Vito
1ff2ddce05
* fix(inspector): fall back to the positive's category and tags for recipe-linked images Maintainer ruling D39 (2026-10-21): a recipe-linked image shows the recipe's own category and tags when set, otherwise the linked positive prompt's, each field on its own and without merging tag sets. Set category (#259) and the Images category and Tags filters work on the positive, so the panel now agrees with them. The inspection library replaces metadata_scope with category_scope and tags_scope so the category chip's hidden scope prefix (D21) and the tag chips' filter-button rule (#260 D2) follow the value actually shown. History's media inspector uses the same shared rule. The concept fixture's positive_links workaround is gone: the comparison now matches the concept without it. * test(inspector): assert the D39 fallback tag chips in their saved order * fix(inspector): treat Unicode whitespace as a blank History recipe category * test(inspector): cover mixed-scope panels, invalid library scopes and the skipped positive tags query
1282 lines
53 KiB
Python
1282 lines
53 KiB
Python
"""Wire projections preserve exact bounded evidence independently of role parsing."""
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import io
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import json
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import struct
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import tempfile
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import unittest
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import zlib
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from pathlib import Path
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from unittest.mock import MagicMock, patch
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from PIL import Image
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from utils.inspection_response import encode_inspection_response
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from utils.prompt_inspector import (
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InspectionRead,
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MAX_METADATA_BYTES,
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MetadataReadError,
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inspect_prompt_roles,
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read_inspection_file,
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read_inspection_metadata,
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)
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from utils.pair_execution import EXECUTION_KEY
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try:
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from tests import inspection_parity as parity
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from tests.open_handles import assert_closed
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except ImportError: # pragma: no cover - discover -s tests puts tests/ first
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import inspection_parity as parity
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from open_handles import assert_closed
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CAP = 8 * 1024 * 1024
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IMAGE = {"root_index": 0, "path": "image.png", "filename": "image.png"}
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PROMPTS = {
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"positive": {"status": "resolved", "text": "portrait", "source": "graph-inferred"},
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"negative": {"status": "resolved", "text": "", "source": "graph-inferred"},
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}
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def inspection(metadata, *, formats=None, carrier=None):
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return InspectionRead(
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metadata=metadata,
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record_formats=(
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formats
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if formats is not None
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else {key: "original-text" for key in metadata}
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),
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video_carrier_text=carrier,
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format="PNG",
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width=4,
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height=4,
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)
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def encode(read, *, prompts=None, file=None, library=None):
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return encode_inspection_response(
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image=IMAGE,
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root_scope="a" * 64,
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file=file
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or {
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"observation": "current-file",
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"source_label": "output",
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"media_type": "image",
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"extension": ".png",
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"size": 100,
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"modified_time": 100,
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},
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prompts=PROMPTS if prompts is None else prompts,
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resolution={"state": "resolved", "sampler_id": "3", "reason": ""},
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inspection=read,
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library=library
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or {
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"status": "none",
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"scope": "saved-library",
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"positive_id": None,
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"pair_id": None,
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"title": None,
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"category": None,
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"tags": [],
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"category_scope": None,
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"tags_scope": None,
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},
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)
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def graph_text(count=3):
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graph = {
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"1": {"class_type": "CLIPTextEncode", "inputs": {"text": "portrait"}},
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"2": {"class_type": "CLIPTextEncode", "inputs": {"text": ""}},
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"3": {
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"class_type": "KSampler",
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"inputs": {
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"positive": ["1", 0],
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"negative": ["2", 0],
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"seed": 9007199254740993,
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"cfg": "EXACT_CFG",
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},
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},
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}
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for index in range(4, count + 1):
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graph[str(index)] = {
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"class_type": "Primitive",
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"inputs": {"value": 1, "labels": [True, False, "ordinary"]},
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}
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return json.dumps(graph).replace('"EXACT_CFG"', "6.5000000000000000001")
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class TestInspectionResponse(unittest.TestCase):
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def test_normalized_numbers_preserve_exact_literals(self):
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text = graph_text().replace(
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'"cfg": 6.5000000000000000001',
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'"cfg": 6.5000000000000000001, "huge": 1e1000000000',
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)
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result = json.loads(encode(inspection({"prompt": text})))
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inputs = result["metadata"]["prompt_graph"]["value"]["3"]["inputs"]
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self.assertEqual(inputs["seed"], "9007199254740993")
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self.assertEqual(inputs["cfg"], "6.5000000000000000001")
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self.assertEqual(inputs["huge"].lower(), "1e+1000000000")
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self.assertEqual(inputs["positive"], ["1", 0])
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self.assertEqual(result["metadata"]["raw"]["prompt"], text)
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self.assertEqual(result["prompts"], PROMPTS)
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def test_normalization_preserves_150_node_graph_with_more_than_500_json_values(
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self,
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):
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text = graph_text(150)
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self.assertGreater(len(text.split(":")), 500)
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for read in (
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inspection({"prompt": text}),
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inspection(
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{"prompt": json.dumps(json.loads(text))},
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formats={"prompt": "reserialized-json"},
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carrier='{"prompt":' + text + ',"unrelated":{"value":1}}',
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),
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):
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result = json.loads(encode(read))
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graph = result["metadata"]["prompt_graph"]
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self.assertEqual(graph["status"], "parsed")
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self.assertEqual(len(graph["value"]), 150)
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self.assertEqual(
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graph["value"]["3"]["inputs"]["cfg"], "6.5000000000000000001"
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)
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self.assertEqual(graph["value"]["3"]["inputs"]["seed"], "9007199254740993")
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self.assertEqual(graph["value"]["3"]["inputs"]["positive"], ["1", 0])
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self.assertIs(graph["value"]["4"]["inputs"]["labels"][0], True)
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self.assertEqual(result["metadata"]["raw"], read.metadata)
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self.assertEqual(result["prompts"], PROMPTS)
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def test_graph_ceiling_is_limited(self):
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# f27: the 20,000-node backstop, built at test time. Prompt nodes count
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# top-level API nodes; workflow nodes include subgraph definitions.
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for count, status in ((20_000, "parsed"), (20_001, "limited")):
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prompt = graph_text(count)
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half = count // 2
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workflow = json.dumps(
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{
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"nodes": [
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{"id": i, "type": "Primitive", "widgets_values": [1, True]}
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for i in range(count - half)
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],
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"definitions": {
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"subgraphs": [
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{"id": "sg", "nodes": [{"id": i} for i in range(half)]}
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]
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},
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}
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)
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for read in (
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inspection({"prompt": prompt, "workflow": workflow}),
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inspection(
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{"prompt": json.dumps(json.loads(prompt)), "workflow": workflow},
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formats={
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"prompt": "reserialized-json",
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"workflow": "reserialized-json",
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},
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carrier='{"other":[],"prompt":'
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+ prompt
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+ ',"workflow":'
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+ workflow
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+ "}",
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),
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):
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result = json.loads(encode(read))
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for key in ("prompt_graph", "workflow_graph"):
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with self.subTest(count=count, key=key):
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self.assertEqual(result["metadata"][key]["status"], status)
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if status == "limited":
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self.assertIsNone(result["metadata"][key]["value"])
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self.assertEqual(result["metadata"]["raw"], read.metadata)
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self.assertEqual(result["prompts"], PROMPTS)
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def test_prompt_graph_with_600_executable_nodes_is_parsed(self):
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graph = parity.build("f03")["prompt"]
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for index in range(100):
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graph[f"{700 + index}"] = {
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"class_type": "PrimitiveInt",
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"inputs": {"value": index},
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}
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self.assertGreater(len(graph), 600)
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text = json.dumps(graph)
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result = json.loads(encode(inspection({"prompt": text})))
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projected = result["metadata"]["prompt_graph"]
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self.assertEqual(projected["status"], "parsed")
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self.assertEqual(len(projected["value"]), len(graph))
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self.assertEqual(projected["value"]["3"]["inputs"]["seed"], 42)
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self.assertEqual(projected["value"]["3"]["inputs"]["cfg"], "6.5")
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self.assertEqual(result["metadata"]["raw"]["prompt"], text)
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def test_workflow_with_513_ui_nodes_is_parsed_and_downloadable(self):
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path = parity.fixture_path("f02")
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chunks = dict(parity.read_text_chunks(path))
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self.assertGreater(len(json.loads(chunks["workflow"])["nodes"]), 513)
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result = json.loads(encode(read_inspection_file(path)))
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metadata = result["metadata"]
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self.assertEqual(metadata["workflow_graph"]["status"], "parsed")
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self.assertEqual(
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metadata["workflow_graph"]["value"]["nodes"],
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json.loads(chunks["workflow"])["nodes"],
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)
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self.assertEqual(metadata["prompt_graph"]["status"], "parsed")
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# The download is the original record text, byte for byte.
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self.assertEqual(metadata["raw"]["workflow"], chunks["workflow"])
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self.assertEqual(metadata["record_formats"]["workflow"], "original-text")
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def test_nan_is_changed_and_meta_keep_prompt_graph_parsed(self):
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path = parity.fixture_path("f14")
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chunks = dict(parity.read_text_chunks(path))
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self.assertIn("NaN", chunks["prompt"])
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source = parity.build("f14")["prompt"]
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result = json.loads(encode(read_inspection_file(path)))
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metadata = result["metadata"]
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graph = metadata["prompt_graph"]
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self.assertEqual(graph["status"], "parsed")
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self.assertEqual(set(graph["value"]), set(source))
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for node_id, node in graph["value"].items():
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self.assertEqual(set(node), {"class_type", "inputs"})
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self.assertEqual(node["class_type"], source[node_id]["class_type"])
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inputs = graph["value"]["3"]["inputs"]
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expected = dict(source["3"]["inputs"], cfg="6.5", denoise="1.0")
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self.assertEqual(inputs, expected)
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self.assertEqual(graph["value"]["4"]["inputs"], source["4"]["inputs"])
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self.assertNotIn("_meta", json.dumps(graph))
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self.assertNotIn("is_changed", json.dumps(graph))
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# Raw records are never modified: the NaN stays in the download.
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self.assertEqual(metadata["raw"]["prompt"], chunks["prompt"])
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self.assertEqual(metadata["workflow_graph"]["status"], "parsed")
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def test_nonfinite_inside_inputs_projects_null(self):
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prompt = (
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'{"3":{"class_type":"KSampler","inputs":{"cfg":NaN,"seed":1,'
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'"denoise":-Infinity,"list":[Infinity,0.5]},"is_changed":[NaN],'
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'"_meta":{"title":"K","weight":Infinity}},"9":{"value":NaN}}'
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)
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workflow = (
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'{"nodes":[{"id":1,"widgets_values":[NaN,1.5,"x"],'
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'"extra":{"v":Infinity}}],"extra":{"ds":{"scale":-Infinity}}}'
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)
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for read in (
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inspection({"prompt": prompt, "workflow": workflow}),
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inspection(
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{"prompt": prompt, "workflow": workflow},
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formats={
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"prompt": "reserialized-json",
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"workflow": "reserialized-json",
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},
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carrier='{"prompt":'
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+ prompt
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+ ',"workflow":'
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+ json.dumps(workflow)
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+ ',"other":{"x":NaN}}',
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),
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):
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result = json.loads(encode(read))
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graph = result["metadata"]["prompt_graph"]
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self.assertEqual(graph["status"], "parsed")
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self.assertEqual(
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graph["value"],
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{
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"3": {
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"class_type": "KSampler",
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"inputs": {
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"cfg": None,
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"seed": 1,
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"denoise": None,
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"list": [None, "0.5"],
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},
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},
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"9": {},
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},
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)
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flow = result["metadata"]["workflow_graph"]
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self.assertEqual(flow["status"], "parsed")
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self.assertEqual(
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flow["value"],
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{
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"nodes": [
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{
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"id": 1,
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"widgets_values": [None, "1.5", "x"],
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"extra": {"v": None},
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}
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],
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"extra": {"ds": {"scale": None}},
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},
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)
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self.assertEqual(result["metadata"]["raw"], read.metadata)
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self.assertEqual(result["prompts"], PROMPTS)
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def test_prompt_projection_keeps_odd_node_shapes_and_rejects_non_objects(self):
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prompt = '{"1":[NaN,2],"2":"text","3":{"inputs":{"a":1}},"4":{"_meta":{}}}'
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expected = {"1": [None, 2], "2": "text", "3": {"inputs": {"a": 1}}, "4": {}}
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carrier_cases = (
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('{"prompt":' + prompt + "}", "parsed"),
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('{"prompt":[1],"workflow":{"nodes":[]}}', "malformed"),
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('{"prompt":' + json.dumps(prompt) + "}", "parsed"),
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("[]", "malformed"),
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)
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result = json.loads(encode(inspection({"prompt": prompt})))
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self.assertEqual(
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result["metadata"]["prompt_graph"], {"status": "parsed", "value": expected}
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)
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for carrier, status in carrier_cases:
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with self.subTest(carrier=carrier):
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result = json.loads(
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encode(
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inspection(
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{"prompt": prompt},
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formats={"prompt": "reserialized-json"},
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carrier=carrier,
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)
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)
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)
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graph = result["metadata"]["prompt_graph"]
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self.assertEqual(graph["status"], status)
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self.assertEqual(
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graph["value"], expected if status == "parsed" else None
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)
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def test_exact_numbers_survive_tolerance(self):
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prompt = (
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'{"3":{"class_type":"KSampler","inputs":{"seed":1152921504606846976,'
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'"steps":1e3,"cfg":0.1,"denoise":1e0,"exact":6.5000000000000000001,'
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'"negative_seed":-1152921504606846976,"safe":9007199254740991},'
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'"is_changed":[NaN]}}'
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)
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workflow = (
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'{"nodes":[{"id":1,"widgets_values":[1152921504606846976,1e3,0.1,NaN]}]}'
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)
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result = json.loads(
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encode(inspection({"prompt": prompt, "workflow": workflow}))
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)
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for key in ("prompt_graph", "workflow_graph"):
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self.assertEqual(result["metadata"][key]["status"], "parsed")
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inputs = result["metadata"]["prompt_graph"]["value"]["3"]["inputs"]
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self.assertEqual(
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inputs,
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{
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"seed": str(2**60),
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"steps": "1E+3",
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"cfg": "0.1",
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"denoise": "1",
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"exact": "6.5000000000000000001",
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"negative_seed": str(-(2**60)),
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"safe": 9007199254740991,
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},
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)
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self.assertEqual(inputs["seed"], "1152921504606846976")
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widgets = result["metadata"]["workflow_graph"]["value"]["nodes"][0]
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self.assertEqual(
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widgets["widgets_values"], ["1152921504606846976", "1E+3", "0.1", None]
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)
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def test_duplicate_json_keys_still_malformed(self):
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for prompt, workflow in (
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('{"1":{},"1":{}}', '{"nodes":[],"nodes":[]}'),
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(
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'{"1":{"class_type":"A","inputs":{},"_meta":{"t":1,"t":2}}}',
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'{"nodes":[{"id":1,"extra":{"a":NaN,"a":NaN}}]}',
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),
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(
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'{"1":{"class_type":"A","inputs":{"x":NaN,"x":1}}}',
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'{"nodes":[{"id":1,"id":2}]}',
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),
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):
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with self.subTest(prompt=prompt):
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result = json.loads(
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encode(inspection({"prompt": prompt, "workflow": workflow}))
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)
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for key in ("prompt_graph", "workflow_graph"):
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self.assertEqual(
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result["metadata"][key], {"status": "malformed", "value": None}
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)
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self.assertEqual(
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result["metadata"]["raw"], {"prompt": prompt, "workflow": workflow}
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)
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valid = '{"1":{"class_type":"A","inputs":{}}}'
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for carrier in (
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'{"prompt":' + valid + ',"prompt":' + valid + "}",
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'{"prompt":' + valid + ',"other":{"a":1,"a":2}}',
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):
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with self.subTest(carrier=carrier):
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result = json.loads(
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encode(
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inspection(
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{"prompt": valid},
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formats={"prompt": "reserialized-json"},
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carrier=carrier,
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)
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)
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)
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self.assertEqual(
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result["metadata"]["prompt_graph"],
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{"status": "malformed", "value": None},
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)
|
|
|
|
def test_strict_projection_depth_is_separate_from_semantic_link_depth(self):
|
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for depth in (64, 65):
|
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# API map root + node + inputs + nested array containers.
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text = (
|
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'{"1":{"class_type":"Primitive","inputs":{"value":'
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+ "[" * (depth - 3)
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+ "0"
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+ "]" * (depth - 3)
|
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+ "}}}"
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)
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result = json.loads(encode(inspection({"prompt": text})))
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|
self.assertEqual(
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result["metadata"]["prompt_graph"]["status"],
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|
"parsed" if depth == 64 else "limited",
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|
)
|
|
carrier = '{"prompt":' + text + "}"
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|
result = json.loads(
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|
encode(
|
|
inspection(
|
|
{"prompt": text},
|
|
formats={"prompt": "reserialized-json"},
|
|
carrier=carrier,
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)
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)
|
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)
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self.assertEqual(result["metadata"]["prompt_graph"]["status"], "limited")
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text = '{"1":{"inputs":{"value":' + "[" * 60 + "0" + "]" * 60 + "}}}"
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result = json.loads(
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encode(
|
|
inspection(
|
|
{"prompt": text},
|
|
formats={"prompt": "reserialized-json"},
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|
carrier='{"prompt":' + text + "}",
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|
)
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)
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)
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self.assertEqual(result["metadata"]["prompt_graph"]["status"], "parsed")
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|
chain = {
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str(i): {
|
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"class_type": "Reroute",
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"inputs": {"value": [str((i + 1) % 150), 0]},
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}
|
|
for i in range(150)
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}
|
|
result = json.loads(encode(inspection({"prompt": json.dumps(chain)})))
|
|
self.assertEqual(result["metadata"]["prompt_graph"]["status"], "parsed")
|
|
self.assertEqual(len(result["metadata"]["prompt_graph"]["value"]), 150)
|
|
|
|
def test_wide_bounded_values_do_not_consume_semantic_visit_budget(self):
|
|
text = json.dumps(
|
|
{
|
|
"1": {
|
|
"inputs": {
|
|
"values": list(range(20000)),
|
|
"fields": {str(i): True for i in range(1000)},
|
|
}
|
|
}
|
|
}
|
|
)
|
|
self.assertLess(len(text.encode()), MAX_METADATA_BYTES)
|
|
body = encode(inspection({"prompt": text}))
|
|
graph = json.loads(body)["metadata"]["prompt_graph"]
|
|
self.assertEqual(graph["status"], "parsed")
|
|
self.assertEqual(len(graph["value"]["1"]["inputs"]["values"]), 20000)
|
|
self.assertEqual(len(graph["value"]["1"]["inputs"]["fields"]), 1000)
|
|
self.assertLess(len(body), CAP)
|
|
|
|
def test_strict_malformed_records_preserve_original_raw_and_roles(self):
|
|
for text in (
|
|
'{"1":{},"1":{}}',
|
|
"{broken",
|
|
"[]",
|
|
"42",
|
|
"[" * 2000,
|
|
):
|
|
result = json.loads(encode(inspection({"prompt": text, "workflow": text})))
|
|
self.assertIn(
|
|
result["metadata"]["prompt_graph"]["status"], ("malformed", "limited")
|
|
)
|
|
self.assertIsNone(result["metadata"]["prompt_graph"]["value"])
|
|
self.assertEqual(
|
|
result["metadata"]["raw"], {"prompt": text, "workflow": text}
|
|
)
|
|
self.assertEqual(result["prompts"], PROMPTS)
|
|
|
|
def test_video_missing_exact_source_is_limited_not_rounded(self):
|
|
rounded = json.dumps(json.loads(graph_text()))
|
|
result = json.loads(
|
|
encode(
|
|
inspection({"prompt": rounded}, formats={"prompt": "reserialized-json"})
|
|
)
|
|
)
|
|
self.assertEqual(
|
|
result["metadata"]["prompt_graph"], {"status": "limited", "value": None}
|
|
)
|
|
self.assertEqual(result["metadata"]["raw"]["prompt"], rounded)
|
|
self.assertEqual(result["prompts"], PROMPTS)
|
|
|
|
def test_response_escaping_omits_graphs_then_entire_raw_atomically(self):
|
|
prompts = {
|
|
role: {
|
|
"status": "resolved",
|
|
"text": "\x01" * 100000,
|
|
"source": "graph-inferred",
|
|
}
|
|
for role in ("positive", "negative")
|
|
}
|
|
source = json.loads(graph_text())
|
|
source["1"]["inputs"]["text"] = prompts["positive"]["text"]
|
|
source["2"]["inputs"]["text"] = prompts["negative"]["text"]
|
|
raw = json.dumps(source)
|
|
for count, raw_retained in ((450000, True), (550000, False)):
|
|
metadata = {"prompt": raw, "parameters": "\x01" * count}
|
|
self.assertLess(
|
|
sum(len(value.encode()) for value in metadata.values()),
|
|
MAX_METADATA_BYTES,
|
|
)
|
|
body = encode(inspection(metadata), prompts=prompts)
|
|
result = json.loads(body)
|
|
self.assertLessEqual(len(body), CAP)
|
|
self.assertEqual(result["image"], IMAGE)
|
|
self.assertEqual(result["prompts"], prompts)
|
|
self.assertEqual(
|
|
result["metadata"]["prompt_graph"], {"status": "limited", "value": None}
|
|
)
|
|
self.assertEqual(
|
|
result["metadata"]["workflow_graph"],
|
|
{"status": "absent", "value": None},
|
|
)
|
|
self.assertEqual(
|
|
result["metadata"]["record_formats"],
|
|
{key: "original-text" for key in metadata},
|
|
)
|
|
if raw_retained:
|
|
self.assertEqual(result["metadata"]["status"], "available")
|
|
self.assertIsNone(result["metadata"]["omitted_reason"])
|
|
self.assertEqual(result["metadata"]["raw"], metadata)
|
|
self.assertEqual(
|
|
result["metadata"]["parameters"], metadata["parameters"]
|
|
)
|
|
else:
|
|
self.assertEqual(result["metadata"]["raw"], {})
|
|
self.assertIsNone(result["metadata"]["parameters"])
|
|
self.assertEqual(result["metadata"]["status"], "limited")
|
|
self.assertEqual(
|
|
result["metadata"]["omitted_reason"], "response-size-limit"
|
|
)
|
|
|
|
def test_response_budget_drops_workflow_graph_before_prompt_graph(self):
|
|
import utils.inspection_response as response
|
|
|
|
with tempfile.TemporaryDirectory() as directory:
|
|
path = parity.fixture_path("f05", directory)
|
|
parity.write_png(path, parity.build("f05"))
|
|
read = read_inspection_file(path)
|
|
|
|
def metadata_at(cap, read):
|
|
with patch.object(response, "MAX_RESPONSE_BYTES", cap):
|
|
body = encode(read)
|
|
self.assertLessEqual(len(body), cap)
|
|
return json.loads(body)["metadata"]
|
|
|
|
# Step 1: the workflow graph alone is dropped; prompt evidence stays.
|
|
step1 = metadata_at(4_500_000, read)
|
|
self.assertEqual(step1["workflow_graph"], {"status": "limited", "value": None})
|
|
self.assertEqual(step1["prompt_graph"]["status"], "parsed")
|
|
self.assertEqual(step1["status"], "available")
|
|
self.assertIn("workflow", step1["raw"])
|
|
|
|
# Step 2: a large prompt graph goes too, while raw records stay.
|
|
large = inspection({"prompt": graph_text(20000)})
|
|
step2 = metadata_at(3_000_000, large)
|
|
self.assertEqual(step2["prompt_graph"], {"status": "limited", "value": None})
|
|
self.assertEqual(step2["workflow_graph"]["status"], "absent")
|
|
self.assertEqual(step2["status"], "available")
|
|
self.assertIn("prompt", step2["raw"])
|
|
|
|
# Step 3: raw is omitted atomically.
|
|
step3 = metadata_at(3_000_000, read)
|
|
self.assertEqual(step3["prompt_graph"]["status"], "limited")
|
|
self.assertEqual(step3["workflow_graph"]["status"], "limited")
|
|
self.assertEqual(step3["raw"], {})
|
|
self.assertEqual(step3["omitted_reason"], "response-size-limit")
|
|
|
|
def test_response_byte_boundary_is_inclusive(self):
|
|
prompts = {
|
|
role: {
|
|
"status": "resolved",
|
|
"text": "\x01" * 100000,
|
|
"source": "graph-inferred",
|
|
}
|
|
for role in ("positive", "negative")
|
|
}
|
|
text = graph_text().replace(
|
|
'"cfg": 6.5000000000000000001', '"cfg":6.5000000000000000001,"label":"猫😀"'
|
|
)
|
|
read = inspection({"prompt": text, "parameters": "\x01" * 500000})
|
|
base_file = {
|
|
"observation": "current-file",
|
|
"source_label": "output",
|
|
"media_type": "image",
|
|
"extension": ".png",
|
|
}
|
|
initial_size = len(encode(read, prompts=prompts, file=base_file))
|
|
self.assertLess(initial_size, CAP)
|
|
for target in (CAP - 1, CAP, CAP + 1):
|
|
extra = target - initial_size
|
|
file = {**base_file, "source_label": "output" + ("x" if extra % 2 else "")}
|
|
parameters = read.metadata["parameters"] + "x" * (extra // 2)
|
|
current = inspection({"prompt": text, "parameters": parameters})
|
|
self.assertLess(
|
|
sum(len(value.encode()) for value in current.metadata.values()),
|
|
MAX_METADATA_BYTES,
|
|
)
|
|
body = encode(current, prompts=prompts, file=file)
|
|
result = json.loads(body)
|
|
if target <= CAP:
|
|
self.assertEqual(len(body), target)
|
|
self.assertEqual(result["metadata"]["prompt_graph"]["status"], "parsed")
|
|
else:
|
|
self.assertLessEqual(len(body), CAP)
|
|
self.assertEqual(
|
|
result["metadata"]["prompt_graph"]["status"], "limited"
|
|
)
|
|
self.assertEqual(result["prompts"], prompts)
|
|
self.assertEqual(result["image"], IMAGE)
|
|
self.assertEqual(result["metadata"]["raw"], current.metadata)
|
|
|
|
def test_optional_display_fields_are_validated_and_library_is_bounded(self):
|
|
file = {
|
|
"size": -1,
|
|
"width": True,
|
|
"height": float("inf"),
|
|
"modified_time": float("nan"),
|
|
"format": 12,
|
|
"observation": "current-file",
|
|
}
|
|
library = {
|
|
"status": "linked",
|
|
"positive_id": 2**53,
|
|
"pair_id": True,
|
|
"tags": ["valid", 3],
|
|
"category": {},
|
|
"title": [],
|
|
}
|
|
result = json.loads(encode(None, file=file, library=library))
|
|
for key in ("size", "width", "height", "modified_time", "format"):
|
|
self.assertNotIn(key, result["file"])
|
|
for key in ("positive_id", "pair_id", "category", "title"):
|
|
self.assertNotIn(key, result["library"])
|
|
self.assertEqual(result["library"]["tags"], ["valid"])
|
|
# An unknown or non-string scope is dropped, never passed through.
|
|
for bad in ("recipe", 3, ["pair"]):
|
|
result = json.loads(
|
|
encode(
|
|
None,
|
|
library={
|
|
"status": "linked",
|
|
"category_scope": bad,
|
|
"tags_scope": bad,
|
|
"tags": [],
|
|
},
|
|
)
|
|
)
|
|
self.assertNotIn("category_scope", result["library"])
|
|
self.assertNotIn("tags_scope", result["library"])
|
|
result = json.loads(
|
|
encode(inspection({}), library={"status": "linked", "tags": ["猫" * 12000]})
|
|
)
|
|
self.assertEqual(result["library"]["status"], "limited")
|
|
self.assertEqual(result["library"]["tags"], [])
|
|
self.assertLess(
|
|
len(json.dumps(result["library"], ensure_ascii=False).encode()), 32 * 1024
|
|
)
|
|
|
|
def test_absent_unreadable_invalid_workflow_and_formats_remain_distinct(self):
|
|
for read, status in (
|
|
(None, "unreadable"),
|
|
(inspection({}), "absent"),
|
|
(inspection({}, formats={"workflow": "invalid"}), "available"),
|
|
):
|
|
result = json.loads(encode(read))
|
|
self.assertEqual(result["metadata"]["status"], status)
|
|
self.assertEqual(result["metadata"]["raw"], {})
|
|
self.assertIsNone(result["metadata"]["parameters"])
|
|
self.assertEqual(result["metadata"]["workflow_graph"]["status"], "malformed")
|
|
|
|
def test_video_null_role_marker_raises_before_successful_read(self):
|
|
with tempfile.TemporaryDirectory() as directory:
|
|
path = Path(directory) / "clip.mp4"
|
|
path.write_bytes(b"fixture")
|
|
for field in ("prompt", "parameters", EXECUTION_KEY):
|
|
for reader in (read_inspection_file, read_inspection_metadata):
|
|
process = MagicMock()
|
|
process.stdout = io.BytesIO(
|
|
json.dumps(
|
|
{"format": {"tags": {"comment": json.dumps({field: None})}}}
|
|
).encode()
|
|
)
|
|
process.poll.return_value = 0
|
|
process.returncode = 0
|
|
with (
|
|
patch(
|
|
"utils.prompt_inspector.ffprobe_path",
|
|
return_value="/tool/ffprobe",
|
|
),
|
|
patch(
|
|
"utils.prompt_inspector.subprocess.Popen",
|
|
return_value=process,
|
|
),
|
|
):
|
|
with self.assertRaises(MetadataReadError):
|
|
reader(path)
|
|
self.assertTrue(process.stdout.closed)
|
|
|
|
def test_original_role_projection_ignores_workflow_without_losing_saved_warning(
|
|
self,
|
|
):
|
|
self.assertEqual(
|
|
inspect_prompt_roles({"workflow": "{}"}, {"prompt_id": 1})["positive"][
|
|
"source"
|
|
],
|
|
"saved-association",
|
|
)
|
|
|
|
def test_unrepresentable_decimal_exponent_preserves_roles_and_raw(self):
|
|
text = graph_text().replace(
|
|
"6.5000000000000000001", "1e1000000000000000000000000"
|
|
)
|
|
for read in (
|
|
inspection({"prompt": text}),
|
|
inspection(
|
|
{"prompt": json.dumps(json.loads(text))},
|
|
formats={"prompt": "reserialized-json"},
|
|
carrier='{"prompt":' + text + "}",
|
|
),
|
|
):
|
|
result = json.loads(encode(read))
|
|
self.assertEqual(
|
|
result["metadata"]["prompt_graph"],
|
|
{"status": "malformed", "value": None},
|
|
)
|
|
self.assertEqual(result["metadata"]["raw"], read.metadata)
|
|
self.assertEqual(result["prompts"], PROMPTS)
|
|
|
|
def test_history_identity_shares_rooted_evidence_and_library_projection(self):
|
|
from utils.inspection_response import encode_history_inspection_response
|
|
|
|
read = inspection({"prompt": graph_text()})
|
|
identity = {
|
|
"occurrence": {
|
|
"run_id": "run",
|
|
"output_node_id": "node",
|
|
"image_ordinal": 2,
|
|
},
|
|
"reference": {"filename": "image.png"},
|
|
"history_epoch": "epoch",
|
|
"current_scope": "scope",
|
|
"location_key": "location",
|
|
"file_identity": "unverified",
|
|
}
|
|
body = json.loads(
|
|
encode_history_inspection_response(
|
|
current_output=identity,
|
|
file={"size": 7, "observation": "current-file"},
|
|
prompts=PROMPTS,
|
|
resolution={"state": "resolved"},
|
|
inspection=read,
|
|
library={"status": "linked", "tags": ["猫" * 12000]},
|
|
)
|
|
)
|
|
rooted = json.loads(
|
|
encode(
|
|
read,
|
|
file={"size": 7, "observation": "current-file"},
|
|
library={"status": "linked", "tags": ["猫" * 12000]},
|
|
)
|
|
)
|
|
self.assertEqual(body["current_output"], identity)
|
|
self.assertEqual(body.get("history_version"), 1)
|
|
self.assertEqual(body.get("history_epoch"), "epoch")
|
|
for key in ("file", "prompts", "metadata", "library"):
|
|
self.assertEqual(body[key], rooted[key])
|
|
self.assertEqual(body["library"]["status"], "limited")
|
|
self.assertNotIn("image", body)
|
|
self.assertNotIn("root_scope", body)
|
|
|
|
|
|
MIB = 1024 * 1024
|
|
|
|
|
|
def _text_chunk(kind, keyword, body):
|
|
return parity._raw_chunk(kind, keyword.encode("latin-1") + b"\0" + body)
|
|
|
|
|
|
def _png_with_chunks(path, chunks):
|
|
"""A tiny real PNG with raw metadata chunks spliced before IEND, then closed."""
|
|
buffer = io.BytesIO()
|
|
with Image.new("RGB", (4, 4), (40, 80, 120)) as image:
|
|
image.save(buffer, format="PNG")
|
|
data = buffer.getvalue()
|
|
iend = data.rindex(b"IEND") - 4
|
|
with open(path, "wb") as stream:
|
|
stream.write(data[:iend])
|
|
for chunk in chunks:
|
|
stream.write(chunk)
|
|
stream.write(data[iend:])
|
|
return path
|
|
|
|
|
|
class TestPerRecordBudgets(unittest.TestCase):
|
|
"""Role records keep the 2 MiB budget; a workflow has its own 4 MiB budget."""
|
|
|
|
def setUp(self):
|
|
temporary = tempfile.TemporaryDirectory()
|
|
self.addCleanup(temporary.cleanup)
|
|
self.addCleanup(assert_closed, self, temporary.name)
|
|
self.directory = Path(temporary.name)
|
|
|
|
def prompt_chunk(self):
|
|
prompt = json.dumps(parity.build("f04")["prompt"]).encode("latin-1")
|
|
return _text_chunk(b"tEXt", "prompt", prompt)
|
|
|
|
def assert_prompts_resolved(self, read):
|
|
from utils.prompt_inspector import inspect_prompt_evidence
|
|
from utils.prompt_pair_resolver import INSPECTION_PROFILE
|
|
|
|
evidence = inspect_prompt_evidence(read.metadata, profile=INSPECTION_PROFILE)
|
|
self.assertEqual(evidence["resolution"]["state"], "resolved")
|
|
self.assertEqual(evidence["prompts"]["positive"]["text"], parity.POS)
|
|
self.assertEqual(evidence["prompts"]["negative"]["text"], parity.NEG)
|
|
|
|
def test_budget_constants(self):
|
|
from utils import prompt_inspector
|
|
|
|
self.assertEqual(prompt_inspector.ROLE_METADATA_BYTES, 2 * MIB)
|
|
self.assertEqual(prompt_inspector.WORKFLOW_METADATA_BYTES, 4 * MIB)
|
|
self.assertEqual(prompt_inspector.MAX_KEYWORD_BYTES, 80)
|
|
self.assertEqual(MAX_METADATA_BYTES, prompt_inspector.ROLE_METADATA_BYTES)
|
|
default = inspection({"prompt": "{}"})
|
|
self.assertEqual(default.limited_records, frozenset())
|
|
|
|
def test_f04_large_workflow_within_budget_no_longer_hides_prompts(self):
|
|
# f04's 2.5 MB workflow is over the old shared 2 MiB budget but within
|
|
# the 4 MiB workflow budget: everything is readable now.
|
|
path = self.directory / "f04.png"
|
|
parity.write_png(path, parity.build("f04"))
|
|
read = read_inspection_file(path)
|
|
self.assert_prompts_resolved(read)
|
|
metadata = json.loads(encode(read))["metadata"]
|
|
self.assertEqual(metadata["status"], "available")
|
|
self.assertEqual(metadata["record_formats"]["workflow"], "original-text")
|
|
self.assertEqual(metadata["workflow_graph"]["status"], "parsed")
|
|
self.assertEqual(metadata["prompt_graph"]["status"], "parsed")
|
|
|
|
def test_oversize_workflow_chunk_keeps_prompt_evidence(self):
|
|
from utils.prompt_inspector import WORKFLOW_METADATA_BYTES
|
|
|
|
built = parity.build("f04") # f04's shape, its note grown past budget
|
|
built["workflow"]["nodes"][-1]["widgets_values"] = [
|
|
"A" * (WORKFLOW_METADATA_BYTES + 1)
|
|
]
|
|
path = self.directory / "f04-oversize.png"
|
|
parity.write_png(path, built)
|
|
read = read_inspection_file(path)
|
|
self.assertNotIn("workflow", read.metadata)
|
|
self.assertEqual(read.limited_records, frozenset({"workflow"}))
|
|
self.assert_prompts_resolved(read)
|
|
metadata = json.loads(encode(read))["metadata"]
|
|
self.assertEqual(metadata["status"], "available")
|
|
self.assertEqual(
|
|
metadata["workflow_graph"], {"status": "limited", "value": None}
|
|
)
|
|
self.assertEqual(metadata["prompt_graph"]["status"], "parsed")
|
|
self.assertEqual(metadata["record_formats"]["workflow"], "limited")
|
|
self.assertEqual(metadata["record_formats"]["prompt"], "original-text")
|
|
self.assertNotIn("workflow", metadata["raw"])
|
|
self.assertIn("prompt", metadata["raw"])
|
|
|
|
def test_oversize_workflow_is_skipped_by_seek_not_read(self):
|
|
from utils.prompt_inspector import WORKFLOW_METADATA_BYTES
|
|
|
|
workflow = b"A" * (WORKFLOW_METADATA_BYTES + 1)
|
|
path = _png_with_chunks(
|
|
self.directory / "seek.png",
|
|
[_text_chunk(b"tEXt", "workflow", workflow), self.prompt_chunk()],
|
|
)
|
|
reads = self.tracked_reads(path)
|
|
self.assertLess(sum(reads), 64 * 1024)
|
|
|
|
def tracked_reads(self, path):
|
|
original_open = type(path).open
|
|
reads = []
|
|
|
|
def tracked_open(item, *args, **kwargs):
|
|
stream = original_open(item, *args, **kwargs)
|
|
original_read = stream.read
|
|
|
|
def read(size=-1):
|
|
value = original_read(size)
|
|
reads.append(len(value))
|
|
return value
|
|
|
|
stream.read = read
|
|
return stream
|
|
|
|
with patch.object(type(path), "open", tracked_open):
|
|
read = read_inspection_file(path)
|
|
self.assert_prompts_resolved(read)
|
|
return reads
|
|
|
|
def test_oversize_compressed_workflow_stops_inflating(self):
|
|
from utils import prompt_inspector
|
|
|
|
workflow = json.dumps({"nodes": [], "note": "A" * (6 * MIB)}).encode()
|
|
compressed = zlib.compress(workflow, 9)
|
|
self.assertLess(len(compressed), prompt_inspector.WORKFLOW_METADATA_BYTES)
|
|
produced = []
|
|
real = zlib.decompressobj
|
|
|
|
class Tracked:
|
|
def __init__(self):
|
|
self.inner = real()
|
|
|
|
def decompress(self, data, max_length=0):
|
|
self.assert_bounded(max_length)
|
|
value = self.inner.decompress(data, max_length)
|
|
produced.append(len(value))
|
|
return value
|
|
|
|
@staticmethod
|
|
def assert_bounded(max_length):
|
|
if not 0 < max_length <= prompt_inspector.WORKFLOW_METADATA_BYTES + 1:
|
|
raise AssertionError(f"unbounded inflate: {max_length}")
|
|
|
|
def __getattr__(self, name):
|
|
return getattr(self.inner, name)
|
|
|
|
for kind, body in (
|
|
(b"zTXt", b"\0" + compressed),
|
|
(b"iTXt", b"\1\0\0\0" + compressed),
|
|
):
|
|
with self.subTest(kind=kind):
|
|
produced.clear()
|
|
path = _png_with_chunks(
|
|
self.directory / "compressed.png",
|
|
[self.prompt_chunk(), _text_chunk(kind, "workflow", body)],
|
|
)
|
|
with patch.object(prompt_inspector.zlib, "decompressobj", Tracked):
|
|
read = read_inspection_file(path)
|
|
self.assertTrue(produced)
|
|
self.assertLessEqual(
|
|
max(produced), prompt_inspector.WORKFLOW_METADATA_BYTES + 1
|
|
)
|
|
self.assertEqual(read.limited_records, frozenset({"workflow"}))
|
|
self.assertEqual(read.record_formats["workflow"], "limited")
|
|
self.assertNotIn("workflow", read.metadata)
|
|
self.assert_prompts_resolved(read)
|
|
|
|
def test_compressed_workflow_over_budget_is_skipped(self):
|
|
from utils.prompt_inspector import WORKFLOW_METADATA_BYTES
|
|
|
|
body = b"\0" + bytes(range(256)) * (WORKFLOW_METADATA_BYTES // 256 + 1)
|
|
path = _png_with_chunks(
|
|
self.directory / "compressed-length.png",
|
|
[_text_chunk(b"zTXt", "workflow", body), self.prompt_chunk()],
|
|
)
|
|
read = read_inspection_file(path)
|
|
self.assertEqual(read.limited_records, frozenset({"workflow"}))
|
|
self.assert_prompts_resolved(read)
|
|
|
|
def test_role_records_over_budget_still_unreadable(self):
|
|
from utils.prompt_inspector import ROLE_METADATA_BYTES
|
|
|
|
prompt = self.prompt_chunk()
|
|
cases = {
|
|
"prompt-text": [
|
|
_text_chunk(b"tEXt", "prompt", b"x" * (ROLE_METADATA_BYTES + 1))
|
|
],
|
|
"prompt-inflate": [
|
|
_text_chunk(
|
|
b"zTXt",
|
|
"prompt",
|
|
b"\0" + zlib.compress(b"x" * (ROLE_METADATA_BYTES + 1)),
|
|
)
|
|
],
|
|
"roles-together": [
|
|
prompt,
|
|
_text_chunk(b"tEXt", "parameters", b"x" * ROLE_METADATA_BYTES),
|
|
],
|
|
"execution-record": [
|
|
prompt,
|
|
_text_chunk(b"tEXt", EXECUTION_KEY, b"x" * (ROLE_METADATA_BYTES + 1)),
|
|
],
|
|
}
|
|
for name, chunks in cases.items():
|
|
with self.subTest(case=name):
|
|
path = _png_with_chunks(self.directory / f"{name}.png", chunks)
|
|
with self.assertRaisesRegex(
|
|
MetadataReadError, "exceeds inspection limits"
|
|
):
|
|
read_inspection_file(path)
|
|
|
|
def test_role_budget_is_not_shared_with_workflow(self):
|
|
from utils.prompt_inspector import ROLE_METADATA_BYTES
|
|
|
|
path = _png_with_chunks(
|
|
self.directory / "shared.png",
|
|
[
|
|
self.prompt_chunk(),
|
|
_text_chunk(b"tEXt", "parameters", b"p" * (ROLE_METADATA_BYTES - 4096)),
|
|
_text_chunk(b"tEXt", "workflow", b"w" * (3 * MIB)),
|
|
],
|
|
)
|
|
read = read_inspection_file(path)
|
|
self.assertEqual(read.limited_records, frozenset())
|
|
self.assertEqual(len(read.metadata["workflow"]), 3 * MIB)
|
|
self.assert_prompts_resolved(read)
|
|
|
|
def test_identical_duplicate_chunks_are_accepted(self):
|
|
path = parity.fixture_path("f15")
|
|
chunks = dict(parity.read_text_chunks(path))
|
|
read = read_inspection_file(path)
|
|
self.assertEqual(read.metadata["prompt"], chunks["prompt"])
|
|
self.assertEqual(read.metadata["workflow"], chunks["workflow"])
|
|
self.assert_prompts_resolved(read)
|
|
metadata = json.loads(encode(read))["metadata"]
|
|
self.assertEqual(metadata["prompt_graph"]["status"], "parsed")
|
|
self.assertEqual(metadata["workflow_graph"]["status"], "parsed")
|
|
|
|
def test_conflicting_duplicate_chunks_fail(self):
|
|
with self.assertRaisesRegex(MetadataReadError, "Duplicate prompt metadata"):
|
|
read_inspection_file(parity.fixture_path("f16"))
|
|
prompt = json.dumps(parity.build("f04")["prompt"]).encode("latin-1")
|
|
cases = {
|
|
# Same decoded text, different bytes on disk: not byte-identical.
|
|
"kind": [
|
|
self.prompt_chunk(),
|
|
_text_chunk(b"zTXt", "prompt", b"\0" + zlib.compress(prompt)),
|
|
],
|
|
"length": [
|
|
self.prompt_chunk(),
|
|
_text_chunk(b"tEXt", "prompt", prompt + b" "),
|
|
],
|
|
"same-length": [
|
|
self.prompt_chunk(),
|
|
_text_chunk(b"tEXt", "prompt", prompt.replace(b"red fox", b"red cat")),
|
|
],
|
|
"workflow": [
|
|
self.prompt_chunk(),
|
|
_text_chunk(b"tEXt", "workflow", b'{"nodes": []}'),
|
|
_text_chunk(b"tEXt", "workflow", b'{"nodes": [1]}'),
|
|
],
|
|
}
|
|
for name, chunks in cases.items():
|
|
with self.subTest(case=name):
|
|
path = _png_with_chunks(self.directory / f"{name}.png", chunks)
|
|
with self.assertRaisesRegex(
|
|
MetadataReadError, "Duplicate prompt metadata"
|
|
):
|
|
read_inspection_file(path)
|
|
|
|
def test_duplicate_of_limited_workflow_stays_limited(self):
|
|
from utils.prompt_inspector import WORKFLOW_METADATA_BYTES
|
|
|
|
oversize = _text_chunk(
|
|
b"tEXt", "workflow", b"A" * (WORKFLOW_METADATA_BYTES + 1)
|
|
)
|
|
path = _png_with_chunks(
|
|
self.directory / "limited-twice.png",
|
|
[oversize, self.prompt_chunk(), oversize],
|
|
)
|
|
read = read_inspection_file(path)
|
|
self.assertEqual(read.limited_records, frozenset({"workflow"}))
|
|
self.assertNotIn("workflow", read.metadata)
|
|
self.assert_prompts_resolved(read)
|
|
|
|
def test_identical_duplicates_do_not_consume_role_budget(self):
|
|
from utils.prompt_inspector import ROLE_METADATA_BYTES
|
|
|
|
parameters = _text_chunk(
|
|
b"tEXt", "parameters", b"p" * (ROLE_METADATA_BYTES * 3 // 4)
|
|
)
|
|
path = _png_with_chunks(
|
|
self.directory / "repeat.png",
|
|
[self.prompt_chunk(), parameters, parameters],
|
|
)
|
|
read = read_inspection_file(path)
|
|
self.assertEqual(len(read.metadata["parameters"]), ROLE_METADATA_BYTES * 3 // 4)
|
|
|
|
def test_workflow_duplicates_are_limited_without_touching_role_records(self):
|
|
from utils import prompt_inspector
|
|
|
|
self.assertEqual(prompt_inspector.DUPLICATE_WORKFLOW_BYTES, 8 * MIB)
|
|
self.assertEqual(prompt_inspector.DUPLICATE_ROLE_BYTES, 4 * MIB)
|
|
workflow = _text_chunk(b"tEXt", "workflow", b"{}" + b" " * 1000)
|
|
size = len(workflow) - 12
|
|
path = _png_with_chunks(
|
|
self.directory / "wf.png", [self.prompt_chunk()] + [workflow] * 6
|
|
)
|
|
added = []
|
|
original = prompt_inspector._PngRecords.add
|
|
|
|
def counting(records, kind, data):
|
|
added.append(len(data))
|
|
return original(records, kind, data)
|
|
|
|
with (
|
|
patch.object(
|
|
prompt_inspector, "DUPLICATE_WORKFLOW_BYTES", size * 2 + size // 2
|
|
),
|
|
patch.object(prompt_inspector._PngRecords, "add", counting),
|
|
):
|
|
read = read_inspection_file(path)
|
|
# Original plus two budgeted duplicates were read; the third is limited.
|
|
self.assertEqual(added.count(size), 3)
|
|
self.assertEqual(read.record_formats["workflow"], "limited")
|
|
self.assertNotIn("workflow", read.metadata)
|
|
self.assertEqual(read.record_formats["prompt"], "original-text")
|
|
self.assert_prompts_resolved(read)
|
|
|
|
def test_role_duplicates_past_their_budget_fail_closed(self):
|
|
from utils import prompt_inspector
|
|
|
|
chunk = self.prompt_chunk()
|
|
size = len(chunk) - 12
|
|
path = _png_with_chunks(self.directory / "dupes.png", [chunk] * 6)
|
|
with patch.object(
|
|
prompt_inspector, "DUPLICATE_ROLE_BYTES", size * 2 + size // 2
|
|
):
|
|
with self.assertRaisesRegex(
|
|
MetadataReadError, "Metadata exceeds inspection limits"
|
|
):
|
|
read_inspection_file(path)
|
|
|
|
def test_over_budget_role_record_never_falls_back_to_other_evidence(self):
|
|
from utils import prompt_inspector
|
|
|
|
chunk = self.prompt_chunk()
|
|
size = len(chunk) - 12
|
|
extras = [
|
|
_text_chunk(b"tEXt", "parameters", b"fallback parameters"),
|
|
_text_chunk(b"tEXt", "workflow", b"{}"),
|
|
]
|
|
path = _png_with_chunks(self.directory / "fallback.png", [chunk] * 6 + extras)
|
|
with patch.object(prompt_inspector, "DUPLICATE_ROLE_BYTES", size * 2):
|
|
with self.assertRaisesRegex(
|
|
MetadataReadError, "Metadata exceeds inspection limits"
|
|
):
|
|
read_inspection_file(path)
|
|
|
|
def test_role_key_can_never_end_up_limited(self):
|
|
from utils import prompt_inspector
|
|
|
|
path = _png_with_chunks(self.directory / "plain.png", [self.prompt_chunk()])
|
|
original = prompt_inspector._PngRecords.skip
|
|
|
|
def limit_role(records, key, length):
|
|
records.limited.add("prompt")
|
|
return original(records, key, length)
|
|
|
|
with patch.object(prompt_inspector._PngRecords, "skip", limit_role):
|
|
with self.assertRaisesRegex(
|
|
MetadataReadError, "Metadata exceeds inspection limits"
|
|
):
|
|
read_inspection_file(path)
|
|
|
|
def test_duplicates_within_the_total_budget_are_unchanged(self):
|
|
path = _png_with_chunks(self.directory / "few.png", [self.prompt_chunk()] * 3)
|
|
read = read_inspection_file(path)
|
|
self.assertEqual(read.record_formats["prompt"], "original-text")
|
|
self.assert_prompts_resolved(read)
|
|
|
|
def test_unretained_text_chunks_are_skipped_without_retention(self):
|
|
software = _text_chunk(b"tEXt", "Software", b"S" * (5 * MIB))
|
|
compressed = _text_chunk(b"zTXt", "Comment", b"\0" + b"not zlib at all")
|
|
path = _png_with_chunks(
|
|
self.directory / "software.png",
|
|
[software, compressed, self.prompt_chunk()],
|
|
)
|
|
reads = self.tracked_reads(path)
|
|
self.assertLess(sum(reads), 64 * 1024)
|
|
read = read_inspection_file(path)
|
|
self.assertEqual(set(read.metadata), {"prompt"})
|
|
|
|
def test_unretained_chunk_with_malformed_keyword_still_fails(self):
|
|
for body in (b"no-separator", b"k" * 100 + b"\0text", b"\0text"):
|
|
with self.subTest(body=body[:12]):
|
|
path = _png_with_chunks(
|
|
self.directory / "keyword.png",
|
|
[self.prompt_chunk(), parity._raw_chunk(b"tEXt", body)],
|
|
)
|
|
with self.assertRaisesRegex(MetadataReadError, "Malformed"):
|
|
read_inspection_file(path)
|
|
|
|
def test_chunk_count_limit_unchanged(self):
|
|
from utils import prompt_inspector
|
|
|
|
self.assertEqual(prompt_inspector.MAX_PNG_CHUNKS, 10_000)
|
|
filler = _text_chunk(b"tEXt", "Comment", b"x")
|
|
for total, readable in ((10_000, True), (10_001, False)):
|
|
with self.subTest(total=total):
|
|
path = _png_with_chunks(self.directory / "count.png", [])
|
|
structural = self.chunk_count(path)
|
|
path = _png_with_chunks(
|
|
self.directory / "count.png",
|
|
[self.prompt_chunk()] + [filler] * (total - structural - 1),
|
|
)
|
|
self.assertEqual(self.chunk_count(path), total)
|
|
if readable:
|
|
self.assert_prompts_resolved(read_inspection_file(path))
|
|
else:
|
|
with self.assertRaisesRegex(MetadataReadError, "chunk count"):
|
|
read_inspection_file(path)
|
|
|
|
@staticmethod
|
|
def chunk_count(path):
|
|
data, offset, count = path.read_bytes(), 8, 0
|
|
while offset < len(data):
|
|
(length,) = struct.unpack(">I", data[offset : offset + 4])
|
|
offset += 12 + length
|
|
count += 1
|
|
return count
|
|
|
|
def test_non_png_workflow_over_budget_is_limited_not_unreadable(self):
|
|
from utils.prompt_inspector import WORKFLOW_METADATA_BYTES
|
|
|
|
prompt = json.dumps(parity.build("f04")["prompt"])
|
|
metadata = {"prompt": prompt, "workflow": "w" * (WORKFLOW_METADATA_BYTES + 1)}
|
|
fake = MagicMock()
|
|
fake.__enter__.return_value = fake
|
|
fake.info, fake.format, fake.size = metadata, "WEBP", (4, 4)
|
|
path = self.directory / "image.webp"
|
|
path.write_bytes(b"RIFF0000WEBP")
|
|
with patch("utils.prompt_inspector.Image.open", return_value=fake):
|
|
read = read_inspection_file(path)
|
|
self.assertEqual(read.limited_records, frozenset({"workflow"}))
|
|
self.assertEqual(
|
|
read.record_formats, {"prompt": "original-text", "workflow": "limited"}
|
|
)
|
|
self.assert_prompts_resolved(read)
|
|
|
|
def test_limited_record_format_omits_raw_and_limits_graph(self):
|
|
read = InspectionRead(
|
|
metadata={"prompt": graph_text(), "workflow": "{}"},
|
|
record_formats={"prompt": "original-text", "workflow": "original-text"},
|
|
video_carrier_text=None,
|
|
format="PNG",
|
|
width=4,
|
|
height=4,
|
|
limited_records=frozenset({"workflow"}),
|
|
)
|
|
metadata = json.loads(encode(read))["metadata"]
|
|
self.assertEqual(metadata["record_formats"]["workflow"], "limited")
|
|
self.assertNotIn("workflow", metadata["raw"])
|
|
self.assertEqual(
|
|
metadata["workflow_graph"], {"status": "limited", "value": None}
|
|
)
|
|
self.assertEqual(metadata["prompt_graph"]["status"], "parsed")
|
|
only = InspectionRead({}, {"workflow": "limited"}, None, "PNG", 4, 4)
|
|
metadata = json.loads(encode(only))["metadata"]
|
|
self.assertEqual(metadata["status"], "available")
|
|
self.assertEqual(metadata["raw"], {})
|
|
self.assertEqual(metadata["record_formats"], {"workflow": "limited"})
|
|
self.assertEqual(metadata["workflow_graph"]["status"], "limited")
|
|
self.assertEqual(metadata["prompt_graph"]["status"], "absent")
|