probe for required encoder for IPAdapters and add to config

invokeai/app/invocations/ip_adapter.py

@@ -1,4 +1,3 @@
-import os
 from builtins import float
 from typing import List, Union
 
@@ -52,16 +51,6 @@ class IPAdapterField(BaseModel):
         return self
 
 
-def get_ip_adapter_image_encoder_model_id(model_path: str):
-    """Read the ID of the image encoder associated with the IP-Adapter at `model_path`."""
-    image_encoder_config_file = os.path.join(model_path, "image_encoder.txt")
-
-    with open(image_encoder_config_file, "r") as f:
-        image_encoder_model = f.readline().strip()
-
-    return image_encoder_model
-
-
 @invocation_output("ip_adapter_output")
 class IPAdapterOutput(BaseInvocationOutput):
     # Outputs
@@ -102,18 +91,7 @@ class IPAdapterInvocation(BaseInvocation):
     def invoke(self, context: InvocationContext) -> IPAdapterOutput:
         # Lookup the CLIP Vision encoder that is intended to be used with the IP-Adapter model.
         ip_adapter_info = context.services.model_records.get_model(self.ip_adapter_model.key)
-        # HACK(ryand): This is bad for a couple of reasons: 1) we are bypassing the model manager to read the model
-        # directly, and 2) we are reading from disk every time this invocation is called without caching the result.
-        # A better solution would be to store the image encoder model reference in the IP-Adapter model info, but this
-        # is currently messy due to differences between how the model info is generated when installing a model from
-        # disk vs. downloading the model.
-        # TODO (LS): Fix the issue above by:
-        #    1. Change IPAdapterConfig definition to include a field for the repo_id of the image encoder model.
-        #    2. Update probe.py to read `image_encoder.txt` and store it in the config.
-        #    3. Change below to get the image encoder from the configuration record.
-        image_encoder_model_id = get_ip_adapter_image_encoder_model_id(
-            os.path.join(context.services.configuration.get_config().models_path, ip_adapter_info.path)
-        )
+        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.services.model_records.search_by_attr(
             model_name=image_encoder_model_name, base_model=BaseModelType.Any, model_type=ModelType.CLIPVision

invokeai/backend/model_manager/config.py

@@ -263,6 +263,7 @@ class IPAdapterConfig(ModelConfigBase):
     """Model config for IP Adaptor format models."""
 
     type: Literal[ModelType.IPAdapter] = ModelType.IPAdapter
+    image_encoder_model_id: str
     format: Literal[ModelFormat.InvokeAI]
 
 

invokeai/backend/model_manager/probe.py

@@ -78,6 +78,10 @@ class ProbeBase(object):
         """Get model scheduler prediction type."""
         return None
 
+    def get_image_encoder_model_id(self) -> Optional[str]:
+        """Get image encoder (IP adapters only)."""
+        return None
+
 
 class ModelProbe(object):
     PROBES: Dict[str, Dict[ModelType, type[ProbeBase]]] = {
@@ -153,6 +157,7 @@ class ModelProbe(object):
         fields["base"] = fields.get("base") or probe.get_base_type()
         fields["variant"] = fields.get("variant") or probe.get_variant_type()
         fields["prediction_type"] = fields.get("prediction_type") or probe.get_scheduler_prediction_type()
+        fields["image_encoder_model_id"] = fields.get("image_encoder_model_id") or probe.get_image_encoder_model_id()
         fields["name"] = fields.get("name") or cls.get_model_name(model_path)
         fields["description"] = (
             fields.get("description") or f"{fields['base'].value} {fields['type'].value} model {fields['name']}"
@@ -669,6 +674,14 @@ class IPAdapterFolderProbe(FolderProbeBase):
                 f"IP-Adapter had unexpected cross-attention dimension: {cross_attention_dim}."
             )
 
+    def get_image_encoder_model_id(self) -> Optional[str]:
+        encoder_id_path = self.model_path / "image_encoder.txt"
+        if not encoder_id_path.exists():
+            return None
+        with open(encoder_id_path, "r") as f:
+            image_encoder_model = f.readline().strip()
+        return image_encoder_model
+
 
 class CLIPVisionFolderProbe(FolderProbeBase):
     def get_base_type(self) -> BaseModelType: