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Diffstat (limited to 'modules/api/models.py')
| -rw-r--r-- | modules/api/models.py | 19 |
1 files changed, 19 insertions, 0 deletions
diff --git a/modules/api/models.py b/modules/api/models.py index a22bc6b3..4a632c68 100644 --- a/modules/api/models.py +++ b/modules/api/models.py @@ -175,6 +175,15 @@ class InterrogateRequest(BaseModel): class InterrogateResponse(BaseModel): caption: str = Field(default=None, title="Caption", description="The generated caption for the image.") +class TrainResponse(BaseModel): + info: str = Field(title="Train info", description="Response string from train embedding or hypernetwork task.") + +class CreateResponse(BaseModel): + info: str = Field(title="Create info", description="Response string from create embedding or hypernetwork task.") + +class PreprocessResponse(BaseModel): + info: str = Field(title="Preprocess info", description="Response string from preprocessing task.") + fields = {} for key, metadata in opts.data_labels.items(): value = opts.data.get(key) @@ -240,3 +249,13 @@ class ArtistItem(BaseModel): score: float = Field(title="Score") category: str = Field(title="Category") +class EmbeddingItem(BaseModel): + step: Optional[int] = Field(title="Step", description="The number of steps that were used to train this embedding, if available") + sd_checkpoint: Optional[str] = Field(title="SD Checkpoint", description="The hash of the checkpoint this embedding was trained on, if available") + sd_checkpoint_name: Optional[str] = Field(title="SD Checkpoint Name", description="The name of the checkpoint this embedding was trained on, if available. Note that this is the name that was used by the trainer; for a stable identifier, use `sd_checkpoint` instead") + shape: int = Field(title="Shape", description="The length of each individual vector in the embedding") + vectors: int = Field(title="Vectors", description="The number of vectors in the embedding") + +class EmbeddingsResponse(BaseModel): + loaded: Dict[str, EmbeddingItem] = Field(title="Loaded", description="Embeddings loaded for the current model") + skipped: Dict[str, EmbeddingItem] = Field(title="Skipped", description="Embeddings skipped for the current model (likely due to architecture incompatibility)")
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