Address PR comments

Signed-off-by: Ashwin Vaidya <[email protected]>

src/anomalib/models/image/vlm_ad/backends/base.py

@@ -26,5 +26,5 @@ def predict(self, image: str | Path, prompt: Prompt) -> str:
 
     @property
     @abstractmethod
-    def reference_image_count(self) -> int:
+    def num_reference_images(self) -> int:
         """Get the number of reference images."""

src/anomalib/models/image/vlm_ad/backends/chat_gpt.py

@@ -10,13 +10,13 @@
 from typing import TYPE_CHECKING
 
 from dotenv import load_dotenv
+from lightning_utilities.core.imports import package_available
 
 from anomalib.models.image.vlm_ad.utils import Prompt
-from anomalib.utils.exceptions import try_import
 
 from .base import Backend
 
-if try_import("openai"):
+if package_available("openai"):
     from openai import OpenAI
 else:
     OpenAI = None
@@ -52,7 +52,7 @@ def add_reference_images(self, image: str | Path) -> None:
         self._ref_images_encoded.append(self._encode_image_to_url(image))
 
     @property
-    def reference_image_count(self) -> int:
+    def num_reference_images(self) -> int:
         """Get the number of reference images."""
         return len(self._ref_images_encoded)
 

src/anomalib/models/image/vlm_ad/backends/huggingface.py

@@ -6,15 +6,15 @@
 import logging
 from pathlib import Path
 
+from lightning_utilities.core.imports import package_available
 from PIL import Image
 from transformers.modeling_utils import PreTrainedModel
 
 from anomalib.models.image.vlm_ad.utils import Prompt
-from anomalib.utils.exceptions import try_import
 
 from .base import Backend
 
-if try_import("transformers"):
+if package_available("transformers"):
     import transformers
     from transformers.modeling_utils import PreTrainedModel
     from transformers.processing_utils import ProcessorMixin
@@ -31,11 +31,8 @@ class Huggingface(Backend):
     def __init__(
         self,
         model_name: str,
-        api_key: str | None = None,
     ) -> None:
         """Initialize the Huggingface backend."""
-        if api_key:
-            logger.warning("API key is not required for Huggingface backend.")
         self.model_name: str = model_name
         self._ref_images: list[str] = []
         self._processor: ProcessorMixin | None = None
@@ -76,7 +73,7 @@ def add_reference_images(self, image: str | Path) -> None:
         self._ref_images.append(Image.open(image))
 
     @property
-    def reference_image_count(self) -> int:
+    def num_reference_images(self) -> int:
         """Get the number of reference images."""
         return len(self._ref_images)
 

src/anomalib/models/image/vlm_ad/backends/ollama.py

@@ -3,6 +3,7 @@
 Assumes that the Ollama service is running in the background.
 See: https://github.com/ollama/ollama
 Ensure that ollama is running. On linux: `ollama serve`
+On Mac and Windows ensure that the ollama service is running by launching from the application list.
 """
 
 # Copyright (C) 2024 Intel Corporation
@@ -11,12 +12,13 @@
 import logging
 from pathlib import Path
 
+from lightning_utilities.core.imports import package_available
+
 from anomalib.models.image.vlm_ad.utils import Prompt
-from anomalib.utils.exceptions import try_import
 
 from .base import Backend
 
-if try_import("ollama"):
+if package_available("ollama"):
     from ollama import chat
     from ollama._client import _encode_image
 else:
@@ -38,7 +40,7 @@ def add_reference_images(self, image: str | Path) -> None:
         self._ref_images_encoded.append(_encode_image(image))
 
     @property
-    def reference_image_count(self) -> int:
+    def num_reference_images(self) -> int:
         """Get the number of reference images."""
         return len(self._ref_images_encoded)
 

src/anomalib/models/image/vlm_ad/lightning_model.py

@@ -29,10 +29,10 @@ def __init__(
         super().__init__()
         self.k_shot = k_shot
         model = VLMModel(model)
-        self.vlm_backend: Backend = self._setup_vlm(model, api_key)
+        self.vlm_backend: Backend = self._setup_vlm_backend(model, api_key)
 
     @staticmethod
-    def _setup_vlm(model: VLMModel, api_key: str | None) -> Backend:
+    def _setup_vlm_backend(model: VLMModel, api_key: str | None) -> Backend:
         if model == VLMModel.LLAMA_OLLAMA:
             return Ollama(model_name=model.value)
         if model == VLMModel.GPT_4O_MINI:
@@ -44,7 +44,7 @@ def _setup_vlm(model: VLMModel, api_key: str | None) -> Backend:
         raise ValueError(msg)
 
     def _setup(self) -> None:
-        if self.k_shot > 0 and self.vlm_backend.reference_image_count != self.k_shot:
+        if self.k_shot > 0 and self.vlm_backend.num_reference_images != self.k_shot:
             logger.info("Collecting reference images from training dataset.")
             dataloader = self.trainer.datamodule.train_dataloader()
             self.collect_reference_images(dataloader)
@@ -54,7 +54,7 @@ def collect_reference_images(self, dataloader: DataLoader) -> None:
         for batch in dataloader:
             for img_path in batch["image_path"]:
                 self.vlm_backend.add_reference_images(img_path)
-                if self.vlm_backend.reference_image_count == self.k_shot:
+                if self.vlm_backend.num_reference_images == self.k_shot:
                     return
 
     @property
@@ -110,18 +110,10 @@ def to_torch(  # type: ignore[override]
         """Skip export to torch."""
         return self._export_not_supported_message()
 
-    def to_onnx(  # type: ignore[override]
-        self,
-        *_,
-        **__,
-    ) -> None:
+    def to_onnx(self, *_, **__) -> None:  # type: ignore[override]
         """Skip export to onnx."""
         return self._export_not_supported_message()
 
-    def to_openvino(  # type: ignore[override]
-        self,
-        *_,
-        **__,
-    ) -> None:
+    def to_openvino(self, *_, **__) -> None:  # type: ignore[override]
         """Skip export to openvino."""
         return self._export_not_supported_message()