8c606a70b5The Mac json-images job (run 25664825326) hit the 30 min step budget while downloading 4 GiB of GGUF assets unauthenticated. The log shows the explicit "You are sending unauthenticated requests to the HF Hub" warning followed by 30 min of zero progress, then job cancellation. macos-14, ubuntu-latest, and windows-latest runners share NAT egress IP pools across the whole GitHub Actions fleet, so the anonymous per-IP rate limit kicks in well before the file size alone would suggest. An authenticated token shifts the budget to per-user. Add HF_TOKEN: secrets.HF_TOKEN to every hf download step across the nine studio CI workflows that pull from HF. The env is scoped to the download step only, not the job, so every other step still runs without HF_TOKEN in its environment and the GitHub secret-masking layer handles log scrubbing. For the Mac json-images step specifically, the model and mmproj downloads now run in parallel under wait, and an ls -lhL after the wait surfaces a partial download as an obvious failure instead of a silent 30 min timeout on the next inference/load call.
1108 lines
48 KiB
YAML
1108 lines
48 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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- name: Cache HF_HOME for ${{ env.GGUF_REPO }}
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id: cache-hf
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uses: actions/cache@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: Prime HF_HOME with the GGUF
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if: steps.cache-hf.outputs.cache-hit != 'true'
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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" "$GGUF_FILE"
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- name: Pre-install Windows tweaks (npm 11 + Defender exclusions)
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shell: pwsh
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# See studio-windows-update-smoke.yml for the full rationale.
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# tl;dr: setup.ps1 needs npm >=11 to skip a 35 s winget Node
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# reinstall, and Defender's real-time scan dominates the
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# frontend / uv-pip-extract steps.
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run: |
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$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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|
|
- 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?",
|
|
"What is the capital of France?",
|
|
"Repeat the city name",
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|
]
|
|
|
|
def run_openai():
|
|
client = OpenAI(base_url = f"{BASE}/v1", api_key = KEY)
|
|
history, replies = [], []
|
|
for prompt in PROMPTS:
|
|
history.append({"role": "user", "content": prompt})
|
|
resp = client.chat.completions.create(
|
|
model = "default",
|
|
messages = history,
|
|
temperature = 0.0,
|
|
max_tokens = 80,
|
|
seed = SEED,
|
|
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
|
|
|
|
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}"},
|
|
)
|
|
history, replies = [], []
|
|
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,
|
|
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
|
|
|
|
for label, runner in (("openai", run_openai), ("anthropic", run_anthropic)):
|
|
first = runner()
|
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second = runner()
|
|
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"
|
|
assert a == b, (
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f"{label} non-deterministic at turn {i} with temperature=0.0:\n"
|
|
f" run1: {a!r}\n run2: {b!r}"
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)
|
|
joined = " ".join(first).lower()
|
|
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
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|
sleep 2
|
|
|
|
- name: Upload logs
|
|
if: always()
|
|
uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a # v7.0.1
|
|
with:
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|
name: windows-openai-anthropic-log
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|
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'
|
|
|
|
- name: Cache GGUF model file
|
|
id: cache-gguf
|
|
uses: actions/cache@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
|
|
with:
|
|
path: gguf-cache
|
|
key: ${{ runner.os }}-gguf-${{ env.GGUF_REPO }}-${{ env.GGUF_FILE }}-v1
|
|
|
|
- name: Download GGUF if cache miss
|
|
if: steps.cache-gguf.outputs.cache-hit != 'true'
|
|
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: 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'
|
|
|
|
- name: Cache HF_HOME for ${{ env.GGUF_REPO }} (model + mmproj)
|
|
id: cache-hf
|
|
uses: actions/cache@27d5ce7f107fe9357f9df03efb73ab90386fccae # v5.0.5
|
|
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
|
|
if: steps.cache-hf.outputs.cache-hit != 'true'
|
|
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: 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
|