DemonGatanjieuandClaude Opus 5.5
f0a026142a
Two more ways under "Redraw with another model" (want: character, background). The character is cut out (InSPyReNet, made solid, grown 12 px); the character way blurs that mask so the second model's redraw fades out at the edge (Differential Diffusion), the background way redraws its inverse; both paste the redraw back through the mask, so the rest of the picture stays the same to the pixel. Denoise 0.45 from GPT's comparison of 2026-11-10. Both built through the real page on the test ComfyUI on Anima (Harem 2.9B, RealSkin, Kirazuri), 1440x1024: outside the soft edge and outside the background nothing changed. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
429 lines
34 KiB
Python
429 lines
34 KiB
Python
"""Ready-made blocks (api/reference_blocks.py) and add_nodes(block=…): what the AI is offered, what a
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block needs here, and the group the page is asked to build. No ComfyUI, no page."""
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import os
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import sys
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import tempfile
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import unittest
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from pathlib import Path
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from unittest import mock
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from PIL import Image
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PLUGIN = Path(__file__).resolve().parents[1]
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sys.path[:0] = [str(PLUGIN), str(PLUGIN.parents[1])]
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from api import ai_pictures, mcp_canvas_edit, mcp_task_tools, reference_blocks # noqa: E402
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from api.mcp_tools import ToolError # noqa: E402
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DETECTORS = {"input": {"required": {"model_name": [["bbox/hand_yolov8n.pt", "bbox/hand_yolov8s.pt", "bbox/face_yolov8m.pt", "segm/person_yolov8m-seg.pt"]]}}}
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UPSCALERS = {"input": {"required": {"model_name": ["COMBO", {"options": ["2x-Lite.pth", "RealESRGAN_x4plus.pth", "4x-UltraSharp.pth"]}]}}}
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CONTROLNETS = {"input": {"required": {"control_net_name": [[
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"SD_1.5/control_v11p_sd15_openpose.safetensors", "anima-lllite-pose-1.safetensors", "SDXL/union-promax.safetensors",
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"NoobAI/noob-openpose.safetensors", "SDXL/xinsir-openpose.safetensors"]]}}}
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BASES = {"SD_1.5/control_v11p_sd15_openpose.safetensors": "SD 1.5", "SDXL/union-promax.safetensors": "SDXL 1.0",
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"NoobAI/noob-openpose.safetensors": "NoobAI", "SDXL/xinsir-openpose.safetensors": "SDXL 1.0"}
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base = lambda name: BASES.get(name, "") # noqa: E731
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LLLITES = {"input": {"required": {"lllite_name": [["SDXL/union-promax.safetensors", "anima-lllite-depth-1.safetensors",
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"anima-lllite-inpainting-v1.safetensors", "anima-lllite-inpainting-v2.safetensors",
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"animaTileRepair_v20.safetensors"]]}}}
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EVERYTHING = {kind: {} for block in reference_blocks.BLOCKS.values() for kind in block["packs"]} | {
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"UltralyticsDetectorProvider": DETECTORS, "UpscaleModelLoader": UPSCALERS, "ControlNetLoader": CONTROLNETS,
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"AnimaLLLiteApply_sdscripts": LLLITES}
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BUILT_IN = {"LoadImage": {}, "KSampler": {}}
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def keep_switches_apart(case):
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"""The panel's switches in a temporary file, not the user's."""
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folder = tempfile.TemporaryDirectory()
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case.addCleanup(folder.cleanup)
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patcher = mock.patch.object(reference_blocks, "_off_path", return_value=os.path.join(folder.name, "ai_blocks.json"))
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patcher.start()
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case.addCleanup(patcher.stop)
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class BlockTests(unittest.TestCase):
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def setUp(self):
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keep_switches_apart(self)
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def test_the_directory_lists_what_can_run_by_use_and_the_rest_by_what_it_needs(self):
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listed = reference_blocks.directory(BUILT_IN)
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self.assertEqual(listed["repaint"], "Repaint an area", "only what runs here: the built-in one, no want to name")
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self.assertIn("LanPaint: repaint best", listed["Not here yet, needs"], "what to install, by pack")
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self.assertIn("upscaler model: upscale", listed["Not here yet, needs"], "built-in nodes, but no upscale model")
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everything = reference_blocks.directory(EVERYTHING)
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self.assertNotIn("Not here yet, needs", everything)
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self.assertEqual(list(everything), list(reference_blocks.JOBS), "a line a use")
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self.assertEqual(everything["follow"], "Follow a given picture (want: pose, layout, lines, style)")
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self.assertEqual(set(reference_blocks.directory()), set(reference_blocks.JOBS), "node list unknown: all, nothing claimed")
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self.assertLess(len(" ".join(everything.values())), 500, "small: it goes with begin_task")
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def test_a_use_picks_the_best_block_this_comfyui_can_run(self):
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self.assertEqual(reference_blocks.pick("repaint", None, EVERYTHING), "inpaint_crop_stitch")
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self.assertEqual(reference_blocks.pick("repaint", None, BUILT_IN), "inpaint_basic", "the pack missing: the built-in one")
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self.assertEqual(reference_blocks.pick("repaint", "best", BUILT_IN), "inpaint_lanpaint", "asked for: its build says what it needs")
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self.assertEqual(reference_blocks.pick("upscale", "2x", EVERYTHING), "upscale_tiled")
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self.assertEqual(reference_blocks.pick("new_background", None, EVERYTHING, scene=True), "place_in_scene", "a second picture given")
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with self.assertRaisesRegex(reference_blocks.BlockError, "follow takes want: pose, layout, lines, style\."):
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reference_blocks.pick("follow", None, EVERYTHING)
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with self.assertRaisesRegex(reference_blocks.BlockError, "repaint takes want: best, or none"):
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reference_blocks.pick("repaint", "fast", EVERYTHING)
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with self.assertRaisesRegex(reference_blocks.BlockError, "No use 'paint'"):
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reference_blocks.pick("paint")
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def test_a_block_turned_off_is_not_offered_and_cannot_be_built(self):
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reference_blocks.set_on("inpaint_lanpaint", False)
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self.assertNotIn("inpaint_lanpaint", " ".join(reference_blocks.directory(EVERYTHING).values()))
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with self.assertRaisesRegex(reference_blocks.BlockError, "turned block inpaint_lanpaint off"):
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reference_blocks.nodes_of("inpaint_lanpaint", EVERYTHING, "a.png")
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shown = {item["name"]: item for item in reference_blocks.status(BUILT_IN)}
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self.assertEqual((shown["inpaint_lanpaint"]["on"], shown["inpaint_lanpaint"]["usable"]), (False, False))
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self.assertEqual(shown["inpaint_lanpaint"]["packs"], [{"name": "LanPaint", "installed": False}])
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self.assertEqual(shown["upscale"]["models"], [{"kind": "upscaler"}])
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self.assertEqual(shown["control_pose"]["packs"], [{"name": "comfyui_controlnet_aux", "installed": False}])
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self.assertTrue(shown["inpaint_basic"]["usable"])
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self.assertEqual(reference_blocks.set_on("inpaint_lanpaint", True), set())
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with self.assertRaises(reference_blocks.BlockError):
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reference_blocks.set_on("nope", True)
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def test_every_block_has_its_words_in_both_languages(self):
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for name, block in reference_blocks.BLOCKS.items():
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with self.subTest(block=name):
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for field in ("title", "about", "source"):
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self.assertTrue(block[field]["zh"] and block[field]["en"])
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self.assertIn(block["job"], reference_blocks.JOBS)
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self.assertTrue(block["short"] and block["after"])
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def test_a_repaint_block_is_the_group_with_the_users_picture(self):
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nodes = reference_blocks.nodes_of("inpaint_crop_stitch", EVERYTHING, " anomalous_inpaint_ab.png ")
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self.assertEqual(nodes["picture"]["inputs"]["image"], "anomalous_inpaint_ab.png")
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self.assertEqual(nodes["condition"]["wire_to"], "$sampler", "the page finds the sampler")
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self.assertEqual(nodes["stitch"]["inputs"]["inpainted_image"], ["$decode", 0])
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self.assertEqual(nodes["crop"]["inputs"]["output_target_width"], 1024, "the settings the distilled workflow used")
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self.assertIsNot(nodes["picture"]["inputs"], reference_blocks.BLOCKS["inpaint_crop_stitch"]["nodes"]["picture"]["inputs"])
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with self.assertRaisesRegex(reference_blocks.BlockError, "needs image"):
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reference_blocks.nodes_of("inpaint_basic", BUILT_IN)
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with self.assertRaisesRegex(reference_blocks.BlockError, "needs scene"):
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reference_blocks.build("place_in_scene", EVERYTHING, "a.png")
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placed = reference_blocks.build("place_in_scene", EVERYTHING, "a.png", scene="beach.png")["nodes"]
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self.assertEqual((placed["picture"]["inputs"]["image"], placed["place"]["inputs"]["image"]), ("a.png", "beach.png"))
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with self.assertRaisesRegex(reference_blocks.BlockError, "not installed here. Use block inpaint_basic"):
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reference_blocks.nodes_of("inpaint_crop_stitch", BUILT_IN, "a.png")
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with self.assertRaisesRegex(reference_blocks.BlockError, "there are: picture, inpaint_crop_stitch"):
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reference_blocks.nodes_of("nope", EVERYTHING)
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def test_detailing_takes_the_detector_models_this_comfyui_has(self):
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nodes = reference_blocks.nodes_of("detail_face_hands", EVERYTHING)
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self.assertEqual(nodes["face_finder"]["inputs"]["model_name"], "bbox/face_yolov8m.pt")
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self.assertEqual(nodes["hand_finder"]["inputs"]["model_name"], "bbox/hand_yolov8s.pt", "s before n")
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self.assertEqual(nodes["face"]["inputs"]["clip"], ["$sampler.positive.clip", "*"])
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no_faces = {**EVERYTHING, "UltralyticsDetectorProvider": {"input": {"required": {"model_name": [["bbox/hand_yolov8s.pt"]]}}}}
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with self.assertRaisesRegex(reference_blocks.BlockError, "No face detector model"):
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reference_blocks.nodes_of("detail_face_hands", no_faces)
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def test_fixing_hands_enlarges_the_picture_then_redraws_each_hand(self):
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self.assertEqual(reference_blocks.pick("detail", "hands", EVERYTHING), "fix_hands")
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self.assertEqual(reference_blocks.pick("detail", None, EVERYTHING), "detail_face_hands", "the plain use stays as it was")
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built = reference_blocks.build("fix_hands", EVERYTHING, "elves.png", lambda: "SDXL 1.0")
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nodes = built["nodes"]
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self.assertEqual((nodes["picture"]["inputs"]["image"], nodes["bigger"]["inputs"]["scale_by"], nodes["encode"]["wire_to"]),
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("elves.png", 1.5, "$sampler"), "the picture, enlarged, in the sampler's place of its latent")
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self.assertEqual(built["roles"], {"sampler": {"denoise": 0.4}})
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# The smaller the picture, the more it is enlarged: to about 4 megapixels, 1× to 2×.
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sized = lambda size: reference_blocks.build("fix_hands", EVERYTHING, "elves.png", lambda: "", size_of=lambda name: size)["nodes"]["bigger"]["inputs"]["scale_by"] # noqa: E731
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self.assertEqual([sized((1280, 832)), sized((832, 1216)), sized((1536, 1024)), sized((2048, 2048)), sized((640, 480))],
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[1.99, 2.0, 1.63, 1.0, 2.0])
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self.assertEqual((nodes["hand_finder"]["inputs"]["model_name"], nodes["hands"]["inputs"]["denoise"], nodes["hands"]["inputs"]["guide_size"]),
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("bbox/hand_yolov8s.pt", 0.45, 768))
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self.assertNotIn("turbo", nodes)
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self.assertIn("batch 4", built["after"])
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with self.assertRaisesRegex(reference_blocks.BlockError, "needs image"):
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reference_blocks.build("fix_hands", EVERYTHING)
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# On an Anima model the Turbo LoRA, when here, makes both passes 10 steps at CFG 1.
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loras = {"LoraLoaderModelOnly": {"input": {"required": {"lora_name": [["Tools\\anima-turbo-lora-v0.1.safetensors",
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"Tools\\anima-turbo-lora-v0.2.safetensors", "style.safetensors"]]}}}}
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anima = reference_blocks.build("fix_hands", {**EVERYTHING, **loras}, "elves.png", lambda: "Anima")
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turbo, hands = anima["nodes"]["turbo"], anima["nodes"]["hands"]
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self.assertEqual((turbo["inputs"]["lora_name"], turbo["wire_to"]), ("Tools\\anima-turbo-lora-v0.2.safetensors", "$sampler"), "the newest")
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self.assertEqual((hands["inputs"]["model"], hands["inputs"]["steps"], hands["inputs"]["cfg"]), (["turbo", 0], 10, 1.0))
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self.assertEqual(anima["roles"]["sampler"]["steps"], 10)
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without = reference_blocks.build("fix_hands", EVERYTHING, "elves.png", lambda: "Anima")
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self.assertNotIn("turbo", without["nodes"], "no Turbo LoRA here: the plain block, which works, only slower")
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self.assertIn("three times faster", without["after"])
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def test_with_sam3_here_the_hands_it_finds_by_word_are_redrawn_before_the_detectors(self):
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sam = {"SAM3_Detect": {}, "MaskToSEGS": {}, "DetailerForEach": {}, "CLIPTextEncode": {},
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"CheckpointLoaderSimple": {"input": {"required": {"ckpt_name": [["SDXL/nova.safetensors", "SAM3/sam3.1_multiplex_fp16.safetensors"]]}}}}
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nodes = reference_blocks.nodes_of("fix_hands", {**EVERYTHING, **sam}, "elves.png")
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self.assertEqual(nodes["hand_seeker"]["inputs"]["ckpt_name"], "SAM3/sam3.1_multiplex_fp16.safetensors")
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self.assertEqual((nodes["hand_words"]["inputs"]["text"], nodes["hand_shapes"]["inputs"]["image"]), ("hand:8", ["$decode", 0]), "up to 8 hands, not the first only")
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self.assertEqual(nodes["shaped_hands"]["inputs"]["segs"], ["hand_areas", 0])
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self.assertEqual(nodes["hands"]["inputs"]["image"], ["shaped_hands", 0], "the detector's pass mends what SAM3's left")
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self.assertNotIn("optional", nodes["shaped_hands"])
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no_model = {**sam, "CheckpointLoaderSimple": {"input": {"required": {"ckpt_name": [["SDXL/nova.safetensors"]]}}}}
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for here in ({**EVERYTHING, **no_model}, {**EVERYTHING, **{key: value for key, value in sam.items() if key != "SAM3_Detect"}}):
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plain = reference_blocks.nodes_of("fix_hands", here, "elves.png")
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self.assertFalse({"hand_seeker", "hand_words", "hand_shapes", "hand_areas", "shaped_hands"} & set(plain), "the pass goes whole")
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self.assertEqual(plain["hands"]["inputs"]["image"], ["$decode", 0])
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loras = {"LoraLoaderModelOnly": {"input": {"required": {"lora_name": [["anima-turbo-lora-v0.2.safetensors"]]}}}}
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anima = reference_blocks.nodes_of("fix_hands", {**EVERYTHING, **sam, **loras}, "elves.png", lambda: "Anima")
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self.assertEqual((anima["shaped_hands"]["inputs"]["model"], anima["shaped_hands"]["inputs"]["steps"]), (["turbo", 0], 10))
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def test_switching_mid_way_says_how_to_enlarge_at_the_switch(self):
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for family in ("SDXL 1.0", "Anima"):
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after = reference_blocks.build("switch_midway", EVERYTHING, None, lambda: family)["after"]
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self.assertIn("LatentUpscaleBy insert_after=first", after)
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self.assertIn('first {"return_with_leftover_noise": "disable"}, second {"add_noise": "enable"}', after,
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"enlarged with its leftover noise, the picture breaks into coloured blocks")
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def test_upscaling_takes_an_upscale_model_and_brings_it_to_a_quarter_larger(self):
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nodes = reference_blocks.nodes_of("upscale", EVERYTHING)
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self.assertEqual((nodes["upscaler"]["inputs"]["model_name"], nodes["fit"]["inputs"]["scale_by"]), ("2x-Lite.pth", 0.625), "a 2× one: enough for 1.25×, less work")
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self.assertEqual((nodes["redraw"]["like"], nodes["redraw"]["inputs"]["denoise"]), ("$sampler", 0.35))
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self.assertEqual(nodes["enlarge"]["inputs"]["image"], ["$save.images", "*"], "the saved picture, stitched or not")
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only_2x = {**EVERYTHING, "UpscaleModelLoader": {"input": {"required": {"model_name": [["2x-Lite.pth"]]}}}}
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self.assertEqual(reference_blocks.nodes_of("upscale", only_2x)["fit"]["inputs"]["scale_by"], 0.625)
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with self.assertRaisesRegex(reference_blocks.BlockError, "No upscale model"):
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reference_blocks.nodes_of("upscale_tiled", {**EVERYTHING, "UpscaleModelLoader": {}})
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self.assertIn("ComfyUI_UltimateSDUpscale: upscale 2x", reference_blocks.directory(BUILT_IN)["Not here yet, needs"])
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def test_the_tile_upscale_redraws_on_its_own_copy_of_the_model(self):
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info = {**EVERYTHING, "ColorMatch": {}}
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self.assertEqual(reference_blocks.pick("upscale", "detail", info), "upscale_tile")
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with self.assertRaisesRegex(reference_blocks.BlockError, "upscale takes want: detail, 2x, or none"):
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reference_blocks.pick("upscale", "steady", info)
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nodes = reference_blocks.build("upscale_tile", info, main_base=lambda: "Anima")["nodes"]
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self.assertEqual(nodes["own"], {"class_type": "UNETLoader", "copy_of": "$sampler.model", "_meta": {"title": "Upscale model"}, "inputs": {}},
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"the canvas's model line copied: the base's model and LoRAs, one swap for a second model")
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self.assertEqual((nodes["tile"]["inputs"]["model"], nodes["tile"]["inputs"]["lllite_name"]), (["own", 0], "animaTileRepair_v20.safetensors"))
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self.assertEqual((nodes["enlarge"]["inputs"]["scale_by"], nodes["redraw"]["inputs"]["denoise"]), (1.22, 0.85), "the tested route")
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self.assertEqual(nodes["match"]["inputs"]["image_ref"], ["$save.images", "*"])
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sdxl = reference_blocks.build("upscale_tile", info, main_base=lambda: "Illustrious")["nodes"]
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self.assertEqual((sdxl["own"]["class_type"], sdxl["redraw"]["inputs"]["model"]), ("CheckpointLoaderSimple", ["own", 0]))
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missing = {**info, "AnimaLLLiteApply_sdscripts": LLLITES | {"input": {"required": {"lllite_name": [["anima-lllite-depth-1.safetensors"]]}}}}
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with self.assertRaises(reference_blocks.MissingModel):
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reference_blocks.build("upscale_tile", missing, main_base=lambda: "Anima")
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def test_refining_only_the_character_or_the_background_pastes_the_rest_back(self):
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self.assertEqual(reference_blocks.directory(EVERYTHING)["refine"], "Redraw with another model (want: midway, character, background)")
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self.assertEqual(reference_blocks.pick("refine", None, EVERYTHING), "refine_other_model", "no want: the whole picture")
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for want, kept_by in (("character", "area_mask"), ("background", "background")):
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with self.subTest(want=want):
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name = reference_blocks.pick("refine", want, EVERYTHING)
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nodes = reference_blocks.build(name, EVERYTHING, main_base=lambda: "Anima")["nodes"]
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self.assertEqual(nodes["second_model"]["class_type"], "UNETLoader")
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self.assertEqual(nodes["cut"]["inputs"]["image"], ["$save.images", "*"], "the step's picture is cut out")
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self.assertEqual((nodes["area"]["inputs"]["mask"], nodes["paste"]["inputs"]["mask"]), ([kept_by, 0], [kept_by, 0]),
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"redrawn where the mask is, and only there pasted onto the picture")
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self.assertEqual((nodes["paste"]["inputs"]["destination"], nodes["save"]["inputs"]["images"]), (["$save.images", "*"], ["paste", 0]))
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self.assertEqual(nodes["redraw"]["inputs"]["denoise"], 0.45, "the tested strength")
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sdxl = reference_blocks.build(name, EVERYTHING, main_base=lambda: "Illustrious")["nodes"]
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self.assertEqual((sdxl["second_model"]["class_type"], sdxl["encode"]["inputs"]["vae"]), ("CheckpointLoaderSimple", ["second_model", 2]))
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character = reference_blocks.build("refine_character", EVERYTHING, main_base=lambda: "Anima")["nodes"]
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self.assertEqual(character["redraw"]["inputs"]["model"], ["soft", 0], "the mask's grey a weaker redraw: the edge fades")
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with self.assertRaisesRegex(reference_blocks.BlockError, "needs comfyui-inspyrenet-rembg"):
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reference_blocks.build("refine_background", BUILT_IN)
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def test_a_picture_from_words_is_built_by_the_model_family_on_the_model_picked(self):
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anima = {**EVERYTHING, "CLIPLoader": {"input": {"required": {"clip_name": [["clip_l.safetensors", "Anima/qwen_3_06b_base.safetensors"]]}}},
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"VAELoader": {"input": {"required": {"vae_name": [["sdxl_vae.safetensors", "Anima/qwenImageGGUF_vae.safetensors"]]}}}}
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self.assertEqual(reference_blocks.pick("picture", None, anima), "picture")
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with self.assertRaisesRegex(reference_blocks.BlockError, "needs the model to draw with"):
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reference_blocks.build("picture", anima, main_base=lambda: "Anima")
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nodes = reference_blocks.build("picture", anima, main_base=lambda: "Anima", model="Anima\harem.safetensors")["nodes"]
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self.assertEqual((nodes["model"]["class_type"], nodes["model"]["inputs"]["unet_name"]), ("UNETLoader", "Anima\harem.safetensors"))
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self.assertEqual((nodes["text_encoder"]["inputs"]["clip_name"], nodes["vae"]["inputs"]["vae_name"]),
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("Anima/qwen_3_06b_base.safetensors", "Anima/qwenImageGGUF_vae.safetensors"), "its own files beside it")
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self.assertEqual([nodes["sampler"]["inputs"][key] for key in ("steps", "cfg", "sampler_name", "scheduler")], [35, 4.4, "dpmpp_2m_sde_gpu", "beta"])
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no_encoder = {**anima, "CLIPLoader": {"input": {"required": {"clip_name": [["clip_l.safetensors"]]}}}}
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||
with self.assertRaisesRegex(reference_blocks.BlockError, "needs a CLIPLoader file named like qwen_3_06b"):
|
||
reference_blocks.build("picture", no_encoder, main_base=lambda: "Anima", model="Anima\harem.safetensors")
|
||
sdxl = reference_blocks.build("picture", anima, main_base=lambda: "Illustrious", model="SDXL/nova.safetensors")["nodes"]
|
||
self.assertEqual((sdxl["model"]["inputs"]["ckpt_name"], sdxl["decode"]["inputs"]["vae"]), ("SDXL/nova.safetensors", ["model", 2]))
|
||
self.assertNotIn("text_encoder", sdxl)
|
||
|
||
def test_a_node_only_making_a_block_better_goes_when_its_pack_is_missing(self):
|
||
nodes = reference_blocks.nodes_of("upscale", {**EVERYTHING, "ColorMatch": {}})
|
||
self.assertEqual((nodes["match"]["inputs"]["image_target"], nodes["save"]["inputs"]["images"]), (["decode", 0], ["match", 0]))
|
||
self.assertNotIn("optional", nodes["match"])
|
||
plain = reference_blocks.nodes_of("upscale", {key: value for key, value in EVERYTHING.items() if key != "ColorMatch"})
|
||
self.assertEqual(("match" in plain, plain["save"]["inputs"]["images"]), (False, ["decode", 0]))
|
||
shown = {item["name"]: item for item in reference_blocks.status(BUILT_IN)}
|
||
self.assertEqual(shown["upscale"]["better_with"], ["ComfyUI-KJNodes"])
|
||
|
||
def test_lanpaint_takes_the_samplers_place(self):
|
||
nodes = reference_blocks.nodes_of("inpaint_lanpaint", EVERYTHING, "a.png")
|
||
self.assertEqual((nodes["sampler"]["replaces"], nodes["decode"]["replaces"]), ("$sampler", "$decode"))
|
||
self.assertEqual(nodes["sampler"]["inputs"]["latent_image"], ["encode", 0])
|
||
with self.assertRaisesRegex(reference_blocks.BlockError, "LanPaint, not installed here. Use block inpaint_crop_stitch"):
|
||
reference_blocks.nodes_of("inpaint_lanpaint", BUILT_IN, "a.png")
|
||
|
||
def test_a_control_block_takes_a_controlnet_that_fits_the_canvas_model(self):
|
||
def control(name, main):
|
||
return reference_blocks.nodes_of(name, EVERYTHING, "ref.png", lambda: main, base)["controlnet"]["inputs"]["control_net_name"]
|
||
self.assertEqual(control("control_pose", "SDXL 1.0"), "SDXL/xinsir-openpose.safetensors", "its very base first")
|
||
self.assertEqual(control("control_pose", "NoobAI"), "NoobAI/noob-openpose.safetensors")
|
||
self.assertEqual(control("control_pose", "Illustrious"), "NoobAI/noob-openpose.safetensors", "of the SDXL family, in list order")
|
||
self.assertEqual(control("control_pose", "SD 1.5"), "SD_1.5/control_v11p_sd15_openpose.safetensors")
|
||
self.assertEqual(control("control_depth", "SDXL 1.0"), "SDXL/union-promax.safetensors", "no depth one: the union one follows depth too")
|
||
with self.assertRaisesRegex(reference_blocks.BlockError, "No depth ControlNet for SD 1.x models"):
|
||
control("control_depth", "SD 1.5")
|
||
self.assertEqual(control("control_pose", ""), "SD_1.5/control_v11p_sd15_openpose.safetensors", "model unknown: the first of the kind")
|
||
with self.assertRaisesRegex(reference_blocks.BlockError, "needs image: the picture to follow"):
|
||
reference_blocks.nodes_of("control_pose", EVERYTHING)
|
||
|
||
def test_on_an_anima_model_a_block_is_built_with_its_lllite(self):
|
||
depth = reference_blocks.build("control_depth", EVERYTHING, "ref.png", lambda: "Anima")
|
||
steer = depth["nodes"]["steer"]
|
||
self.assertEqual((steer["class_type"], steer["inputs"]["lllite_name"], steer["wire_to"]),
|
||
("AnimaLLLiteApply_sdscripts", "anima-lllite-depth-1.safetensors", "$sampler"))
|
||
self.assertEqual(set(depth["nodes"]), {"reference", "depth", "steer", "look"}, "no ControlNet loader; the map left to look at")
|
||
self.assertIn("Anima", depth["after"])
|
||
repaint = reference_blocks.build("inpaint_crop_stitch", EVERYTHING, "a.png", lambda: "Anima")["nodes"]
|
||
self.assertEqual((repaint["patch"]["inputs"]["lllite_name"], repaint["patch"]["inputs"]["model"], "wire_to" in repaint["soft"]),
|
||
("anima-lllite-inpainting-v2.safetensors", ["soft", 0], False), "the newest, after the soft mask")
|
||
self.assertEqual(reference_blocks.nodes_of("control_depth", EVERYTHING, "ref.png", lambda: "SDXL 1.0", base)["controlnet"]["inputs"]["control_net_name"],
|
||
"SDXL/union-promax.safetensors", "other models: the ControlNet")
|
||
without = {key: value for key, value in EVERYTHING.items() if key != "AnimaLLLiteApply_sdscripts"}
|
||
with self.assertRaisesRegex(reference_blocks.BlockError, "needs ComfyUI-Anima-LLLite"):
|
||
reference_blocks.build("control_pose", without, "ref.png", lambda: "Anima")
|
||
|
||
def test_a_union_controlnet_is_told_what_to_follow_and_new_files_go_by_their_folder(self):
|
||
info = {**EVERYTHING, "SetUnionControlNetType": {}, "ControlNetLoader": {"input": {"required": {"control_net_name": [[
|
||
"NoobAI/noob-sdxl-controlnet-tile.fp16.safetensors", "SDXL_1.0/xinsir-union-promax.safetensors", "animaTileRepair_v20.safetensors"]]}}}}
|
||
held = reference_blocks.nodes_of("upscale_tile", info, None, lambda: "NoobAI")
|
||
self.assertEqual(held["controlnet"]["inputs"]["control_net_name"], "NoobAI/noob-sdxl-controlnet-tile.fp16.safetensors",
|
||
"not scanned yet: its NoobAI folder says its base")
|
||
self.assertNotIn("union_type", held)
|
||
self.assertEqual((held["redraw"]["inputs"]["positive"], held["redraw"]["inputs"]["denoise"]), (["hold", 0], 0.5))
|
||
lines = reference_blocks.nodes_of("color_lineart", info, "lines.png", lambda: "Illustrious")
|
||
self.assertEqual(lines["controlnet"]["inputs"]["control_net_name"], "SDXL_1.0/xinsir-union-promax.safetensors")
|
||
self.assertEqual((lines["union_type"]["inputs"]["type"], lines["steer"]["inputs"]["control_net"]),
|
||
("canny/lineart/anime_lineart/mlsd", ["union_type", 0]), "the union model told it is lineart")
|
||
self.assertEqual(lines["lines"]["class_type"], "ImageInvert", "white lines on black, as the ControlNet reads them")
|
||
anima = reference_blocks.nodes_of("upscale_tile", {**info, "AnimaLLLiteApply_sdscripts": {"input": {"required": {"lllite_name": [[
|
||
"animaTileRepair_v20.safetensors", "anima-lllite-depth-1.safetensors"]]}}}}, None, lambda: "Anima")
|
||
self.assertEqual((anima["tile"]["inputs"]["lllite_name"], anima["redraw"]["inputs"]["model"]), ("animaTileRepair_v20.safetensors", ["tile", 0]))
|
||
|
||
def test_the_models_list_says_where_each_comes_from_and_how_to_check_it(self):
|
||
from api.download_sources import allowed_download_url
|
||
for key, model in reference_blocks.MODELS.items():
|
||
with self.subTest(model=key):
|
||
self.assertRegex(model["sha256"], r"^[0-9a-f]{64}$")
|
||
self.assertGreater(model["size"], 0)
|
||
self.assertTrue(model["license"] and model["file"] and model["folder"])
|
||
self.assertTrue(model["sources"] and all(allowed_download_url(source["url"]) for source in model["sources"]),
|
||
"Anomalous's downloader takes each link")
|
||
for name, block in reference_blocks.BLOCKS.items():
|
||
with self.subTest(block=name):
|
||
self.assertTrue(set(block.get("models") or []) <= set(reference_blocks.MODELS), "recommends only listed models")
|
||
|
||
def test_the_panel_and_the_ai_hear_how_a_block_was_tried(self):
|
||
with mock.patch.object(reference_blocks, "_installed", side_effect=lambda model: model["file"].startswith("2x")):
|
||
shown = {item["name"]: item for item in reference_blocks.status(EVERYTHING)}
|
||
upscale = shown["upscale"]
|
||
self.assertEqual([(item["id"], item["installed"]) for item in upscale["recommended"]][:2],
|
||
[("2x_animesharp_v4", True), ("4x_ultrasharp", False)])
|
||
self.assertEqual(upscale["tested"]["vram_gb"], 6)
|
||
words = reference_blocks.build("upscale_tile", EVERYTHING, None, lambda: "")["tested"]
|
||
self.assertIn("6 GB card", words)
|
||
self.assertIn("about 127 s for Anima", words)
|
||
self.assertEqual(reference_blocks.build("inpaint_basic", EVERYTHING, "a.png")["tested"], "", "not tried: nothing claimed")
|
||
|
||
def test_every_link_names_a_node_of_its_block_or_a_role(self):
|
||
for name, block in reference_blocks.BLOCKS.items():
|
||
for variant, key, spec in [(variant, *item) for variant in [block, *(block.get("variants") or {}).values()] for item in variant["nodes"].items()]:
|
||
for value in spec["inputs"].values():
|
||
if isinstance(value, list):
|
||
with self.subTest(block=name, node=key):
|
||
self.assertTrue(all(part in variant["nodes"] or part.split(".")[0] in ("$sampler", "$decode", "$save", "$loader")
|
||
for part in value[0].split("|")))
|
||
for field in ("wire_to", "like", "replaces"):
|
||
if field in spec:
|
||
self.assertIn(spec[field].split(".")[0], ("$sampler", "$decode", "$save", "$loader")) # like may follow a path
|
||
|
||
|
||
class AddBlockTests(unittest.TestCase):
|
||
def setUp(self):
|
||
keep_switches_apart(self)
|
||
for name, value in (("_page", {"nodes": {}, "reaches_output": True}), ("object_info", EVERYTHING)):
|
||
patcher = mock.patch.object(mcp_canvas_edit, name, return_value=value)
|
||
setattr(self, name.strip("_"), patcher.start())
|
||
self.addCleanup(patcher.stop)
|
||
|
||
def test_the_page_gets_the_block_spliced_in_with_replace(self):
|
||
answer = mcp_canvas_edit.add_nodes({}, block="inpaint_crop_stitch", image="a.png", near_node_id=5)
|
||
action, payload = self.page.call_args[0]
|
||
self.assertEqual((action, payload["replace"], payload["near_node_id"]), ("add_nodes", True, 5))
|
||
self.assertEqual(payload["roles"], {"sampler": {"denoise": 0.45}}, "the sampler's strength set with it")
|
||
self.assertEqual(payload["nodes"]["picture"]["inputs"]["image"], "a.png")
|
||
self.assertIn("set_prompt it to what belongs in the area", answer["next"], "what to do next with this block")
|
||
|
||
def test_a_control_block_asks_the_page_for_the_model_and_copies_the_picture_to_input(self):
|
||
answers = {"block_model": {"model": "noob.safetensors", "loras": []}, "add_nodes": {"nodes": {}, "reaches_output": True}}
|
||
self.page.side_effect = lambda action, payload=None, **_: answers[action]
|
||
with mock.patch.object(ai_pictures, "to_input", return_value="anomalous_reference_x.png") as to_input, \
|
||
mock.patch.object(mcp_canvas_edit, "_base_of", side_effect=base), \
|
||
mock.patch.object(mcp_canvas_edit.model_advice, "_main_base", return_value="Illustrious"):
|
||
mcp_canvas_edit.add_nodes({}, block="control_pose", image="ai_inbox/ref.png")
|
||
to_input.assert_called_once_with("ai_inbox/ref.png")
|
||
self.assertEqual([call[0][0] for call in self.page.call_args_list], ["block_model", "add_nodes"])
|
||
nodes = self.page.call_args[0][1]["nodes"]
|
||
self.assertEqual((nodes["reference"]["inputs"]["image"], nodes["controlnet"]["inputs"]["control_net_name"]),
|
||
("anomalous_reference_x.png", "NoobAI/noob-openpose.safetensors"), "Illustrious is of the SDXL family")
|
||
|
||
def test_a_model_missing_from_the_lists_is_looked_for_again_after_they_are_read_anew(self):
|
||
stale = {key: value for key, value in EVERYTHING.items() if key != "UpscaleModelLoader"}
|
||
self.object_info.side_effect = [stale, EVERYTHING]
|
||
with mock.patch.object(mcp_canvas_edit.model_download, "forget_file_lists") as forget:
|
||
mcp_canvas_edit.add_nodes({}, block="upscale")
|
||
forget.assert_called_once()
|
||
self.assertEqual(self.page.call_args[0][1]["nodes"]["upscaler"]["inputs"]["model_name"], "2x-Lite.pth")
|
||
self.object_info.side_effect = [stale, stale]
|
||
with mock.patch.object(mcp_canvas_edit.model_download, "forget_file_lists"), self.assertRaisesRegex(ToolError, "No upscale model"):
|
||
mcp_canvas_edit.add_nodes({}, block="upscale")
|
||
|
||
def test_nodes_or_block_not_both_and_errors_reach_the_ai(self):
|
||
for arguments in ({}, {"nodes": {"a": {"class_type": "LoadImage"}}, "block": "inpaint_basic"}):
|
||
with self.assertRaisesRegex(ToolError, "Give one of: use .* block .* or nodes"):
|
||
mcp_canvas_edit.add_nodes({}, **arguments)
|
||
self.object_info.return_value = BUILT_IN
|
||
with self.assertRaisesRegex(ToolError, "inpaint_basic instead"):
|
||
mcp_canvas_edit.add_nodes({}, block="inpaint_crop_stitch", image="a.png")
|
||
with self.assertRaisesRegex(ToolError, "follow takes want"):
|
||
mcp_canvas_edit.add_nodes({}, use="follow", image="a.png")
|
||
self.assertFalse(self.page.called)
|
||
|
||
def test_begin_task_hands_the_ai_the_directory(self):
|
||
with mock.patch.object(mcp_task_tools.ai_tasks, "begin_task", return_value={"id": "t", "title": "修手"}), \
|
||
mock.patch.object(mcp_task_tools.ai_tasks, "get_task", return_value={"id": "t", "steps": []}):
|
||
blocks = mcp_task_tools.begin_task({"client": "A"}, "修手")["blocks"]
|
||
self.assertIn("add_nodes(use=", blocks["note"])
|
||
self.assertIn("Repaint an area", blocks["repaint"])
|
||
self.object_info.side_effect = ToolError("down")
|
||
self.assertNotIn("needs", " ".join(mcp_task_tools._blocks({}).values()), "no node list: the plain directory")
|
||
|
||
|
||
class ReferencePictureTests(unittest.TestCase):
|
||
def test_a_handed_picture_is_copied_to_input_once_and_an_input_one_stays(self):
|
||
with tempfile.TemporaryDirectory() as output, tempfile.TemporaryDirectory() as input_dir:
|
||
os.makedirs(os.path.join(output, "ai_inbox"))
|
||
Image.new("RGBA", (8, 8), "red").save(os.path.join(output, "ai_inbox", "ref.png"))
|
||
Image.new("RGB", (8, 8), "blue").save(os.path.join(input_dir, "mine.png"))
|
||
folders = ai_pictures.ai_tasks.folder_paths
|
||
with mock.patch.object(folders, "get_output_directory", return_value=output), \
|
||
mock.patch.object(folders, "get_input_directory", return_value=input_dir):
|
||
name = ai_pictures.to_input("ai_inbox/ref.png")
|
||
self.assertEqual(ai_pictures.to_input("ai_inbox\\ref.png"), name, "the same picture, the same file")
|
||
self.assertEqual(ai_pictures.to_input("ai_inbox/ref.png [output]"), name, "as Load Image names an output picture")
|
||
self.assertEqual(ai_pictures.to_input("mine.png"), "mine.png")
|
||
with self.assertRaises(ToolError):
|
||
ai_pictures.to_input("ai_inbox/gone.png")
|
||
self.assertTrue(name.startswith("anomalous_reference_"))
|
||
self.assertEqual(sorted(os.listdir(input_dir)), sorted(["mine.png", name]))
|
||
with Image.open(os.path.join(input_dir, name)) as copied:
|
||
self.assertEqual(copied.mode, "RGBA", "its transparency is LoadImage's MASK")
|
||
|
||
|
||
if __name__ == "__main__":
|
||
unittest.main()
|