add_argument(
"--base-lock",
help = "optional override: read base package-lock.json from this path. "
@ -918,7 +944,9 @@ def main() -> int:
print(f" - {w}")
print()
if missing_imports:
print(f"Imports without a matching package.json dep ({len(missing_imports)}):")
print(
f"Imports without a matching package.json dep ({len(missing_imports)}):"
)
for file, ln, spec in missing_imports[:20]:
print(f" - {file}:{ln} imports '{spec}'")
print()
@ -956,7 +984,9 @@ def main() -> int:
return 1
return 0
print(f"Checking {len(removed)} removed package(s) from studio/frontend/package.json")
print(
f"Checking {len(removed)} removed package(s) from studio/frontend/package.json"
)
print(f"Base: {args.base} Head: working tree")
print()
@ -980,7 +1010,9 @@ def main() -> int:
top = f"node_modules/{name}"
top_path = top if top in reachable_paths else None
nested = sorted(
p for p in reachable_paths if p != top and p.endswith(f"/node_modules/{name}")
p
for p in reachable_paths
if p != top and p.endswith(f"/node_modules/{name}")
)
return top_path, nested
@ -1026,7 +1058,9 @@ def main() -> int:
_print_hygiene()
if failures:
print(f"FAIL: {len(failures)} removed package(s) still referenced and not resolvable")
print(
f"FAIL: {len(failures)} removed package(s) still referenced and not resolvable"
)
for name, _ in failures:
print(f" - {name}")
return 1

View file

@ -38,7 +38,9 @@ HIGH = "HIGH"
class Finding:
__slots__ = ("severity", "name", "version", "kind", "detail")
def __init__(self, severity: str, name: str, version: str, kind: str, detail: str) -> None:
def __init__(
self, severity: str, name: str, version: str, kind: str, detail: str
) -> None:
self.severity = severity
self.name = name
self.version = version
@ -161,7 +163,9 @@ def diff_new_install_scripts(base_lock: dict, head_lock: dict) -> list[Finding]:
if key in base:
continue # pre-existing install-script dep; not in scope
name = head[key]
version = key[len(name) + 1 :] if key.startswith(name + "@") else "<unversioned>"
version = (
key[len(name) + 1 :] if key.startswith(name + "@") else "<unversioned>"
)
scripts = _fetch_registry_scripts(name, version)
if scripts:
detail = "; ".join(f"{h}={cmd!r}" for h, cmd in scripts.items())

View file

@ -123,7 +123,9 @@ def remove_redundant_passes(text: str) -> tuple[str, bool]:
lines = text.splitlines(keepends=True)
changed = False
for node in sorted(redundant, key=lambda item: (item.lineno, item.col_offset), reverse=True):
for node in sorted(
redundant, key=lambda item: (item.lineno, item.col_offset), reverse=True
):
start = node.lineno - 1
end = (node.end_lineno or node.lineno) - 1
if start >= len(lines):
@ -181,7 +183,11 @@ def remove_blank_after_short_import(text: str) -> tuple[str, bool]:
out: list[list[ast.stmt]] = []
for attr in ("body", "orelse", "finalbody"):
val = getattr(node, attr, None)
if isinstance(val, list) and val and all(isinstance(s, ast.stmt) for s in val):
if (
isinstance(val, list)
and val
and all(isinstance(s, ast.stmt) for s in val)
):
out.append(val)
return out
@ -199,7 +205,9 @@ def remove_blank_after_short_import(text: str) -> tuple[str, bool]:
j += 1
if j + 1 < len(suite): # an import block followed by another statement
last_imp, nxt = suite[j], suite[j + 1]
gap = range((last_imp.end_lineno or last_imp.lineno) + 1, nxt.lineno)
gap = range(
(last_imp.end_lineno or last_imp.lineno) + 1, nxt.lineno
)
nums = [n for n in gap if 1 <= n <= len(lines)]
if nums and all(lines[n - 1].strip() == "" for n in nums):
drop.update(nums)
@ -211,7 +219,13 @@ def remove_blank_after_short_import(text: str) -> tuple[str, bool]:
return "".join(kept), True
_STRING_TRIVIA = (tokenize.NL, tokenize.NEWLINE, tokenize.COMMENT, tokenize.INDENT, tokenize.DEDENT)
_STRING_TRIVIA = (
tokenize.NL,
tokenize.NEWLINE,
tokenize.COMMENT,
tokenize.INDENT,
tokenize.DEDENT,
)
_DEF_MIN_PARAMS_FOR_MULTILINE = 3 # signatures with < this many params stay one line

View file

@ -3,14 +3,13 @@
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
#
# ──────────────────────────────────────────────────────────────────────────────
# Enable ROCm-on-WSL for AMD GPUs (Strix Halo/Point APUs AND discrete Radeon RX
# 7000/9000). Verified on gfx1151 (Radeon 8060S) and gfx1200 (Radeon RX 9060 XT).
# Enable ROCm-on-WSL for AMD Strix Halo (Radeon 8060S / gfx1151)
# ──────────────────────────────────────────────────────────────────────────────
# install.sh routes the detected arch to the right ROCm wheels once a runtime exists;
# what it does NOT do is install AMD's ROCm userspace + the WSL DXG bridge (librocdxg).
# This helper does that Linux-side prerequisite on Ubuntu 24.04 WSL2, invoked by
# install.sh when it sees an AMD GPU via /dev/dxg but no ROCm yet. Arch-agnostic: the
# arch is auto-detected from rocminfo (override UNSLOTH_WSL_GFX=gfx1200). Idempotent.
# install.sh already routes gfx1151 to the right ROCm wheels once a ROCm runtime
# is present; what it does NOT do is install AMD's ROCm userspace + the WSL DXG
# bridge. This helper automates that Linux-side prerequisite on Ubuntu 24.04
# WSL2 and is invoked by install.sh when it sees a Strix Halo APU in WSL (via
# /dev/dxg) but no ROCm runtime yet. Fully idempotent (re-run just re-verifies).
#
# Manual, admin-gated Windows prerequisite: an AMD Adrenalin driver with
# production ROCDXG/WSL support (26.2.2+). install.ps1 offers to update it. Once
@ -35,12 +34,10 @@ set -euo pipefail
# ── Tunables (override via env) ──────────────────────────────────────────────
ROCM_VER="${UNSLOTH_WSL_ROCM_VER:-7.2.1}" # ROCm release to install
# GPU arch: empty = auto-detect from rocminfo after install (override UNSLOTH_WSL_GFX=gfx1200).
# The ROCm + librocdxg setup is arch-agnostic; only verify + the smoke test need the arch.
GFX="${UNSLOTH_WSL_GFX:-}"
GFX="gfx1151"
LIBROCDXG_REF="${UNSLOTH_LIBROCDXG_REF:-develop}" # ROCm/librocdxg git ref to build
# AMD's wheel index for the (optional) smoke test; resolved after arch detection.
TORCH_INDEX=""
# AMD's gfx1151 wheel index (same one install.sh uses); only for the smoke test.
TORCH_INDEX="${UNSLOTH_AMD_ROCM_MIRROR:-https://repo.amd.com/rocm/whl}/${GFX}/"
# Optional torch smoke test (throwaway venv). OFF by default: install.sh installs
# torch itself into the real venv right after, so a duplicate download is wasteful.
SMOKE_TEST="${UNSLOTH_WSL_SMOKE_TEST:-0}"
@ -219,16 +216,16 @@ fi
echo "${ROCM_DIR}/lib" | $SUDO tee /etc/ld.so.conf.d/rocm.conf >/dev/null
$SUDO ldconfig
# ── Step 4: persist environment (system-wide so Unsloth's worker inherits it) ──
# ── Step 4: persist environment (system-wide so Studio's worker inherits it) ──
say "Persisting ROCm-on-WSL environment"
_envfile="/etc/profile.d/unsloth-rocm-wsl.sh"
$SUDO tee "$_envfile" >/dev/null <<EOF
# >>> Unsloth ROCm-on-WSL >>>
# >>> Unsloth ROCm-on-WSL (gfx1151) >>>
export HSA_ENABLE_DXG_DETECTION=1
export TORCH_ROCM_AOTRITON_ENABLE_EXPERIMENTAL=1
export PATH="${ROCM_DIR}/bin:\${PATH}"
export LD_LIBRARY_PATH="${ROCM_DIR}/lib:\${LD_LIBRARY_PATH:-}"
# <<< Unsloth ROCm-on-WSL <<<
# <<< Unsloth ROCm-on-WSL (gfx1151) <<<
EOF
# also drop into ~/.bashrc for interactive shells
if [ -n "${HOME:-}" ] && ! grep -q "Unsloth ROCm-on-WSL" "${HOME}/.bashrc" 2>/dev/null; then
@ -240,50 +237,32 @@ export PATH="${ROCM_DIR}/bin:${PATH}"
export LD_LIBRARY_PATH="${ROCM_DIR}/lib:${LD_LIBRARY_PATH:-}"
# ── Step 5: verify the runtime enumerates the GPU ────────────────────────────
say "Verifying rocminfo enumerates the GPU over DXG"
say "Verifying rocminfo sees ${GFX}"
# Capture rocminfo into a var BEFORE grepping: piping into `grep -q` SIGPIPEs
# rocminfo on first match, which under `set -o pipefail` turns a successful match
# into a pipeline failure.
# into a pipeline failure. Match the gfx1151 ISA "Name:" agent exactly (not a
# broad gfx1[0-9]) so a generic fallback ISA or unrelated RDNA GPU can't pass.
_rocminfo_out="$(rocminfo 2>/dev/null || true)"
# GPU agents advertise an ISA "Name: gfxNNNN". Match gfx[1-9] (excludes gfx000, the CPU
# agent), drop the "gfx*-generic" fallback ISA, and take the first real GPU arch.
_detected_gfx="$(printf '%s\n' "$_rocminfo_out" | grep -E 'Name:[[:space:]]*gfx[1-9]' | grep -v 'generic' | grep -oE 'gfx[1-9][0-9a-z]*' | head -1 || true)"
if [ -z "$_detected_gfx" ]; then
if ! printf '%s\n' "$_rocminfo_out" | grep -qE "Name:[[:space:]]*${GFX}([^0-9]|$)"; then
printf '%s\n' "$_rocminfo_out" | head -25 >&2 || true
die "rocminfo did not enumerate any GPU agent. Most common cause: the Windows AMD driver predates production ROCDXG -- update Adrenalin (install.ps1 offers this), reboot, and re-run."
die "rocminfo did not enumerate a ${GFX} GPU agent. Most common cause: the Windows AMD driver predates production ROCDXG -- update Adrenalin (install.ps1 offers this), reboot, and re-run."
fi
# Honour a caller-pinned arch (sanity-check via a consuming grep, not grep -q: under
# pipefail -q would SIGPIPE printf on large output and misreport the arch); else adopt.
if [ -n "$GFX" ] && ! printf '%s\n' "$_rocminfo_out" | grep -E "Name:[[:space:]]*${GFX}([^0-9]|$)" >/dev/null; then
die "rocminfo enumerated '${_detected_gfx}' but not the requested UNSLOTH_WSL_GFX='${GFX}'."
fi
GFX="${GFX:-$_detected_gfx}"
# Display-only summary: best-effort (|| true) so head's early pipe-close under
# `set -o pipefail` can't fail the bootstrap after verification already passed.
printf '%s\n' "$_rocminfo_out" | grep -E 'Marketing Name|Device Type|Compute Unit' | grep -iE "Radeon|GPU|Compute" | head -3 || true
note "ROCm-on-WSL runtime is live for ${GFX}."
# ── Step 6 (optional): torch smoke test from AMD's per-arch wheel index ───────
# ── Step 6 (optional): torch smoke test from the gfx1151 index ───────────────
if [ "$SMOKE_TEST" = "1" ]; then
say "Smoke-testing PyTorch on ${GFX} (throwaway venv)"
# Map the detected arch to AMD's repo.amd.com wheel family index.
case "$GFX" in
gfx1200|gfx1201) _fam="gfx120X-all" ;;
gfx1100|gfx1101|gfx1102|gfx1103) _fam="gfx110X-all" ;;
*) _fam="$GFX" ;; # gfx1150/gfx1151/gfx90a: own index
esac
TORCH_INDEX="${UNSLOTH_AMD_ROCM_MIRROR:-https://repo.amd.com/rocm/whl}/${_fam}/"
_venv="${HOME}/.unsloth/rocm-smoketest"
rm -rf "$_venv"; python3 -m venv "$_venv"
"$_venv/bin/pip" install --quiet --upgrade pip
# AMD arch index is primary (torch + triton); PyPI only an extra for pure-py
# gfx1151 index is primary (torch + triton); PyPI only an extra for pure-py
# deps. The constraint keeps pip on the ROCm wheel, not a newer PyPI CUDA torch.
"$_venv/bin/pip" install --index-url "$TORCH_INDEX" \
--extra-index-url https://pypi.org/simple "$TORCH_CONSTRAINT" || \
die "torch install from ${TORCH_INDEX} failed."
# WSL: torch's bundled ROCr must load the DXG bridge -- drop librocdxg into torch/lib.
_tlib="$("$_venv/bin/python" -c 'import torch,os;print(os.path.join(os.path.dirname(torch.__file__),"lib"))' 2>/dev/null || true)"
[ -d "$_tlib" ] && cp -f "${ROCM_DIR}"/lib/librocdxg.so* "$_tlib"/ 2>/dev/null || true
"$_venv/bin/python" - <<'PY'
import torch
ok = torch.cuda.is_available()

View file

@ -29,7 +29,9 @@ from pathlib import Path
try:
import yaml
except ImportError:
print("ERROR: PyYAML is required. Install with 'pip install pyyaml'", file = sys.stderr)
print(
"ERROR: PyYAML is required. Install with 'pip install pyyaml'", file = sys.stderr
)
sys.exit(2)
REPO_ROOT = Path(__file__).resolve().parents[1]
@ -52,14 +54,14 @@ def _normalise_on(on_field):
def _load_workflow(path: Path):
try:
return yaml.safe_load(path.read_text(encoding = "utf-8"))
return yaml.safe_load(path.read_text())
except Exception as exc:
print(f"ERROR: failed to parse {path}: {exc}", file = sys.stderr)
sys.exit(2)
def _extract_cache_keys(path: Path) -> list[str]:
text = path.read_text(encoding = "utf-8")
text = path.read_text()
keys: list[str] = []
for m in re.finditer(r"(?:^|\n)\s*key:\s*([^\n]+)", text):
keys.append(m.group(1).strip())
@ -104,7 +106,7 @@ def main() -> int:
for t in RESTRICTED_TRIGGERS:
if t in triggers:
text = path.read_text(encoding = "utf-8")
text = path.read_text()
if "lint:workflow_triggers-allow-workflow_run" not in text:
findings.append(
f"{path.name}: RESTRICTED trigger '{t}' requires an "
@ -133,7 +135,9 @@ def main() -> int:
)
if findings:
print("Workflow trigger lint failed with the following issues:", file = sys.stderr)
print(
"Workflow trigger lint failed with the following issues:", file = sys.stderr
)
for f in findings:
print(f" - {f}", file = sys.stderr)
return 1

View file

@ -2,7 +2,7 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
"""Lockfile supply-chain audit for the Unsloth frontend and Tauri shell.
"""Lockfile supply-chain audit for the Studio frontend and Tauri shell.
Runs BEFORE `npm ci` / `cargo fetch` in CI. Refuses to proceed when a
lockfile contains patterns indicating supply-chain injection (npm
@ -294,7 +294,7 @@ CARGO_REGISTRY_SOURCE = "registry+https://github.com/rust-lang/crates.io-index"
# Cargo non-registry source allowlist: `(crate_name, exact_source_string)`.
# Both must match verbatim; bumping the pinned SHA forces a re-review.
# Unsloth's Tauri shell pulls `fix-path-env` from git because it is not
# Studio's Tauri shell pulls `fix-path-env` from git because it is not
# published to crates.io; commit c4c45d5 was reviewed when it landed.
CARGO_SOURCE_ALLOWLIST: tuple[tuple[str, str], ...] = (
(
@ -459,7 +459,9 @@ def audit_npm_lockfile(path: Path) -> list[Finding]:
path = str(path),
package = key,
kind = "blocked-known-malicious",
detail = (f"{pkg_name}@{version} is on the BLOCKED_NPM_VERSIONS list"),
detail = (
f"{pkg_name}@{version} is on the BLOCKED_NPM_VERSIONS list"
),
)
)
@ -663,7 +665,9 @@ def main(argv: list[str] | None = None) -> int:
"--cargo-lockfile",
action = "append",
default = None,
help = ("Path to a Cargo.lock (repeatable). Default: studio/src-tauri/Cargo.lock."),
help = (
"Path to a Cargo.lock (repeatable). Default: studio/src-tauri/Cargo.lock."
),
)
parser.add_argument(
"--strict",

View file

@ -155,7 +155,9 @@ def convert_cell_to_python(source: str, *, allow_shell: bool = True) -> str:
cmd_lines.append(lines[i].strip())
full_cmd = "\n".join(cmd_lines)
result.extend(_emit_shell_command(indent, full_cmd, allow_shell = allow_shell))
result.extend(
_emit_shell_command(indent, full_cmd, allow_shell = allow_shell)
)
# %cd path -> os.chdir(path)
elif stripped.startswith("%cd "):
@ -278,7 +280,9 @@ def convert_notebook_to_script(
source_name = source
output_filename = filename.replace(".ipynb", ".py")
output_filename = output_filename.replace("(", "").replace(")", "").replace("-", "_")
output_filename = (
output_filename.replace("(", "").replace(")", "").replace("-", "_")
)
if output_dir:
output_path = os.path.join(output_dir, output_filename)
@ -297,7 +301,9 @@ def convert_notebook_to_script(
def main():
import argparse
class Formatter(argparse.ArgumentDefaultsHelpFormatter, argparse.RawDescriptionHelpFormatter):
class Formatter(
argparse.ArgumentDefaultsHelpFormatter, argparse.RawDescriptionHelpFormatter
):
pass
parser = argparse.ArgumentParser(
@ -311,8 +317,12 @@ Examples:
python notebook_to_python.py https://github.com/unslothai/notebooks/blob/main/nb/Oute_TTS_(1B).ipynb
""",
)
parser.add_argument("notebooks", nargs = "+", help = "Notebook files or URLs to convert.")
parser.add_argument("-o", "--output", dest = "output_dir", default = ".", help = "Output directory.")
parser.add_argument(
"notebooks", nargs = "+", help = "Notebook files or URLs to convert."
)
parser.add_argument(
"-o", "--output", dest = "output_dir", default = ".", help = "Output directory."
)
# Default True for backwards compat; pass --no-allow-shell for untrusted notebooks.
parser.add_argument(
"--allow-shell",

View file

@ -87,7 +87,9 @@ COLAB_ORACLE_FILES: dict[str, str] = {
"apt-list-gpu.txt": "colab_apt_list.gpu.txt",
"os-info-gpu.txt": "colab_os_info.gpu.txt",
}
COLAB_ORACLE_BASE_URL = "https://raw.githubusercontent.com/googlecolab/backend-info/main/"
COLAB_ORACLE_BASE_URL = (
"https://raw.githubusercontent.com/googlecolab/backend-info/main/"
)
# ----- Compat tables. PRs add rows as new releases land. ----- #
@ -95,8 +97,8 @@ COLAB_ORACLE_BASE_URL = "https://raw.githubusercontent.com/googlecolab/backend-i
# Source: pytorch/torchcodec compatibility matrix on its README.
TORCH_TORCHCODEC: dict[str, set[str]] = {
"2.10": {"0.10"},
"2.9": {"0.8", "0.9"},
"2.8": {"0.6", "0.7"},
"2.9": {"0.7", "0.8", "0.9"},
"2.8": {"0.6"},
"2.7": {"0.3", "0.4", "0.5"},
"2.6": {"0.2", "0.3"},
"2.5": {"0.1", "0.2"},
@ -187,7 +189,9 @@ def install_cells(nb: dict[str, Any]) -> list[tuple[int, str]]:
if first and first[0].strip().startswith("%%capture"):
out.append((i, src))
continue
if re.search(r"^[ \t]*!\s*(uv\s+)?pip\s+(install|uninstall)\b", src, re.MULTILINE):
if re.search(
r"^[ \t]*!\s*(uv\s+)?pip\s+(install|uninstall)\b", src, re.MULTILINE
):
out.append((i, src))
return out
@ -318,7 +322,9 @@ def parse_pip_line(line: str, line_no: int = 0) -> PipInvocation | None:
if t in ("install", "uninstall"):
continue
packages.append(t)
return PipInvocation(tool = tool, flags = flags, packages = packages, raw = line, line_no = line_no)
return PipInvocation(
tool = tool, flags = flags, packages = packages, raw = line, line_no = line_no
)
def _glue_line_continuations(text: str) -> list[tuple[int, str]]:
@ -403,7 +409,9 @@ def pypi_metadata(name: str, version: str) -> dict[str, Any] | None:
return data
def transitive_constraint(name: str, version: str, target: str) -> tuple[str | None, list[str]]:
def transitive_constraint(
name: str, version: str, target: str
) -> tuple[str | None, list[str]]:
"""Return (raw_specifier_string_or_None, list_of_(op,version) tuples)
for the constraint that `name==version` places on `target`.
"""
@ -477,7 +485,10 @@ def resolved_set(install_cell: str, colab: dict[str, str]) -> dict[str, str]:
out[sp.name] = ver
pinned.add(sp.name)
elif op == "<=" and sp.name not in pinned:
if sp.name not in upper_bounds or cmp_versions(ver, upper_bounds[sp.name]) < 0:
if (
sp.name not in upper_bounds
or cmp_versions(ver, upper_bounds[sp.name]) < 0
):
upper_bounds[sp.name] = ver
# Apply upper bounds where Colab's preinstall violates them.
for name, ub in upper_bounds.items():
@ -492,7 +503,9 @@ def resolved_set(install_cell: str, colab: dict[str, str]) -> dict[str, str]:
# ----- Rules ----- #
def rule_inst_001_git_plus(install_cell: str, file: str, cell_idx: int) -> list[Finding]:
def rule_inst_001_git_plus(
install_cell: str, file: str, cell_idx: int
) -> list[Finding]:
findings: list[Finding] = []
for inv in iter_pip_invocations(install_cell):
if any("git+" in p for p in inv.packages) or "git+" in inv.raw:
@ -680,7 +693,9 @@ def rule_inst_005_transformers_tokenizers(
_RE_DOUBLE_BANG = re.compile(r"^[ \t]*!{2,}\s*pip\b", re.MULTILINE)
def rule_inst_006_double_bang(install_cell: str, file: str, cell_idx: int) -> list[Finding]:
def rule_inst_006_double_bang(
install_cell: str, file: str, cell_idx: int
) -> list[Finding]:
findings: list[Finding] = []
for m in _RE_DOUBLE_BANG.finditer(install_cell):
line_no = install_cell.count("\n", 0, m.start()) + 1
@ -771,7 +786,9 @@ POLICY_CLAUSES_DEFAULT = [
]
def extract_policy_clauses(update_script: pathlib.Path) -> list[tuple[str, re.Pattern[str], Any]]:
def extract_policy_clauses(
update_script: pathlib.Path,
) -> list[tuple[str, re.Pattern[str], Any]]:
"""Best-effort scan of update_all_notebooks.py for canonical phrases;
falls back to POLICY_CLAUSES_DEFAULT (which we use directly today). The
permissive regexes avoid false positives on template rewords."""
@ -831,7 +848,11 @@ def cmd_drift(args: argparse.Namespace) -> int:
print(f"FAIL: {update_script} not found", file = sys.stderr)
return 2
# Stash any pre-existing dirty state, run the updater, diff, restore.
head = subprocess.check_output(["git", "rev-parse", "HEAD"], cwd = nbdir).decode().strip()
head = (
subprocess.check_output(["git", "rev-parse", "HEAD"], cwd = nbdir)
.decode()
.strip()
)
subprocess.run(
["git", "-C", str(nbdir), "stash", "--include-untracked"],
check = False,
@ -932,7 +953,9 @@ def cmd_convert(args: argparse.Namespace) -> int:
hint = proc.stderr[-200:].strip(),
)
)
print(f"converted {len(notebooks) - len(failed)}/{len(notebooks)} notebooks to {out}")
print(
f"converted {len(notebooks) - len(failed)}/{len(notebooks)} notebooks to {out}"
)
_emit(failed)
return 0 if not failed else 1
@ -942,7 +965,11 @@ def cmd_convert(args: argparse.Namespace) -> int:
def cmd_lint(args: argparse.Namespace) -> int:
nbdir = pathlib.Path(args.notebooks_dir).resolve()
colab_path = pathlib.Path(args.colab_pin).resolve() if args.colab_pin else COLAB_FALLBACK_FILE
colab_path = (
pathlib.Path(args.colab_pin).resolve()
if args.colab_pin
else COLAB_FALLBACK_FILE
)
colab = parse_pip_freeze(colab_path)
if not colab:
print(
@ -982,9 +1009,13 @@ def cmd_lint(args: argparse.Namespace) -> int:
first_cell = cells[0][0] if cells else None
findings += rule_inst_003_peft_torchao(merged, oracle, rel, first_cell)
findings += rule_inst_004_torchcodec_torch(merged, oracle, rel, first_cell)
findings += rule_inst_005_transformers_tokenizers(merged, oracle, rel, first_cell)
findings += rule_inst_005_transformers_tokenizers(
merged, oracle, rel, first_cell
)
if not args.no_pypi:
findings += rule_inst_002_no_deps_transitive(merged, oracle, rel, first_cell)
findings += rule_inst_002_no_deps_transitive(
merged, oracle, rel, first_cell
)
findings += scan_user_cells(nb, rel)
_emit(findings)
return 0 if not any(f.severity == "error" for f in findings) else 1
@ -1159,7 +1190,9 @@ def cmd_colab_diff(args: argparse.Namespace) -> int:
print(f"::warning::colab-diff: could not fetch {url}: {e}")
continue
if not snap_path.exists():
print(f"::warning::colab-diff: no committed snapshot at {snap_path}; skipping")
print(
f"::warning::colab-diff: no committed snapshot at {snap_path}; skipping"
)
continue
snapshot_text = snap_path.read_text(encoding = "utf-8", errors = "replace")
parser = _COLAB_ORACLE_PARSERS[upstream_name]

View file

@ -1,377 +0,0 @@
#!/usr/bin/env python3
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
"""Measure where Unsloth Studio's startup time goes, per platform.
Nothing measured this before: the backend logs "lifespan startup completed in X ms"
but no test or CI job asserted a budget, and studio_test_kit discards the elapsed
time of its /healthz poll. A first local run (Linux, warm cache, fast server CPU)
found `import main` alone costs 6.6s before the server can bind, dominated by eager
module-level imports pulled in by the `routes` package:
torch 1930 ms self
unsloth_zoo 914 ms self
routes 779 ms self
transformers 524 ms self
Phases measured:
import `python -X importtime -c "import main"`, top cumulative + per-package self
spawn process start -> first byte on stdout
healthz process start -> /api/health (or /healthz) answers 200
lifespan the backend's own "lifespan startup completed in X ms" log line
Usage:
python scripts/profile_startup.py --repeats 3 --json out.json
python scripts/profile_startup.py --import-only # no server, no port needed
Exit code is 0 unless --max-healthz-seconds is given and exceeded.
"""
from __future__ import annotations
import argparse
import json
import math
import os
import platform
import re
import shutil
import socket
import statistics
import subprocess
import sys
import threading
import time
import urllib.error
import urllib.request
from pathlib import Path
REPO_ROOT = Path(__file__).resolve().parents[1]
BACKEND = REPO_ROOT / "studio" / "backend"
_IMPORTTIME_RE = re.compile(r"import time:\s+(\d+)\s+\|\s+(\d+)\s+\|(\s*)(\S.*)")
def _free_port() -> int:
with socket.socket() as s:
s.bind(("127.0.0.1", 0))
return int(s.getsockname()[1])
def profile_imports(python: str, top: int = 15) -> dict:
"""Cumulative and self import cost for the backend's module graph.
Run in a subprocess with -X importtime: the numbers are only meaningful for a
cold interpreter, and importing in-process would measure a warm sys.modules.
"""
proc = subprocess.run(
[python, "-X", "importtime", "-c", "import sys; sys.path.insert(0, '.'); import main"],
cwd = BACKEND,
capture_output = True,
text = True,
timeout = 900,
)
rows = []
for line in proc.stderr.splitlines():
m = _IMPORTTIME_RE.match(line)
if m:
rows.append((int(m.group(1)), int(m.group(2)), m.group(4).strip()))
if not rows:
return {"ok": False, "error": (proc.stderr or proc.stdout)[-2000:]}
if proc.returncode != 0:
# Rows survive up to the failure, so any total from a partial graph is wrong.
return {
"ok": False,
"error": (proc.stderr or proc.stdout)[-2000:],
"partial_rows": len(rows),
}
by_cum = sorted(rows, key = lambda r: -r[1])
# Total comes from the `main` row, not by_cum[0]: -X importtime also prints the
# interpreter's own startup graph (`site`), which can outrank a trivial main.
main_row = next((r for r in reversed(rows) if r[2] == "main"), None)
if main_row is None:
return {
"ok": False,
"error": "no `import main` row in -X importtime output\n"
+ (proc.stderr or proc.stdout)[-2000:],
}
self_by_pkg: dict[str, int] = {}
for self_us, _cum, name in rows:
pkg = name.split(".")[0]
self_by_pkg[pkg] = self_by_pkg.get(pkg, 0) + self_us
return {
"ok": True,
"total_seconds": round(main_row[1] / 1e6, 3),
"top_cumulative": [
{"module": n, "seconds": round(c / 1e6, 3)} for _s, c, n in by_cum[:top]
],
"self_by_package_ms": {
k: round(v / 1000) for k, v in sorted(self_by_pkg.items(), key = lambda x: -x[1])[:top]
},
}
def _terminate_tree(proc: subprocess.Popen) -> None:
"""Stop the server AND its children, which on Windows are a separate process.
CI profiles `Scripts/unsloth.exe`, a distlib launcher stub that CreateProcess's
the venv python and waits, so terminate() reaps the stub only: the real backend
keeps the inherited stdout handle, the reader thread never sees EOF, and
--repeats strands one server per iteration on the shared UNSLOTH_STUDIO_HOME.
taskkill /T walks the tree, as unsloth_cli/commands/start.py already does.
"""
if proc.poll() is not None:
return
if os.name == "nt":
try:
killed = subprocess.run(
["taskkill", "/PID", str(proc.pid), "/T", "/F"],
capture_output = True,
timeout = 30,
check = False,
)
if killed.returncode == 0:
return
except Exception:
# taskkill missing or timed out; fall through so the stub still dies.
pass
# check=False: a nonzero taskkill does not raise, so fall through as well.
proc.terminate()
def profile_launch(
bin_path: str,
port: int,
timeout_s: int = 300,
) -> dict:
"""Spawn the backend the way the desktop app does and time it to first 200."""
log_lines: list[str] = []
first_byte: list[float] = []
t0 = time.perf_counter()
proc = subprocess.Popen(
[bin_path, "studio", "--api-only", "-H", "127.0.0.1", "-p", str(port)],
cwd = REPO_ROOT,
stdout = subprocess.PIPE,
stderr = subprocess.STDOUT,
text = True,
bufsize = 1,
)
def _drain() -> None:
# Runs alongside the health polling: the first read timestamps the spawn
# phase, and an undrained pipe blocks the backend before it binds.
for line in proc.stdout:
if not first_byte:
first_byte.append(time.perf_counter() - t0)
log_lines.append(line.rstrip("\n"))
reader = threading.Thread(target = _drain, daemon = True)
reader.start()
t_healthz = None
deadline = t0 + timeout_s
try:
while time.perf_counter() < deadline:
if proc.poll() is not None:
break
if t_healthz is None:
for url in (
f"http://127.0.0.1:{port}/api/health",
f"http://127.0.0.1:{port}/healthz",
):
try:
with urllib.request.urlopen(url, timeout = 2) as r:
if r.status == 200:
t_healthz = time.perf_counter() - t0
break
except (urllib.error.URLError, OSError, TimeoutError):
pass
if t_healthz is not None:
break
time.sleep(0.25)
finally:
_terminate_tree(proc)
try:
# Safe: the reader drains the pipe, so the child cannot block on write().
proc.wait(timeout = 30)
except subprocess.TimeoutExpired:
proc.kill()
proc.wait()
reader.join(timeout = 10)
t_first_byte = first_byte[0] if first_byte else None
lifespan_ms = None
for line in log_lines:
m = re.search(r"lifespan startup completed in ([\d.]+)ms", line)
if m:
lifespan_ms = float(m.group(1))
return {
"spawn_seconds": round(t_first_byte, 3) if t_first_byte is not None else None,
"healthz_seconds": round(t_healthz, 3) if t_healthz is not None else None,
"lifespan_ms": lifespan_ms,
"reached_healthz": t_healthz is not None,
"log_tail": log_lines[-25:],
}
def python_version_of(python: str) -> str:
"""Version of the interpreter that runs the imports, not the one running us.
--python points at the installed Studio venv while this script runs under the
runner's system python, so platform.python_version() would label it wrong.
"""
if python == sys.executable:
return platform.python_version()
try:
proc = subprocess.run(
[python, "-c", "import platform; print(platform.python_version())"],
capture_output = True,
text = True,
timeout = 60,
)
if proc.returncode == 0 and proc.stdout.strip():
return proc.stdout.strip()
except (OSError, subprocess.SubprocessError):
pass
return "unknown"
def find_bin() -> str | None:
home = os.environ.get("UNSLOTH_STUDIO_HOME") or str(Path.home() / ".unsloth" / "studio")
names = ["unsloth.exe", "unsloth"] if platform.system() == "Windows" else ["unsloth"]
subdirs = ["unsloth_studio/Scripts", "unsloth_studio/bin", "bin", "Scripts"]
for sd in subdirs:
for n in names:
p = Path(home) / sd / n
if p.exists():
return str(p)
return shutil.which("unsloth")
def main(argv: list[str]) -> int:
ap = argparse.ArgumentParser(
description = __doc__, formatter_class = argparse.RawDescriptionHelpFormatter
)
ap.add_argument(
"--repeats",
type = int,
default = 1,
help = "launch repeats; the median is reported (imports are measured once)",
)
ap.add_argument(
"--python",
default = sys.executable,
help = "interpreter used for the import profile (default: this one)",
)
ap.add_argument("--bin", help = "path to the unsloth CLI (default: autodetect)")
ap.add_argument(
"--import-only",
action = "store_true",
help = "skip the server phases (no install needed beyond the deps)",
)
ap.add_argument(
"--max-healthz-seconds",
type = float,
help = "fail if the median time to a healthy port exceeds this",
)
ap.add_argument("--json", help = "write the full report here")
a = ap.parse_args(argv)
# range(0) launches nothing, leaving the budget check with nothing to fail on.
if a.repeats < 1:
ap.error("--repeats must be at least 1")
# Same reason: --import-only never launches anything.
if a.import_only and a.max_healthz_seconds is not None:
ap.error("--max-healthz-seconds cannot be combined with --import-only")
# nan and inf parse fine as floats but `med > budget` is then always False,
# so the gate would report success without ever bounding anything.
if a.max_healthz_seconds is not None and not math.isfinite(a.max_healthz_seconds):
ap.error("--max-healthz-seconds must be a finite number")
report: dict = {
"platform": platform.system().lower(),
"machine": platform.machine(),
"python": python_version_of(a.python),
"cpu_count": os.cpu_count(),
}
print("== import graph ==")
report["imports"] = profile_imports(a.python)
imp = report["imports"]
if imp.get("ok"):
print(f" import main: {imp['total_seconds']}s")
for row in imp["top_cumulative"][:8]:
print(f" {row['seconds']:7.3f}s {row['module']}")
print(" self time by package (ms):")
for k, v in list(imp["self_by_package_ms"].items())[:8]:
print(f" {v:8} ms {k}")
else:
print(f" FAILED: {imp.get('error', '')[:400]}")
if not a.import_only:
bin_path = a.bin or find_bin()
if not bin_path:
print(
"== launch == skipped: no unsloth CLI found "
"(set UNSLOTH_STUDIO_HOME or pass --bin)"
)
report["launch"] = {"skipped": "no unsloth CLI found"}
else:
print(f"== launch == {bin_path}")
runs = []
for i in range(a.repeats):
r = profile_launch(bin_path, _free_port())
runs.append(r)
print(
f" run {i + 1}: healthz={r['healthz_seconds']}s "
f"lifespan={r['lifespan_ms']}ms reached={r['reached_healthz']}"
)
got = [r["healthz_seconds"] for r in runs if r["healthz_seconds"] is not None]
report["launch"] = {
"runs": runs,
"failed_runs": sum(1 for r in runs if not r["reached_healthz"]),
"healthz_median_seconds": round(statistics.median(got), 3) if got else None,
"healthz_max_seconds": round(max(got), 3) if got else None,
}
if got:
print(
f" median time to healthy port: {report['launch']['healthz_median_seconds']}s"
)
if a.json:
Path(a.json).write_text(json.dumps(report, indent = 2), encoding = "utf-8")
print(f"\nwrote {a.json}")
if a.max_healthz_seconds is not None:
launch = report.get("launch") or {}
med = launch.get("healthz_median_seconds")
failed = launch.get("failed_runs") or 0
if failed:
# Failed launches fail the budget; dropping them would keep only the fast ones.
print(
f"::error::startup regression: {failed} of {len(launch.get('runs') or [])} "
f"launches never became healthy within the timeout"
)
return 1
if med is None:
# Nothing measured: exiting 0 would pass a requested budget without a
# single health request, so fail closed.
print(
"::error::startup regression: no healthz measurement, so the "
f"{a.max_healthz_seconds}s budget was never checked "
f"({launch.get('skipped') or 'launch phase produced no runs'})"
)
return 1
elif med > a.max_healthz_seconds:
print(
f"::error::startup regression: {med}s median to a healthy port "
f"exceeds the {a.max_healthz_seconds}s budget"
)
return 1
return 0
if __name__ == "__main__":
raise SystemExit(main(sys.argv[1:]))

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@ -1,5 +0,0 @@
{
"_comment": "scan_npm_packages.py allowlist. Each entry is a HIGH/CRITICAL finding manually judged benign. Matched on (package, package-relative path, pattern, evidence hash); a new payload under an already-listed package/path/pattern reopens instead of riding the entry. severity is for review only. Regenerate with --write-baseline AFTER reviewing every line. EMPTY by design: a full scan of studio/frontend/package-lock.json (915 packages) produced 0 findings, so nothing needs suppressing and the CI gate can run enforcing (SCAN_ENFORCE=1) as-is. If a future dependency adds a reviewed-benign HIGH/CRITICAL, add it here rather than weakening a pattern.",
"version": 3,
"entries": []
}

File diff suppressed because it is too large Load diff

File diff suppressed because one or more lines are too long

View file

@ -2,7 +2,7 @@
# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
"""Stamp and verify display-only Unsloth release metadata for builds."""
"""Stamp and verify display-only Studio release metadata for builds."""
from __future__ import annotations
@ -42,7 +42,9 @@ def _atomic_write_text(
REPO_ROOT = Path(__file__).resolve().parents[1]
BUILD_INFO_PATH = REPO_ROOT / "studio" / "backend" / "utils" / "_studio_release_build.py"
BUILD_INFO_PATH = (
REPO_ROOT / "studio" / "backend" / "utils" / "_studio_release_build.py"
)
BUILD_INFO_SUFFIX = "studio/backend/utils/_studio_release_build.py"
VERSION_RE = re.compile(r"^v\d+\.\d+\.\d+(?:-[0-9A-Za-z.][0-9A-Za-z.-]*)?$")
GIT_DESCRIBE_SUFFIX_RE = re.compile(r"-\d+-g[0-9A-Fa-f]+(?:-dirty)?$")
@ -50,7 +52,7 @@ MAX_VERSION_LENGTH = 64
PLACEHOLDER = """# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
\"\"\"Build-stamped Unsloth release metadata.
\"\"\"Build-stamped Studio release metadata.
Release builds may rewrite this module in the build workspace before creating
Python artifacts. Keep the committed value neutral so source checkouts do not
@ -145,7 +147,7 @@ def build_info_source(version: str | None) -> str:
return f'''# SPDX-License-Identifier: AGPL-3.0-only
# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
"""Build-stamped Unsloth release metadata."""
"""Build-stamped Studio release metadata."""
STUDIO_RELEASE_VERSION = {literal}
'''
@ -168,7 +170,7 @@ def stamp(require_release: bool) -> int:
version, source = resolve_version()
if version is not None and not is_valid_version(version):
print(
f"Invalid Unsloth release version from {source}: {version!r}",
f"Invalid Studio release version from {source}: {version!r}",
file = sys.stderr,
)
return 2
@ -196,9 +198,9 @@ def stamp(require_release: bool) -> int:
if version is None:
if require_release:
print(
"No Unsloth release version available. Set "
"No Studio release version available. Set "
"UNSLOTH_STUDIO_RELEASE_VERSION, build from a GitHub tag, "
"or run from an exact local Unsloth release tag.",
"or run from an exact local Studio release tag.",
file = sys.stderr,
)
return 2
@ -207,7 +209,7 @@ def stamp(require_release: bool) -> int:
return 0
_atomic_write_text(BUILD_INFO_PATH, build_info_source(version), encoding = "utf-8")
print(f"Stamping Unsloth release version {version} from {source}", file = sys.stderr)
print(f"Stamping Studio release version {version} from {source}", file = sys.stderr)
print(version)
return 0
@ -233,7 +235,7 @@ def _read_sdist_member(path: Path) -> str | None:
def verify_dist(expected: str, dist_dir: Path) -> int:
if not is_valid_version(expected):
print(f"Invalid expected Unsloth release version: {expected!r}", file = sys.stderr)
print(f"Invalid expected Studio release version: {expected!r}", file = sys.stderr)
return 2
artifacts = list(dist_dir.glob("*.whl")) + list(dist_dir.glob("*.tar.gz"))
@ -251,14 +253,14 @@ def verify_dist(expected: str, dist_dir: Path) -> int:
if content is None:
failures.append(f"{artifact.name}: missing {BUILD_INFO_SUFFIX}")
elif expected_line not in content:
failures.append(f"{artifact.name}: Unsloth release version mismatch")
failures.append(f"{artifact.name}: Studio release version mismatch")
if failures:
for failure in failures:
print(failure, file = sys.stderr)
return 2
print(f"Verified Unsloth release version {expected} in {len(artifacts)} artifact(s)")
print(f"Verified Studio release version {expected} in {len(artifacts)} artifact(s)")
return 0

View file

@ -74,7 +74,9 @@ def desired_key(name: str, versions: list[str]) -> str:
return f"{name}@{' || '.join(versions)}"
def compute_renames(policy: dict, lock_versions: dict[str, list[str]]) -> dict[str, str]:
def compute_renames(
policy: dict, lock_versions: dict[str, list[str]]
) -> dict[str, str]:
renames: dict[str, str] = {}
for key in policy:
name, rng = split_spec(key)
@ -93,7 +95,9 @@ def main(argv: list[str] | None = None) -> int:
ap = argparse.ArgumentParser(description = __doc__)
mode = ap.add_mutually_exclusive_group(required = True)
mode.add_argument("--check", action = "store_true", help = "exit 1 if pins are stale")
mode.add_argument("--fix", action = "store_true", help = "rewrite package.json in place")
mode.add_argument(
"--fix", action = "store_true", help = "rewrite package.json in place"
)
ap.add_argument(
"--dir",
type = Path,
@ -105,20 +109,26 @@ def main(argv: list[str] | None = None) -> int:
pkg_path = args.dir / "package.json"
lock_path = args.dir / "package-lock.json"
if not pkg_path.exists() or not lock_path.exists():
print(f"sync-allow-scripts: nothing to do ({args.dir} has no package.json + lockfile)")
print(
f"sync-allow-scripts: nothing to do ({args.dir} has no package.json + lockfile)"
)
return 0
pkg = json.loads(pkg_path.read_text(encoding = "utf-8"))
policy = pkg.get("allowScripts")
if not isinstance(policy, dict) or not policy:
print("sync-allow-scripts: no allowScripts policy in package.json, nothing to do")
print(
"sync-allow-scripts: no allowScripts policy in package.json, nothing to do"
)
return 0
lock = json.loads(lock_path.read_text(encoding = "utf-8"))
renames = compute_renames(policy, script_versions_from_lock(lock))
if not renames:
print(f"sync-allow-scripts: {len(policy)} allowScripts entries in sync with the lockfile")
print(
f"sync-allow-scripts: {len(policy)} allowScripts entries in sync with the lockfile"
)
return 0
for old, new in renames.items():
@ -132,7 +142,9 @@ def main(argv: list[str] | None = None) -> int:
return 1
pkg["allowScripts"] = {renames.get(k, k): v for k, v in policy.items()}
pkg_path.write_text(json.dumps(pkg, indent = 2, ensure_ascii = False) + "\n", encoding = "utf-8")
pkg_path.write_text(
json.dumps(pkg, indent = 2, ensure_ascii = False) + "\n", encoding = "utf-8"
)
print(
f"sync-allow-scripts: re-pinned {len(renames)} entr{'y' if len(renames) == 1 else 'ies'} in {pkg_path}"
)

View file

@ -22,68 +22,19 @@ function Uninstall-UnslothStudio {
param([string]$Path)
if ([string]::IsNullOrWhiteSpace($Path)) { return }
if (-not (Test-Path -LiteralPath $Path)) { return }
for ($attempt = 1; $attempt -le 4; $attempt++) {
for ($attempt = 1; $attempt -le 3; $attempt++) {
try {
Remove-Item -LiteralPath $Path -Recurse -Force -ErrorAction Stop
} catch {
if ($attempt -lt 4) { Start-Sleep -Milliseconds 700; continue }
_Substep "could not remove: $Path ($($_.Exception.Message))" "Yellow"
return
}
# Remove-Item -Recurse can report success yet leave a transiently-locked
# child (e.g. unsloth.ico in Explorer's icon cache); verify + retry so we
# never falsely claim "removed" or orphan the dir.
if (-not (Test-Path -LiteralPath $Path)) {
_Substep "removed: $Path" "Green"
return
} catch {
if ($attempt -lt 3) { Start-Sleep -Milliseconds 700; continue }
_Substep "could not remove: $Path ($($_.Exception.Message))" "Yellow"
}
if ($attempt -lt 4) { Start-Sleep -Milliseconds 700; continue }
_Substep "still present (files held open): $Path" "Yellow"
}
}
# Remove the shared data dir, but keep unsloth.ico if a WSL shortcut still points
# at it (else that shortcut blanks); uninstall.sh drops it when WSL is removed.
function _RemoveDataDirKeepingWslIcon {
param(
[string]$DataDir,
# WSL-shortcut search dirs; default Start Menu + Desktop, overridable for tests.
[string[]]$ShortcutDirs = $null
)
if ([string]::IsNullOrWhiteSpace($DataDir)) { return }
if (-not (Test-Path -LiteralPath $DataDir)) { return }
# $null = not passed (use defaults); test $null not truthiness so an explicit
# @() is honored (-not @() is $true).
if ($null -eq $ShortcutDirs) {
# Guard $env:APPDATA: it can be unset in service/CI Windows contexts, where
# an unguarded Join-Path emits a noisy parameter-binding error.
$ShortcutDirs = @()
if (-not [string]::IsNullOrWhiteSpace($env:APPDATA)) {
$ShortcutDirs += Join-Path $env:APPDATA "Microsoft\Windows\Start Menu\Programs"
}
try {
$desktop = [Environment]::GetFolderPath("Desktop")
if (-not [string]::IsNullOrWhiteSpace($desktop)) { $ShortcutDirs += $desktop }
} catch {}
}
$wslShortcuts = @()
foreach ($d in $ShortcutDirs) {
if ($d -and (Test-Path -LiteralPath $d)) {
$wslShortcuts += Get-ChildItem -LiteralPath $d -Filter "Unsloth Studio (WSL*.lnk" -ErrorAction SilentlyContinue
}
}
if (@($wslShortcuts).Count -eq 0) {
_RemovePath $DataDir
return
}
# A WSL shortcut survives: drop everything except its shared icon.
_Substep "keeping $(Join-Path $DataDir 'unsloth.ico') for the WSL shortcut" "Gray"
Get-ChildItem -LiteralPath $DataDir -Force -ErrorAction SilentlyContinue | ForEach-Object {
if ($_.Name -ne "unsloth.ico") { _RemovePath $_.FullName }
}
}
# A path is an Unsloth-owned root iff one of install.ps1's sentinels exists:
# A path is a Studio-owned root iff one of install.ps1's sentinels exists:
# <root>\share\studio.conf, <root>\unsloth_studio\.unsloth-studio-owned,
# or <root>\bin\unsloth.exe.
function _IsStudioRoot {
@ -164,7 +115,7 @@ function Uninstall-UnslothStudio {
return $p
}
# Discover non-default Unsloth roots from env vars + studio.conf files.
# Discover non-default Studio roots from env vars + studio.conf files.
# Mirrors install.ps1's precedence: UNSLOTH_STUDIO_HOME wins, STUDIO_HOME
# is ignored when both are set, so uninstalling install A doesn't also
# delete install B if the user has a stale STUDIO_HOME pointing at B.
@ -207,7 +158,7 @@ function Uninstall-UnslothStudio {
# Return $true iff the PID's image path lives under one of $KnownRoots.
# Prevents killing an unrelated process that happens to listen on a stale
# Unsloth port.
# Studio port.
function _PidUnderKnownRoot {
param([int]$Pid_, [string[]]$KnownRoots)
if (-not $KnownRoots -or $KnownRoots.Count -eq 0) { return $false }
@ -223,8 +174,8 @@ function Uninstall-UnslothStudio {
return $false
}
# Stop an Unsloth backend whose port is recorded in <DataDir>\studio.port.
# Only kills if the listening PID's exe path is under a known Unsloth root.
# Stop a Studio backend whose port is recorded in <DataDir>\studio.port.
# Only kills if the listening PID's exe path is under a known Studio root.
function _StopByPortFile {
param([string]$PortFile, [string[]]$KnownRoots)
if (-not (Test-Path -LiteralPath $PortFile -PathType Leaf)) { return }
@ -336,9 +287,6 @@ function Uninstall-UnslothStudio {
$defaultUnslothHome = if ($env:USERPROFILE) { Join-Path $env:USERPROFILE ".unsloth" } else { $null }
$defaultLlamaCpp = if ($defaultUnslothHome) { Join-Path $defaultUnslothHome "llama.cpp" } else { $null }
$defaultCache = if ($defaultUnslothHome) { Join-Path $defaultUnslothHome ".cache" } else { $null }
# Isolated Node.js runtime (install_node_prebuilt.py), a sibling of studio in
# default mode. No-op in env/custom mode (nested under the custom root) and absent.
$defaultNode = if ($defaultUnslothHome) { Join-Path $defaultUnslothHome "node" } else { $null }
# llama.cpp atomic-install staging root (install_llama_prebuilt.py .staging,
# sibling of the install dir). Usually pruned after activate, but an interrupted
# build can leave a "<name>.staging-XXXX" tree; removing it lets the empty-dir
@ -362,7 +310,7 @@ function Uninstall-UnslothStudio {
_StopStudioProcesses -KnownRoots $knownRoots
# Also stop anything holding a handle on the exact paths we delete (llama-server,
# the CLI shim, an mp-fork python with a venv DLL) so the dir delete isn't refused.
_StopProcessesLockingRoots -Roots (@($knownRoots) + @($defaultDataDir, $defaultLlamaCpp, $defaultCache, $defaultNode))
_StopProcessesLockingRoots -Roots (@($knownRoots) + @($defaultDataDir, $defaultLlamaCpp, $defaultCache))
# ── Remove custom-root install trees ──
_Step "Removing data and install directories..."
@ -372,7 +320,7 @@ function Uninstall-UnslothStudio {
continue
}
if (-not (_IsStudioRoot $r)) {
_Substep "refusing to remove non-Unsloth path: $r" "Yellow"
_Substep "refusing to remove non-Studio path: $r" "Yellow"
continue
}
_RemovePath $r
@ -380,18 +328,12 @@ function Uninstall-UnslothStudio {
# Default install dir (always at %USERPROFILE%\.unsloth\studio when present).
if ($defaultStudioHome) { _RemovePath $defaultStudioHome }
# Default data dir.
if ($defaultDataDir) { _RemoveDataDirKeepingWslIcon $defaultDataDir }
if ($defaultDataDir) { _RemovePath $defaultDataDir }
# Default-mode shared llama.cpp build + cache (siblings of studio under
# ~/.unsloth). No-op in env/custom mode and when absent.
if ($defaultLlamaCpp) { _RemovePath $defaultLlamaCpp }
if ($defaultCache) { _RemovePath $defaultCache }
# Isolated Node.js runtime (sibling of studio under ~/.unsloth). No-op in env/
# custom mode (nested under the custom root, removed with it) and when absent.
if ($defaultNode) { _RemovePath $defaultNode }
if ($defaultStaging) { _RemovePath $defaultStaging }
# llama.cpp install lock (serializes the shared build); a stray lock keeps
# ~/.unsloth from being pruned below. No-op in env/custom mode and when absent.
if ($defaultUnslothHome) { _RemovePath (Join-Path $defaultUnslothHome ".llama.cpp.install.lock") }
# Drop ~/.unsloth itself, but ONLY if now empty -- never nuke unrelated content.
if ($defaultUnslothHome -and (Test-Path -LiteralPath $defaultUnslothHome) -and
-not (Get-ChildItem -LiteralPath $defaultUnslothHome -Force -ErrorAction SilentlyContinue)) {
@ -420,11 +362,6 @@ function Uninstall-UnslothStudio {
}
} catch { }
# Re-sweep: the first pass may have left unsloth.ico locked by Explorer/SMEH for
# the native shortcut; that handle is now freed. (A surviving WSL shortcut still
# keeps the icon -- see the helper.)
if ($defaultDataDir -and (Test-Path -LiteralPath $defaultDataDir)) { _RemoveDataDirKeepingWslIcon $defaultDataDir }
# ── Clean user PATH and registry backup ──
_Step "Cleaning user PATH and registry..."
try {
@ -436,7 +373,7 @@ function Uninstall-UnslothStudio {
$entries = $rawPath -split ';'
$kept = New-Object System.Collections.ArrayList
$removedAny = $false
# Only remove PATH entries that live inside an Unsloth root we
# Only remove PATH entries that live inside a Studio root we
# actually own (default or env-mode). A literal substring
# match on `unsloth_studio` would clobber unrelated user
# virtualenvs that happen to share the name.

View file

@ -12,7 +12,7 @@
set -e
# Stop an Unsloth server via its PID file (written by install.sh's _spawn_terminal).
# Stop a Studio server via its PID file (written by install.sh's _spawn_terminal).
_kill_pid_file() {
_pid_file="$1"
[ -f "$_pid_file" ] || return 0
@ -47,7 +47,7 @@ _pkill_studio() {
command -v pkill >/dev/null 2>&1 || return 0
# Scope fallback patterns to the install roots we are removing so a
# different Unsloth install (different UNSLOTH_STUDIO_HOME) is not touched.
# different Studio install (different UNSLOTH_STUDIO_HOME) is not touched.
_kill_roots="$HOME/.unsloth/studio"
_roots_from_conf=$(_custom_studio_roots 2>/dev/null || true)
[ -n "$_roots_from_conf" ] && _kill_roots="$_kill_roots
@ -89,7 +89,7 @@ _remove_path() {
fi
}
# Accept as Unsloth root only if Unsloth sentinels exist (matches install.sh's
# Accept as Studio root only if Studio sentinels exist (matches install.sh's
# env-mode ownership guard at install.sh:1358-1361). A bare unsloth_studio/
# directory is NOT enough -- require the install-time owner marker so a user
# directory that happens to contain a folder named "unsloth_studio" is safe.
@ -175,8 +175,8 @@ _custom_studio_roots() {
_from_conf "$HOME/.local/share/unsloth/studio.conf"
}
# Remove $HOME/.local/bin/unsloth only if it's an Unsloth-managed symlink.
# Unsloth's install.sh writes this as a symlink into the studio venv
# Remove $HOME/.local/bin/unsloth only if it's a Studio-managed symlink.
# Studio's install.sh writes this as a symlink into the studio venv
# (install.sh: `ln -sfn "$VENV_DIR/bin/unsloth" "$_shim_path"`). A
# pip-installed `unsloth` CLI is a regular file — leave it alone to avoid
# wiping an unrelated install.
@ -206,7 +206,7 @@ _custom_studio_roots | while IFS= read -r _custom_root; do
continue
fi
if ! _is_studio_root "$_custom_root"; then
echo " refusing to remove non-Unsloth path: $_custom_root" >&2
echo " refusing to remove non-Studio path: $_custom_root" >&2
continue
fi
_remove_path "$_custom_root"
@ -217,16 +217,10 @@ _remove_path "$HOME/.unsloth/studio"
# when absent. A user-set UNSLOTH_LLAMA_CPP_PATH is intentionally kept.
_remove_path "$HOME/.unsloth/llama.cpp"
_remove_path "$HOME/.unsloth/.cache"
# Isolated Node.js runtime (install_node_prebuilt.py), a sibling of studio in
# default mode. No-op in env/custom mode (nested under the custom root) and absent.
_remove_path "$HOME/.unsloth/node"
# llama.cpp atomic-install staging root (install_llama_prebuilt.py .staging).
# Normally pruned after activate, but an interrupted build can leave it behind;
# removing it lets the rmdir below succeed. No-op in env/custom mode and absent.
_remove_path "$HOME/.unsloth/.staging"
# llama.cpp install lock (serializes the shared build); a stray one keeps ~/.unsloth
# from being pruned below. No-op in env/custom mode and when absent.
_remove_path "$HOME/.unsloth/.llama.cpp.install.lock"
# ROCm-on-WSL helper artifacts (librocdxg build clone + smoke-test venv). No-op
# where they don't exist; removing them lets the rmdir below succeed.
_remove_path "$HOME/.unsloth/librocdxg"
@ -234,7 +228,7 @@ _remove_path "$HOME/.unsloth/rocm-smoketest"
# Drop ~/.unsloth only if now empty (rmdir refuses non-empty, so user content is kept).
rmdir "$HOME/.unsloth" 2>/dev/null || true
_remove_path "$HOME/.local/share/unsloth"
# CLI shim: only the symlink Unsloth created, never a pip-installed file.
# CLI shim: only the symlink Studio created, never a pip-installed file.
_remove_cli_shim
echo "Removing desktop shortcut and launcher lock..."
@ -304,50 +298,11 @@ case "$_os" in
Remove-Item -LiteralPath $_.FullName -Force -ErrorAction SilentlyContinue
} catch { }
}
}
# Keep the shared icon while any Unsloth shortcut still uses it (native
# install or another WSL distro); drop it only with the last one.
$iconInUse = $false;
foreach ($d in $dirs) {
if (-not $d -or -not (Test-Path -LiteralPath $d)) { continue }
if (Get-ChildItem -LiteralPath $d -Filter "Unsloth Studio*.lnk" -ErrorAction SilentlyContinue) { $iconInUse = $true; break }
}
# Guard LOCALAPPDATA: empty on a service/SYSTEM account makes
# Join-Path throw, aborting the icon cleanup (mirror uninstall.ps1).
if (-not [string]::IsNullOrWhiteSpace($env:LOCALAPPDATA)) {
$iconDir = Join-Path $env:LOCALAPPDATA "Unsloth Studio";
$ico = Join-Path $iconDir "unsloth.ico";
if ((-not $iconInUse) -and (Test-Path -LiteralPath $ico)) { Remove-Item -LiteralPath $ico -Force -ErrorAction SilentlyContinue }
if ((Test-Path -LiteralPath $iconDir) -and -not (Get-ChildItem -LiteralPath $iconDir -Force -ErrorAction SilentlyContinue)) { Remove-Item -LiteralPath $iconDir -Recurse -Force -ErrorAction SilentlyContinue }
}' >/dev/null 2>&1 || true
fi
# Remove $1's shared unsloth.ico only if no Unsloth shortcut (native install
# or another WSL distro) still uses it, then drop the dir if empty. Reciprocal
# of uninstall.ps1's _RemoveDataDirKeepingWslIcon (keeps the icon for a
# surviving WSL shortcut when the native side is removed).
_drop_shared_icon_if_unused() {
_du="$1"
_icodir="$_du/AppData/Local/Unsloth Studio"
_icon_in_use=0
for _sd in \
"$_du/Desktop" \
"$_du/OneDrive/Desktop" \
"$_du"/OneDrive*/Desktop \
"$_du/AppData/Roaming/Microsoft/Windows/Start Menu/Programs"; do
[ -d "$_sd" ] || continue
for _any in "$_sd"/"Unsloth Studio"*.lnk; do
[ -e "$_any" ] && { _icon_in_use=1; break; }
done
[ "$_icon_in_use" = "1" ] && break
done
if [ "$_icon_in_use" = "0" ]; then
[ -f "$_icodir/unsloth.ico" ] && rm -f "$_icodir/unsloth.ico" 2>/dev/null || true
fi
[ -d "$_icodir" ] && rmdir "$_icodir" 2>/dev/null || true
}
# Fallback when powershell.exe can't run (interop disabled): remove WSL .lnk
# files via drvfs. The "Unsloth Studio (WSL..." name is WSL-specific, so a
# native install's "Unsloth Studio.lnk" never matches.
# Fallback when powershell.exe can't run (interop disabled): remove the
# WSL .lnk files via drvfs. The "Unsloth Studio (WSL..." name is
# WSL-specific, so a native install's "Unsloth Studio.lnk" never matches.
if [ "$_ps_ran" = "0" ]; then
for _drive in /mnt/c /mnt/d /mnt/e; do
[ -d "$_drive/Users" ] || continue
@ -370,8 +325,6 @@ case "$_os" in
done
fi
done
# Drop the shared icon only when no shortcut still needs it.
_drop_shared_icon_if_unused "$_udir"
done
done
fi

View file

@ -131,7 +131,8 @@ def _walk_yaml_diff(
"""Print a path-keyed summary of the first structural / scalar diff."""
if type(b) is not type(a):
print(
f" type-diff at {prefix or '/'}: " f"{type(b).__name__} -> {type(a).__name__}",
f" type-diff at {prefix or '/'}: "
f"{type(b).__name__} -> {type(a).__name__}",
)
return
if isinstance(b, dict):

View file

@ -161,7 +161,9 @@ class _Builder(ast.NodeVisitor):
def _visit_stmt(self, node: ast.AST, scope: Scope) -> None:
if isinstance(node, (ast.Import, ast.ImportFrom)):
star = isinstance(node, ast.ImportFrom) and any(a.name == "*" for a in node.names)
star = isinstance(node, ast.ImportFrom) and any(
a.name == "*" for a in node.names
)
if star:
scope.star_import = True
for alias in node.names:
@ -349,7 +351,9 @@ class _Builder(ast.NodeVisitor):
self._bind_args(node.args, child)
self._visit_expr(node.body, child)
return
if isinstance(node, (ast.ListComp, ast.SetComp, ast.GeneratorExp, ast.DictComp)):
if isinstance(
node, (ast.ListComp, ast.SetComp, ast.GeneratorExp, ast.DictComp)
):
child = Scope("comp", f"{scope.qualname}.<comp>", scope)
for i, gen in enumerate(node.generators):
# first iterable evaluates in the enclosing scope
@ -564,12 +568,6 @@ def compare(before_src: str, after_src: str, path: str) -> list[tuple[str, str]]
for n, tids in b["module_import_targets"].items():
if tids & after_used:
continue # resolved -> fine
# `from __future__ import ...` is a compiler directive, not a runtime
# binding: the name (`annotations`, ...) is never loaded, so it can never
# "resolve" to a use. Skip it so a legitimately-added future import
# (e.g. `annotations` for lazy PEP 604 `X | None` on py3.9) is not flagged.
if all(t.startswith("from:__future__:") for t in tids):
continue
newly_added = bool(tids - before_module_targets)
was_used_before = bool(tids & before_used)
if newly_added or was_used_before:
@ -587,30 +585,9 @@ def compare(before_src: str, after_src: str, path: str) -> list[tuple[str, str]]
)
# 3. TARGET-CHANGED (same scope+name resolves to a different import target)
# Only a *swap* is dangerous: a BEFORE target that is no longer reachable in
# AFTER means a reference was silently re-pointed. A pure superset growth
# (tbefore <= tafter) is the benign `import pkg.subA` + `import pkg.subB`
# case: both statements bind the same top-level name `pkg` to the same
# package object and only *add* submodule attributes (e.g. adding
# `import urllib.error` next to `import urllib.request`). Nothing the name
# resolved to before is lost, so no reference is re-pointed -- skip it.
#
# A deliberate *relocation* is also benign and must not block: when a name
# keeps its spelling but its import source is moved A -> B in THIS diff (the
# old `from A import x` is removed at module level and a new `from B import x`
# is added), the swap is intentional, not a silent re-point to a pre-existing
# different object. This mirrors the relocation tolerance already applied to
# TARGET-MISSING. The dangerous case -- the name now resolving to a target
# that already existed before (shadow/clash) -- is NOT exempted.
removed_module_targets = before_module_targets - after_module_targets
for key, tafter in b["target_by_use"].items():
tbefore = a["target_by_use"].get(key)
if tbefore and tbefore != tafter and (tbefore - tafter):
lost = tbefore - tafter
gained = tafter - tbefore
relocated = lost <= removed_module_targets and gained <= added_module_targets
if relocated:
continue
if tbefore and tbefore != tafter:
findings.append(
(
"BLOCKER",
@ -633,7 +610,9 @@ def compare(before_src: str, after_src: str, path: str) -> list[tuple[str, str]]
for scope, names in b["ambiguous"].items():
new = names - a["ambiguous"].get(scope, set())
for n in sorted(new):
findings.append(("WARN", f"{path}: AMBIGUOUS-BIND '{n}' import+non-import in {scope}"))
findings.append(
("WARN", f"{path}: AMBIGUOUS-BIND '{n}' import+non-import in {scope}")
)
# 6. TARGET-MISSING (informational): a scope stopped resolving to an import
# target. Real bugs are covered above; remaining cases are relocated code.
@ -645,7 +624,9 @@ def compare(before_src: str, after_src: str, path: str) -> list[tuple[str, str]]
if t in added_module_targets
else " [target not re-added here -> likely relocated/deleted]"
)
findings.append(("INFO", f"{path}: TARGET-MISSING {t} in scope {scope}{relocated}"))
findings.append(
("INFO", f"{path}: TARGET-MISSING {t} in scope {scope}{relocated}")
)
return findings
@ -790,7 +771,9 @@ def audit_files(paths: list[str]) -> int:
ok = n_err == 0 and n_fp == 0
print(
"\nAUDIT:",
"ROBUST (no crashes, no false positives vs pyflakes)" if ok else "NEEDS WORK (see above)",
"ROBUST (no crashes, no false positives vs pyflakes)"
if ok
else "NEEDS WORK (see above)",
)
return 0 if ok else 1
@ -826,12 +809,18 @@ def main() -> int:
blockers = [f for f in findings if f[0] == "BLOCKER"]
warns = [f for f in findings if f[0] == "WARN"]
infos = [f for f in findings if f[0] == "INFO"]
status = "CLEAN" if not blockers and not warns else ("BLOCKERS" if blockers else "WARNINGS")
status = (
"CLEAN"
if not blockers and not warns
else ("BLOCKERS" if blockers else "WARNINGS")
)
print(f"\n=== {path}: {status} ===")
for sev, m in blockers + warns + infos:
print(f" [{sev}] {m}")
any_blocker = any_blocker or bool(blockers)
print("\nOVERALL:", "FAIL (blockers found)" if any_blocker else "PASS (no blockers)")
print(
"\nOVERALL:", "FAIL (blockers found)" if any_blocker else "PASS (no blockers)"
)
return 1 if any_blocker else 0

View file

@ -1,34 +0,0 @@
# Unsloth Studio MCP server
Unsloth can expose a local MCP server so an MCP client can inspect models and
GPU state, validate recipes, start or stop training, inspect recipe output, and
export a loaded model.
The server is disabled by default. Enable it for a local Unsloth process with:
```bash
UNSLOTH_STUDIO_ENABLE_MCP=1 \
UNSLOTH_STUDIO_MCP_TOKEN='use-a-local-secret' \
unsloth studio
```
The endpoint is `http://127.0.0.1:8888/mcp/` when Unsloth uses its default port
(a request to `/mcp` redirects to the canonical `/mcp/`). Use the actual Unsloth
port when it is configured differently.
The high-impact tools are:
- `studio_status` and `list_local_models` for discovery
- `get_training_status`, `start_training`, `stop_training`, and `list_training_runs`
- `validate_recipe`, `get_recipe_job_status`, and `get_recipe_job_dataset`
- `load_checkpoint` and `export_gguf`
`start_training` accepts the same fields as the Unsloth `TrainingStartRequest`.
The request is validated by the existing Pydantic model before a subprocess is
started. Export paths use the existing Unsloth validation as well.
The endpoint always requires `UNSLOTH_STUDIO_MCP_TOKEN` and checks an exact
Bearer token for both HTTP and WebSocket connections. Keep it on localhost
unless the deployment has an authenticated reverse proxy. The MCP endpoint is
intentionally opt-in because tools can consume GPU memory, write model
artifacts, and stop active work.

View file

@ -1,145 +1,134 @@
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/unslothai/unsloth/blob/main/studio/Unsloth_Studio_Colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "markdown",
"metadata": {
"id": "6b87de59"
},
"source": [
"To run this, press \"*Runtime*\" and press \"*Run all*\" on a **free** Tesla T4 Google Colab instance!\n",
"<div class=\"align-center\">\n",
"<a href=\"https://unsloth.ai/\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png\" width=\"115\"></a>\n",
"<a href=\"https://discord.gg/unsloth\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/Discord button.png\" width=\"145\"></a>\n",
"<a href=\"https://unsloth.ai/docs/\"><img src=\"https://github.com/unslothai/unsloth/blob/main/images/documentation%20green%20button.png?raw=true\" width=\"125\"></a> Join Discord if you need help + ⭐ <i>Star us on <a href=\"https://github.com/unslothai/unsloth\">Github</a> </i> ⭐\n",
"</div>\n",
"\n",
"To install Unsloth Studio on your local device, follow [our guide](https://unsloth.ai/docs/new/unsloth-studio/install). Unsloth Studio is licensed [AGPL-3.0](https://github.com/unslothai/unsloth/blob/main/studio/LICENSE.AGPL-3.0).\n",
"\n",
"### Unsloth Studio\n",
"\n",
"Train and run open models with [**Unsloth Studio**](https://unsloth.ai/docs/new/unsloth-studio/start). NEW! Installation should now only take 2 mins!\n",
"\n",
"\n",
"We are actively working on making Unsloth Studio install on Colab T4 GPUs faster.\n",
"\n",
"[Features](https://unsloth.ai/docs/new/unsloth-studio#features) • [Quickstart](https://unsloth.ai/docs/new/unsloth-studio/start) • [Data Recipes](https://unsloth.ai/docs/new/unsloth-studio/data-recipe) • [Unsloth Chat](https://unsloth.ai/docs/new/unsloth-studio/chat) • [Export](https://unsloth.ai/docs/new/unsloth-studio/export)"
],
"id": "6b87de59"
},
{
"cell_type": "markdown",
"metadata": {
"id": "e4206349"
},
"source": [
"<p align=\"left\"><img src=\"https://github.com/unslothai/unsloth/raw/main/studio/frontend/public/studio%20github%20landscape%20colab%20display.png\" width=\"600\"></p>"
],
"id": "e4206349"
},
{
"cell_type": "markdown",
"metadata": {
"id": "27da2957"
},
"source": [
"### Setup: Clone repo and run setup"
],
"id": "27da2957"
},
{
"cell_type": "code",
"metadata": {
"id": "27e68f91"
},
"source": "!git clone --depth 1 --branch main https://github.com/unslothai/unsloth.git\n%cd /content/unsloth\n!chmod +x studio/setup.sh && ./studio/setup.sh --local",
"execution_count": null,
"outputs": [],
"id": "27e68f91"
},
{
"cell_type": "markdown",
"metadata": {
"id": "3e1771a9"
},
"source": [
"### Start Unsloth Studio"
],
"id": "3e1771a9"
},
{
"cell_type": "code",
"metadata": {
"id": "277e431e"
},
"source": [
"import sys\n",
"sys.path.insert(0, \"/content/unsloth/studio/backend\")\n",
"from colab import start\n",
"\n",
"# On Colab, start() auto-opens a Cloudflare link and prints admin login credentials.\n",
"# Use the Cloudflare link above the ready card to open Studio (in-cell iframes often stay blank).\n",
"start()\n",
"\n",
"# To skip the Cloudflare tunnel and try the in-notebook proxy iframe only:\n",
"# start(cloudflare=False)"
],
"execution_count": null,
"outputs": [],
"id": "277e431e"
},
{
"cell_type": "markdown",
"metadata": {
"id": "f2b0c6a1"
},
"source": [
"And we're done! If you have any questions on Unsloth, we have a [Discord](https://discord.gg/unsloth) channel! If you find any bugs or want to keep updated with the latest LLM stuff, or need help, join projects etc, feel free to join our Discord!\n",
"\n",
"Some other resources:\n",
"1. Looking to use Unsloth locally? Read our [Installation Guide](https://unsloth.ai/docs/get-started/install) for details on installing Unsloth on Windows, Docker, AMD, Intel GPUs.\n",
"2. Learn how to do Reinforcement Learning with our [RL Guide and notebooks](https://unsloth.ai/docs/get-started/reinforcement-learning-rl-guide).\n",
"3. Read our guides and notebooks for [Text-to-speech (TTS)](https://unsloth.ai/docs/basics/text-to-speech-tts-fine-tuning) and [vision](https://unsloth.ai/docs/basics/vision-fine-tuning) model support.\n",
"4. Explore our [LLM Tutorials Directory](https://unsloth.ai/docs/models/tutorials-how-to-fine-tune-and-run-llms) to find dedicated guides for each model.\n",
"5. Need help with Inference? Read our [Inference & Deployment page](https://unsloth.ai/docs/basics/inference-and-deployment) for details on using vLLM, llama.cpp, Ollama etc.\n",
"\n",
"<div class=\"align-center\">\n",
" <a href=\"https://unsloth.ai\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png\" width=\"115\"></a>\n",
" <a href=\"https://discord.gg/unsloth\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/Discord.png\" width=\"145\"></a>\n",
" <a href=\"https://unsloth.ai/docs/\"><img src=\"https://github.com/unslothai/unsloth/blob/main/images/documentation%20green%20button.png?raw=true\" width=\"125\"></a>\n",
"\n",
" Join Discord if you need help + ⭐️ <i>Star us on <a href=\"https://github.com/unslothai/unsloth\">Github</a> </i> ⭐️\n",
"\n",
" <b>This notebook is licensed <a href=\"https://github.com/unslothai/unsloth/blob/main/studio/LICENSE.AGPL-3.0\">AGPL-3.0</a></b>\n",
"</div>"
],
"id": "f2b0c6a1"
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"gpuType": "T4",
"provenance": [],
"include_colab_link": true
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/unslothai/unsloth/blob/main/studio/Unsloth_Studio_Colab.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
"nbformat": 4,
"nbformat_minor": 5
{
"cell_type": "markdown",
"id": "6b87de59",
"metadata": {
"id": "6b87de59"
},
"source": [
"To run this, press \"*Runtime*\" and press \"*Run all*\" on a **free** Tesla T4 Google Colab instance!\n",
"<div class=\"align-center\">\n",
"<a href=\"https://unsloth.ai/\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png\" width=\"115\"></a>\n",
"<a href=\"https://discord.gg/unsloth\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/Discord button.png\" width=\"145\"></a>\n",
"<a href=\"https://unsloth.ai/docs/\"><img src=\"https://github.com/unslothai/unsloth/blob/main/images/documentation%20green%20button.png?raw=true\" width=\"125\"></a> Join Discord if you need help + ⭐ <i>Star us on <a href=\"https://github.com/unslothai/unsloth\">Github</a> </i> ⭐\n",
"</div>\n",
"\n",
"To install Unsloth Studio on your local device, follow [our guide](https://unsloth.ai/docs/new/unsloth-studio/install). Unsloth Studio is licensed [AGPL-3.0](https://github.com/unslothai/unsloth/blob/main/studio/LICENSE.AGPL-3.0).\n",
"\n",
"### Unsloth Studio\n",
"\n",
"Train and run open models with [**Unsloth Studio**](https://unsloth.ai/docs/new/unsloth-studio/start). NEW! Installation should now only take 2 mins!\n",
"\n",
"\n",
"We are actively working on making Unsloth Studio install on Colab T4 GPUs faster.\n",
"\n",
"[Features](https://unsloth.ai/docs/new/unsloth-studio#features) • [Quickstart](https://unsloth.ai/docs/new/unsloth-studio/start) • [Data Recipes](https://unsloth.ai/docs/new/unsloth-studio/data-recipe) • [Studio Chat](https://unsloth.ai/docs/new/unsloth-studio/chat) • [Export](https://unsloth.ai/docs/new/unsloth-studio/export)"
]
},
{
"cell_type": "markdown",
"id": "e4206349",
"metadata": {
"id": "e4206349"
},
"source": [
"<p align=\"left\"><img src=\"https://github.com/unslothai/unsloth/raw/main/studio/frontend/public/studio%20github%20landscape%20colab%20display.png\" width=\"600\"></p>"
]
},
{
"cell_type": "markdown",
"id": "27da2957",
"metadata": {
"id": "27da2957"
},
"source": [
"### Setup: Clone repo and run setup"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "27e68f91",
"metadata": {
"id": "27e68f91"
},
"outputs": [],
"source": "!git clone --depth 1 --branch main https://github.com/unslothai/unsloth.git\n%cd /content/unsloth\n!chmod +x studio/setup.sh && ./studio/setup.sh --local"
},
{
"cell_type": "markdown",
"id": "3e1771a9",
"metadata": {
"id": "3e1771a9"
},
"source": [
"### Start Unsloth Studio"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "277e431e",
"metadata": {
"id": "277e431e"
},
"outputs": [],
"source": "import sys\nsys.path.insert(0, \"/content/unsloth/studio/backend\")\nfrom colab import start\nstart()"
},
{
"cell_type": "markdown",
"id": "f2b0c6a1",
"metadata": {
"id": "f2b0c6a1"
},
"source": [
"And we're done! If you have any questions on Unsloth, we have a [Discord](https://discord.gg/unsloth) channel! If you find any bugs or want to keep updated with the latest LLM stuff, or need help, join projects etc, feel free to join our Discord!\n",
"\n",
"Some other resources:\n",
"1. Looking to use Unsloth locally? Read our [Installation Guide](https://unsloth.ai/docs/get-started/install) for details on installing Unsloth on Windows, Docker, AMD, Intel GPUs.\n",
"2. Learn how to do Reinforcement Learning with our [RL Guide and notebooks](https://unsloth.ai/docs/get-started/reinforcement-learning-rl-guide).\n",
"3. Read our guides and notebooks for [Text-to-speech (TTS)](https://unsloth.ai/docs/basics/text-to-speech-tts-fine-tuning) and [vision](https://unsloth.ai/docs/basics/vision-fine-tuning) model support.\n",
"4. Explore our [LLM Tutorials Directory](https://unsloth.ai/docs/models/tutorials-how-to-fine-tune-and-run-llms) to find dedicated guides for each model.\n",
"5. Need help with Inference? Read our [Inference & Deployment page](https://unsloth.ai/docs/basics/inference-and-deployment) for details on using vLLM, llama.cpp, Ollama etc.\n",
"\n",
"<div class=\"align-center\">\n",
" <a href=\"https://unsloth.ai\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png\" width=\"115\"></a>\n",
" <a href=\"https://discord.gg/unsloth\"><img src=\"https://github.com/unslothai/unsloth/raw/main/images/Discord.png\" width=\"145\"></a>\n",
" <a href=\"https://unsloth.ai/docs/\"><img src=\"https://github.com/unslothai/unsloth/blob/main/images/documentation%20green%20button.png?raw=true\" width=\"125\"></a>\n",
"\n",
" Join Discord if you need help + ⭐️ <i>Star us on <a href=\"https://github.com/unslothai/unsloth\">Github</a> </i> ⭐️\n",
"\n",
" <b>This notebook is licensed <a href=\"https://github.com/unslothai/unsloth/blob/main/studio/LICENSE.AGPL-3.0\">AGPL-3.0</a></b>\n",
"</div>"
]
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"gpuType": "T4",
"provenance": [],
"include_colab_link": true
},
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

View file

@ -3,7 +3,7 @@
Source: google/gemma-4-31B-it HF discussion/PR #118 (adds the preserve_thinking
flag plus null-rendering, string-arguments validation, balanced turn tags, empty
messages handling, and OpenAI image_url/input_audio aliases).
Unsloth-local changes vs PR #118:
Studio-local changes vs PR #118:
1. preserve_thinking defaults to false (see SETUP block below).
2. The empty "<|channel>thought\n<channel|>" block on enable_thinking=false is
NOT emitted. Google ships a distinct template for E2B/E4B (google/gemma-4-E2B-it,

View file

@ -3,7 +3,7 @@
Source: google/gemma-4-31B-it HF discussion/PR #118 (adds the preserve_thinking
flag plus null-rendering, string-arguments validation, balanced turn tags, empty
messages handling, and OpenAI image_url/input_audio aliases).
Unsloth-local change: preserve_thinking defaults to false (see SETUP block below).
Studio-local change: preserve_thinking defaults to false (see SETUP block below).
Applied to unsloth/gemma-4-*-GGUF models so the embedded GGUF template does not
need re-downloading. Keep in sync with upstream if PR #118 changes.
-#}

View file

@ -30,7 +30,6 @@ lora:
vision_all_linear: false
use_rslora: false
use_loftq: false
use_dora: false
finetune_vision_layers: true
finetune_language_layers: true
finetune_attention_modules: true

View file

@ -235,13 +235,6 @@
"min_p": 0.1,
"repetition_penalty": 1.0
},
"deepseek-v4": {
"temperature": 1.0,
"top_p": 1.0,
"top_k": -1,
"min_p": 0.0,
"repetition_penalty": 1.0
},
"deepseek-r1": {
"temperature": 0.6,
"top_p": 0.95,
@ -284,13 +277,6 @@
"min_p": 0.01,
"repetition_penalty": 1.0
},
"minimax-m2.7": {
"temperature": 1.0,
"top_p": 0.95,
"top_k": 40,
"min_p": 0.01,
"repetition_penalty": 1.0
},
"minimax-m2.5": {
"temperature": 1.0,
"top_p": 0.95,
@ -401,10 +387,10 @@
"phi-4", "phi-3",
"mistral-nemo", "mistral-small", "mistral-large", "magistral", "ministral",
"devstral", "pixtral",
"deepseek-v4", "deepseek-r1", "deepseek-v3", "deepseek-ocr",
"deepseek-r1", "deepseek-v3", "deepseek-ocr",
"glm-5", "glm-4",
"nemotron",
"minimax-m2.7", "minimax-m2.5", "minimax",
"minimax-m2.5", "minimax",
"gpt-oss", "granite-4",
"kimi-k2", "kimi",
"lfm2", "smollm", "olmo", "falcon", "ernie", "seed", "grok", "mimo"

View file

@ -30,7 +30,6 @@ lora:
vision_all_linear: false
use_rslora: false
use_loftq: false
use_dora: false
finetune_vision_layers: true
finetune_language_layers: true
finetune_attention_modules: true

View file

@ -2,6 +2,7 @@
# Used for models without specific configurations
training:
trust_remote_code: false
max_seq_length: 2048
# num_epochs: 4
num_epochs: 0
@ -33,7 +34,6 @@ lora:
- "down_proj"
use_rslora: false
use_loftq: false
use_dora: false
finetune_vision_layers: true
finetune_language_layers: true
finetune_attention_modules: true
@ -48,6 +48,7 @@ logging:
log_frequency: 10
inference:
trust_remote_code: false
temperature: 0.7
top_p: 0.95
top_k: -1

View file

@ -34,7 +34,6 @@ lora:
- "down_proj"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false

View file

@ -30,7 +30,6 @@ lora:
- "query"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false

View file

@ -30,7 +30,6 @@ lora:
- "value"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false

View file

@ -33,7 +33,6 @@ lora:
- "down_proj"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false

View file

@ -29,7 +29,6 @@ lora:
- "Wqkv"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false

View file

@ -3,6 +3,7 @@
# Also applies to: unsloth/ERNIE-4.5-21B-A3B-PT
training:
trust_remote_code: false
max_seq_length: 2048
# num_epochs: 4
num_epochs: 0
@ -34,7 +35,6 @@ lora:
- "down_proj"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false
@ -42,3 +42,6 @@ logging:
enable_tensorboard: false
tensorboard_dir: "runs"
log_frequency: 10
inference:
trust_remote_code: false

View file

@ -4,6 +4,7 @@
# added inference parameters from unsloth notebook
training:
trust_remote_code: true
max_seq_length: 2048
# num_epochs: 4
num_epochs: 0
@ -35,7 +36,6 @@ lora:
- "down_proj"
use_rslora: false
use_loftq: false
use_dora: false
finetune_vision_layers: true
finetune_language_layers: true
finetune_attention_modules: true
@ -49,6 +49,7 @@ logging:
log_frequency: 10
inference:
trust_remote_code: true
temperature: 1.5
min_p: 0.1

View file

@ -3,6 +3,7 @@
# Also applies to: tiiuae/Falcon-H1-0.5B-Instruct, unsloth/Falcon-H1-0.5B-Instruct
training:
trust_remote_code: false
max_seq_length: 2048
# num_epochs: 4
num_epochs: 0
@ -34,7 +35,6 @@ lora:
- "down_proj"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false
@ -42,3 +42,6 @@ logging:
enable_tensorboard: false
tensorboard_dir: "runs"
log_frequency: 10
inference:
trust_remote_code: false

View file

@ -4,6 +4,7 @@
# added inference parameters from Ollama
training:
trust_remote_code: false
max_seq_length: 4096
# num_epochs: 4
num_epochs: 0
@ -35,7 +36,6 @@ lora:
- "down_proj"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false
@ -45,5 +45,6 @@ logging:
log_frequency: 10
inference:
trust_remote_code: false
temperature: 0
top_p: 0.9

View file

@ -4,6 +4,7 @@
# added inference parameters from unsloth guides
training:
trust_remote_code: false
max_seq_length: 4096
# num_epochs: 4
num_epochs: 0
@ -35,7 +36,6 @@ lora:
- "down_proj"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false
@ -45,6 +45,7 @@ logging:
log_frequency: 10
inference:
trust_remote_code: false
temperature: 1.0
top_k: 64
top_p: 0.95

View file

@ -2,6 +2,7 @@
# Based on Gemma2_(9B)-Alpaca.ipynb (same defaults for larger models)
training:
trust_remote_code: false
max_seq_length: 2048
# num_epochs: 4
num_epochs: 0
@ -33,7 +34,6 @@ lora:
- "down_proj"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false
@ -41,3 +41,6 @@ logging:
enable_tensorboard: false
tensorboard_dir: "runs"
log_frequency: 10
inference:
trust_remote_code: false

View file

@ -3,6 +3,7 @@
# Also applies to: unsloth/gemma-2-2b-bnb-4bit, google/gemma-2-2b
training:
trust_remote_code: false
max_seq_length: 2048
# num_epochs: 4
num_epochs: 0
@ -34,7 +35,6 @@ lora:
- "down_proj"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false
@ -42,3 +42,6 @@ logging:
enable_tensorboard: false
tensorboard_dir: "runs"
log_frequency: 10
inference:
trust_remote_code: false

View file

@ -4,6 +4,7 @@
# added inference parameters from unsloth guides
training:
trust_remote_code: false
max_seq_length: 2048
# num_epochs: 4
num_epochs: 0
@ -35,7 +36,6 @@ lora:
- "down_proj"
use_rslora: false
use_loftq: false
use_dora: false
logging:
enable_wandb: false
@ -45,6 +45,7 @@ logging:
log_frequency: 10
inference:
trust_remote_code: false
temperature: 1.0
top_k: 64
top_p: 0.95

View file

@ -4,6 +4,7 @@
# added inference parameters from unsloth guides
training:
trust_remote_code: false
max_seq_length: 2048
# num_epochs: 4
num_epochs: 0
@ -29,7 +30,6 @@ lora:
- "all-linear"
use_rslora: false
use_loftq: false
use_dora: false
finetune_vision_layers: true
finetune_language_layers: true
finetune_attention_modules: true
@ -43,6 +43,7 @@ logging:
log_frequency: 10
inference:
trust_remote_code: false
temperature: 1.0
top_k: 64
top_p: 0.95

View file

@ -4,6 +4,7 @@
# added inference parameters from unsloth guides
training:
trust_remote_code: false
max_seq_length: 2048
# num_epochs: 4
num_epochs: 0
@ -29,7 +30,6 @@ lora:
- "all-linear"
use_rslora: false
use_loftq: false
use_dora: false
finetune_vision_layers: true
finetune_language_layers: true
finetune_attention_modules: true
@ -43,6 +43,7 @@ logging:
log_frequency: 10
inference:
trust_remote_code: false
temperature: 1.0
top_k: 64
top_p: 0.95

View file

@ -4,6 +4,7 @@
# added inference parameters from unsloth guides
training:
trust_remote_code: false
max_seq_length: 2048
# num_epochs: 2
num_epochs: 0
@ -29,7 +30,6 @@ lora:
- "all-linear"
use_rslora: false
use_loftq: false
use_dora: false
finetune_vision_layers: true
finetune_language_layers: true
finetune_attention_modules: true
@ -43,6 +43,7 @@ logging:
log_frequency: 10
inference:
trust_remote_code: false
temperature: 1.0
top_k: 64
top_p: 0.95

View file

@ -4,6 +4,7 @@
# added inference parameters from unsloth guides
training:
trust_remote_code: false
max_seq_length: 1024
# num_epochs: 4
num_epochs: 0
@ -29,7 +30,6 @@ lora:
- "all-linear"
use_rslora: false
use_loftq: false
use_dora: false
finetune_vision_layers: true
finetune_language_layers: true
finetune_attention_modules: true
@ -45,6 +45,7 @@ logging:
audio_input: true
inference:
trust_remote_code: false
temperature: 1.0
top_k: 64
top_p: 0.95

View file

@ -4,6 +4,7 @@
# added inference parameters from unsloth guides
training:
trust_remote_code: false
max_seq_length: 2048
# num_epochs: 2
num_epochs: 0
@ -29,7 +30,6 @@ lora:
- "all-linear"
use_rslora: false
use_loftq: false
use_dora: false
finetune_vision_layers: true
finetune_language_layers: true
finetune_attention_modules: true
@ -45,6 +45,7 @@ logging:
audio_input: true
inference:
trust_remote_code: false
temperature: 1.0
top_k: 64
top_p: 0.95

View file

@ -2,6 +2,7 @@
# Also applies to: google/gemma-4-26B-A4B-it, unsloth/gemma-4-26B-A4B-it-GGUF
training:
trust_remote_code: false
max_seq_length: 2048
num_epochs: 0
learning_rate: 2e-4
@ -26,7 +27,6 @@ lora:
- "all-linear"
use_rslora: false
use_loftq: false
use_dora: false
finetune_vision_layers: true
finetune_language_layers: true
finetune_attention_modules: true
@ -40,6 +40,7 @@ logging:
log_frequency: 10
inference:
trust_remote_code: false
temperature: 1.0
top_p: 0.95
top_k: 64

View file

@ -2,6 +2,7 @@
# Also applies to: google/gemma-4-26B-A4B
training:
trust_remote_code: false
max_seq_length: 2048
num_epochs: 0
learning_rate: 2e-4
@ -26,7 +27,6 @@ lora:
- "all-linear"
use_rslora: false
use_loftq: false
use_dora: false
finetune_vision_layers: true
finetune_language_layers: true
finetune_attention_modules: true
@ -40,6 +40,7 @@ logging:
log_frequency: 10
inference:
trust_remote_code: false
temperature: 1.0
top_p: 0.95
top_k: 64

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