Files
ComfyUI-Lora-Manager/tests/services/test_download_routing.py
T
Will Miao 3aa32120df fix(downloads): route unknown checkpoint baseModels to diffusion models by default
CivitAI labels new DiT architectures (MiniMax H3, future Flux/Wan/Qwen
variants) as model.type "Checkpoint" with plain "Model" file entries,
so the DIFFUSION_MODEL_BASE_MODELS allowlist could never keep up and
such downloads were mis-routed to the checkpoint roots (e.g. model
2877206 / version 3374439). The set of true full-checkpoint families is
closed, so the baseModel fallback is inverted:

1. file type UNet/Diffusion Model -> unet (unchanged)
2. baseModel in DIFFUSION_MODEL_BASE_MODELS (now incl. MiniMax H3) -> unet
3. baseModel in new CHECKPOINT_BASE_MODELS (SD 1.x/2.x/3.x, SDXL, Pony,
   Illustrious, NoobAI) -> checkpoint
4. unknown/empty baseModel -> new unknown_base_model_routing setting,
   defaulting to diffusion models

The setting is exposed under Settings > Downloads, validated in
SettingsManager, and threaded into both the download manager and the
download routing endpoint so they keep agreeing.
2026-10-02 09:58:01 +08:00

187 lines
6.3 KiB
Python

"""Tests for the shared download routing decision."""
import pytest
from py.services.download_routing import is_diffusion_model_download
@pytest.mark.parametrize("file_type", ["UNet", "Diffusion Model"])
def test_file_type_signal_routes_to_unet(file_type):
assert is_diffusion_model_download(
"checkpoint", file_types=[file_type], base_model="SDXL 1.0"
)
def test_base_model_fallback_routes_to_unet():
"""The reported Anima case: file type is plain "Model", but the
baseModel is a known diffusion model."""
assert is_diffusion_model_download(
"checkpoint", file_types=["Model"], base_model="Anima"
)
def test_minimax_h3_routes_to_unet():
"""CivitAI model 2877206: type "Checkpoint", baseModel "MiniMax H3",
all file entries typed "Model"."""
assert is_diffusion_model_download(
"checkpoint", file_types=["Model"], base_model="MiniMax H3"
)
@pytest.mark.parametrize("base_model", ["SDXL 1.0", "Illustrious", "SD 1.5", "SD 3.5 Large"])
def test_known_checkpoint_base_models_stay_on_checkpoint_roots(base_model):
"""CHECKPOINT_BASE_MODELS members never route to unet, even when the
unknown-base-model default is diffusion."""
assert not is_diffusion_model_download(
"checkpoint", file_types=["Model"], base_model=base_model
)
def test_unknown_base_model_defaults_to_unet():
"""New DiT families appear faster than the allowlist can track them, so
unknown baseModels route to unet by default."""
assert is_diffusion_model_download(
"checkpoint", file_types=["Model"], base_model="Brand New Arch"
)
def test_unknown_base_model_honors_checkpoint_setting():
assert not is_diffusion_model_download(
"checkpoint",
file_types=["Model"],
base_model="Brand New Arch",
unknown_base_model_default="checkpoint",
)
def test_unknown_base_model_checkpoint_setting_still_loses_to_file_type():
"""The file-type signal stays first regardless of the setting."""
assert is_diffusion_model_download(
"checkpoint",
file_types=["Diffusion Model"],
base_model="SDXL 1.0",
unknown_base_model_default="checkpoint",
)
def test_non_checkpoint_types_never_route_to_unet():
assert not is_diffusion_model_download(
"lora", file_types=["UNet"], base_model="Anima"
)
assert not is_diffusion_model_download(
"embedding", file_types=["Diffusion Model"], base_model="Anima"
)
def test_empty_base_model_follows_unknown_default():
assert is_diffusion_model_download("checkpoint")
assert is_diffusion_model_download("checkpoint", file_types=[], base_model="")
assert not is_diffusion_model_download(
"checkpoint",
file_types=[],
base_model="",
unknown_base_model_default="checkpoint",
)
from py.services.download_routing import resolve_other_download_sub_type
class TestResolveOtherDownloadSubType:
"""Fixed priority: explicit file pick > model.type > file.type fallback."""
def test_explicit_file_pick_wins_over_model_type(self):
"""User explicitly picked a VAE component file of a Checkpoint model —
the picked file type wins."""
assert (
resolve_other_download_sub_type(
"Checkpoint", file_types=["Model", "VAE"], selected_file_type="VAE"
)
== "vae"
)
@pytest.mark.parametrize(
"selected,expected",
[
("VAE", "vae"),
("Upscaler", "upscaler"),
("Text Encoder", "text_encoder"),
("Vision Encoder", "clip_vision"),
("CLIPVision", "clip_vision"),
("ControlNet", "controlnet"),
],
)
def test_explicit_file_pick_maps_all_known_types(self, selected, expected):
assert (
resolve_other_download_sub_type("Other", selected_file_type=selected)
== expected
)
@pytest.mark.parametrize(
"model_type,expected",
[
("VAE", "vae"),
("Upscaler", "upscaler"),
("TextEncoder", "text_encoder"),
("CLIP", "text_encoder"),
("CLIPVision", "clip_vision"),
("Controlnet", "controlnet"),
],
)
def test_model_type_mapping(self, model_type, expected):
assert resolve_other_download_sub_type(model_type) == expected
def test_model_type_beats_unmappable_file_pick(self):
"""An explicit pick whose file type does not map (e.g. plain 'Model')
falls through to model.type."""
assert (
resolve_other_download_sub_type(
"TextEncoder", selected_file_type="Model"
)
== "text_encoder"
)
def test_bundled_component_files_never_override_model_type(self):
"""Anti-misrouting: a TextEncoder model bundling a VAE component file
must stay text_encoder — file types are a fallback, not an override."""
assert (
resolve_other_download_sub_type(
"TextEncoder", file_types=["Model", "VAE"]
)
== "text_encoder"
)
assert (
resolve_other_download_sub_type(
"Controlnet", file_types=["Model", "Text Encoder"]
)
== "controlnet"
)
def test_file_type_fallback_when_model_type_unmapped(self):
"""model.type 'Other' (or retired values) maps to nothing, so the
first mappable file type decides."""
assert (
resolve_other_download_sub_type("Other", file_types=["Model", "Upscaler"])
== "upscaler"
)
def test_file_type_fallback_for_civarchive_payload(self):
"""CivArchive-shaped payload: same fields, same decision path."""
assert (
resolve_other_download_sub_type(
"Other",
file_types=["Config", "Text Encoder"],
)
== "text_encoder"
)
@pytest.mark.parametrize("model_type", ["Other", "", "SomethingNew"])
def test_undecidable_returns_none(self, model_type):
assert (
resolve_other_download_sub_type(model_type, file_types=["Model"]) is None
)
assert resolve_other_download_sub_type(model_type) is None
def test_model_type_matching_is_case_insensitive(self):
assert resolve_other_download_sub_type("vAe") == "vae"