Artificial Sweetener
f863fcf645
Add VAE encode/decode option nodes across legacy and Comfy v3 exports, with tooltip and registration coverage. Preserve cloned model graph composition for differential diffusion in tiled and regional sampling paths.
287 lines
8.5 KiB
Python
287 lines
8.5 KiB
Python
# SimpleSyrup - workflow-focused ComfyUI extensions for image generation
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# Copyright (C) 2026 Artificial Sweetener and contributors
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# SPDX-License-Identifier: AGPL-3.0-or-later
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"""Tests for Comfy graph provenance tracing."""
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from __future__ import annotations
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from typing import Any
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from simple_syrup.domain.graph_provenance import BrokenProvenance, VaeDecodeProvenance
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from simple_syrup.runtime.comfy_graph_provenance import trace_vae_decode_provenance
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class TransparentNode:
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"""Fake node that declares exact value pass-through provenance."""
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GRAPH_PASSTHROUGH_OUTPUTS = {0: "value"}
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class NonTransparentNode:
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"""Fake node that intentionally has no pass-through contract."""
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class MalformedTransparentNode:
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"""Fake node with invalid pass-through metadata."""
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GRAPH_PASSTHROUGH_OUTPUTS = {0: 1}
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def test_direct_vae_decode_resolves_samples_and_vae_links() -> None:
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"""Direct VAEDecode image output resolves to the source latent and VAE."""
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prompt = {
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"decode": {
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"class_type": "VAEDecode",
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"inputs": {"samples": ["latent", 0], "vae": ["loader", 2]},
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}
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}
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result = trace_vae_decode_provenance(prompt, ["decode", 0], {})
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assert isinstance(result, VaeDecodeProvenance)
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assert result.decode_node_id == "decode"
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assert result.image_output == ("decode", 0)
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assert result.samples_link == ("latent", 0)
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assert result.vae_link == ("loader", 2)
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def test_vae_decode_options_resolves_samples_and_vae_links() -> None:
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"""VAE Decode (Options) output resolves to the source latent and VAE."""
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prompt = {
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"decode": {
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"class_type": "SimpleSyrup.VAEDecodeOptions",
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"inputs": {
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"use_tiling": True,
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"samples": ["latent", 0],
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"vae": ["loader", 2],
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"tile_size": 512,
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"overlap": 64,
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"temporal_size": 64,
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"temporal_overlap": 8,
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},
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}
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}
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result = trace_vae_decode_provenance(prompt, ["decode", 0], {})
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assert isinstance(result, VaeDecodeProvenance)
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assert result.decode_node_id == "decode"
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assert result.image_output == ("decode", 0)
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assert result.samples_link == ("latent", 0)
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assert result.vae_link == ("loader", 2)
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def test_transparent_node_resolves_to_upstream_vae_decode() -> None:
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"""A declared pass-through node is traversed to its source link."""
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prompt = {
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"marker": {
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"class_type": "TransparentNode",
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"inputs": {"value": ["decode", 0]},
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},
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"decode": {
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"class_type": "VAEDecode",
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"inputs": {"samples": ["latent", 0], "vae": ["loader", 2]},
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},
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}
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result = trace_vae_decode_provenance(
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prompt,
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["marker", 0],
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{"TransparentNode": TransparentNode},
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)
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assert isinstance(result, VaeDecodeProvenance)
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assert result.samples_link == ("latent", 0)
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def test_multiple_transparent_nodes_resolve_to_upstream_vae_decode() -> None:
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"""Transparent marker chains preserve decode provenance."""
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prompt = {
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"outer": {
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"class_type": "TransparentNode",
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"inputs": {"value": ["inner", 0]},
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},
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"inner": {
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"class_type": "TransparentNode",
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"inputs": {"value": ["decode", 0]},
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},
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"decode": {
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"class_type": "VAEDecode",
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"inputs": {"samples": ["latent", 0], "vae": ["loader", 2]},
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},
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}
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result = trace_vae_decode_provenance(
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prompt,
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["outer", 0],
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{"TransparentNode": TransparentNode},
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)
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assert isinstance(result, VaeDecodeProvenance)
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assert result.decode_node_id == "decode"
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def test_non_transparent_node_breaks_provenance() -> None:
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"""Nodes without an exact pass-through contract stop tracing."""
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result = trace_vae_decode_provenance(
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{
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"edited": {
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"class_type": "NonTransparentNode",
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"inputs": {"image": ["decode", 0]},
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}
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},
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["edited", 0],
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{"NonTransparentNode": NonTransparentNode},
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)
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assert isinstance(result, BrokenProvenance)
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assert result.reason == "source node does not declare exact pass-through provenance"
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assert result.node_id == "edited"
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assert result.class_type == "NonTransparentNode"
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def test_vae_decode_non_image_output_breaks_provenance() -> None:
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"""Only VAEDecode output slot 0 is trusted as decoded image provenance."""
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result = trace_vae_decode_provenance(
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{
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"decode": {
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"class_type": "VAEDecode",
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"inputs": {"samples": ["latent", 0], "vae": ["loader", 2]},
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}
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},
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["decode", 1],
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{},
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)
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assert isinstance(result, BrokenProvenance)
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assert result.reason == "VAEDecode output is not the image output"
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def test_vae_decode_options_non_image_output_breaks_provenance() -> None:
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"""Only VAE Decode (Options) output slot 0 is trusted as image provenance."""
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result = trace_vae_decode_provenance(
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{
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"decode": {
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"class_type": "SimpleSyrup.VAEDecodeOptions",
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"inputs": {"samples": ["latent", 0], "vae": ["loader", 2]},
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}
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},
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["decode", 1],
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{},
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)
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assert isinstance(result, BrokenProvenance)
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assert result.reason == "VAEDecode output is not the image output"
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assert result.class_type == "SimpleSyrup.VAEDecodeOptions"
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def test_missing_samples_link_breaks_provenance() -> None:
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"""VAEDecode without a graph-linked samples input cannot supply provenance."""
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result = trace_vae_decode_provenance(
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{"decode": {"class_type": "VAEDecode", "inputs": {"samples": "latent"}}},
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["decode", 0],
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{},
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)
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assert isinstance(result, BrokenProvenance)
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assert result.reason == "VAEDecode samples input is not a graph link"
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def test_vae_decode_options_missing_samples_link_breaks_provenance() -> None:
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"""VAE Decode (Options) requires a graph-linked samples input."""
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result = trace_vae_decode_provenance(
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{
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"decode": {
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"class_type": "SimpleSyrup.VAEDecodeOptions",
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"inputs": {"samples": "latent"},
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}
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},
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["decode", 0],
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{},
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)
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assert isinstance(result, BrokenProvenance)
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assert result.reason == "VAEDecode samples input is not a graph link"
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assert result.class_type == "SimpleSyrup.VAEDecodeOptions"
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def test_missing_node_breaks_provenance() -> None:
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"""Missing source nodes produce broken provenance."""
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result = trace_vae_decode_provenance({}, ["missing", 0], {})
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assert isinstance(result, BrokenProvenance)
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assert result.reason == "source node is missing"
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assert result.node_id == "missing"
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def test_malformed_passthrough_metadata_breaks_provenance() -> None:
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"""Invalid transparency metadata is treated as unsafe."""
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prompt: dict[str, dict[str, Any]] = {
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"marker": {
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"class_type": "MalformedTransparentNode",
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"inputs": {"value": ["decode", 0]},
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}
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}
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result = trace_vae_decode_provenance(
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prompt,
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["marker", 0],
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{"MalformedTransparentNode": MalformedTransparentNode},
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)
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assert isinstance(result, BrokenProvenance)
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assert result.reason == "pass-through metadata is malformed"
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def test_cycle_is_detected() -> None:
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"""Tracing stops when transparent nodes form a cycle."""
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prompt = {
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"a": {"class_type": "TransparentNode", "inputs": {"value": ["b", 0]}},
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"b": {"class_type": "TransparentNode", "inputs": {"value": ["a", 0]}},
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}
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result = trace_vae_decode_provenance(
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prompt,
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["a", 0],
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{"TransparentNode": TransparentNode},
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)
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assert isinstance(result, BrokenProvenance)
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assert result.reason == "provenance trace contains a cycle"
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def test_hop_limit_is_enforced() -> None:
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"""Tracing stops before walking unbounded transparent chains."""
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prompt = {
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"a": {"class_type": "TransparentNode", "inputs": {"value": ["b", 0]}},
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"b": {"class_type": "TransparentNode", "inputs": {"value": ["decode", 0]}},
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"decode": {
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"class_type": "VAEDecode",
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"inputs": {"samples": ["latent", 0], "vae": ["loader", 2]},
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},
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}
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result = trace_vae_decode_provenance(
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prompt,
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["a", 0],
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{"TransparentNode": TransparentNode},
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max_hops=1,
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)
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assert isinstance(result, BrokenProvenance)
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assert result.reason == "provenance trace exceeded the hop limit"
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