DemonGatanjieuandClaude Opus 5.5
2280e55fde
A run with Gemini 3.8 Flash asked for picture to picture and built it node by node, 13 failed calls on the way, with an official example ready:
- list_workflows was 23,630 characters on 17 cards, 21,033 of them settings. Antigravity files an answer over about 4,000 away, unread. A list of more than 3 now goes with name, route, tags and short notes.
- Examples showed only when no saved workflow matched, and only by English words: 图生图 found nothing. They are always named now, and found by their Chinese titles, img2img, txt2img and inpaint.
- Every card's route line was empty, and cards_of found nothing, since c84b596: _list_recipes leaves the graph out, and the tests fed cards that had one. Both ask for it now, with a test on a file on disk.
A waiting task the user wrote to also takes its name from what they wrote, instead of the AI's "take the task".
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
87 lines
4.8 KiB
Python
87 lines
4.8 KiB
Python
"""A saved workflow's route in one line for the AI (api/workflow_route.py), read from the serialized graph
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with stand-in widget names, and its place in list_workflows."""
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import json
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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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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 example_workflows, mcp_routes, mcp_tools, workflow_route # noqa: E402
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NAMES = {
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"UNETLoader": ["unet_name", "weight_dtype"],
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"LoraLoader": ["lora_name", "strength_model", "strength_clip"],
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"KSampler": ["seed", "control_after_generate", "steps", "cfg", "sampler_name", "scheduler", "denoise"],
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"KSamplerAdvanced": ["add_noise", "noise_seed", "control_after_generate", "steps", "cfg", "sampler_name", "scheduler",
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"start_at_step", "end_at_step", "return_with_leftover_noise"],
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"LatentUpscaleBy": ["upscale_method", "scale_by"],
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}
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def node(id_, type_, inputs=(), values=(), mode=0):
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return {"id": id_, "type": type_, "mode": mode, "inputs": [{"name": name, "link": link} for name, link in inputs],
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"widgets_values": list(values)}
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def two_passes(second="Anima\\miaomiaoRealskin_anima13.safetensors"):
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"""The two-pass card: a base, then enlarged and redrawn on a second model under a Tile LLLite, then a colour match."""
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nodes = [
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node(1, "UNETLoader", values=["Anima\\MiaoMiao Harem_Anima_1.5.safetensors", "default"]),
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node(16, "LoraLoader", [("model", 1)], ["style.safetensors", 1, 1]),
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node(30, "UNETLoader", values=[second, "default"]),
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node(2, "CLIPTextEncode", values=["a lake"]),
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node(6, "EmptyLatentImage", values=[832, 1216, 1]),
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node(32, "KSamplerAdvanced", [("model", 2), ("positive", 3), ("negative", 3), ("latent_image", 4)],
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["enable", 7, "fixed", 35, 4.4, "dpmpp_2m_sde_gpu", "beta", 0, 35, "disable"]),
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node(7, "VAEDecode", [("samples", 5)]),
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node(9, "SaveImage", [("images", 6)], ["base"]),
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node(10, "VAEEncode", [("pixels", 7)]),
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node(11, "LatentUpscaleBy", [("samples", 8)], ["bislerp", 1.22]),
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node(18, "AnimaLLLiteApply_sdscripts", [("model", 9), ("image", 10)], ["animaTileRepair_v20.safetensors", 0.7]),
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node(19, "KSampler", [("model", 11), ("positive", 3), ("negative", 3), ("latent_image", 12)],
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[3, "increment", 30, 4.4, "euler", "normal", 0.85]),
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node(20, "VAEDecode", [("samples", 13)]),
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node(21, "ColorMatch", [("image_ref", 14), ("image_target", 15)]),
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node(22, "SaveImage", [("images", 16)], ["upscaled"]),
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]
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links = [[1, 1, 0], [2, 16, 0], [3, 2, 0], [4, 6, 0], [5, 32, 0], [6, 7, 0], [7, 7, 0], [8, 10, 0], [9, 30, 0], [10, 7, 0],
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[11, 18, 0], [12, 11, 0], [13, 19, 0], [14, 7, 0], [15, 20, 0], [16, 21, 0]]
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return {"nodes": nodes, "links": [[link_id, origin, slot, 0, 0, "*"] for link_id, origin, slot in links]}
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class RouteTests(unittest.TestCase):
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def line(self, workflow):
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return workflow_route.line(workflow, lambda kind: NAMES.get(kind, []))
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def test_a_two_pass_card_says_its_passes_models_and_control(self):
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self.assertEqual(self.line(two_passes()),
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"2 passes: base steps 0-35 on MiaoMiao Harem_Anima_1.5 + LoRA style -> enlarge 1.22x, redraw 30 steps "
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"denoise 0.85 on miaomiaoRealskin_anima13 with animaTileRepair_v20 -> then ColorMatch")
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def test_a_bypassed_redraw_leaves_one_pass(self):
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workflow = two_passes()
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next(item for item in workflow["nodes"] if item["id"] == 19)["mode"] = 4
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self.assertTrue(self.line(workflow).startswith("1 pass: base steps 0-35 on MiaoMiao Harem_Anima_1.5"))
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def test_no_sampler_no_route_and_unknown_types_stay_unnamed(self):
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self.assertEqual(self.line({"nodes": [node(1, "UNETLoader", values=["a.safetensors"])], "links": []}), "")
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self.assertIn("on MiaoMiao Harem_Anima_1.5", workflow_route.line(two_passes(), lambda kind: []))
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def test_a_card_on_disk_keeps_its_route_where_the_ai_reads_it(self):
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with tempfile.TemporaryDirectory() as directory:
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Path(directory, "recipe_1.json").write_text(json.dumps({"name": "Two", "workflow": two_passes()}), encoding="utf-8")
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with mock.patch.object(mcp_tools, "get_recipes_dir", return_value=directory), mock.patch.object(mcp_tools, "plans", return_value={}), \
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mock.patch.object(mcp_routes, "get_recipes_dir", return_value=directory), mock.patch.object(example_workflows, "for_ai", return_value=[]):
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listed = mcp_tools.list_workflows()["workflows"][0]["route"]
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cards = list(mcp_routes._cards())
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self.assertTrue(listed.startswith("2 passes"), listed)
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self.assertEqual((cards[0][0], len(cards[0][1]), cards[0][2]), ("Two", 2, listed))
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if __name__ == "__main__":
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unittest.main()
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