Local embeddings support (CLI autocomplete) (#2211)

* integrate local embeds with HF embeds

* Update concepts_lib.py

* Update concepts_lib.py

Co-authored-by: BuildTools <unconfigured@null.spigotmc.org>
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>

.gitignore

@@ -1,4 +1,5 @@
 # ignore default image save location and model symbolic link
+embeddings/
 outputs/
 models/ldm/stable-diffusion-v1/model.ckpt
 **/restoration/codeformer/weights

ldm/invoke/concepts_lib.py

@@ -19,6 +19,7 @@ class Concepts(object):
         '''
         self.root = root or Globals.root
         self.hf_api = HfApi()
+        self.local_concepts = dict()
         self.concept_list = None
         self.concepts_loaded = dict()
         self.triggers = dict()            # concept name to trigger phrase
@@ -28,17 +29,28 @@ class Concepts(object):
 
     def list_concepts(self)->list:
         '''
-        Return a list of all the concepts by name, without the 'sd-concepts-library' part.
+        Return a list of all the concepts by name, without the 'sd-concepts-library' part. 
+        Also adds local concepts in invokeai/embeddings folder.
         '''
+        local_concepts_now = self.get_local_concepts(os.path.join(self.root, 'embeddings'))
+        local_concepts_to_add = set(local_concepts_now).difference(set(self.local_concepts))
+        self.local_concepts.update(local_concepts_now)
+
         if self.concept_list is not None:
+            if local_concepts_to_add:
+                self.concept_list.extend(list(local_concepts_to_add))
+                return self.concept_list
+            return self.concept_list
+        else:
+            try:
+                models = self.hf_api.list_models(filter=ModelFilter(model_name='sd-concepts-library/'))
+                self.concept_list = [a.id.split('/')[1] for a in models]
+                # when init, add all in dir. when not init, add only concepts added between init and now
+                self.concept_list.extend(list(local_concepts_to_add))
+            except Exception as e:
+                print(f' ** WARNING: Hugging Face textual inversion concepts libraries could not be loaded. The error was {str(e)}.')
+                print(' ** You may load .bin and .pt file(s) manually using the --embedding_directory argument.')
             return self.concept_list
-        try:
-            models = self.hf_api.list_models(filter=ModelFilter(model_name='sd-concepts-library/'))
-            self.concept_list = [a.id.split('/')[1] for a in models]
-        except Exception as e:
-            print(f' ** WARNING: Hugging Face textual inversion concepts libraries could not be loaded. The error was {str(e)}.')
-            print(' ** You may load .bin and .pt file(s) manually using the --embedding_directory argument.')
-        return self.concept_list
 
     def get_concept_model_path(self, concept_name:str)->str:
         '''
@@ -58,6 +70,12 @@ class Concepts(object):
         '''
         if concept_name in self.triggers:
             return self.triggers[concept_name]
+        elif self.concept_is_local(concept_name):
+            trigger = f'<{concept_name}>'   
+            self.triggers[concept_name] = trigger
+            self.concept_names[trigger] = concept_name
+            return trigger
+        
         file = self.get_concept_file(concept_name, 'token_identifier.txt', local_only=True)
         if not file:
             return None
@@ -115,10 +133,20 @@ class Concepts(object):
         return self.match_concept.sub(do_replace, prompt)
 
     def get_concept_file(self, concept_name:str, file_name:str='learned_embeds.bin' , local_only:bool=False)->str:
-        if not self.concept_is_downloaded(concept_name) and not local_only:
+        if not (self.concept_is_downloaded(concept_name) or self.concept_is_local(concept_name) or local_only):
             self.download_concept(concept_name)
-        path = os.path.join(self._concept_path(concept_name), file_name)
+        
+        # get local path in invokeai/embeddings if local concept
+        if self.concept_is_local(concept_name):
+            concept_path = self._concept_local_path(concept_name)
+            path = concept_path
+        else:
+            concept_path = self._concept_path(concept_name)
+            path = os.path.join(concept_path, file_name)
         return path if os.path.exists(path) else None
+    
+    def concept_is_local(self, concept_name)->bool:
+        return concept_name in self.local_concepts
 
     def concept_is_downloaded(self, concept_name)->bool:
         concept_directory = self._concept_path(concept_name)
@@ -167,3 +195,16 @@ class Concepts(object):
 
     def _concept_path(self, concept_name:str)->str:
         return os.path.join(self.root,'models','sd-concepts-library',concept_name)
+
+    def _concept_local_path(self, concept_name:str)->str:
+        filename = self.local_concepts[concept_name] 
+        return os.path.join(self.root,'embeddings',filename)
+
+    def get_local_concepts(self, loc_dir:str):
+        locs_dic = dict()
+        if os.path.isdir(loc_dir):
+            for file in os.listdir(loc_dir):
+                f = os.path.splitext(file)
+                if f[1] == '.bin' or f[1] == '.pt':
+                    locs_dic[f[0]] = file
+        return locs_dic

ldm/invoke/readline.py

@@ -126,6 +126,7 @@ class Completer(object):
             elif re.search('(-S\s*|--seed[=\s])\d*$',buffer):
                 self.matches= self._seed_completions(text,state)
 
+            # looking for an embedding concept
             elif re.search('<[\w-]*$',buffer):
                 self.matches= self._concept_completions(text,state)
 
@@ -272,12 +273,15 @@ class Completer(object):
     def add_embedding_terms(self, terms:list[str]):
         self.embedding_terms = set(terms)
         if self.concepts:
-            self.embedding_terms.update(self.concepts)
+            self.embedding_terms.update(set(self.concepts.list_concepts()))
 
     def _concept_completions(self, text, state):
         if self.concepts is None:
-            self.concepts = set(Concepts().list_concepts())
+            # cache Concepts() instance so we can check for updates in concepts_list during runtime.
-            self.embedding_terms.update(self.concepts)
+            self.concepts = Concepts()
+            self.embedding_terms.update(set(self.concepts.list_concepts()))
+        else:
+            self.embedding_terms.update(set(self.concepts.list_concepts()))
 
         partial = text[1:]  # this removes the leading '<'
         if len(partial) == 0: