fix(civitai): improve metadata parsing for nested structures, see #700

- Refactor metadata detection to handle nested "meta" objects
- Add support for lowercase "lora:" hash keys
- Extract metadata from nested "meta" field when present
- Update tests to verify nested metadata parsing
- Handle case-insensitive LORA hash detection

The changes ensure proper parsing of Civitai image metadata that may be wrapped in nested structures, improving compatibility with different API response formats.

py/recipes/parsers/civitai_image.py

@@ -23,13 +23,34 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
         """
         if not metadata or not isinstance(metadata, dict):
             return False
-            
-        # Check for key markers specific to Civitai image metadata
-        return any([
-            "resources" in metadata,
-            "civitaiResources" in metadata,
-            "additionalResources" in metadata
-        ])
+
+        def has_markers(payload: Dict[str, Any]) -> bool:
+            return any(
+                key in payload
+                for key in (
+                    "resources",
+                    "civitaiResources",
+                    "additionalResources",
+                )
+            )
+
+        if has_markers(metadata):
+            return True
+
+        hashes = metadata.get("hashes")
+        if isinstance(hashes, dict) and any(str(key).lower().startswith("lora:") for key in hashes):
+            return True
+
+        nested_meta = metadata.get("meta")
+        if isinstance(nested_meta, dict):
+            if has_markers(nested_meta):
+                return True
+
+            hashes = nested_meta.get("hashes")
+            if isinstance(hashes, dict) and any(str(key).lower().startswith("lora:") for key in hashes):
+                return True
+
+        return False
     
     async def parse_metadata(self, metadata, recipe_scanner=None, civitai_client=None) -> Dict[str, Any]:
         """Parse metadata from Civitai image format
@@ -45,6 +66,26 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
         try:
             # Get metadata provider instead of using civitai_client directly
             metadata_provider = await get_default_metadata_provider()
+
+            # Civitai image responses may wrap the actual metadata inside a "meta" key
+            if (
+                isinstance(metadata, dict)
+                and "meta" in metadata
+                and isinstance(metadata["meta"], dict)
+            ):
+                inner_meta = metadata["meta"]
+                if any(
+                    key in inner_meta
+                    for key in (
+                        "resources",
+                        "civitaiResources",
+                        "additionalResources",
+                        "hashes",
+                        "prompt",
+                        "negativePrompt",
+                    )
+                ):
+                    metadata = inner_meta
             
             # Initialize result structure
             result = {
@@ -62,8 +103,9 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
             lora_hashes = {}
             if "hashes" in metadata and isinstance(metadata["hashes"], dict):
                 for key, hash_value in metadata["hashes"].items():
-                    if key.startswith("LORA:"):
-                        lora_name = key.replace("LORA:", "")
+                    key_str = str(key)
+                    if key_str.lower().startswith("lora:"):
+                        lora_name = key_str.split(":", 1)[1]
                         lora_hashes[lora_name] = hash_value
             
             # Extract prompt and negative prompt

py/services/recipes/analysis_service.py

@@ -107,6 +107,12 @@ class RecipeAnalysisService:
                     raise RecipeDownloadError("No image URL found in Civitai response")
                 await self._download_image(image_url, temp_path)
                 metadata = image_info.get("meta") if "meta" in image_info else None
+                if (
+                    isinstance(metadata, dict)
+                    and "meta" in metadata
+                    and isinstance(metadata["meta"], dict)
+                ):
+                    metadata = metadata["meta"]
             else:
                 await self._download_image(url, temp_path)
 

tests/services/test_civitai_image_parser.py

@@ -60,6 +60,46 @@ async def test_parse_metadata_creates_loras_from_hashes(monkeypatch):
     }
 
 
+@pytest.mark.asyncio
+async def test_parse_metadata_handles_nested_meta_and_lowercase_hashes(monkeypatch):
+    async def fake_metadata_provider():
+        return None
+
+    monkeypatch.setattr(
+        "py.recipes.parsers.civitai_image.get_default_metadata_provider",
+        fake_metadata_provider,
+    )
+
+    parser = CivitaiApiMetadataParser()
+
+    metadata = {
+        "id": 106706587,
+        "meta": {
+            "prompt": "An enigmatic silhouette",
+            "hashes": {
+                "model": "ee75fd24a4",
+                "lora:mj": "de49e1e98c",
+                "LORA:Another_Earth_2": "dc11b64a8b",
+            },
+            "resources": [
+                {
+                    "hash": "ee75fd24a4",
+                    "name": "stoiqoNewrealityFLUXSD35_f1DAlphaTwo",
+                    "type": "model",
+                }
+            ],
+        },
+    }
+
+    assert parser.is_metadata_matching(metadata)
+
+    result = await parser.parse_metadata(metadata)
+
+    assert result["gen_params"]["prompt"] == "An enigmatic silhouette"
+    assert {l["name"] for l in result["loras"]} == {"mj", "Another_Earth_2"}
+    assert {l["hash"] for l in result["loras"]} == {"de49e1e98c", "dc11b64a8b"}
+
+
 @pytest.mark.asyncio
 async def test_parse_metadata_populates_checkpoint_and_rewrites_thumbnails(monkeypatch):
     checkpoint_info = {