Make visual features configurable by the user

libs/community/langchain_community/tools/azure_ai_services/image_analysis.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import logging
-from typing import Any, Dict, Optional
+from typing import Any, Dict, List, Optional
 
 from langchain_core.callbacks import CallbackManagerForToolRun
 from langchain_core.tools import BaseTool
@@ -22,16 +22,17 @@ class AzureAiServicesImageAnalysisTool(BaseTool):
     https://learn.microsoft.com/en-us/azure/ai-services/computer-vision/quickstarts-sdk/image-analysis-client-library-40
     """
 
-    azure_ai_services_key: str = ""  #: :meta private:
-    azure_ai_services_endpoint: str = ""  #: :meta private:
+    azure_ai_services_key: Optional[str] = None  #: :meta private:
+    azure_ai_services_endpoint: Optional[str] = None  #: :meta private:
+    visual_features: Optional[List[str]] = None
     image_analysis_client: Any  #: :meta private:
-    visual_features: Any  #: :meta private:
+    formatted_features: Any #: :meta private:
 
     name: str = "azure_ai_services_image_analysis"
     description: str = (
         "A wrapper around Azure AI Services Image Analysis. "
         "Useful for when you need to analyze images. "
-        "Input should be a url to an image."
+        "Input must be a url string or path string to an image."
     )
 
     @model_validator(mode="before")
@@ -67,36 +68,36 @@ def validate_environment(cls, values: Dict) -> Any:
             raise RuntimeError(
                 f"Initialization of Azure AI Vision Image Analysis client failed: {e}"
             )
-
-        values["visual_features"] = [
-            VisualFeatures.TAGS,
-            VisualFeatures.OBJECTS,
-            VisualFeatures.CAPTION,
-            VisualFeatures.READ,
-        ]
+
+        visual_features: List[str] = values.get("visual_features", ["TAGS"])
+        values["formatted_features"] = [
+                        VisualFeatures[feat.upper()] for feat in visual_features
+                        ]
 
         return values
 
     def _image_analysis(self, image_path: str) -> Dict:
         try:
             from azure.ai.vision.imageanalysis import ImageAnalysisClient
+            from azure.ai.vision.imageanalysis.models import VisualFeatures
         except ImportError:
             pass
 
         self.image_analysis_client: ImageAnalysisClient
-
+        self.formatted_features: List[VisualFeatures]
+
         image_src_type = detect_file_src_type(image_path)
         if image_src_type == "local":
             with open(image_path, "rb") as image_file:
                 image_data = image_file.read()
             result = self.image_analysis_client.analyze(
                 image_data=image_data,
-                visual_features=self.visual_features,
+                visual_features=self.formatted_features,
             )
         elif image_src_type == "remote":
             result = self.image_analysis_client.analyze_from_url(
                 image_url=image_path,
-                visual_features=self.visual_features,
+                visual_features=self.formatted_features,
             )
         else:
             raise ValueError(f"Invalid image path: {image_path}")