feat: harden local runtime and verification

installer/scripts/launch-local.sh

@@ -0,0 +1,17 @@
+#!/usr/bin/env bash
+set -euo pipefail
+set +x
+
+cd "$(dirname "${BASH_SOURCE[0]}")/../.."
+
+if [[ -z "${OBLITERATUS_SECRET_COMMAND:-}" ]] && \
+   [[ -x /home/roctinam/.local/bin/obliteratus-secret-broker ]]; then
+  export OBLITERATUS_SECRET_COMMAND=/home/roctinam/.local/bin/obliteratus-secret-broker
+fi
+
+# Avoid dynamic mixing between PyTorch's bundled cuDNN and a host cuDNN
+# installation. Causal convolutions and attention use other CUDA kernels.
+export OBLITERATUS_DISABLE_CUDNN="${OBLITERATUS_DISABLE_CUDNN:-1}"
+
+exec .venv/bin/python app.py --host "${OBLITERATUS_HOST:-127.0.0.1}" \
+  --port "${OBLITERATUS_PORT:-7860}"

installer/scripts/setup.sh

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+#!/usr/bin/env bash
+set -euo pipefail
+set +x
+
+cd "$(dirname "${BASH_SOURCE[0]}")/../.."
+
+uv sync --locked --extra spaces --extra dev --no-editable
+
+enable_cuda="${ENABLE_CUDA:-auto}"
+if [[ "$enable_cuda" != "false" ]] && command -v nvidia-smi >/dev/null 2>&1; then
+  torch_version="$(.venv/bin/python -c 'import torch; print(torch.__version__.split("+", 1)[0])')"
+  UV_TORCH_BACKEND=cu130 uv pip install \
+    --python .venv/bin/python \
+    --reinstall-package torch \
+    "torch==$torch_version"
+fi
+
+uv pip check --python .venv/bin/python
+.venv/bin/python - <<'PY'
+import shutil
+import torch
+
+if torch.cuda.is_available():
+    probe = torch.arange(16, device="cuda", dtype=torch.float32).square().sum()
+    assert probe.device.type == "cuda"
+    torch.backends.cudnn.enabled = False
+    torch.backends.cuda.enable_cudnn_sdp(False)
+    conv_input = torch.randn(1, 8, 32, device="cuda", dtype=torch.float16)
+    conv_weight = torch.randn(8, 8, 3, device="cuda", dtype=torch.float16)
+    convolution = torch.nn.functional.conv1d(conv_input, conv_weight)
+    q = torch.randn(1, 2, 32, 16, device="cuda", dtype=torch.float16)
+    attention = torch.nn.functional.scaled_dot_product_attention(q, q, q, is_causal=True)
+    torch.cuda.synchronize()
+    assert convolution.device.type == "cuda" and torch.isfinite(convolution).all()
+    assert attention.device.type == "cuda" and torch.isfinite(attention).all()
+elif shutil.which("nvidia-smi"):
+    raise SystemExit("NVIDIA hardware detected but the installed PyTorch runtime cannot use CUDA")
+PY

installer/scripts/verify.sh

@@ -0,0 +1,37 @@
+#!/usr/bin/env bash
+set -euo pipefail
+set +x
+
+cd "$(dirname "${BASH_SOURCE[0]}")/../.."
+
+.venv/bin/python - <<'PY'
+import os
+import shutil
+import torch
+
+from obliteratus.credential_sources import secret_available
+
+assert torch.ones(1).add(1).item() == 2
+if shutil.which("nvidia-smi"):
+    assert torch.cuda.is_available(), "NVIDIA GPU detected but CUDA is unavailable"
+    assert torch.ones(1, device="cuda").device.type == "cuda"
+    torch.backends.cudnn.enabled = False
+    torch.backends.cuda.enable_cudnn_sdp(False)
+    conv_input = torch.randn(1, 8, 32, device="cuda", dtype=torch.float16)
+    conv_weight = torch.randn(8, 8, 3, device="cuda", dtype=torch.float16)
+    convolution = torch.nn.functional.conv1d(conv_input, conv_weight)
+    q = torch.randn(1, 2, 32, 16, device="cuda", dtype=torch.float16)
+    attention = torch.nn.functional.scaled_dot_product_attention(q, q, q, is_causal=True)
+    torch.cuda.synchronize()
+    assert convolution.device.type == "cuda" and torch.isfinite(convolution).all()
+    assert attention.device.type == "cuda" and torch.isfinite(attention).all()
+
+broker = os.environ.get("OBLITERATUS_SECRET_COMMAND")
+if broker:
+    assert os.path.isabs(broker)
+    assert secret_available("HF_TOKEN")
+    assert secret_available("OPENROUTER_API_KEY")
+PY
+
+.venv/bin/pytest -q --no-cov tests/test_device_boundaries.py tests/test_secrets.py \
+  tests/test_abliterate.py::TestCoherenceScoring