Extract TI loading logic into util, disallow it from ever failing a generation

invokeai/app/invocations/compel.py

@@ -16,7 +16,7 @@ from invokeai.app.invocations.fields import (
 from invokeai.app.invocations.primitives import ConditioningOutput
 from invokeai.app.services.model_records import UnknownModelException
 from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.app.util.ti_utils import extract_ti_triggers_from_prompt
+from invokeai.app.util.ti_utils import generate_ti_list
 from invokeai.backend.lora import LoRAModelRaw
 from invokeai.backend.model_manager.config import ModelType
 from invokeai.backend.model_patcher import ModelPatcher
@@ -86,26 +86,7 @@ class CompelInvocation(BaseInvocation):
 
         # loras = [(context.models.get(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
 
-        ti_list: List[Tuple[str, TextualInversionModelRaw]] = []
-        for trigger in extract_ti_triggers_from_prompt(self.prompt):
-            name_or_key = trigger[1:-1]
-            try:
-                loaded_model = context.models.load(key=name_or_key)
-                model = loaded_model.model
-                assert isinstance(model, TextualInversionModelRaw)
-                ti_list.append((name_or_key, model))
-            except UnknownModelException:
-                try:
-                    loaded_model = context.models.load_by_attrs(
-                        model_name=name_or_key, base_model=text_encoder_info.config.base, model_type=ModelType.TextualInversion
-                    )
-                    model = loaded_model.model
-                    assert isinstance(model, TextualInversionModelRaw)
-                    ti_list.append((name_or_key, model))
-                except UnknownModelException:
-                    logger.warning(f'trigger: "{trigger}" not found')
-            except ValueError:
-                logger.warning(f'trigger: "{trigger}" more than one similarly-named textual inversion models')
+        ti_list = generate_ti_list(self.prompt, text_encoder_info.config.base, context)
 
         with (
             ModelPatcher.apply_ti(tokenizer_model, text_encoder_model, ti_list) as (
@@ -206,26 +187,7 @@ class SDXLPromptInvocationBase:
 
         # loras = [(context.models.get(**lora.dict(exclude={"weight"})).context.model, lora.weight) for lora in self.clip.loras]
 
-        ti_list: List[Tuple[str, TextualInversionModelRaw]] = []
-        for trigger in extract_ti_triggers_from_prompt(prompt):
-            name_or_key = trigger[1:-1]
-            try:
-                loaded_model = context.models.load(key=name_or_key)
-                model = loaded_model.model
-                assert isinstance(model, TextualInversionModelRaw)
-                ti_list.append((name_or_key, model))
-            except UnknownModelException:
-                try:
-                    loaded_model = context.models.load_by_attrs(
-                        model_name=name_or_key, base_model=text_encoder_info.config.base, model_type=ModelType.TextualInversion
-                    )
-                    model = loaded_model.model
-                    assert isinstance(model, TextualInversionModelRaw)
-                    ti_list.append((name_or_key, model))
-                except UnknownModelException:
-                    logger.warning(f'trigger: "{trigger}" not found')
-            except ValueError:
-                logger.warning(f'trigger: "{trigger}" more than one similarly-named textual inversion models')
+        ti_list = generate_ti_list(prompt, text_encoder_info.config.base, context)
 
         with (
             ModelPatcher.apply_ti(tokenizer_model, text_encoder_model, ti_list) as (

invokeai/app/util/ti_utils.py

@@ -1,8 +1,44 @@
 import re
+from typing import List, Tuple
+
+from invokeai.backend.model_manager.config import BaseModelType, ModelType
+from invokeai.backend.textual_inversion import TextualInversionModelRaw
+from invokeai.app.services.shared.invocation_context import InvocationContext
+from invokeai.app.services.model_records import UnknownModelException
+import invokeai.backend.util.logging as logger
 
 
-def extract_ti_triggers_from_prompt(prompt: str) -> list[str]:
-    ti_triggers = []
+def extract_ti_triggers_from_prompt(prompt: str) -> List[str]:
+    ti_triggers: List[str] = []
     for trigger in re.findall(r"<[a-zA-Z0-9., _-]+>", prompt):
-        ti_triggers.append(trigger)
+        ti_triggers.append(str(trigger))
     return ti_triggers
+
+def generate_ti_list(prompt: str, base: BaseModelType, context: InvocationContext) -> List[Tuple[str, TextualInversionModelRaw]]:
+    ti_list: List[Tuple[str, TextualInversionModelRaw]] = []
+    for trigger in extract_ti_triggers_from_prompt(prompt):
+        name_or_key = trigger[1:-1]
+        try:
+            loaded_model = context.models.load(key=name_or_key)
+            model = loaded_model.model
+            assert isinstance(model, TextualInversionModelRaw)
+            assert loaded_model.config.base == base
+            ti_list.append((name_or_key, model))
+        except UnknownModelException:
+            try:
+                loaded_model = context.models.load_by_attrs(
+                    model_name=name_or_key, base_model=base, model_type=ModelType.TextualInversion
+                )
+                model = loaded_model.model
+                assert isinstance(model, TextualInversionModelRaw)
+                assert loaded_model.config.base == base
+                ti_list.append((name_or_key, model))
+            except UnknownModelException:
+                pass
+        except ValueError:
+            logger.warning(f'trigger: "{trigger}" more than one similarly-named textual inversion models')
+        except AssertionError:
+            logger.warning(f'trigger: "{trigger}" not a valid textual inversion model for this graph')
+        except Exception:
+            logger.warning(f'Failed to load TI model for trigger: "{trigger}"')
+    return ti_list