fix: add support for parsing python generated json with NaN/infinite (#12217)

## Summary

API and other legacy JSON generated by python `json.dumps` can contain
`NaN` and `Infinity` which cannot be parsed with JS `JSON.parse`. This
adds regex to replace these invalid tokens with `null`.

## Changes

- **What**: 
- add regex replace on bare NaN/infinity tokens after JSON.parse fails
- update call sites
- tests

## Review Focus
- The regex should only rewrite bare NaN/-Infinity/Infinity and not
touch string values or other invalid tokens.
- A small regex was chosen over JSON5 due to package size (30.3kB
Minified, 9kB Minified + Gzipped) or a manual parser due to the
unnecessarily complexity vs a single regex replace.
- The happy path is run first, the safe parse is only executed if that
failed, meaning no overhead the vast majority of the time and no
possiblity of corrupting valid workflows due to a bug in the fallback
parser
- Multiple call sites had to be updated due to pre-existing architecture
of the various parsers, an issue for unifying these is logged for future
cleanup
- New binary fixtures added for validating e2e import using real files

┆Issue is synchronized with this [Notion
page](https://www.notion.so/PR-12217-fix-add-support-for-parsing-python-generated-json-with-NaN-infinite-35f6d73d365081889fc7f4af823f29c1)
by [Unito](https://www.unito.io)

Author: pythongosssss

browser_tests/tests/metadataWorkflowImport.spec.ts

@@ -25,6 +25,21 @@ const FIXTURES: readonly MetadataFixture[] = [
   { fileName: 'with_metadata.webm', parser: 'ebml (webm)' }
 ] as const
 
+// NaN-variant fixtures embed only an API-format prompt containing bare
+// `NaN`/`Infinity` tokens (Python's `json.dumps` default). The loader must
+// tolerate Python generated JSON for these to import successfully.
+const NAN_FIXTURES: readonly MetadataFixture[] = [
+  { fileName: 'with_nan_metadata.json', parser: 'json' },
+  { fileName: 'with_nan_metadata.png', parser: 'png' },
+  { fileName: 'with_nan_metadata.avif', parser: 'avif' },
+  { fileName: 'with_nan_metadata.webp', parser: 'webp' },
+  { fileName: 'with_nan_metadata.flac', parser: 'flac' },
+  { fileName: 'with_nan_metadata.mp3', parser: 'mp3' },
+  { fileName: 'with_nan_metadata.opus', parser: 'ogg' },
+  { fileName: 'with_nan_metadata.mp4', parser: 'isobmff' },
+  { fileName: 'with_nan_metadata.webm', parser: 'ebml (webm)' }
+] as const
+
 test.describe(
   'Metadata drop-to-load workflow import',
   { tag: ['@workflow'] },
@@ -58,5 +73,42 @@ test.describe(
         })
       })
     }
+
+    for (const { fileName, parser } of NAN_FIXTURES) {
+      test(`loads Python JSON prompt with NaN/Infinity from ${fileName} (${parser})`, async ({
+        comfyPage
+      }) => {
+        await test.step(`drop ${fileName} on canvas`, async () => {
+          await comfyPage.dragDrop.dragAndDropFilePath(
+            metadataFixturePath(fileName)
+          )
+        })
+
+        await test.step('graph contains only the embedded KSampler', async () => {
+          await expect
+            .poll(() => comfyPage.nodeOps.getGraphNodesCount())
+            .toBe(1)
+
+          const ksamplers =
+            await comfyPage.nodeOps.getNodeRefsByType('KSampler')
+          expect(
+            ksamplers,
+            'exactly one KSampler should have been loaded from the NaN-laden prompt'
+          ).toHaveLength(1)
+        })
+
+        await test.step('NaN-coerced widget values are 0', async () => {
+          const [ksampler] =
+            await comfyPage.nodeOps.getNodeRefsByType('KSampler')
+          for (const widgetName of ['cfg', 'denoise']) {
+            const widget = await ksampler.getWidgetByName(widgetName)
+            expect(
+              await widget.getValue(),
+              `${widgetName} should be 0 after NaN coercion to null`
+            ).toBe(0)
+          }
+        })
+      })
+    }
   }
 )

scripts/generate-embedded-metadata-test-files.py

@@ -36,8 +36,19 @@
 }
 PROMPT = {'1': {'class_type': 'KSampler', 'inputs': {}}}
 
+# API-format prompt with bare NaN/Infinity tokens (as Python's json.dumps emits
+# by default). The NaN variant fixtures omit the workflow field so the loader
+# must route through prompt-parsing, which trips JSON.parse on bare NaN.
+PROMPT_NAN = {
+    '1': {
+        'class_type': 'KSampler',
+        'inputs': {'cfg': float('nan'), 'denoise': float('inf')},
+    }
+}
+
 WORKFLOW_JSON = json.dumps(WORKFLOW, separators=(',', ':'))
 PROMPT_JSON = json.dumps(PROMPT, separators=(',', ':'))
+PROMPT_NAN_JSON = json.dumps(PROMPT_NAN, separators=(',', ':'))
 
 
 def out(name: str) -> str:
@@ -53,15 +64,21 @@ def make_1x1_image() -> Image.Image:
     return Image.new('RGB', (1, 1), (255, 0, 0))
 
 
-def build_exif_bytes() -> bytes:
+def build_exif_bytes(
+    workflow_str: str | None = WORKFLOW_JSON,
+    prompt_str: str | None = PROMPT_JSON,
+) -> bytes:
     """Build EXIF bytes matching the backend's tag assignments.
 
     Backend: 0x010F (Make) = "workflow:<json>", 0x0110 (Model) = "prompt:<json>"
+    Pass ``None`` to omit a tag.
     """
     img = make_1x1_image()
     exif = img.getexif()
-    exif[0x010F] = f'workflow:{WORKFLOW_JSON}'
-    exif[0x0110] = f'prompt:{PROMPT_JSON}'
+    if workflow_str is not None:
+        exif[0x010F] = f'workflow:{workflow_str}'
+    if prompt_str is not None:
+        exif[0x0110] = f'prompt:{prompt_str}'
     return exif.tobytes()
 
 
@@ -93,15 +110,20 @@ def generate_av_fixture(
     codec: str,
     rate: int = 44100,
     options: dict | None = None,
+    *,
+    prompt_json: str | None = PROMPT_JSON,
+    workflow_json: str | None = WORKFLOW_JSON,
 ):
     """Generate an audio fixture via PyAV container.metadata[], matching the backend."""
     path = out(name)
     container = av.open(path, mode='w', format=fmt, options=options or {})
     stream = container.add_stream(codec, rate=rate)
     stream.layout = 'mono'
 
-    container.metadata['prompt'] = PROMPT_JSON
-    container.metadata['workflow'] = WORKFLOW_JSON
+    if prompt_json is not None:
+        container.metadata['prompt'] = prompt_json
+    if workflow_json is not None:
+        container.metadata['workflow'] = workflow_json
 
     sample_fmt = stream.codec_context.codec.audio_formats[0].name
     samples = stream.codec_context.frame_size or 1024
@@ -175,6 +197,63 @@ def generate_webm():
     generate_av_fixture('with_metadata.webm', 'webm', 'libvorbis')
 
 
+def generate_nan_variants():
+    """Per-format fixtures carrying ONLY a NaN/Infinity-laden API prompt.
+
+    These force the loader through the prompt-parsing path, where Python's
+    bare NaN/Infinity tokens trip JSON.parse.
+    """
+    img = make_1x1_image()
+    info = PngInfo()
+    info.add_text('prompt', PROMPT_NAN_JSON)
+    img.save(out('with_nan_metadata.png'), 'PNG', pnginfo=info)
+    report('with_nan_metadata.png')
+
+    exif_nan = build_exif_bytes(workflow_str=None, prompt_str=PROMPT_NAN_JSON)
+
+    img = make_1x1_image()
+    img.save(out('with_nan_metadata.webp'), 'WEBP', exif=exif_nan)
+    report('with_nan_metadata.webp')
+
+    img = make_1x1_image()
+    img.save(out('with_nan_metadata.avif'), 'AVIF', exif=exif_nan)
+    report('with_nan_metadata.avif')
+
+    generate_av_fixture(
+        'with_nan_metadata.flac', 'flac', 'flac',
+        prompt_json=PROMPT_NAN_JSON, workflow_json=None,
+    )
+    generate_av_fixture(
+        'with_nan_metadata.opus', 'opus', 'libopus', rate=48000,
+        prompt_json=PROMPT_NAN_JSON, workflow_json=None,
+    )
+    generate_av_fixture(
+        'with_nan_metadata.mp3', 'mp3', 'libmp3lame',
+        prompt_json=PROMPT_NAN_JSON, workflow_json=None,
+    )
+    generate_av_fixture(
+        'with_nan_metadata.webm', 'webm', 'libvorbis',
+        prompt_json=PROMPT_NAN_JSON, workflow_json=None,
+    )
+
+    path = out('with_nan_metadata.mp4')
+    subprocess.run([
+        'ffmpeg', '-y', '-loglevel', 'error',
+        '-f', 'lavfi', '-i', 'anullsrc=r=44100:cl=mono',
+        '-t', '0.01', '-c:a', 'aac', '-b:a', '32k',
+        '-movflags', 'use_metadata_tags',
+        '-metadata', f'prompt={PROMPT_NAN_JSON}',
+        path,
+    ], check=True)
+    report('with_nan_metadata.mp4')
+
+    # Direct JSON file containing API-format prompt with bare NaN/Infinity.
+    json_path = out('with_nan_metadata.json')
+    with open(json_path, 'w', encoding='utf-8') as f:
+        f.write(PROMPT_NAN_JSON)
+    report('with_nan_metadata.json')
+
+
 if __name__ == '__main__':
     print('Generating fixtures...')
     generate_png()
@@ -185,4 +264,5 @@ def generate_webm():
     generate_mp3()
     generate_mp4()
     generate_webm()
+    generate_nan_variants()
     print('Done.')

src/platform/workflow/utils/workflowExtractionUtil.ts

@@ -9,6 +9,7 @@ import { getOutputAssetMetadata } from '@/platform/assets/schemas/assetMetadataS
 import { getAssetUrl } from '@/platform/assets/utils/assetUrlUtil'
 import { getWorkflowDataFromFile } from '@/scripts/metadata/parser'
 import { getJobWorkflow } from '@/services/jobOutputCache'
+import { parseJsonWithNonFinite } from '@/utils/jsonUtil'
 
 /**
  * Extract workflow from AssetItem using jobs API
@@ -51,11 +52,11 @@ export async function extractWorkflowFromAsset(asset: AssetItem): Promise<{
       // Handle both string and object workflow data
       const workflow =
         typeof workflowData.workflow === 'string'
-          ? JSON.parse(workflowData.workflow)
-          : workflowData.workflow
+          ? parseJsonWithNonFinite<ComfyWorkflowJSON>(workflowData.workflow)
+          : (workflowData.workflow as ComfyWorkflowJSON)
 
       return {
-        workflow: workflow as ComfyWorkflowJSON,
+        workflow,
         filename: baseFilename
       }
     }

src/scripts/app.ts

@@ -84,6 +84,7 @@ import type { ComfyExtension, MissingNodeType } from '@/types/comfy'
 import type { ExtensionManager } from '@/types/extensionTypes'
 import type { NodeExecutionId } from '@/types/nodeIdentification'
 import { graphToPrompt } from '@/utils/executionUtil'
+import { parseJsonWithNonFinite } from '@/utils/jsonUtil'
 import { getCnrIdFromProperties } from '@/platform/nodeReplacement/cnrIdUtil'
 import { rescanAndSurfaceMissingNodes } from '@/platform/nodeReplacement/missingNodeScan'
 import {
@@ -1091,7 +1092,7 @@ export class ComfyApp {
       }
 
       // Check for old clipboard format
-      const data = JSON.parse(template.data)
+      const data = parseJsonWithNonFinite<{ reroutes?: unknown }>(template.data)
       if (!data.reroutes) {
         deserialiseAndCreate(template.data, app.canvas)
       } else {
@@ -1802,7 +1803,9 @@ export class ComfyApp {
       let workflowObj: ComfyWorkflowJSON | undefined = undefined
       try {
         workflowObj =
-          typeof workflow === 'string' ? JSON.parse(workflow) : workflow
+          typeof workflow === 'string'
+            ? parseJsonWithNonFinite<ComfyWorkflowJSON>(workflow)
+            : (workflow as ComfyWorkflowJSON)
 
         // Only load workflow if parsing succeeded AND validation passed
         if (
@@ -1831,7 +1834,9 @@ export class ComfyApp {
     if (prompt) {
       try {
         const promptObj =
-          typeof prompt === 'string' ? JSON.parse(prompt) : prompt
+          typeof prompt === 'string'
+            ? parseJsonWithNonFinite<ComfyApiWorkflow>(prompt)
+            : prompt
         if (this.isApiJson(promptObj)) {
           this.loadApiJson(promptObj, fileName)
           return

src/scripts/metadata/__fixtures__/helpers.ts

@@ -8,6 +8,12 @@ export const EXPECTED_PROMPT = {
   '1': { class_type: 'KSampler', inputs: {} }
 }
 
+// API prompt as parsed from the `with_nan_metadata.*` fixtures, after the
+// loader coerces bare NaN/Infinity tokens to null.
+export const EXPECTED_PROMPT_NAN_COERCED = {
+  '1': { class_type: 'KSampler', inputs: { cfg: null, denoise: null } }
+}
+
 type ReadMethod = 'readAsText' | 'readAsArrayBuffer'
 
 export function mockFileReaderError(method: ReadMethod): void {

src/scripts/metadata/__fixtures__/with_nan_metadata.avif

@@ -0,0 +1 @@
+{"1":{"class_type":"KSampler","inputs":{"cfg":NaN,"denoise":Infinity}}}