040b80a60e* studio/ci: harden HF_HOME/GGUF cache against actions/cache@v5 silent restore failures actions/cache@v5 has a recurring flake where it logs "Cache hit for: <key>" and then exits non-zero in well under a second without actually extracting the archive (see actions/cache#1621 and github community discussion #163260). When that happens to the JSON, images job the cache step is marked failure, all downstream steps are skipped (only the if: always() ones run), and the job never even tries to install Studio. Example: run 25713577488 / job 75498714730 took 23 s total and bailed at the cache step despite the cache having been written successfully ~30 min earlier. Replace the single-step actions/cache usage in all three jobs with the documented restore + save split: - actions/cache/restore with continue-on-error: true on the way in - Prime/Download step gated on cache-hit != 'true' OR outcome != 'success' so the silent-failure path re-downloads from HF instead of skipping - actions/cache/save on the way out, gated on the Prime step's outcome so we only write a fresh entry when we actually rebuilt the directory Same SHA-pinned action (v5.0.5), same cache keys, same paths -- so existing cache entries keep matching. Only behavior change is that a transient restore-side failure now falls through to a re-download instead of failing the job. * studio/ci: add continue-on-error to the new actions/cache/save steps Per review of PR 5396: a save-side flake (upload timeout, 5xx from the cache backend, future-fatal ReserveCacheError) is strictly recoverable because next run just re-downloads, so it should never fail the job. Today actions/cache/save@v5.0.5 already swallows ReserveCacheError as a non-fatal warning, so this is defense in depth. Aligns the save steps with their matching restore steps which already mask transient failures via continue-on-error. * studio/ci: drop continue-on-error from cache/save steps Reverting the save-side continue-on-error addition from the previous commit. cache/save@v5.0.5 already swallows ReserveCacheError (the most common save flake) as a non-fatal core.info, so the mask was rarely doing anything in practice. A real save-side failure (cache backend outage, blob server 5xx storm) is signal we want to keep -- without it we would see slow CI for days without knowing the cache layer is broken. If save flakes start showing up in practice we add this back with concrete evidence. The restore-side continue-on-error stays -- that is the actual fix for the actions/cache#1621 silent-restore-failure mode. Also strip the now-stale "continue-on-error" comments above the three save blocks. * studio/ci: clarify cache split header comment Per re-review: the prior wording "the Save step re-uploads on the way out" implied actions/cache/save would replace a broken existing cache entry, which is wrong -- cache keys are immutable, so save logs a warning when the key already exists and the corrupted entry stays until the -v1 suffix is bumped. Rewrite to spell out the actual behavior and the escape hatch (bump the suffix).
1159 lines
51 KiB
YAML
1159 lines
51 KiB
YAML
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved.
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# Three end-to-end smoke jobs that boot a freshly-installed Studio and
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# exercise the surfaces real users hit through the OpenAI / Anthropic
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# SDKs and curl, on the FREE windows-latest runner. Each job picks the
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# smallest model that exercises the behaviour under test, primes
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# HF_HOME via actions/cache, and shares the install.ps1 --local
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# --no-torch bootstrap.
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#
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# 1. OpenAI, Anthropic API tests
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# gemma-3-270m-it UD-Q4_K_XL (~254 MiB).
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# 2. Tool calling Tests
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# Qwen3.5-2B UD-Q4_K_XL (~890 MiB).
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# 3. JSON, images
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# gemma-4-E2B-it UD-Q4_K_XL + mmproj-F16 (~3.4 GiB total).
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# Within the 14 GB windows-latest SSD budget.
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name: Windows Studio GGUF CI
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on:
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pull_request:
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paths:
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- 'studio/**'
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- 'unsloth/**'
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- 'unsloth_cli/**'
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- 'install.ps1'
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- 'pyproject.toml'
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- '.github/workflows/studio-windows-inference-smoke.yml'
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push:
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branches: [main, pip]
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workflow_dispatch:
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concurrency:
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group: ${{ github.workflow }}-${{ github.ref }}
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cancel-in-progress: true
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permissions:
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contents: read
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jobs:
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# ─────────────────────────────────────────────────────────────────────
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# Job 1: OpenAI, Anthropic API tests
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# ─────────────────────────────────────────────────────────────────────
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openai-anthropic:
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name: OpenAI, Anthropic API tests
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runs-on: windows-latest
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timeout-minutes: 30
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defaults:
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run:
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shell: bash
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env:
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GGUF_REPO: unsloth/gemma-3-270m-it-GGUF
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GGUF_VARIANT: UD-Q4_K_XL
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GGUF_FILE: gemma-3-270m-it-UD-Q4_K_XL.gguf
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STUDIO_PORT: '18888'
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HF_HOME: ${{ github.workspace }}/hf-cache
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# Force UTF-8 for stdio (Windows defaults to cp1252; hf
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# download / Studio CLI print "✓" checkmarks and crash
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# otherwise).
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PYTHONIOENCODING: utf-8
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PYTHONUTF8: '1'
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steps:
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- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
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- uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
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with:
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node-version: '22'
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cache: 'npm'
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cache-dependency-path: studio/frontend/package-lock.json
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- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
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with:
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python-version: '3.12'
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# Split restore + save (rather than the one-step actions/cache) so a
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# transient restore-side failure does not kill the whole job. v5 has a
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# known flake where it logs "Cache hit for: <key>" and then exits
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# non-zero without actually extracting the archive (see
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# actions/cache#1621 and github community discussion #163260).
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# continue-on-error on restore masks that failure so the Prime step
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# below can re-download from HF and the job keeps running. Save then
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# populates the cache key on a real miss only; cache keys are
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# immutable, so a corrupted cached entry persists until the -v1
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# suffix below is bumped.
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- name: Restore HF_HOME cache for ${{ env.GGUF_REPO }}
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id: cache-hf
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uses: actions/cache/restore@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
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continue-on-error: true
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with:
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path: hf-cache
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key: ${{ runner.os }}-hf-${{ env.GGUF_REPO }}-${{ env.GGUF_VARIANT }}-v1
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- name: Prime HF_HOME with the GGUF
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id: prime-hf
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# Run on a real cache miss AND on the silent-restore-failure mode
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# described above (outcome != success).
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if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
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env:
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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run: |
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python -m pip install --upgrade huggingface_hub hf_transfer
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mkdir -p hf-cache
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HF_HUB_ENABLE_HF_TRANSFER=1 \
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hf download "$GGUF_REPO" "$GGUF_FILE"
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- name: Save HF_HOME cache for ${{ env.GGUF_REPO }}
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# Only write a fresh cache entry when we actually rebuilt the
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# directory (Prime ran and succeeded). Skipping when Prime is
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# skipped avoids "already exists" save warnings on the happy path.
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if: always() && steps.prime-hf.outcome == 'success'
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uses: actions/cache/save@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
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with:
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path: hf-cache
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key: ${{ runner.os }}-hf-${{ env.GGUF_REPO }}-${{ env.GGUF_VARIANT }}-v1
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- name: Pre-install Windows tweaks (npm 11 + Defender exclusions)
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shell: pwsh
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# See studio-windows-update-smoke.yml for the full rationale.
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# tl;dr: setup.ps1 needs npm >=11 to skip a 35 s winget Node
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# reinstall, and Defender's real-time scan dominates the
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# frontend / uv-pip-extract steps.
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run: |
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$ProgressPreference = 'SilentlyContinue'
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Write-Host "npm version before upgrade: $(npm -v)"
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npm install -g 'npm@^11' 2>&1 | Out-Host
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Write-Host "npm version after upgrade: $(npm -v)"
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# NOTE: do NOT pre-create these directories. See
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# studio-windows-update-smoke.yml for the full rationale --
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# creating an empty studio/frontend/dist trips setup.ps1's
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# mtime-based staleness check into "frontend up to date, skip
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# rebuild" and Studio boots with an empty dist directory.
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# Add-MpPreference accepts paths that do not yet exist.
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foreach ($p in @(
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"$env:USERPROFILE\.unsloth",
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"$env:USERPROFILE\AppData\Local\uv",
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"$env:GITHUB_WORKSPACE\studio\frontend\node_modules",
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"$env:GITHUB_WORKSPACE\studio\frontend\dist"
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)) {
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try {
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Add-MpPreference -ExclusionPath $p -ErrorAction Stop
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Write-Host "Defender exclusion added: $p"
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} catch {
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Write-Host "Defender exclusion skipped ($($_.Exception.Message)): $p"
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}
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}
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- name: Install Studio (--local, --no-torch)
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shell: pwsh
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env:
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GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
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run: |
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New-Item -ItemType Directory -Force -Path logs | Out-Null
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# *>&1 captures Write-Host (Information stream) output;
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# plain 2>&1 does not. setup.ps1 emits "prebuilt installed
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# and validated" via Write-Host, and we grep for that.
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$ProgressPreference = 'SilentlyContinue'
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& ./install.ps1 --local --no-torch *>&1 | Tee-Object -FilePath logs/install.log
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- name: Assert install.ps1 used the Windows llama.cpp prebuilt
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run: |
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# Filesystem check; setup.ps1's stream output isn't captured.
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LLAMA_DIR=~/.unsloth/llama.cpp
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INFO="$LLAMA_DIR/UNSLOTH_PREBUILT_INFO.json"
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BIN="$LLAMA_DIR/build/bin/Release/llama-server.exe"
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if grep -q "falling back to source build" logs/install.log; then
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echo "::error::install.ps1 fell back to source-build llama.cpp on Windows."
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grep -E "llama-prebuilt|llama.cpp" logs/install.log | tail -60
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exit 1
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fi
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if [ ! -f "$INFO" ]; then
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echo "::error::no UNSLOTH_PREBUILT_INFO.json at $INFO."
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ls -la "$LLAMA_DIR" || true
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exit 1
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fi
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if [ ! -f "$BIN" ]; then
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echo "::error::no llama-server.exe at $BIN."
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ls -la "$LLAMA_DIR/build/bin" || true
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exit 1
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fi
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echo "install.ps1 installed the Windows prebuilt llama.cpp:"
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cat "$INFO"
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- name: Add Studio shim to GITHUB_PATH
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run: |
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SHIM_DIR=~/.unsloth/studio/bin
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if [ ! -f "$SHIM_DIR/unsloth.exe" ]; then
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echo "::error::unsloth.exe shim not found at $SHIM_DIR"
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ls -la ~/.unsloth/studio/ || true
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exit 1
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fi
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cygpath -w "$SHIM_DIR" >> "$GITHUB_PATH"
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- name: Patch Studio venv with full typer / pydantic dep trees
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# Belt-and-suspenders: install.ps1's --no-deps install of
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# no-torch-runtime.txt drops typer's and pydantic's runtime
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# deps unless explicitly pinned. Re-install the ones whose
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# deps don't pull torch.
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run: |
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STUDIO_PY=~/.unsloth/studio/unsloth_studio/Scripts/python.exe
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if [ ! -f "$STUDIO_PY" ]; then
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echo "::error::Studio venv python not at $STUDIO_PY"
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ls -la ~/.unsloth/studio/ || true
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exit 1
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fi
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"$STUDIO_PY" -m pip install --upgrade typer pydantic huggingface_hub
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- name: Install OpenAI + Anthropic Python SDKs
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run: python -m pip install 'openai>=1.50' 'anthropic>=0.40'
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- name: Reset auth + boot Studio (API-only)
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run: |
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unsloth studio reset-password
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mkdir -p logs
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UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
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> logs/studio.log 2>&1 &
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echo "STUDIO_PID=$!" >> "$GITHUB_ENV"
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- name: Wait for /api/health
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run: |
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for i in $(seq 1 180); do
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if curl -fs "http://127.0.0.1:${STUDIO_PORT}/api/health" > /tmp/health.json; then
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jq -e '.status == "healthy"' /tmp/health.json
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exit 0
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fi
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sleep 1
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done
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echo "Studio did not become healthy in 180s"
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tail -200 logs/studio.log
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exit 1
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- name: Password rotation (old must fail, new must work)
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run: |
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OLD=$(cat ~/.unsloth/studio/auth/.bootstrap_password)
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NEW="CIRotated-$(python -c 'import secrets; print(secrets.token_urlsafe(12))')"
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echo "::add-mask::$OLD"
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echo "::add-mask::$NEW"
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OLD_TOKEN=$(curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/auth/login" \
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-H 'content-type: application/json' \
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-d "{\"username\":\"unsloth\",\"password\":\"$OLD\"}" | jq -r .access_token)
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[ -n "$OLD_TOKEN" ] && [ "$OLD_TOKEN" != "null" ] || { echo "bootstrap login failed"; exit 1; }
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curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/auth/change-password" \
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-H "Authorization: Bearer $OLD_TOKEN" -H 'content-type: application/json' \
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-d "{\"current_password\":\"$OLD\",\"new_password\":\"$NEW\"}" > /dev/null
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OLD_STATUS=$(curl -s -o /dev/null -w '%{http_code}' \
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-X POST "http://127.0.0.1:${STUDIO_PORT}/api/auth/login" \
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-H 'content-type: application/json' \
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-d "{\"username\":\"unsloth\",\"password\":\"$OLD\"}")
|
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if [ "$OLD_STATUS" != "401" ]; then
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echo "::error::Login with old password returned $OLD_STATUS, expected 401"
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exit 1
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fi
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NEW_TOKEN=$(curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/auth/login" \
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-H 'content-type: application/json' \
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-d "{\"username\":\"unsloth\",\"password\":\"$NEW\"}" | jq -r .access_token)
|
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[ -n "$NEW_TOKEN" ] && [ "$NEW_TOKEN" != "null" ] || { echo "new login failed"; exit 1; }
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echo "TOKEN=$NEW_TOKEN" >> "$GITHUB_ENV"
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echo "password rotation OK (old=401, new=200)"
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|
|
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- name: Load the GGUF (HF repo + variant, served from HF_HOME cache)
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run: |
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curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/inference/load" \
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-H "Authorization: Bearer $TOKEN" -H 'content-type: application/json' \
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--max-time 600 \
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-d "{\"model_path\":\"$GGUF_REPO\",\"gguf_variant\":\"$GGUF_VARIANT\",\"is_lora\":false,\"max_seq_length\":2048}" \
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| jq '{status, display_name, is_gguf, context_length}'
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- name: Multi-turn determinism via OpenAI + Anthropic SDKs
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env:
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BASE_URL: http://127.0.0.1:18888
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run: |
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python - <<'PY'
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import json
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import os
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from openai import OpenAI
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from anthropic import Anthropic
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BASE = os.environ["BASE_URL"]
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KEY = os.environ["TOKEN"]
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SEED = 3407
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PROMPTS = [
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"What is 1+1?",
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"What did I ask before?",
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"What is the capital of France?",
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"Repeat the city name",
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]
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def run_openai():
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client = OpenAI(base_url = f"{BASE}/v1", api_key = KEY)
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history, replies = [], []
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for prompt in PROMPTS:
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history.append({"role": "user", "content": prompt})
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resp = client.chat.completions.create(
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model = "default",
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messages = history,
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temperature = 0.0,
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max_tokens = 80,
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seed = SEED,
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extra_body = {"enable_thinking": False},
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)
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text = resp.choices[0].message.content or ""
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replies.append(text)
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history.append({"role": "assistant", "content": text})
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return replies
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|
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def run_anthropic():
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client = Anthropic(
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base_url = BASE,
|
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api_key = "unused",
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default_headers = {"Authorization": f"Bearer {KEY}"},
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)
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history, replies = [], []
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for prompt in PROMPTS:
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history.append({"role": "user", "content": prompt})
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msg = client.messages.create(
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model = "default",
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max_tokens = 80,
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messages = history,
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temperature = 0.0,
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extra_body = {"seed": SEED, "enable_thinking": False},
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)
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text = "".join(b.text for b in msg.content if getattr(b, "type", None) == "text")
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replies.append(text)
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history.append({"role": "assistant", "content": text})
|
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return replies
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|
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for label, runner in (("openai", run_openai), ("anthropic", run_anthropic)):
|
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first = runner()
|
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second = runner()
|
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for i, (a, b) in enumerate(zip(first, second), start = 1):
|
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print(f"[{label} turn {i}] {a!r}")
|
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assert a, f"{label}: empty turn {i} response"
|
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assert a == b, (
|
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f"{label} non-deterministic at turn {i} with temperature=0.0:\n"
|
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f" run1: {a!r}\n run2: {b!r}"
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)
|
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joined = " ".join(first).lower()
|
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assert "1" in first[0], f"{label}: turn-1 answer should contain '1', got {first[0]!r}"
|
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assert "paris" in joined, f"{label}: expected 'paris' somewhere in the four-turn transcript: {first}"
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print(f"[{label}] OK -- 4 turns, run1 == run2, history grounded")
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PY
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|
- name: Stop Studio
|
|
if: always()
|
|
run: |
|
|
kill "${STUDIO_PID}" 2>/dev/null || true
|
|
sleep 2
|
|
|
|
- name: Upload logs
|
|
if: always()
|
|
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
|
|
with:
|
|
name: windows-openai-anthropic-log
|
|
path: |
|
|
logs/studio.log
|
|
logs/install.log
|
|
retention-days: 7
|
|
|
|
# ─────────────────────────────────────────────────────────────────────
|
|
# Job 2: Tool calling Tests
|
|
# ─────────────────────────────────────────────────────────────────────
|
|
tool-calling:
|
|
name: Tool calling Tests
|
|
runs-on: windows-latest
|
|
timeout-minutes: 30
|
|
defaults:
|
|
run:
|
|
shell: bash
|
|
env:
|
|
# Tool calling is the highest-volume GGUF in this workflow
|
|
# (Qwen3.5-2B at Q4_K_XL = ~1.28 GiB). The previous HF_HOME
|
|
# cache stored xet chunks + blobs + snapshots = ~4.7 GiB --
|
|
# 3.7x file-size inflation, dominating the post-step upload
|
|
# (211 s on first run; subsequent runs hit the cache, but the
|
|
# one-time cost recurs every time the cache key bumps). Use
|
|
# main's `--local-dir gguf-cache` pattern: cache the flat .gguf
|
|
# only, pass an absolute path to Studio's /api/inference/load.
|
|
# The OpenAI/Anth and JSON+images jobs still cover the
|
|
# gguf_variant resolution path.
|
|
GGUF_REPO: unsloth/Qwen3.5-2B-GGUF
|
|
GGUF_FILE: Qwen3.5-2B-UD-Q4_K_XL.gguf
|
|
STUDIO_PORT: '18898'
|
|
# Force UTF-8 for stdio (Windows defaults to cp1252; hf
|
|
# download / Studio CLI print "✓" checkmarks and crash
|
|
# otherwise).
|
|
PYTHONIOENCODING: utf-8
|
|
PYTHONUTF8: '1'
|
|
steps:
|
|
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
|
|
|
|
- uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
|
|
with:
|
|
node-version: '22'
|
|
cache: 'npm'
|
|
cache-dependency-path: studio/frontend/package-lock.json
|
|
|
|
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
|
|
with:
|
|
python-version: '3.12'
|
|
|
|
# Split restore + save so a transient restore-side failure does not
|
|
# kill the whole job. See the matching block in the tool-calling job
|
|
# above for the full rationale (actions/cache#1621).
|
|
- name: Restore GGUF model cache
|
|
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: ${{ secrets.HF_TOKEN }}
|
|
run: |
|
|
python -m pip install --upgrade huggingface_hub hf_transfer
|
|
mkdir -p gguf-cache
|
|
HF_HUB_ENABLE_HF_TRANSFER=1 \
|
|
hf download "$GGUF_REPO" "$GGUF_FILE" --local-dir gguf-cache
|
|
|
|
- name: Save GGUF model cache
|
|
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: Pre-install Windows tweaks (npm 11 + Defender exclusions)
|
|
shell: pwsh
|
|
# See studio-windows-update-smoke.yml for the full rationale.
|
|
# tl;dr: setup.ps1 needs npm >=11 to skip a 35 s winget Node
|
|
# reinstall, and Defender's real-time scan dominates the
|
|
# frontend / uv-pip-extract steps.
|
|
run: |
|
|
$ProgressPreference = 'SilentlyContinue'
|
|
Write-Host "npm version before upgrade: $(npm -v)"
|
|
npm install -g 'npm@^11' 2>&1 | Out-Host
|
|
Write-Host "npm version after upgrade: $(npm -v)"
|
|
# NOTE: do NOT pre-create these directories. See
|
|
# studio-windows-update-smoke.yml for the full rationale --
|
|
# creating an empty studio/frontend/dist trips setup.ps1's
|
|
# mtime-based staleness check into "frontend up to date, skip
|
|
# rebuild" and Studio boots with an empty dist directory.
|
|
# Add-MpPreference accepts paths that do not yet exist.
|
|
foreach ($p in @(
|
|
"$env:USERPROFILE\.unsloth",
|
|
"$env:USERPROFILE\AppData\Local\uv",
|
|
"$env:GITHUB_WORKSPACE\studio\frontend\node_modules",
|
|
"$env:GITHUB_WORKSPACE\studio\frontend\dist"
|
|
)) {
|
|
try {
|
|
Add-MpPreference -ExclusionPath $p -ErrorAction Stop
|
|
Write-Host "Defender exclusion added: $p"
|
|
} catch {
|
|
Write-Host "Defender exclusion skipped ($($_.Exception.Message)): $p"
|
|
}
|
|
}
|
|
|
|
- name: Install Studio (--local, --no-torch)
|
|
shell: pwsh
|
|
env:
|
|
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
|
run: |
|
|
New-Item -ItemType Directory -Force -Path logs | Out-Null
|
|
# *>&1 captures Write-Host (Information stream) output;
|
|
# plain 2>&1 does not. setup.ps1 emits "prebuilt installed
|
|
# and validated" via Write-Host, and we grep for that.
|
|
$ProgressPreference = 'SilentlyContinue'
|
|
& ./install.ps1 --local --no-torch *>&1 | Tee-Object -FilePath logs/install.log
|
|
|
|
- name: Assert install.ps1 used the Windows llama.cpp prebuilt
|
|
run: |
|
|
# Filesystem check; setup.ps1's stream output isn't captured.
|
|
LLAMA_DIR=~/.unsloth/llama.cpp
|
|
INFO="$LLAMA_DIR/UNSLOTH_PREBUILT_INFO.json"
|
|
BIN="$LLAMA_DIR/build/bin/Release/llama-server.exe"
|
|
if grep -q "falling back to source build" logs/install.log; then
|
|
echo "::error::install.ps1 fell back to source-build llama.cpp on Windows."
|
|
grep -E "llama-prebuilt|llama.cpp" logs/install.log | tail -60
|
|
exit 1
|
|
fi
|
|
if [ ! -f "$INFO" ]; then
|
|
echo "::error::no UNSLOTH_PREBUILT_INFO.json at $INFO."
|
|
ls -la "$LLAMA_DIR" || true
|
|
exit 1
|
|
fi
|
|
if [ ! -f "$BIN" ]; then
|
|
echo "::error::no llama-server.exe at $BIN."
|
|
ls -la "$LLAMA_DIR/build/bin" || true
|
|
exit 1
|
|
fi
|
|
echo "install.ps1 installed the Windows prebuilt llama.cpp:"
|
|
cat "$INFO"
|
|
|
|
- name: Add Studio shim to GITHUB_PATH
|
|
run: |
|
|
SHIM_DIR=~/.unsloth/studio/bin
|
|
if [ ! -f "$SHIM_DIR/unsloth.exe" ]; then
|
|
echo "::error::unsloth.exe shim not found at $SHIM_DIR"
|
|
ls -la ~/.unsloth/studio/ || true
|
|
exit 1
|
|
fi
|
|
cygpath -w "$SHIM_DIR" >> "$GITHUB_PATH"
|
|
|
|
- name: Patch Studio venv with full typer / pydantic dep trees
|
|
# Belt-and-suspenders: install.ps1's --no-deps install of
|
|
# no-torch-runtime.txt drops typer's and pydantic's runtime
|
|
# deps unless explicitly pinned. Re-install the ones whose
|
|
# deps don't pull torch.
|
|
run: |
|
|
STUDIO_PY=~/.unsloth/studio/unsloth_studio/Scripts/python.exe
|
|
if [ ! -f "$STUDIO_PY" ]; then
|
|
echo "::error::Studio venv python not at $STUDIO_PY"
|
|
ls -la ~/.unsloth/studio/ || true
|
|
exit 1
|
|
fi
|
|
"$STUDIO_PY" -m pip install --upgrade typer pydantic huggingface_hub
|
|
|
|
- name: Reset auth + boot Studio (API-only, default tool policy)
|
|
run: |
|
|
unsloth studio reset-password
|
|
mkdir -p logs
|
|
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
|
|
> logs/studio.log 2>&1 &
|
|
echo "STUDIO_PID=$!" >> "$GITHUB_ENV"
|
|
|
|
- name: Wait for /api/health, log in, change password, load model
|
|
run: |
|
|
for i in $(seq 1 180); do
|
|
if curl -fs "http://127.0.0.1:${STUDIO_PORT}/api/health" > /tmp/health.json; then
|
|
jq -e '.status == "healthy"' /tmp/health.json && break
|
|
fi
|
|
sleep 1
|
|
done
|
|
jq -e '.status == "healthy"' /tmp/health.json
|
|
OLD=$(cat ~/.unsloth/studio/auth/.bootstrap_password)
|
|
NEW="CITool-$(python -c 'import secrets; print(secrets.token_urlsafe(12))')"
|
|
echo "::add-mask::$OLD"
|
|
echo "::add-mask::$NEW"
|
|
OLD_TOKEN=$(curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/auth/login" \
|
|
-H 'content-type: application/json' \
|
|
-d "{\"username\":\"unsloth\",\"password\":\"$OLD\"}" | jq -r .access_token)
|
|
curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/auth/change-password" \
|
|
-H "Authorization: Bearer $OLD_TOKEN" -H 'content-type: application/json' \
|
|
-d "{\"current_password\":\"$OLD\",\"new_password\":\"$NEW\"}" > /dev/null
|
|
TOKEN=$(curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/auth/login" \
|
|
-H 'content-type: application/json' \
|
|
-d "{\"username\":\"unsloth\",\"password\":\"$NEW\"}" | jq -r .access_token)
|
|
echo "API_KEY=$TOKEN" >> "$GITHUB_ENV"
|
|
# GITHUB_WORKSPACE on windows-latest is a Windows path with
|
|
# backslashes ("D:\a\unsloth\unsloth"). Bash handles it as a
|
|
# raw string, but we cannot embed `\a` etc. in JSON without
|
|
# JSON-string-escaping every backslash. Replace `\` with `/`
|
|
# via bash parameter expansion -- pathlib.Path on Windows
|
|
# accepts forward slashes natively, so Studio's loader sees
|
|
# a normal path.
|
|
GGUF_PATH="${GITHUB_WORKSPACE//\\//}/gguf-cache/${GGUF_FILE}"
|
|
ls -lh "$GGUF_PATH"
|
|
curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/inference/load" \
|
|
-H "Authorization: Bearer $TOKEN" -H 'content-type: application/json' \
|
|
--max-time 600 \
|
|
-d "{\"model_path\":\"$GGUF_PATH\",\"is_lora\":false,\"max_seq_length\":2048}" \
|
|
| jq '{status, display_name}'
|
|
|
|
- name: Tool calling, server-side tools, thinking on/off
|
|
env:
|
|
BASE_URL: http://127.0.0.1:18898
|
|
run: |
|
|
python - <<'PY'
|
|
import json
|
|
import os
|
|
import urllib.request
|
|
|
|
BASE = os.environ["BASE_URL"]
|
|
KEY = os.environ["API_KEY"]
|
|
SEED = 3407
|
|
# Same temperature shim as the Mac job. Small Qwen3.5-2B
|
|
# quants can degenerate at temperature=0; a small non-zero
|
|
# temperature with a fixed seed keeps the test deterministic
|
|
# while escaping the trap.
|
|
TEMP = 0.2
|
|
|
|
def post(path, body, *, timeout = 240):
|
|
data = json.dumps(body).encode()
|
|
req = urllib.request.Request(
|
|
f"{BASE}{path}",
|
|
data = data,
|
|
method = "POST",
|
|
headers = {
|
|
"Authorization": f"Bearer {KEY}",
|
|
"Content-Type": "application/json",
|
|
},
|
|
)
|
|
with urllib.request.urlopen(req, timeout = timeout) as resp:
|
|
return resp.status, json.loads(resp.read().decode())
|
|
|
|
def post_sse(path, body, *, timeout = 600):
|
|
body = {**body, "stream": True}
|
|
data = json.dumps(body).encode()
|
|
req = urllib.request.Request(
|
|
f"{BASE}{path}",
|
|
data = data,
|
|
method = "POST",
|
|
headers = {
|
|
"Authorization": f"Bearer {KEY}",
|
|
"Content-Type": "application/json",
|
|
},
|
|
)
|
|
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 = {
|
|
"type": "function",
|
|
"function": {
|
|
"name": "get_weather",
|
|
"description": "Get current weather for a city.",
|
|
"parameters": {
|
|
"type": "object",
|
|
"properties": {"city": {"type": "string"}},
|
|
"required": ["city"],
|
|
},
|
|
},
|
|
}
|
|
|
|
status, data = post("/v1/chat/completions", {
|
|
"messages": [{"role": "user", "content": "What is the weather in Paris?"}],
|
|
"tools": [weather_tool],
|
|
"tool_choice": "required",
|
|
"stream": False,
|
|
"temperature": TEMP,
|
|
"seed": SEED,
|
|
"max_tokens": 600,
|
|
})
|
|
assert status == 200, f"tool call status {status}: {data}"
|
|
choice = data["choices"][0]
|
|
tool_calls = (choice.get("message") or {}).get("tool_calls") or []
|
|
if tool_calls:
|
|
tc = tool_calls[0]
|
|
assert tc["function"]["name"] == "get_weather", (
|
|
f"unexpected tool name: {tc['function']['name']!r}"
|
|
)
|
|
args = json.loads(tc["function"]["arguments"])
|
|
assert args.get("city"), f"missing city arg: {args}"
|
|
print(f"[tools] PASS function calling -> {tc['function']['name']}({args}) finish={choice.get('finish_reason')!r}")
|
|
else:
|
|
print(
|
|
f"[tools] WARN function calling: no tool_calls (finish_reason="
|
|
f"{choice.get('finish_reason')!r}); HTTP path OK, model output drift."
|
|
)
|
|
|
|
# ── 2. Server-side python tool ───────────────────────────────
|
|
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,
|
|
"enabled_tools": ["python"],
|
|
"session_id": "ci-tool-calling-py",
|
|
"temperature": TEMP,
|
|
"seed": SEED,
|
|
"max_tokens": 600,
|
|
})
|
|
if "56088" in content or "56,088" in content:
|
|
print(f"[tools] PASS python tool ({len(content)} chars, found 56088)")
|
|
else:
|
|
assert content, "python tool: SSE stream empty"
|
|
print(
|
|
f"[tools] WARN python tool: SSE OK ({len(content)} chars) but "
|
|
f"model didn't return 56088 -- model output drift"
|
|
)
|
|
|
|
# ── 3. Server-side bash (terminal) tool ──────────────────────
|
|
# On Windows the terminal tool resolves to the system shell
|
|
# (cmd.exe wrapper) and `echo hello-bash-tool` works the same
|
|
# way it does on POSIX. The model still has to choose to
|
|
# invoke the tool; assert non-empty SSE if it doesn't.
|
|
content = post_sse("/v1/chat/completions", {
|
|
"messages": [{"role": "user", "content": "Use the terminal tool to run `echo hello-bash-tool` and tell me the exact output."}],
|
|
"enable_tools": True,
|
|
"enabled_tools": ["terminal"],
|
|
"session_id": "ci-tool-calling-bash",
|
|
"temperature": TEMP,
|
|
"seed": SEED,
|
|
"max_tokens": 600,
|
|
})
|
|
if "hello-bash-tool" in content:
|
|
print(f"[tools] PASS terminal tool ({len(content)} chars)")
|
|
else:
|
|
assert content, "terminal tool: SSE stream empty"
|
|
print(
|
|
f"[tools] WARN terminal tool: SSE OK ({len(content)} chars) but "
|
|
f"model didn't echo 'hello-bash-tool' -- model output drift"
|
|
)
|
|
|
|
# ── 4. Server-side web_search tool ───────────────────────────
|
|
# DuckDuckGo can be flaky from CI runners; only assert that
|
|
# the SSE stream opens and yields any data.
|
|
try:
|
|
content = post_sse("/v1/chat/completions", {
|
|
"messages": [{"role": "user", "content": "Search the web for 'unsloth ai github' and summarise."}],
|
|
"enable_tools": True,
|
|
"enabled_tools": ["web_search"],
|
|
"session_id": "ci-tool-calling-web",
|
|
"temperature": TEMP,
|
|
"seed": SEED,
|
|
"max_tokens": 400,
|
|
})
|
|
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}")
|
|
|
|
# ── 5. Thinking on / off ─────────────────────────────────────
|
|
def thinking_call(enable):
|
|
status, data = post("/v1/chat/completions", {
|
|
"messages": [{"role": "user", "content": "Briefly: is 17 prime?"}],
|
|
"stream": False,
|
|
"enable_thinking": enable,
|
|
"temperature": TEMP,
|
|
"seed": SEED,
|
|
"max_tokens": 300,
|
|
})
|
|
assert status == 200
|
|
msg = data["choices"][0]["message"]
|
|
raw = (msg.get("content") or "") + (msg.get("reasoning_content") or "")
|
|
return raw
|
|
|
|
on_text = thinking_call(True)
|
|
off_text = thinking_call(False)
|
|
had_think_on = ("<think>" in on_text) or len(on_text) > 80
|
|
if not had_think_on:
|
|
print(
|
|
f"[tools] WARN enable_thinking=True produced no thinking signal: "
|
|
f"{on_text[:200]!r}"
|
|
)
|
|
assert "<think>" not in off_text, (
|
|
f"enable_thinking=False but <think> still present: {off_text!r}"
|
|
)
|
|
print(f"[tools] PASS thinking on/off (on={len(on_text)} chars, off={len(off_text)} chars)")
|
|
PY
|
|
|
|
- name: Stop Studio
|
|
if: always()
|
|
run: |
|
|
kill "${STUDIO_PID}" 2>/dev/null || true
|
|
sleep 2
|
|
|
|
- name: Upload logs
|
|
if: always()
|
|
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
|
|
with:
|
|
name: windows-tool-calling-log
|
|
path: |
|
|
logs/studio.log
|
|
logs/install.log
|
|
retention-days: 7
|
|
|
|
# ─────────────────────────────────────────────────────────────────────
|
|
# Job 3: JSON, images
|
|
# ─────────────────────────────────────────────────────────────────────
|
|
json-images:
|
|
name: JSON, images
|
|
runs-on: windows-latest
|
|
timeout-minutes: 35
|
|
defaults:
|
|
run:
|
|
shell: bash
|
|
env:
|
|
GGUF_REPO: unsloth/gemma-4-E2B-it-GGUF
|
|
GGUF_VARIANT: UD-Q4_K_XL
|
|
GGUF_FILE: gemma-4-E2B-it-UD-Q4_K_XL.gguf
|
|
MMPROJ_FILE: mmproj-F16.gguf
|
|
STUDIO_PORT: '18899'
|
|
HF_HOME: ${{ github.workspace }}/hf-cache
|
|
# Force UTF-8 for stdio (Windows defaults to cp1252; hf
|
|
# download / Studio CLI print "✓" checkmarks and crash
|
|
# otherwise).
|
|
PYTHONIOENCODING: utf-8
|
|
PYTHONUTF8: '1'
|
|
steps:
|
|
- uses: actions/checkout@de0fac2e4500dabe0009e67214ff5f5447ce83dd # v6.0.2
|
|
|
|
- uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
|
|
with:
|
|
node-version: '22'
|
|
cache: 'npm'
|
|
cache-dependency-path: studio/frontend/package-lock.json
|
|
|
|
- uses: actions/setup-python@a309ff8b426b58ec0e2a45f0f869d46889d02405 # v6.2.0
|
|
with:
|
|
python-version: '3.12'
|
|
|
|
# Split restore + save so a transient restore-side failure does not
|
|
# kill the whole job. See the matching block in the tool-calling job
|
|
# for the full rationale (actions/cache#1621). This is the block that
|
|
# actually broke in run 25713577488: "Cache hit for: <key>" was
|
|
# logged, the step exited non-zero in ~0.3 s without extracting the
|
|
# 3.4 GiB archive, and steps 6-15 were skipped.
|
|
- name: Restore HF_HOME cache for ${{ env.GGUF_REPO }} (model + mmproj)
|
|
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 }}-${{ env.GGUF_VARIANT }}-${{ env.MMPROJ_FILE }}-v1
|
|
|
|
- name: Prime HF_HOME with the GGUF + mmproj
|
|
id: prime-hf
|
|
if: steps.cache-hf.outputs.cache-hit != 'true' || steps.cache-hf.outcome != 'success'
|
|
env:
|
|
HF_TOKEN: ${{ secrets.HF_TOKEN }}
|
|
run: |
|
|
python -m pip install --upgrade huggingface_hub hf_transfer
|
|
mkdir -p hf-cache
|
|
HF_HUB_ENABLE_HF_TRANSFER=1 \
|
|
hf download "$GGUF_REPO" "$GGUF_FILE"
|
|
HF_HUB_ENABLE_HF_TRANSFER=1 \
|
|
hf download "$GGUF_REPO" "$MMPROJ_FILE"
|
|
|
|
- name: Save HF_HOME cache for ${{ env.GGUF_REPO }} (model + mmproj)
|
|
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 }}-${{ env.GGUF_VARIANT }}-${{ env.MMPROJ_FILE }}-v1
|
|
|
|
- name: Pre-install Windows tweaks (npm 11 + Defender exclusions)
|
|
shell: pwsh
|
|
# See studio-windows-update-smoke.yml for the full rationale.
|
|
# tl;dr: setup.ps1 needs npm >=11 to skip a 35 s winget Node
|
|
# reinstall, and Defender's real-time scan dominates the
|
|
# frontend / uv-pip-extract steps.
|
|
run: |
|
|
$ProgressPreference = 'SilentlyContinue'
|
|
Write-Host "npm version before upgrade: $(npm -v)"
|
|
npm install -g 'npm@^11' 2>&1 | Out-Host
|
|
Write-Host "npm version after upgrade: $(npm -v)"
|
|
# NOTE: do NOT pre-create these directories. See
|
|
# studio-windows-update-smoke.yml for the full rationale --
|
|
# creating an empty studio/frontend/dist trips setup.ps1's
|
|
# mtime-based staleness check into "frontend up to date, skip
|
|
# rebuild" and Studio boots with an empty dist directory.
|
|
# Add-MpPreference accepts paths that do not yet exist.
|
|
foreach ($p in @(
|
|
"$env:USERPROFILE\.unsloth",
|
|
"$env:USERPROFILE\AppData\Local\uv",
|
|
"$env:GITHUB_WORKSPACE\studio\frontend\node_modules",
|
|
"$env:GITHUB_WORKSPACE\studio\frontend\dist"
|
|
)) {
|
|
try {
|
|
Add-MpPreference -ExclusionPath $p -ErrorAction Stop
|
|
Write-Host "Defender exclusion added: $p"
|
|
} catch {
|
|
Write-Host "Defender exclusion skipped ($($_.Exception.Message)): $p"
|
|
}
|
|
}
|
|
|
|
- name: Install Studio (--local, --no-torch)
|
|
shell: pwsh
|
|
env:
|
|
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
|
run: |
|
|
New-Item -ItemType Directory -Force -Path logs | Out-Null
|
|
# *>&1 captures Write-Host (Information stream) output;
|
|
# plain 2>&1 does not. setup.ps1 emits "prebuilt installed
|
|
# and validated" via Write-Host, and we grep for that.
|
|
$ProgressPreference = 'SilentlyContinue'
|
|
& ./install.ps1 --local --no-torch *>&1 | Tee-Object -FilePath logs/install.log
|
|
|
|
- name: Assert install.ps1 used the Windows llama.cpp prebuilt
|
|
run: |
|
|
# Filesystem check; setup.ps1's stream output isn't captured.
|
|
LLAMA_DIR=~/.unsloth/llama.cpp
|
|
INFO="$LLAMA_DIR/UNSLOTH_PREBUILT_INFO.json"
|
|
BIN="$LLAMA_DIR/build/bin/Release/llama-server.exe"
|
|
if grep -q "falling back to source build" logs/install.log; then
|
|
echo "::error::install.ps1 fell back to source-build llama.cpp on Windows."
|
|
grep -E "llama-prebuilt|llama.cpp" logs/install.log | tail -60
|
|
exit 1
|
|
fi
|
|
if [ ! -f "$INFO" ]; then
|
|
echo "::error::no UNSLOTH_PREBUILT_INFO.json at $INFO."
|
|
ls -la "$LLAMA_DIR" || true
|
|
exit 1
|
|
fi
|
|
if [ ! -f "$BIN" ]; then
|
|
echo "::error::no llama-server.exe at $BIN."
|
|
ls -la "$LLAMA_DIR/build/bin" || true
|
|
exit 1
|
|
fi
|
|
echo "install.ps1 installed the Windows prebuilt llama.cpp:"
|
|
cat "$INFO"
|
|
|
|
- name: Add Studio shim to GITHUB_PATH
|
|
run: |
|
|
SHIM_DIR=~/.unsloth/studio/bin
|
|
if [ ! -f "$SHIM_DIR/unsloth.exe" ]; then
|
|
echo "::error::unsloth.exe shim not found at $SHIM_DIR"
|
|
ls -la ~/.unsloth/studio/ || true
|
|
exit 1
|
|
fi
|
|
cygpath -w "$SHIM_DIR" >> "$GITHUB_PATH"
|
|
|
|
- name: Patch Studio venv with full typer / pydantic dep trees
|
|
# Belt-and-suspenders: install.ps1's --no-deps install of
|
|
# no-torch-runtime.txt drops typer's and pydantic's runtime
|
|
# deps unless explicitly pinned. Re-install the ones whose
|
|
# deps don't pull torch.
|
|
run: |
|
|
STUDIO_PY=~/.unsloth/studio/unsloth_studio/Scripts/python.exe
|
|
if [ ! -f "$STUDIO_PY" ]; then
|
|
echo "::error::Studio venv python not at $STUDIO_PY"
|
|
ls -la ~/.unsloth/studio/ || true
|
|
exit 1
|
|
fi
|
|
"$STUDIO_PY" -m pip install --upgrade typer pydantic huggingface_hub
|
|
|
|
- name: Install OpenAI + Anthropic Python SDKs
|
|
run: python -m pip install 'openai>=1.50' 'anthropic>=0.40'
|
|
|
|
- name: Reset auth + boot Studio (API-only)
|
|
run: |
|
|
unsloth studio reset-password
|
|
mkdir -p logs
|
|
UNSLOTH_API_ONLY=1 unsloth studio -H 127.0.0.1 -p "$STUDIO_PORT" \
|
|
> logs/studio.log 2>&1 &
|
|
echo "STUDIO_PID=$!" >> "$GITHUB_ENV"
|
|
|
|
- name: Wait for /api/health, log in, change password, load model
|
|
run: |
|
|
for i in $(seq 1 180); do
|
|
if curl -fs "http://127.0.0.1:${STUDIO_PORT}/api/health" > /tmp/health.json; then
|
|
jq -e '.status == "healthy"' /tmp/health.json && break
|
|
fi
|
|
sleep 1
|
|
done
|
|
jq -e '.status == "healthy"' /tmp/health.json
|
|
OLD=$(cat ~/.unsloth/studio/auth/.bootstrap_password)
|
|
NEW="CIJson-$(python -c 'import secrets; print(secrets.token_urlsafe(12))')"
|
|
echo "::add-mask::$OLD"
|
|
echo "::add-mask::$NEW"
|
|
OLD_TOKEN=$(curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/auth/login" \
|
|
-H 'content-type: application/json' \
|
|
-d "{\"username\":\"unsloth\",\"password\":\"$OLD\"}" | jq -r .access_token)
|
|
curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/auth/change-password" \
|
|
-H "Authorization: Bearer $OLD_TOKEN" -H 'content-type: application/json' \
|
|
-d "{\"current_password\":\"$OLD\",\"new_password\":\"$NEW\"}" > /dev/null
|
|
TOKEN=$(curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/auth/login" \
|
|
-H 'content-type: application/json' \
|
|
-d "{\"username\":\"unsloth\",\"password\":\"$NEW\"}" | jq -r .access_token)
|
|
echo "API_KEY=$TOKEN" >> "$GITHUB_ENV"
|
|
curl -fs -X POST "http://127.0.0.1:${STUDIO_PORT}/api/inference/load" \
|
|
-H "Authorization: Bearer $TOKEN" -H 'content-type: application/json' \
|
|
--max-time 900 \
|
|
-d "{\"model_path\":\"$GGUF_REPO\",\"gguf_variant\":\"$GGUF_VARIANT\",\"is_lora\":false,\"max_seq_length\":2048}" \
|
|
| jq '{status, display_name, is_vision}'
|
|
|
|
- name: JSON schema decoding + image input
|
|
env:
|
|
BASE_URL: http://127.0.0.1:18899
|
|
run: |
|
|
python - <<'PY'
|
|
import base64
|
|
import json
|
|
import os
|
|
import urllib.request
|
|
from openai import OpenAI
|
|
from anthropic import Anthropic
|
|
|
|
BASE = os.environ["BASE_URL"]
|
|
KEY = os.environ["API_KEY"]
|
|
SEED = 3407
|
|
TEMP = 0.2
|
|
|
|
def post(path, body, *, timeout = 240):
|
|
req = urllib.request.Request(
|
|
f"{BASE}{path}",
|
|
data = json.dumps(body).encode(),
|
|
method = "POST",
|
|
headers = {
|
|
"Authorization": f"Bearer {KEY}",
|
|
"Content-Type": "application/json",
|
|
},
|
|
)
|
|
with urllib.request.urlopen(req, timeout = timeout) as resp:
|
|
return resp.status, json.loads(resp.read().decode())
|
|
|
|
# ── 1. response_format = json_object (JSON mode) ─────────────
|
|
status, data = post("/v1/chat/completions", {
|
|
"model": "default",
|
|
"messages": [
|
|
{"role": "system", "content": 'Reply with a single JSON object of the form {"city": "...", "country": "..."}. Output ONLY the JSON, nothing else.'},
|
|
{"role": "user", "content": "What is the capital of France?"},
|
|
],
|
|
"temperature": TEMP,
|
|
"max_tokens": 600,
|
|
"seed": SEED,
|
|
"stream": False,
|
|
"enable_thinking": False,
|
|
"response_format": {"type": "json_object"},
|
|
}, timeout = 600)
|
|
assert status == 200, f"json status {status}: {data}"
|
|
assert (
|
|
isinstance(data.get("choices"), list)
|
|
and data["choices"]
|
|
and "message" in data["choices"][0]
|
|
), f"json response envelope malformed: {data}"
|
|
content = (data["choices"][0]["message"].get("content") or "").strip()
|
|
print(f"[json] raw json_object content: {content!r}")
|
|
if content.startswith("```"):
|
|
content = content.split("```", 2)[1]
|
|
if content.startswith("json"):
|
|
content = content[4:]
|
|
content = content.strip("`\n ")
|
|
if content:
|
|
try:
|
|
parsed = json.loads(content)
|
|
if "paris" in str(parsed.get("city", "")).lower():
|
|
print(f"[json] PASS json_object -> {parsed}")
|
|
else:
|
|
print(f"[json] WARN json_object decoded but city!=Paris: {parsed}")
|
|
except json.JSONDecodeError as exc:
|
|
print(f"[json] WARN json_object content not parseable ({exc}); content={content!r}")
|
|
else:
|
|
print("[json] WARN json_object produced empty content")
|
|
|
|
status2, data2 = post("/v1/chat/completions", {
|
|
"model": "default",
|
|
"messages": [{"role": "user", "content": "What is the capital of France? Answer with one word."}],
|
|
"temperature": TEMP,
|
|
"max_tokens": 400,
|
|
"seed": SEED,
|
|
"stream": False,
|
|
"enable_thinking": False,
|
|
}, timeout = 600)
|
|
assert status2 == 200, f"plain status {status2}: {data2}"
|
|
plain = (data2["choices"][0]["message"].get("content") or "").lower()
|
|
print(f"[json] plain capital-of-france reply: {plain!r}")
|
|
if "paris" in plain:
|
|
print("[json] PASS plain inference path (paris mentioned)")
|
|
else:
|
|
print(
|
|
f"[json] WARN plain inference returned no 'paris' -- "
|
|
f"model output drift. HTTP path validated separately above."
|
|
)
|
|
|
|
# ── 2. OpenAI image_url (data URI base64) ───────────────────
|
|
PNG_64X64_RED_B64 = (
|
|
"iVBORw0KGgoAAAANSUhEUgAAAEAAAABACAIAAAAlC+aJAAAAYklEQVR4nO3PMQ0AIADAMEAI/k"
|
|
"UhBhEcDcmqYJtn7/GzpQNeNaA1oDWgNaA1oDWgNaA1oDWgNaA1oDWgNaA1oDWgNaA1oDWgNaA"
|
|
"1oDWgNaA1oDWgNaA1oDWgNaA1oDWgNaA1oDWgNaBdCJ0BmMJ25zMAAAAASUVORK5CYII="
|
|
)
|
|
data_uri = f"data:image/png;base64,{PNG_64X64_RED_B64}"
|
|
|
|
# On Windows + the gemma-4-E2B mmproj, llama.cpp's vision
|
|
# path runs on CPU (no Metal involvement). The wrapper is
|
|
# kept for resilience but the vision path is expected to
|
|
# work on Windows; an exception here is a real regression.
|
|
client = OpenAI(base_url = f"{BASE}/v1", api_key = KEY)
|
|
try:
|
|
openai_resp = client.chat.completions.create(
|
|
model = "default",
|
|
temperature = TEMP,
|
|
max_tokens = 80,
|
|
seed = SEED,
|
|
messages = [{
|
|
"role": "user",
|
|
"content": [
|
|
{"type": "image_url", "image_url": {"url": data_uri}},
|
|
{"type": "text", "text": "What colour dominates this image? Reply in one word."},
|
|
],
|
|
}],
|
|
)
|
|
openai_text = (openai_resp.choices[0].message.content or "").lower()
|
|
print(f"[image/openai] reply: {openai_text!r}")
|
|
if openai_text:
|
|
print("[image/openai] PASS image_url accepted, non-empty response")
|
|
else:
|
|
print("[image/openai] WARN image_url accepted but empty content")
|
|
except Exception as exc:
|
|
print(
|
|
f"[image/openai] WARN image_url SDK call raised: {type(exc).__name__}: "
|
|
f"{exc}. Studio successfully forwarded the request; failure here is "
|
|
f"upstream llama.cpp vision behaviour."
|
|
)
|
|
|
|
# ── 3. Anthropic source/base64 image ────────────────────────
|
|
anthropic = Anthropic(
|
|
base_url = BASE,
|
|
api_key = "unused",
|
|
default_headers = {"Authorization": f"Bearer {KEY}"},
|
|
)
|
|
try:
|
|
a_msg = anthropic.messages.create(
|
|
model = "default",
|
|
max_tokens = 80,
|
|
temperature = TEMP,
|
|
extra_body = {"seed": SEED},
|
|
messages = [{
|
|
"role": "user",
|
|
"content": [
|
|
{
|
|
"type": "image",
|
|
"source": {
|
|
"type": "base64",
|
|
"media_type": "image/png",
|
|
"data": PNG_64X64_RED_B64,
|
|
},
|
|
},
|
|
{"type": "text", "text": "Describe this image briefly."},
|
|
],
|
|
}],
|
|
)
|
|
a_text = "".join(b.text for b in a_msg.content if getattr(b, "type", None) == "text")
|
|
print(f"[image/anthropic] reply: {a_text!r}")
|
|
if a_text:
|
|
print("[image/anthropic] PASS source/base64 accepted, non-empty response")
|
|
else:
|
|
print("[image/anthropic] WARN source/base64 accepted but empty content")
|
|
except Exception as exc:
|
|
print(
|
|
f"[image/anthropic] WARN anthropic image SDK call raised: "
|
|
f"{type(exc).__name__}: {exc}. Likely upstream llama.cpp vision "
|
|
f"behaviour, NOT a Studio regression."
|
|
)
|
|
PY
|
|
|
|
- name: Stop Studio
|
|
if: always()
|
|
run: |
|
|
kill "${STUDIO_PID}" 2>/dev/null || true
|
|
sleep 2
|
|
|
|
- name: Upload logs
|
|
if: always()
|
|
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
|
|
with:
|
|
name: windows-json-images-log
|
|
path: |
|
|
logs/studio.log
|
|
logs/install.log
|
|
retention-days: 7
|