ci.yml

name: ci

on:
  push:
  pull_request:
  # closed-loop job runs on pull_request (gate) and manual dispatch (see below).
  workflow_dispatch:

jobs:
  # -------------------------------------------------------------------------
  # build: configure, compile, run model-independent unit tests.
  # Runs on every push and pull_request.  Never downloads a model — fast gate.
  # -------------------------------------------------------------------------
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with:
          submodules: recursive

      - name: configure
        # GGML_NATIVE=OFF for portability in CI (no host-cpu ISA extensions)
        run: cmake -B build -DPARAKEET_BUILD_TESTS=ON -DGGML_NATIVE=OFF

      - name: build
        run: cmake --build build -j

      - name: test (model-independent only)
        # -LE model excludes the model-labelled tests (check_convert,
        # test_model_loader, check_baseline) that need the Python venv and the
        # cached NeMo checkpoint.  Those will run in a separate workflow_dispatch
        # job once a models bundle is published (Phase 4).
        run: ctest --test-dir build --output-on-failure -LE model

  # -------------------------------------------------------------------------
  # server-e2e: drive the real parakeet-server over HTTP.
  #
  # Runs on pull_request (merge gate) and manual workflow_dispatch. Not on every
  # push: it downloads the ~125 MB tdt_ctc-110m-q4_k model via the alias path.
  # Much lighter than closed-loop (no NeMo/Python venv) — it builds the server,
  # then tests/server_e2e.sh starts it, transcribes tests/fixtures/speech.wav in
  # json/text/verbose_json (with word timestamps), and checks the 400 paths.
  # -------------------------------------------------------------------------
  server-e2e:
    if: github.event_name == 'pull_request' || github.event_name == 'workflow_dispatch'
    runs-on: ubuntu-latest
    timeout-minutes: 20
    steps:
      - uses: actions/checkout@v4
        with:
          submodules: recursive

      - name: Install build dependencies
        run: |
          sudo apt-get update
          sudo apt-get install -y cmake build-essential curl ca-certificates

      - name: Configure
        run: |
          cmake -B build \
            -DPARAKEET_BUILD_SERVER=ON \
            -DPARAKEET_BUILD_TESTS=ON \
            -DGGML_NATIVE=OFF

      - name: Build parakeet-server
        run: cmake --build build --target parakeet-server -j

      - name: Run server e2e
        # PARAKEET_SERVER_E2E=1 flips the test from skip (77) to a real run.
        env:
          PARAKEET_SERVER_E2E: "1"
          # First-run model download speed varies on hosted runners; the job
          # timeout remains the outer cap.
          PARAKEET_SERVER_E2E_READY_TIMEOUT: "600"
        run: ctest --test-dir build --output-on-failure -R '^server_e2e$'

  # -------------------------------------------------------------------------
  # closed-loop: full end-to-end transcript assertion.
  #
  # Runs on pull_request (merge gate) and manual workflow_dispatch. Not on every
  # push, since this job downloads nvidia/parakeet-tdt_ctc-110m (~440 MB via
  # NeMo/HuggingFace Hub) and installs the nemo_toolkit Python env (~60 min).
  #
  # What it does:
  #   1. Check out the repo (submodules recursive).
  #   2. Install system build deps + Python 3.12 + pip.
  #   3. Create a venv and install CPU torch + scripts/requirements.txt
  #      (nemo_toolkit[asr] + gguf) — same setup as the developer guide.
  #   4. Build the project (GGML_NATIVE=OFF for runner portability,
  #      PARAKEET_BUILD_TESTS=ON, PARAKEET_BUILD_CLI=ON).
  #   5. Convert nvidia/parakeet-tdt_ctc-110m → /tmp/pk110m_cl.gguf
  #      (F32, default dtype; NeMo auto-downloads the checkpoint on first use).
  #   6. Run `parakeet-cli transcribe` on tests/fixtures/speech.wav with
  #      --decoder tdt (the TDT head of the hybrid model).
  #   7. Assert the output matches the committed NeMo reference transcript:
  #        "Well, I don't wish to see it any more, observed Phoebe,
  #         turning away her eyes. It is certainly very like the old portrait."
  #      Fail the job if it doesn't match.
  # -------------------------------------------------------------------------
  closed-loop:
    if: github.event_name == 'pull_request' || github.event_name == 'workflow_dispatch'
    runs-on: ubuntu-latest
    timeout-minutes: 60
    steps:
      - name: Checkout (with submodules)
        uses: actions/checkout@v4
        with:
          submodules: recursive

      - name: Install system build dependencies
        run: |
          sudo apt-get update
          sudo apt-get install -y cmake build-essential python3 python3-venv python3-pip

      - name: Set up Python venv
        # CPU-only torch wheel; nemo_toolkit[asr] + gguf from requirements.txt.
        # Mirror the developer setup documented in AGENTS.md / README.md.
        run: |
          python3 -m venv .venv
          .venv/bin/pip install --quiet --upgrade pip
          .venv/bin/pip install --quiet torch --index-url https://download.pytorch.org/whl/cpu
          .venv/bin/pip install --quiet -r scripts/requirements.txt

      - name: Configure CMake
        run: |
          cmake -B build \
            -DPARAKEET_BUILD_TESTS=ON \
            -DPARAKEET_BUILD_CLI=ON \
            -DGGML_NATIVE=OFF

      - name: Build
        run: cmake --build build -j

      - name: Convert nvidia/parakeet-tdt_ctc-110m to GGUF
        # NeMo downloads the ~440 MB checkpoint from HuggingFace on first use.
        # The resulting GGUF is ~438 MB (F32).
        run: |
          .venv/bin/python scripts/convert_parakeet_to_gguf.py \
            --model nvidia/parakeet-tdt_ctc-110m \
            --output /tmp/pk110m_cl.gguf

      - name: Transcribe speech fixture with TDT decoder
        run: |
          ./build/examples/cli/parakeet-cli transcribe \
            --model /tmp/pk110m_cl.gguf \
            --input tests/fixtures/speech.wav \
            --decoder tdt \
            > /tmp/cl_transcript.txt
          echo "--- transcript ---"
          cat /tmp/cl_transcript.txt

      - name: Assert transcript matches NeMo reference
        # Reference transcript (TDT head, hybrid 110m) committed to docs/parity.md
        # and validated at WER 0.0 vs NeMo 2.7.3 (see docs/parity.md § Phase 3).
        run: |
          EXPECTED="Well, I don't wish to see it any more, observed Phoebe, turning away her eyes. It is certainly very like the old portrait."
          ACTUAL="$(cat /tmp/cl_transcript.txt)"
          python3 - <<'PYEOF'
          import sys
          expected = "Well, I don't wish to see it any more, observed Phoebe, turning away her eyes. It is certainly very like the old portrait."
          with open("/tmp/cl_transcript.txt") as f:
              actual = f.read().strip()
          if actual == expected:
              print("PASS: transcript matches NeMo reference (WER 0.0)")
              sys.exit(0)
          else:
              print("FAIL: transcript mismatch")
              print(f"  expected: {expected!r}")
              print(f"  actual:   {actual!r}")
              sys.exit(1)
          PYEOF