Merge branch 'AUTOMATIC1111:master' into sub-quad_attn_opt

2 files changed, 40 insertions, 14 deletions

diff --git a/modules/api/api.py b/modules/api/api.py
index 1ceba75d..9c670f00 100644
--- a/modules/api/api.py
+++ b/modules/api/api.py
@@ -100,6 +100,7 @@ class Api:
         self.add_api_route("/sdapi/v1/prompt-styles", self.get_prompt_styles, methods=["GET"], response_model=List[PromptStyleItem])
         self.add_api_route("/sdapi/v1/artist-categories", self.get_artists_categories, methods=["GET"], response_model=List[str])
         self.add_api_route("/sdapi/v1/artists", self.get_artists, methods=["GET"], response_model=List[ArtistItem])
+        self.add_api_route("/sdapi/v1/embeddings", self.get_embeddings, methods=["GET"], response_model=EmbeddingsResponse)
         self.add_api_route("/sdapi/v1/refresh-checkpoints", self.refresh_checkpoints, methods=["POST"])
         self.add_api_route("/sdapi/v1/create/embedding", self.create_embedding, methods=["POST"], response_model=CreateResponse)
         self.add_api_route("/sdapi/v1/create/hypernetwork", self.create_hypernetwork, methods=["POST"], response_model=CreateResponse)
@@ -121,7 +122,6 @@ class Api:
 
     def text2imgapi(self, txt2imgreq: StableDiffusionTxt2ImgProcessingAPI):
         populate = txt2imgreq.copy(update={ # Override __init__ params
-            "sd_model": shared.sd_model,
             "sampler_name": validate_sampler_name(txt2imgreq.sampler_name or txt2imgreq.sampler_index),
             "do_not_save_samples": True,
             "do_not_save_grid": True
@@ -129,15 +129,14 @@ class Api:
         )
         if populate.sampler_name:
             populate.sampler_index = None  # prevent a warning later on
-        p = StableDiffusionProcessingTxt2Img(**vars(populate))
-        # Override object param
-
-        shared.state.begin()
 
         with self.queue_lock:
+            p = StableDiffusionProcessingTxt2Img(sd_model=shared.sd_model, **vars(populate))
+
+            shared.state.begin()
             processed = process_images(p)
+            shared.state.end()
 
-        shared.state.end()
 
         b64images = list(map(encode_pil_to_base64, processed.images))
 
@@ -153,7 +152,6 @@ class Api:
             mask = decode_base64_to_image(mask)
 
         populate = img2imgreq.copy(update={ # Override __init__ params
-            "sd_model": shared.sd_model,
             "sampler_name": validate_sampler_name(img2imgreq.sampler_name or img2imgreq.sampler_index),
             "do_not_save_samples": True,
             "do_not_save_grid": True,
@@ -165,16 +163,14 @@ class Api:
 
         args = vars(populate)
         args.pop('include_init_images', None)  # this is meant to be done by "exclude": True in model, but it's for a reason that I cannot determine.
-        p = StableDiffusionProcessingImg2Img(**args)
-
-        p.init_images = [decode_base64_to_image(x) for x in init_images]
-
-        shared.state.begin()
 
         with self.queue_lock:
-            processed = process_images(p)
+            p = StableDiffusionProcessingImg2Img(sd_model=shared.sd_model, **args)
+            p.init_images = [decode_base64_to_image(x) for x in init_images]
 
-        shared.state.end()
+            shared.state.begin()
+            processed = process_images(p)
+            shared.state.end()
 
         b64images = list(map(encode_pil_to_base64, processed.images))
 
@@ -332,6 +328,26 @@ class Api:
     def get_artists(self):
         return [{"name":x[0], "score":x[1], "category":x[2]} for x in shared.artist_db.artists]
 
+    def get_embeddings(self):
+        db = sd_hijack.model_hijack.embedding_db
+
+        def convert_embedding(embedding):
+            return {
+                "step": embedding.step,
+                "sd_checkpoint": embedding.sd_checkpoint,
+                "sd_checkpoint_name": embedding.sd_checkpoint_name,
+                "shape": embedding.shape,
+                "vectors": embedding.vectors,
+            }
+
+        def convert_embeddings(embeddings):
+            return {embedding.name: convert_embedding(embedding) for embedding in embeddings.values()}
+
+        return {
+            "loaded": convert_embeddings(db.word_embeddings),
+            "skipped": convert_embeddings(db.skipped_embeddings),
+        }
+
     def refresh_checkpoints(self):
         shared.refresh_checkpoints()
 
diff --git a/modules/api/models.py b/modules/api/models.py
index c446ce7a..4a632c68 100644
--- a/modules/api/models.py
+++ b/modules/api/models.py
@@ -249,3 +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)")
\ No newline at end of file