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Complete the following steps to create a .NET console app to connect to an AI model.
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## Add the app code
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The app uses the [`Microsoft.Extensions.AI`](https://www.nuget.org/packages/Microsoft.Extensions.AI/) package to send and receive requests to the AI model and is designed to provide users with information about hiking trails.
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This app uses the [`Microsoft.Extensions.AI`](https://www.nuget.org/packages/Microsoft.Extensions.AI/) package to send and receive requests to the AI model. The app provides users with information about hiking trails.
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1. In the **Program.cs** file, add the following code to connect and authenticate to the AI model.
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1. In the `Program.cs` file, add the following code to connect and authenticate to the AI model.
> <xref:Azure.Identity.DefaultAzureCredential> searches for authentication credentials from your local tooling. If you aren't using the `azd` template to provision the Azure OpenAI resource, you'll need to assign the `Azure AI Developer` role to the account you used to sign in to Visual Studio or the Azure CLI. For more information, see [Authenticate to Azure AI services with .NET](../azure-ai-services-authentication.md).
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Vector stores or vector databases are essential for tasks like semantic search, Retrieval Augmented Generation (RAG), and other scenarios that require grounding generative AI responses. While relational databases and document databases are optimized for structured and semi-structured data, vector databases are built to efficiently store, index, and manage data represented as embedding vectors. As a result, the indexing and search algorithms used by vector databases are optimized to efficiently retrieve data that can be used downstream in your applications.
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Locate and open the saved image in the app *bin* directory, which should resemble the following:
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Locate and open the saved image in the app `bin` directory, which should resemble the following:
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:::image type="content" source="../media/assistants/generated-sales-graph.png" alt-text="A graph showing the visualization generated by the AI model.":::
Copy file name to clipboardExpand all lines: docs/ai/quickstarts/evaluate-ai-response.md
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Run the test using your preferred test workflow, for example, by using the CLI command `dotnet test` or through [Test Explorer](/visualstudio/test/run-unit-tests-with-test-explorer).
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## Clean up resources
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If you no longer need them, delete the Azure OpenAI resource and GPT-4 model deployment.
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1. In the [Azure Portal](https://aka.ms/azureportal), navigate to the Azure OpenAI resource.
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1. Select the Azure OpenAI resource, and then select **Delete**.
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## Next steps
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- Evaluate the responses from different OpenAI models.
1. To provision an Azure OpenAI service and model, complete the steps in the [Create and deploy an Azure OpenAI Service resource](/azure/ai-services/openai/how-to/create-resource) article.
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1. From a terminal or command prompt, navigate to the root of your project directory.
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dotnet user-secrets set AZURE_OPENAI_ENDPOINT <your-azure-openai-endpoint>
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dotnet user-secrets set AZURE_OPENAI_GPT_NAME <your-azure-openai-model-name>
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