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fix(recipe): resolve base_model from parser and prevent empty checkpoint save on CivitAI import

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- Apply CivitaiApiMetadataParser's base_model result to metadata in
  _do_import_remote_recipe and _do_import_from_url (was previously discarded)
- Extract baseModel from raw civitai_info before populate_checkpoint_from_civitai
  so it's not lost when the type check rejects non-checkpoint model versions
- Only format and save checkpoint entry when it has real data (modelId, versionId,
  name, or version), preventing empty {'type': 'checkpoint'} stubs
This commit is contained in:
Will Miao
2026-06-01 17:58:08 +08:00
parent bfe7b5e1c7
commit ccf1c6f2ae
2 changed files with 56 additions and 28 deletions
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45
py/recipes/enrichment.py
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@@ -190,27 +190,42 @@ class RecipeEnricher:
existing_cp = recipe.get("checkpoint")
if existing_cp is None:
existing_cp = {}
# Extract baseModel from raw civitai_info before populate_checkpoint_from_civitai
# (populate may reject non-checkpoint types and lose this data)
base_model_from_civitai: str = ""
if isinstance(civitai_info, dict):
base_model_from_civitai = civitai_info.get("baseModel", "") or ""
elif isinstance(civitai_info, tuple) and len(civitai_info) > 0 and isinstance(civitai_info[0], dict):
base_model_from_civitai = civitai_info[0].get("baseModel", "") or ""
checkpoint_data = await RecipeMetadataParser.populate_checkpoint_from_civitai(existing_cp, civitai_info)
# 1. First, resolve base_model using full data before we format it away
# 1. Resolve base_model from checkpoint_data first, then fall back to raw civitai_info
current_base_model = recipe.get("base_model")
resolved_base_model = checkpoint_data.get("baseModel")
resolved_base_model = checkpoint_data.get("baseModel") or base_model_from_civitai
if resolved_base_model:
# Update if empty OR if it matches our generic prefix but is less specific
is_generic = not current_base_model or current_base_model.lower() in ["flux", "sdxl", "sd15"]
if is_generic and resolved_base_model != current_base_model:
recipe["base_model"] = resolved_base_model
# 2. Format according to requirements: type, modelId, modelVersionId, modelName, modelVersionName
formatted_checkpoint = {
"type": "checkpoint",
"modelId": checkpoint_data.get("modelId"),
"modelVersionId": checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
"modelName": checkpoint_data.get("name"), # In base.py, 'name' is populated from civitai_data['model']['name']
"modelVersionName": checkpoint_data.get("version") # In base.py, 'version' is populated from civitai_data['name']
}
# Remove None values
recipe["checkpoint"] = {k: v for k, v in formatted_checkpoint.items() if v is not None}
# 2. Only format and save checkpoint if it has real data (not just type after type rejection)
has_checkpoint_data = any([
checkpoint_data.get("modelId"),
checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
checkpoint_data.get("name"),
checkpoint_data.get("version"),
])
if has_checkpoint_data:
formatted_checkpoint = {
"type": "checkpoint",
"modelId": checkpoint_data.get("modelId"),
"modelVersionId": checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
"modelName": checkpoint_data.get("name"),
"modelVersionName": checkpoint_data.get("version"),
}
recipe["checkpoint"] = {k: v for k, v in formatted_checkpoint.items() if v is not None}
return True
else:
# Fallback to name extraction if we don't already have one