Review comments

sdk/ai/azure-ai-projects/CHANGELOG.md

@@ -23,11 +23,12 @@ See [Agents package document and samples](https://github.com/Azure/azure-sdk-for
 * The method `.inference.get_azure_openai_client()` now supports returning an authenticated `AzureOpenAI` client to be used with
 AI models deployed to the Project's AI Services. This is in addition to the existing option to get an `AzureOpenAI` client for one of the connected Azure OpenAI services.
 * Import `PromptTemplate` from `azure.ai.projects` instead of `azure.ai.projects.prompts`.
-* The method `.to_evaluator_model_config` on connection is removed. In place of `model_config` use `deployment_name` for LLM based evaluators.
-* The method `upload_file` on `AIProjectClient` had been removed, use `dataset.upload_file` instead.
-* Evaluator Ids are available using the Enum `EvaluatorIds`and no longer require `azure-ai-evaluation` package to be installed.
-* Property `scope` on `AIProjectClient` is removed, use Project Endpoint instead.
-* Property `id` on Evaluation is replace with `name`.
+* The class ConnectionProperties was renamed to Connection, and its properties have changed.
+* The method `.to_evaluator_model_config` on `ConnectionProperties` is no longer required and does not have an equivalent method on `Connection`. When constructing the EvaluatorConfiguration class, the `init_params` element now requires `deployment_name` instead of `model_config`.
+* The method `upload_file` on `AIProjectClient` had been removed, use `datasets.upload_file` instead.
+* Evaluator Ids are available using the Enum `EvaluatorIds` and no longer require `azure-ai-evaluation` package to be installed.
+* Property `scope` on `AIProjectClient` is removed, use AI Foundry Project endpoint instead.
+* Property `id` on Evaluation is replaced with `name`.
 
 ### Sample updates
 

sdk/ai/azure-ai-projects/samples/evaluation/sample_evaluations.py

@@ -21,7 +21,7 @@
        Azure AI Foundry project.
     2) CONNECTION_NAME - Required. The name of the Azure Storage Account connection to use for uploading files.
     3) DATASET_NAME - Optional. The name of the Dataset to create and use in this sample.
-    4) DATASET_VERSION - Optional. The first version of the Dataset to create and use in this sample.
+    4) DATASET_VERSION - Optional. The version of the Dataset to create and use in this sample.
     6) DATA_FOLDER - Optional. The folder path where the data files for upload are located.
 """
 
@@ -56,7 +56,7 @@
 
         # [START evaluations_sample]
         print(
-            "Upload a single file and create a new Dataset to reference the file. Here we explicitly specify the dataset version."
+            "Upload a single file and create a new Dataset to reference the file."
         )
         dataset: DatasetVersion = project_client.datasets.upload_file(
             name=dataset_name,

sdk/ai/azure-ai-projects/samples/evaluation/sample_evaluations_async.py

@@ -21,7 +21,7 @@
        Azure AI Foundry project.
     2) CONNECTION_NAME - Required. The name of the Azure Storage Account connection to use for uploading files.
     3) DATASET_NAME - Optional. The name of the Dataset to create and use in this sample.
-    4) DATASET_VERSION - Optional. The first version of the Dataset to create and use in this sample.
+    4) DATASET_VERSION - Optional. The version of the Dataset to create and use in this sample.
     6) DATA_FOLDER - Optional. The folder path where the data files for upload are located.
 """
 import asyncio
@@ -55,9 +55,8 @@ async def main() -> None:
         async with AIProjectClient(endpoint=endpoint, credential=credential) as project_client:
 
             # [START evaluations_sample]
-            TODO : Uncomment the following lines once dataset creation works
             print(
-                "Upload a single file and create a new Dataset to reference the file. Here we explicitly specify the dataset version."
+                "Upload a single file and create a new Dataset to reference the file."
             )
             dataset: DatasetVersion = await project_client.datasets.upload_file(
                 name=dataset_name,