diff --git a/invokeai/app/invocations/ip_adapter.py b/invokeai/app/invocations/ip_adapter.py
index cb686c906b..0fc9c90128 100644
--- a/invokeai/app/invocations/ip_adapter.py
+++ b/invokeai/app/invocations/ip_adapter.py
@@ -15,7 +15,7 @@ from invokeai.app.invocations.model import ModelIdentifierField
 from invokeai.app.invocations.primitives import ImageField
 from invokeai.app.invocations.util import validate_begin_end_step, validate_weights
 from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.backend.model_manager.config import BaseModelType, IPAdapterConfig, ModelType
+from invokeai.backend.model_manager.config import AnyModelConfig, BaseModelType, IPAdapterConfig, ModelType
 
 
 class IPAdapterField(BaseModel):
@@ -89,17 +89,32 @@ class IPAdapterInvocation(BaseInvocation):
         assert isinstance(ip_adapter_info, IPAdapterConfig)
         image_encoder_model_id = ip_adapter_info.image_encoder_model_id
         image_encoder_model_name = image_encoder_model_id.split("/")[-1].strip()
-        image_encoder_models = context.models.search_by_attrs(
-            name=image_encoder_model_name, base=BaseModelType.Any, type=ModelType.CLIPVision
-        )
-        assert len(image_encoder_models) == 1
+        image_encoder_model = self._get_image_encoder(context, image_encoder_model_name)
         return IPAdapterOutput(
             ip_adapter=IPAdapterField(
                 image=self.image,
                 ip_adapter_model=self.ip_adapter_model,
-                image_encoder_model=ModelIdentifierField.from_config(image_encoder_models[0]),
+                image_encoder_model=ModelIdentifierField.from_config(image_encoder_model),
                 weight=self.weight,
                 begin_step_percent=self.begin_step_percent,
                 end_step_percent=self.end_step_percent,
             ),
         )
+
+    def _get_image_encoder(self, context: InvocationContext, image_encoder_model_name: str) -> AnyModelConfig:
+        found = False
+        while not found:
+            image_encoder_models = context.models.search_by_attrs(
+                name=image_encoder_model_name, base=BaseModelType.Any, type=ModelType.CLIPVision
+            )
+            found = len(image_encoder_models) > 0
+            if not found:
+                context.logger.warning(
+                    f"The image encoder required by this IP Adapter ({image_encoder_model_name}) is not installed."
+                )
+                context.logger.warning("Downloading and installing now. This may take a while.")
+                installer = context._services.model_manager.install
+                job = installer.heuristic_import(f"InvokeAI/{image_encoder_model_name}")
+                installer.wait_for_job(job, timeout=600)  # wait up to 10 minutes - then raise a TimeoutException
+        assert len(image_encoder_models) == 1
+        return image_encoder_models[0]