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go use data quickstart
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‎articles/ai-services/openai/includes/use-your-data-go.md

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ms.date: 01/17/2025
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---
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### Microsoft Entra ID prerequisites
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For the recommended keyless authentication with Microsoft Entra ID, you need to:
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- Install the [Azure CLI](/cli/azure/install-azure-cli) used for keyless authentication with Microsoft Entra ID.
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- Assign the `Cognitive Services User` role to your user account. You can assign roles in the Azure portal under **Access control (IAM)** > **Add role assignment**.
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## Set up
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1. Create a new folder `dall-e-quickstart` and go to the quickstart folder with the following command:
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```shell
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mkdir dall-e-quickstart && cd dall-e-quickstart
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```
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1. For the **recommended** keyless authentication with Microsoft Entra ID, sign in to Azure with the following command:
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```console
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az login
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```
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[!INCLUDE [Set up required variables](./use-your-data-common-variables.md)]
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## Create a Go environment
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## Run the quickstart
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1. Create a new folder named *openai-go* for your project and a new Go code file named *sample.go*. Change into that directory:
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The sample code in this quickstart uses Microsoft Entra ID for the recommended keyless authentication. If you prefer to use an API key, you can replace the `NewDefaultAzureCredential` implementation with `NewKeyCredential`.
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```cmd
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mkdir openai-go
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cd openai-go
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```
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#### [Microsoft Entra ID](#tab/keyless)
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```go
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azureOpenAIEndpoint := os.Getenv("AZURE_OPENAI_ENDPOINT")
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credential, err := azidentity.NewDefaultAzureCredential(nil)
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client, err := azopenai.NewClient(azureOpenAIEndpoint, credential, nil)
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```
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#### [API key](#tab/api-key)
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```go
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azureOpenAIEndpoint := os.Getenv("AZURE_OPENAI_ENDPOINT")
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azureOpenAIKey := os.Getenv("AZURE_OPENAI_API_KEY")
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credential := azcore.NewKeyCredential(azureOpenAIKey)
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client, err := azopenai.NewClientWithKeyCredential(azureOpenAIEndpoint, credential, nil)
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```
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---
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#### [Microsoft Entra ID](#tab/keyless)
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## Create the app
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To run the sample:
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1. From the project directory, open the *sample.go* file and add the following code:
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1. Create a new file named *quickstart.go*. Copy the following code into the *quickstart.go* file.
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```golang
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package main
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)
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func main() {
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azureOpenAIKey := os.Getenv("AZURE_OPENAI_API_KEY")
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azureOpenAIEndpoint := os.Getenv("AZURE_OPENAI_ENDPOINT")
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credential, err := azidentity.NewDefaultAzureCredential(nil)
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client, err := azopenai.NewClient(azureOpenAIEndpoint, credential, nil)
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modelDeploymentID := os.Getenv("AZURE_OPENAI_DEPLOYMENT_NAME")
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// Ex: "https://<your-azure-openai-host>.openai.azure.com"
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// Azure AI Search configuration
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searchIndex := os.Getenv("AZURE_AI_SEARCH_INDEX")
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searchEndpoint := os.Getenv("AZURE_AI_SEARCH_ENDPOINT")
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searchAPIKey := os.Getenv("AZURE_AI_SEARCH_API_KEY")
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if modelDeploymentID == "" || azureOpenAIEndpoint == "" || searchIndex == "" || searchEndpoint == "" || searchAPIKey == "" {
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fmt.Fprintf(os.Stderr, "Skipping example, environment variables missing\n")
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return
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}
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client, err := azopenai.NewClientWithKeyCredential(azureOpenAIEndpoint, credential, nil)
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if err != nil {
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// Implement application specific error handling logic.
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log.Printf("ERROR: %s", err)
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return
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}
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resp, err := client.GetChatCompletions(context.TODO(), azopenai.ChatCompletionsOptions{
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Messages: []azopenai.ChatRequestMessageClassification{
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&azopenai.ChatRequestUserMessage{Content: azopenai.NewChatRequestUserMessageContent("What are my available health plans?")},
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},
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MaxTokens: to.Ptr[int32](512),
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AzureExtensionsOptions: []azopenai.AzureChatExtensionConfigurationClassification{
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&azopenai.AzureSearchChatExtensionConfiguration{
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// This allows Azure OpenAI to use an Azure AI Search index.
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// Answers are based on the model's pretrained knowledge
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// and the latest information available in the designated data source.
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Parameters: &azopenai.AzureSearchChatExtensionParameters{
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Endpoint: &searchEndpoint,
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IndexName: &searchIndex,
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Authentication: &azopenai.OnYourDataAPIKeyAuthenticationOptions{
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Key: &searchAPIKey,
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},
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},
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},
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},
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DeploymentName: &modelDeploymentID,
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}, nil)
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if err != nil {
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// Implement application specific error handling logic.
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log.Printf("ERROR: %s", err)
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return
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}
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fmt.Fprintf(os.Stderr, "Extensions Context Role: %s\nExtensions Context (length): %d\n",
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*resp.Choices[0].Message.Role,
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len(*resp.Choices[0].Message.Content))
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fmt.Fprintf(os.Stderr, "ChatRole: %s\nChat content: %s\n",
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*resp.Choices[0].Message.Role,
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*resp.Choices[0].Message.Content,
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)
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}
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```
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1. Run the following command to create a new Go module:
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```shell
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go mod init quickstart.go
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```
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1. Run `go mod tidy` to install the required dependencies:
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```cmd
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go mod tidy
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```
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1. Run the following command to run the sample:
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```shell
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go run quickstart.go
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```
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#### [API key](#tab/api-key)
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To run the sample:
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1. Create a new file named *quickstart.go*. Copy the following code into the *quickstart.go* file.
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```golang
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package main
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import (
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"context"
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"fmt"
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"log"
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"os"
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"github.com/Azure/azure-sdk-for-go/sdk/ai/azopenai"
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"github.com/Azure/azure-sdk-for-go/sdk/azcore"
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"github.com/Azure/azure-sdk-for-go/sdk/azcore/to"
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)
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func main() {
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azureOpenAIEndpoint := os.Getenv("AZURE_OPENAI_ENDPOINT")
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azureOpenAIKey := os.Getenv("AZURE_OPENAI_API_KEY")
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modelDeploymentID := os.Getenv("AZURE_OPENAI_DEPLOYMENT_NAME")
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// Azure AI Search configuration
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searchIndex := os.Getenv("AZURE_AI_SEARCH_INDEX")
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return
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}
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keyCredential := azcore.NewKeyCredential(azureOpenAIKey)
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credential := azcore.NewKeyCredential(azureOpenAIKey)
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// In Azure OpenAI you must deploy a model before you can use it in your client. For more information
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// see here: https://learn.microsoft.com/azure/cognitive-services/openai/how-to/create-resource
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client, err := azopenai.NewClientWithKeyCredential(azureOpenAIEndpoint, keyCredential, nil)
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client, err := azopenai.NewClientWithKeyCredential(azureOpenAIEndpoint, credential, nil)
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if err != nil {
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// TODO: Update the following line with your application specific error handling logic
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log.Fatalf("ERROR: %s", err)
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}
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if err != nil {
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// Implement application specific error handling logic.
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log.Printf("ERROR: %s", err)
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return
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}
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resp, err := client.GetChatCompletions(context.TODO(), azopenai.ChatCompletionsOptions{
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Messages: []azopenai.ChatRequestMessageClassification{
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AzureExtensionsOptions: []azopenai.AzureChatExtensionConfigurationClassification{
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&azopenai.AzureSearchChatExtensionConfiguration{
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// This allows Azure OpenAI to use an Azure AI Search index.
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//
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// > Because the model has access to, and can reference specific sources to support its responses, answers are not only based on its pretrained knowledge
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// > but also on the latest information available in the designated data source. This grounding data also helps the model avoid generating responses
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// > based on outdated or incorrect information.
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//
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// Quote from here: https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/use-your-data
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// Answers are based on the model's pretrained knowledge
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// and the latest information available in the designated data source.
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Parameters: &azopenai.AzureSearchChatExtensionParameters{
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Endpoint: &searchEndpoint,
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IndexName: &searchIndex,
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}, nil)
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if err != nil {
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// TODO: Update the following line with your application specific error handling logic
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log.Fatalf("ERROR: %s", err)
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}
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// Implement application specific error handling logic.
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log.Printf("ERROR: %s", err)
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return
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}
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fmt.Fprintf(os.Stderr, "Extensions Context Role: %s\nExtensions Context (length): %d\n",
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*resp.Choices[0].Message.Role,
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}
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```
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> [!IMPORTANT]
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> For production, use a secure way of storing and accessing your credentials like [Azure Key Vault](/azure/key-vault/general/overview). For more information about credential security, see the Azure AI services [security](../../security-features.md) article.
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1. Run the following command to create a new Go module:
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```shell
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go mod init quickstart.go
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```
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1. Now open a command prompt and run the following:
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1. Run `go mod tidy` to install the required dependencies:
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```cmd
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go mod init sample.go
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```
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1. Next run:
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```cmd
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go mod tidy
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go run sample.go
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```
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The application prints the response including both answers to your query and citations from your uploaded files.
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1. Run the following command to run the sample:
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```shell
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go run quickstart.go
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```
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---
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The application prints the response including both answers to your query and citations from your uploaded files.

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