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/diffusers_load_pipeline.md

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+---
+name: diffusers_load_pipeline
+kind: function
+lang: py
+domain: ml
+version: "1.0.0"
+purity: impure
+signature: "def diffusers_load_pipeline(model: ModelRef, device: str = 'auto', dtype: str = 'fp16') -> Any"
+description: "Carga un pipeline diffusers (AutoPipelineForText2Image) con cache global por (model_key, dtype, device). Segunda llamada con mismos parametros retorna el objeto cacheado sin recargar disco."
+tags: [diffusers, ml, image-generation, pipeline, cache, torch]
+uses_functions: [torch_device_select_py_ml]
+uses_types: [model_ref_py_ml]
+returns: []
+returns_optional: false
+error_type: "error_go_core"
+imports: [torch, diffusers]
+params:
+  - name: model
+    desc: "Referencia al modelo. model.path si disponible (ruta local), model.name si no (HuggingFace Hub o nombre corto)."
+  - name: device
+    desc: "Preferencia de device: 'auto' (CUDA>MPS>CPU), 'cuda', 'cuda:N', 'mps', 'cpu'. Default 'auto'."
+  - name: dtype
+    desc: "Precision del modelo: 'fp16' (torch.float16 + variant=fp16), 'bf16' (bfloat16), 'fp32' (float32). Default 'fp16'."
+output: "Pipeline diffusers cargado y movido al device. Callable via pipe(prompt=..., ...). Cacheado en _PIPELINE_CACHE."
+tested: true
+tests:
+  - "carga pipeline y retorna callable"
+  - "segunda carga usa cache (< 100ms)"
+test_file_path: "python/functions/ml/tests/test_diffusers_backend.py"
+file_path: "python/functions/ml/diffusers_load_pipeline.py"
+---
+
+## Ejemplo
+
+```python
+import sys
+sys.path.insert(0, "python/functions/ml")
+from diffusers_load_pipeline import diffusers_load_pipeline
+from model_ref import ModelRef
+
+model = ModelRef(
+    name="sd-turbo",
+    model_type="sd15",
+    quantization="fp16",
+    path="/home/lucas/vaults/imagegen_models/diffusers/sd-turbo",
+)
+pipe = diffusers_load_pipeline(model, device="cuda", dtype="fp16")
+# Segunda llamada: cache hit, < 100ms
+pipe2 = diffusers_load_pipeline(model, device="cuda", dtype="fp16")
+assert pipe is pipe2
+```
+
+## Notas
+
+Cache global `_PIPELINE_CACHE` indexado por `(model_key, dtype, resolved_device)`.
+`model_key` es `model.path` si no es None, sino `model.name`.
+
+Para liberar memoria: usar `diffusers_unload(pipe=None)` que llama `_clear_pipeline_cache()`.
+
+Imports lazy de torch y diffusers dentro de la funcion — ImportError descriptivo si no instalados.