chore: auto-commit (95 archivos)

- cmd/fn/doctor.go
- cmd/fn/main.go
- cpp/apps/primitives_gallery/playground/tables/CMakeLists.txt
- cpp/apps/primitives_gallery/playground/tables/data_table.cpp
- cpp/apps/primitives_gallery/playground/tables/data_table_logic.cpp
- cpp/apps/primitives_gallery/playground/tables/data_table_logic.h
- cpp/apps/primitives_gallery/playground/tables/self_test.cpp
- cpp/apps/primitives_gallery/playground/tables/tql.cpp
- cpp/apps/primitives_gallery/playground/tables/viz.cpp
- cpp/apps/primitives_gallery/playground/tables/viz.h
- ...

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

python/functions/ml/cuda_available.md

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+---
+name: cuda_available
+kind: function
+lang: py
+domain: ml
+version: "1.0.0"
+purity: impure
+signature: "def cuda_available() -> dict"
+description: "Detecta si CUDA esta disponible via torch. Devuelve device_count, nombres de GPU y version de CUDA. Si torch no esta instalado, retorna available=False sin lanzar excepcion."
+tags: [cuda, gpu, torch, pytorch, hardware, probe, ml, device]
+uses_functions: []
+uses_types: []
+returns: []
+returns_optional: false
+error_type: "error_go_core"
+imports: []
+params: []
+output: "dict con claves: available (bool), device_count (int), devices (list[str] con nombres de GPU), torch_version (str o 'not_installed'), cuda_version (str | None)"
+tested: true
+tests:
+  - "sin torch retorna available=False y torch_version=not_installed"
+  - "con torch sin cuda retorna available=False y device_count=0"
+  - "claves del dict siempre presentes"
+test_file_path: "python/functions/ml/tests/test_cuda_available.py"
+file_path: "python/functions/ml/cuda_available.py"
+---
+
+## Ejemplo
+
+```python
+from ml.cuda_available import cuda_available
+
+info = cuda_available()
+# Sin GPU:
+# {
+#   "available": False,
+#   "device_count": 0,
+#   "devices": [],
+#   "torch_version": "2.3.0",
+#   "cuda_version": None
+# }
+
+# Con GPU:
+# {
+#   "available": True,
+#   "device_count": 1,
+#   "devices": ["NVIDIA RTX 4090"],
+#   "torch_version": "2.3.0",
+#   "cuda_version": "12.1"
+# }
+
+# Sin torch instalado:
+# {
+#   "available": False,
+#   "device_count": 0,
+#   "devices": [],
+#   "torch_version": "not_installed",
+#   "cuda_version": None
+# }
+```
+
+## Notas
+
+- Nunca lanza ImportError aunque torch no este instalado.
+- `cuda_version` es la version de CUDA con la que fue compilado torch, no necesariamente la del sistema.
+- Usar junto a `torch_device_select` para elegir device y `gpu_info` para estadisticas de VRAM.
+- impure: depende del estado del hardware y de librerias del sistema en tiempo de ejecucion.