feat(ml): comfyui_build_img2vid_workflow builder img2vid SVD (API format)

Builder puro que construye el dict de un workflow ComfyUI img2vid (Stable Video
Diffusion) en API format a partir de una imagen estatica. Cadena de 7 nodos:
ImageOnlyCheckpointLoader(svd.safetensors, todo-en-uno) + LoadImage ->
SVD_img2vid_Conditioning -> VideoLinearCFGGuidance -> KSampler(denoise 1.0) ->
VAEDecode -> SaveAnimatedWEBP. SVD condiciona por CLIP_VISION de la imagen (sin
prompt de texto); movimiento via motion_bucket_id.

class_type/inputs verificados contra /object_info del servidor vivo. Validacion
estructural con comfyui_validate_workflow: 0 errores. 4 tests verdes. Sin submit
de generacion (GPU en uso por otro agente).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

python/functions/ml/tests/test_comfyui_build_img2vid_workflow.py

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+"""Tests de estructura para comfyui_build_img2vid_workflow (funcion pura, SVD)."""
+
+import os
+import sys
+
+sys.path.insert(0, os.path.dirname(__file__))
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", ".."))
+
+from ml.comfyui_build_img2vid_workflow import comfyui_build_img2vid_workflow
+from _comfyui_wf_assert import assert_api_format, class_types, node_by_ct
+
+
+def test_estructura_y_nodos_svd():
+    wf = comfyui_build_img2vid_workflow("example.png")
+    assert_api_format(wf)
+    cts = class_types(wf)
+    for ct in (
+        "ImageOnlyCheckpointLoader",
+        "LoadImage",
+        "SVD_img2vid_Conditioning",
+        "VideoLinearCFGGuidance",
+        "KSampler",
+        "VAEDecode",
+        "SaveAnimatedWEBP",
+    ):
+        assert ct in cts, f"falta {ct} en SVD img2vid"
+    # El checkpoint SVD es todo-en-uno cargado con el loader image-only.
+    assert node_by_ct(wf, "ImageOnlyCheckpointLoader")["inputs"]["ckpt_name"] == (
+        "svd.safetensors"
+    )
+    # La imagen base entra por LoadImage.
+    assert node_by_ct(wf, "LoadImage")["inputs"]["image"] == "example.png"
+
+
+def test_cableado_de_nodos():
+    wf = comfyui_build_img2vid_workflow("example.png")
+    cond = node_by_ct(wf, "SVD_img2vid_Conditioning")["inputs"]
+    # clip_vision y vae salen del checkpoint image-only (outputs 1 y 2).
+    assert cond["clip_vision"] == ["15", 1]
+    assert cond["vae"] == ["15", 2]
+    assert cond["init_image"] == ["23", 0]
+    ks = node_by_ct(wf, "KSampler")["inputs"]
+    # KSampler usa el MODEL post VideoLinearCFGGuidance y los 3 outputs del cond.
+    assert ks["model"] == ["14", 0]
+    assert ks["positive"] == ["12", 0]
+    assert ks["negative"] == ["12", 1]
+    assert ks["latent_image"] == ["12", 2]
+    assert ks["denoise"] == 1.0
+    # VideoLinearCFGGuidance toma el MODEL crudo del checkpoint.
+    assert node_by_ct(wf, "VideoLinearCFGGuidance")["inputs"]["model"] == ["15", 0]
+
+
+def test_params_se_reflejan():
+    wf = comfyui_build_img2vid_workflow(
+        "fox_front.png",
+        width=768,
+        height=448,
+        video_frames=25,
+        motion_bucket_id=200,
+        fps=10,
+        augmentation_level=0.2,
+        steps=25,
+        cfg=3.0,
+        min_cfg=1.5,
+        seed=7,
+        filename_prefix="myclip",
+    )
+    cond = node_by_ct(wf, "SVD_img2vid_Conditioning")["inputs"]
+    assert cond["width"] == 768 and cond["height"] == 448
+    assert cond["video_frames"] == 25
+    assert cond["motion_bucket_id"] == 200
+    assert cond["fps"] == 10
+    assert cond["augmentation_level"] == 0.2
+    ks = node_by_ct(wf, "KSampler")["inputs"]
+    assert ks["steps"] == 25 and ks["cfg"] == 3.0 and ks["seed"] == 7
+    assert node_by_ct(wf, "VideoLinearCFGGuidance")["inputs"]["min_cfg"] == 1.5
+    save = node_by_ct(wf, "SaveAnimatedWEBP")["inputs"]
+    assert save["filename_prefix"] == "myclip"
+    # SaveAnimatedWEBP declara fps como FLOAT en /object_info.
+    assert save["fps"] == 10.0
+    assert isinstance(save["fps"], float)
+
+
+def test_determinista():
+    a = comfyui_build_img2vid_workflow("example.png", seed=7)
+    b = comfyui_build_img2vid_workflow("example.png", seed=7)
+    assert a == b