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OpenAI Chat Streaming with Data in Go
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This sample demonstrates how to use the OpenAI Chat API with data streaming in a Go console application.
main.go
openai_chat_completions_streaming_with_data_hello_world.go
How to generate this sample
Output
AI - Azure AI CLI, Version 1.0.0
Copyright (c) 2024 Microsoft Corporation. All Rights Reserved.
This PUBLIC PREVIEW version may change at any time.
See: https://aka.ms/azure-ai-cli-public-preview
Generating 'openai-chat-streaming-with-data' in 'openai-chat-streaming-with-data-go' (3 files)...
go.mod
main.go
openai_chat_completions_streaming_with_data_hello_world.go
Generating 'openai-chat-streaming-with-data' in 'openai-chat-streaming-with-data-go' (3 files)... DONE!
main.go
STEP 1: Read the configuration settings from environment variables and initialize variables.
main.go
openAIAPIKey := os.Getenv("AZURE_OPENAI_API_KEY")
if openAIAPIKey == "" {
openAIAPIKey = "<insert your OpenAI API key here>"
}
openAIApiVersion := os.Getenv("AZURE_OPENAI_API_VERSION")
if openAIApiVersion == "" {
openAIApiVersion = "<insert your open api version here>"
}
openAIEndpoint := os.Getenv("AZURE_OPENAI_ENDPOINT")
if openAIEndpoint == "" {
openAIEndpoint = "<insert your OpenAI endpoint here>"
}
openAIChatDeploymentName := os.Getenv("AZURE_OPENAI_CHAT_DEPLOYMENT")
if openAIChatDeploymentName == "" {
openAIChatDeploymentName = "<insert your OpenAI chat deployment name here>"
}
openAISystemPrompt := os.Getenv("AZURE_OPENAI_SYSTEM_PROMPT")
if openAISystemPrompt == "" {
openAISystemPrompt = "You are a helpful AI assistant."
}
openAIEmbeddingsDeploymentName := os.Getenv("AZURE_OPENAI_EMBEDDING_DEPLOYMENT")
if openAIEmbeddingsDeploymentName == "" {
openAIEmbeddingsDeploymentName = "<insert your OpenAI embeddings deployment name here>"
}
openAIEndpoint = strings.TrimSuffix(openAIEndpoint, "/")
azureSearchApiKey := os.Getenv("AZURE_AI_SEARCH_KEY")
if azureSearchApiKey == "" {
azureSearchApiKey = "<insert your search api key here>"
}
azureSearchEndpoint := os.Getenv("AZURE_AI_SEARCH_ENDPOINT")
if azureSearchEndpoint == "" {
azureSearchEndpoint = "<insert your search endpoint here>"
}
azureSearchIndexName := os.Getenv("AZURE_AI_SEARCH_INDEX_NAME")
if azureSearchIndexName == "" {
azureSearchIndexName = "<insert your search index name here>"
}
if openAIEndpoint == "" || openAIAPIKey == "" || openAIChatDeploymentName == "" || openAISystemPrompt == "" {
fmt.Println("Please set the environment variables.")
os.Exit(1)
}
chat, err := NewOpenAIChatCompletionsWithDataStreamingExample(openAIEndpoint, openAIAPIKey, openAIChatDeploymentName, openAISystemPrompt, azureSearchEndpoint, azureSearchApiKey, azureSearchIndexName, openAIEmbeddingsDeploymentName)
if err != nil {
log.Fatalf("ERROR: %s", err)
}
for {
fmt.Print("User: ")
input, _ := getUserInput()
if input == "exit" || input == "" {
break
}
fmt.Printf("\nAssistant: ")
_, err := chat.GetChatCompletionsStream(input, func(content string) {
fmt.Printf("%s", content)
})
if err != nil {
log.Fatalf("ERROR: %s", err)
}
fmt.Printf("\n\n")
}
STEP 2: Validate the environment variables and exit if any required variable is missing.
main.go
if openAIEndpoint == "" || openAIAPIKey == "" || openAIChatDeploymentName == "" || openAISystemPrompt == "" {
fmt.Println("Please set the environment variables.")
os.Exit(1)
}
STEP 3: Initialize the helper class with the configuration settings.
main.go
chat, err := NewOpenAIChatCompletionsWithDataStreamingExample(openAIEndpoint, openAIAPIKey, openAIChatDeploymentName, openAISystemPrompt, azureSearchEndpoint, azureSearchApiKey, azureSearchIndexName, openAIEmbeddingsDeploymentName)
if err != nil {
log.Fatalf("ERROR: %s", err)
}
STEP 4: Obtain user input, use the helper class to get the assistant's response, and display responses as they are received.
main.go
for {
fmt.Print("User: ")
input, _ := getUserInput()
if input == "exit" || input == "" {
break
}
fmt.Printf("\nAssistant: ")
_, err := chat.GetChatCompletionsStream(input, func(content string) {
fmt.Printf("%s", content)
})
if err != nil {
log.Fatalf("ERROR: %s", err)
}
fmt.Printf("\n\n")
}
openai_chat_completions_streaming_with_data_hello_world.go
STEP 1: Create the client and initialize chat message history with a system message and data sources.
openai_chat_completions_streaming_with_data_hello_world.go
type OpenAIChatCompletionsWithDataStreamingExample struct {
client *azopenai.Client
options *azopenai.ChatCompletionsOptions
}
func NewOpenAIChatCompletionsWithDataStreamingExample(
openAIEndpoint string,
openAIAPIKey string,
openAIChatDeploymentName string,
openAISystemPrompt string,
azureSearchEndpoint string,
azureSearchApiKey string,
azureSearchIndexName string,
openAIEmbeddingsDeploymentName string,
) (*OpenAIChatCompletionsWithDataStreamingExample, error) {
keyCredential := azcore.NewKeyCredential(openAIAPIKey)
client, err := azopenai.NewClientWithKeyCredential(openAIEndpoint, keyCredential, nil)
if err != nil {
return nil, err
}
messages := []azopenai.ChatRequestMessageClassification{
&azopenai.ChatRequestSystemMessage{
Content: &openAISystemPrompt,
},
}
options := &azopenai.ChatCompletionsOptions{
DeploymentName: &openAIChatDeploymentName,
Messages: messages,
AzureExtensionsOptions: []azopenai.AzureChatExtensionConfigurationClassification{
&azopenai.AzureCognitiveSearchChatExtensionConfiguration{
Parameters: &azopenai.AzureCognitiveSearchChatExtensionParameters{
Endpoint: &azureSearchEndpoint,
IndexName: &azureSearchIndexName,
Authentication: &azopenai.OnYourDataAPIKeyAuthenticationOptions{
Key: &azureSearchApiKey,
},
QueryType: to.Ptr(azopenai.AzureCognitiveSearchQueryTypeVectorSimpleHybrid),
EmbeddingDependency: &azopenai.OnYourDataDeploymentNameVectorizationSource{
DeploymentName: &openAIEmbeddingsDeploymentName,
Type: to.Ptr(azopenai.OnYourDataVectorizationSourceTypeDeploymentName),
},
},
},
},
}
return &OpenAIChatCompletionsWithDataStreamingExample{
client: client,
options: options,
}, nil
}
STEP 2: When the user provides input, add the user message to the chat message history.
openai_chat_completions_streaming_with_data_hello_world.go
func (chat *OpenAIChatCompletionsWithDataStreamingExample) ClearConversation() {
chat.options.Messages = chat.options.Messages[:1]
}
func (chat *OpenAIChatCompletionsWithDataStreamingExample) GetChatCompletionsStream(userPrompt string, callback func(content string)) (string, error) {
chat.options.Messages = append(chat.options.Messages, &azopenai.ChatRequestUserMessage{Content: azopenai.NewChatRequestUserMessageContent(userPrompt)})
resp, err := chat.client.GetChatCompletionsStream(context.TODO(), *chat.options, nil)
if err != nil {
return "", err
}
defer resp.ChatCompletionsStream.Close()
responseContent := ""
for {
chatCompletions, err := resp.ChatCompletionsStream.Read()
if errors.Is(err, io.EOF) {
break
}
if err != nil {
return "", err
}
for _, choice := range chatCompletions.Choices {
content := ""
if choice.Delta.Content != nil {
content = *choice.Delta.Content
}
if choice.FinishReason != nil {
finishReason := *choice.FinishReason
if finishReason == azopenai.CompletionsFinishReasonTokenLimitReached {
content = content + "\nWARNING: Exceeded token limit!"
}
}
if content == "" {
continue
}
if callback != nil {
callback(content)
}
responseContent += content
}
}
chat.options.Messages = append(chat.options.Messages, &azopenai.ChatRequestAssistantMessage{Content: to.Ptr(responseContent)})
return responseContent, nil
}