feat(recipes): preserve embedded ComfyUI workflow on remote imports

CivitAI serves a re-encoded, metadata-free optimized rendition as the recipe
preview, so the ComfyUI workflow embedded in the original image was dropped:
imported recipes reported has_workflow=false and never offered "Send Workflow
to ComfyUI" even when the source image carried one.

Recover the workflow from the original rendition and carry it to the save step
as data, so the stored preview stays the small optimized image:

- ExifUtils: embed a caller-supplied workflow during optimize_image's single
  encode pass, and add embed_workflow() to patch WebP EXIF in place (used by
  the verbatim skip_optimize branch and as a safety net).
- RecipePersistenceService.save_recipe: embed metadata["workflow"] before
  detecting has_workflow.
- analyze_remote_image: return the workflow recovered from the original
  rendition it already downloads for EXIF parsing.
- RecipeManagementHandler: add _fetch_original_media() and workflow helpers;
  _do_import_from_url reuses them, and _do_import_remote_recipe fetches the
  original only when CivitAI reports a ComfyUI payload (meta.comfy) so
  workflow-less images pay no extra bandwidth.
- Batch URL imports and the import modal forward the recovered workflow.

Verified against the reported image: has_workflow flips from false to true and
the recovered workflow matches the original (25 nodes, same graph id).

tests/utils/test_exif_utils.py

@@ -211,6 +211,104 @@ def test_update_image_metadata_preserves_png_workflow(tmp_path):
         )
 
 
+def test_optimize_image_embeds_supplied_workflow_when_source_has_none(tmp_path):
+    """Import paths hand the workflow over as data when the preview source is
+    metadata-free (CivitAI's optimized rendition); optimize_image must embed
+    it while re-encoding, otherwise the recipe loses has_workflow."""
+    image_path = tmp_path / "optimized.webp"
+    Image.new("RGB", (64, 32), color="red").save(image_path, format="WEBP", quality=85)
+
+    workflow = {"nodes": [{"id": 1}], "last_node_id": 1}
+    optimized_data, extension = ExifUtils.optimize_image(
+        str(image_path),
+        target_width=32,
+        format="webp",
+        quality=85,
+        preserve_metadata=True,
+        workflow=workflow,
+    )
+
+    optimized_path = tmp_path / f"embedded{extension}"
+    optimized_path.write_bytes(optimized_data)
+
+    metadata = ExifUtils._load_structured_metadata(str(optimized_path))
+    assert metadata["workflow"] == json.dumps(workflow)
+
+
+def test_optimize_image_keeps_source_workflow_over_supplied(tmp_path):
+    image_path = tmp_path / "source.png"
+    png_info = PngImagePlugin.PngInfo()
+    png_info.add_text("workflow", '{"nodes":[{"id":7}]}')
+    Image.new("RGB", (64, 32), color="red").save(image_path, pnginfo=png_info)
+
+    optimized_data, extension = ExifUtils.optimize_image(
+        str(image_path),
+        target_width=32,
+        format="webp",
+        quality=85,
+        preserve_metadata=True,
+        workflow={"nodes": [{"id": 1}]},
+    )
+
+    optimized_path = tmp_path / f"sourcewins{extension}"
+    optimized_path.write_bytes(optimized_data)
+
+    metadata = ExifUtils._load_structured_metadata(str(optimized_path))
+    assert metadata["workflow"] == '{"nodes":[{"id":7}]}'
+
+
+def test_embed_workflow_adds_workflow_to_metadata_free_webp(tmp_path):
+    image_path = tmp_path / "preview.webp"
+    Image.new("RGB", (32, 32), color="blue").save(image_path, format="WEBP", quality=85)
+
+    workflow = json.dumps({"nodes": [{"id": 1}]})
+    returned = ExifUtils.embed_workflow(str(image_path), workflow)
+
+    assert returned == str(image_path)
+    metadata = ExifUtils._load_structured_metadata(str(image_path))
+    assert metadata["workflow"] == workflow
+    with Image.open(image_path) as img:
+        assert img.size == (32, 32)
+
+
+def test_embed_workflow_adds_workflow_to_metadata_free_png(tmp_path):
+    image_path = tmp_path / "preview.png"
+    Image.new("RGB", (32, 32), color="blue").save(image_path)
+
+    workflow = {"nodes": [{"id": 3}]}
+    ExifUtils.embed_workflow(str(image_path), workflow)
+
+    metadata = ExifUtils._load_structured_metadata(str(image_path))
+    assert metadata["workflow"] == json.dumps(workflow)
+
+
+def test_embed_workflow_leaves_existing_workflow_untouched(tmp_path):
+    image_path = tmp_path / "preview.png"
+    png_info = PngImagePlugin.PngInfo()
+    png_info.add_text("workflow", '{"nodes":[{"id":9}]}')
+    Image.new("RGB", (32, 32), color="green").save(image_path, pnginfo=png_info)
+
+    ExifUtils.embed_workflow(str(image_path), {"nodes": [{"id": 1}]})
+
+    with Image.open(image_path) as img:
+        assert img.info["workflow"] == '{"nodes":[{"id":9}]}'
+
+
+def test_embed_workflow_ignores_unsupported_payloads_and_containers(tmp_path):
+    image_path = tmp_path / "preview.webp"
+    Image.new("RGB", (16, 16), color="black").save(image_path, format="WEBP")
+
+    # Nothing to embed / unsupported payload types are no-ops.
+    assert ExifUtils.embed_workflow(str(image_path), None) == str(image_path)
+    assert ExifUtils.embed_workflow(str(image_path), "") == str(image_path)
+    assert ExifUtils.embed_workflow(str(image_path), 123) == str(image_path)
+    assert ExifUtils._load_structured_metadata(str(image_path))["workflow"] is None
+
+    video_path = tmp_path / "clip.mp4"
+    video_path.write_bytes(b"video")
+    assert ExifUtils.embed_workflow(str(video_path), {"nodes": []}) == str(video_path)
+
+
 # --- ISOBMFF / brotli extraction tests ---
 
 import struct