fix: restore .NET quickstart to match upstream (remove from Python PR)

Remove duplicated front matter/title/intro block that was accidentally
spliced into the .NET quickstart article body. Revert azure.yaml and
gpt-4.1-mini cross-cutting fixes so this file matches upstream/main
exactly and drops out of the Python PR #4702 diff. Those fixes live
in their own PRs (#4700, #4701, #4705).

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Author: diberry

articles/cosmos-db/quickstart-vector-store-dotnet.md

@@ -22,30 +22,6 @@ ms.custom:
 
 Learn to use vector search in Azure Cosmos DB to store and query vector data efficiently. This quickstart provides a guided tour of key vector search techniques using a [.NET sample app](https://github.com/Azure-Samples/cosmos-db-vector-samples/tree/main/nosql-vector-search-dotnet) on GitHub.
 
-The app uses a sample hotel dataset in a ---
-
-title: Quickstart - Azure Cosmos DB vector search with .NET
-description: Learn how to use vector search in Azure Cosmos DB with .NET. Store and query vector data efficiently in your applications. 
-author: alexwolfmsft
-ms.author: alexwolf
-ms.reviewer: khelanmodi
-ms.devlang: csharp
-ms.topic: quickstart-sdk
-ms.date: 02/06/2026
-ms.service: azure-cosmos-db
-ms.subservice: nosql
-ai-usage: ai-assisted
-ms.custom:
-  - devx-track-dotnet
-  - devx-track-dotnet-ai
-  - devx-track-data-ai
-# CustomerIntent: As a developer, I want to learn how to use vector search in .NET applications with Azure Cosmos DB.
----
-
-# Quickstart: Vector search with .NET in Azure Cosmos DB
-
-Learn to use vector search in Azure Cosmos DB to store and query vector data efficiently. This quickstart provides a guided tour of key vector search techniques using a [.NET sample app](https://github.com/Azure-Samples/cosmos-db-vector-samples/tree/main/nosql-vector-search-dotnet) on GitHub.
-
 The app uses a sample hotel dataset in a JSON file with calculated vectors from the `text-embedding-3-small` model. The hotel data includes hotel names, locations, descriptions, and vector embeddings.
 
 ## Prerequisites
@@ -108,7 +84,7 @@ To provision resources:
     git clone https://github.com/Azure-Samples/cosmos-db-vector-samples.git
     ```
 
-1. Navigate to the root folder of the cloned repository (where `azure.yaml` is located), for example:
+1. Navigate to the root folder of the cloned repository (where `azure.yml` is located), for example:
 
     ```bash
     cd cosmos-db-vector-samples
@@ -127,7 +103,7 @@ Follow the prompts to select your Azure subscription and environment.
 * **Azure Cosmos DB**: Serverless account with the `Hotels` database and containers
 * **Azure OpenAI**: Resource with deployments for:
   * Embedding model: `text-embedding-3-small`
-  * Chat model: `gpt-4.1-mini`
+  * Chat model: `gpt-4o-mini`
 * **Managed Identity**: User-assigned identity for secure access.
 * Azure RBAC role assignments that enable Microsoft Entra ID (passwordless) access for the managed identity to Azure Cosmos DB and Azure OpenAI.
 
@@ -330,4 +306,4 @@ In the preceding code, the `CosmosDBService` performs the following tasks:
 - [Vector search in Azure Cosmos DB](gen-ai/vector-search-overview.md)
 - [Document Indexer for Azure Cosmos DB (preview)](gen-ai/document-indexer.md)
 - [Vector embeddings in Azure Cosmos DB](gen-ai/vector-embeddings.md)
-- [Azure RBAC built-in roles](/azure/role-based-access-control/built-in-roles)
+- [Azure RBAC built-in roles](/azure/role-based-access-control/built-in-roles)