Merge branch 'main' into security/scan-ckpt-files-main

invokeai/backend/generator/base.py

@@ -154,6 +154,7 @@ class InvokeAIGenerator(metaclass=ABCMeta):
         for i in iteration_count:
             results = generator.generate(prompt,
                                          conditioning=(uc, c, extra_conditioning_info),
+                                         step_callback=step_callback,
                                          sampler=scheduler,
                                          **generator_args,
                                          )

invokeai/backend/model_management/model_manager.py

@@ -362,6 +362,7 @@ class ModelManager(object):
             raise NotImplementedError(
                 f"Unknown model format {model_name}: {model_format}"
             )
+        self._add_embeddings_to_model(model)
         
         # usage statistics
         toc = time.time()
@@ -434,10 +435,9 @@ class ModelManager(object):
         # square images???
         width = pipeline.unet.config.sample_size * pipeline.vae_scale_factor
         height = width
-
         print(f"   | Default image dimensions = {width} x {height}")
-        self._add_embeddings_to_model(pipeline)
         
+        self._add_embeddings_to_model(pipeline)
         return pipeline, width, height, model_hash
 
     def _load_ckpt_model(self, model_name, mconfig):

invokeai/backend/stable_diffusion/concepts_lib.py

@@ -6,7 +6,6 @@ The interface is through the Concepts() object.
 """
 import os
 import re
-import traceback
 from typing import Callable
 from urllib import error as ul_error
 from urllib import request
@@ -15,7 +14,6 @@ from huggingface_hub import (
     HfApi,
     HfFolder,
     ModelFilter,
-    ModelSearchArguments,
     hf_hub_url,
 )
 
@@ -84,7 +82,7 @@ class HuggingFaceConceptsLibrary(object):
         """
         if not concept_name in self.list_concepts():
             print(
-                f"This concept is not a local embedding trigger, nor is it a HuggingFace concept. Generation will continue without the concept."
+                f"{concept_name} is not a local embedding trigger, nor is it a HuggingFace concept. Generation will continue without the concept."
             )
             return None
         return self.get_concept_file(concept_name.lower(), "learned_embeds.bin")
@@ -236,7 +234,7 @@ class HuggingFaceConceptsLibrary(object):
         except ul_error.HTTPError as e:
             if e.code == 404:
                 print(
-                    f"This concept is not known to the Hugging Face library. Generation will continue without the concept."
+                    f"Concept {concept_name} is not known to the Hugging Face library. Generation will continue without the concept."
                 )
             else:
                 print(
@@ -246,7 +244,7 @@ class HuggingFaceConceptsLibrary(object):
             return False
         except ul_error.URLError as e:
             print(
-                f"ERROR: {str(e)}. This may reflect a network issue. Generation will continue without the concept."
+                f"ERROR while downloading {concept_name}: {str(e)}. This may reflect a network issue. Generation will continue without the concept."
             )
             os.rmdir(dest)
             return False

pyproject.toml

@@ -38,7 +38,7 @@ dependencies = [
   "albumentations",
   "click",
   "clip_anytorch",          # replacing "clip @ https://github.com/openai/CLIP/archive/eaa22acb90a5876642d0507623e859909230a52d.zip",
-  "compel==1.0.1",
+  "compel==1.0.4",
   "datasets",
   "diffusers[torch]~=0.14",
   "dnspython==2.2.1",