Я недавно перешел с M5 на 1.0.0 и просто задаюсь вопросом, правильно ли настраиваются эти конфигурации и бобы. Я использую соединение на основе Azure Openai, а также поддержку модели встраивания.
import com.azure.ai.openai.OpenAIClient;
import com.azure.ai.openai.OpenAIClientBuilder;
import com.azure.core.credential.AccessToken;
import com.azure.core.credential.TokenCredential;
import com.azure.core.util.ClientOptions;
import org.springframework.ai.azure.openai.AzureOpenAiChatModel;
import org.springframework.ai.azure.openai.AzureOpenAiChatOptions;
import org.springframework.ai.azure.openai.AzureOpenAiEmbeddingModel;
import org.springframework.ai.azure.openai.AzureOpenAiEmbeddingOptions;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.stringtemplate.v4.STGroup;
import org.stringtemplate.v4.STGroupFile;
import reactor.core.publisher.Mono;
import java.time.OffsetDateTime;
import java.util.List;
import static com.azure.ai.openai.OpenAIServiceVersion.V2023_05_15;
import static io.micrometer.observation.ObservationRegistry.NOOP;
import static java.time.Duration.ofHours;
import static org.springframework.ai.document.MetadataMode.EMBED;
/**
* Defines Gen AI configuration
*
*/
@Configuration
public class OpenAiConfig {
@Value("${spring.ai.azure.openai.endpoint:}")
private String chatModelEndpoint;
@Value("${spring.ai.azure.openai.chat.options.deployment-name:}")
private String chatModelDeploymentName;
@Value("${spring.ai.azure.openai.embedding.endpoint:}")
private String embeddingModelEndpoint;
@Value("${spring.ai.azure.openai.embedding.options.deployment-name:}")
private String embeddingModelDeploymentName;
@Value("${spring.ai.azure.openai.chat.options.api-version:}")
private String apiVersion;
@Value("${spring.ai.azure.openai.token.lifetime:10}")
private int tokenLifetime;
@Value("#{'${template.file.paths}'.split(',')}")
private List templateFilePaths;
private final AzureAuthenticationService azureAuthenticationService;
/**
* Constructs an OpenAiConfig instance with the provided AzureAuthenticationService.
*
* @param azureAuthenticationService AzureAuthenticationService to be used for fetching access tokens.
*/
public OpenAiConfig(AzureAuthenticationService azureAuthenticationService) {
this.azureAuthenticationService = azureAuthenticationService;
}
/**
* Creates a TokenCredential bean that provides access tokens for Azure services.
* The token is fetched from Microsoft Entra ID (formerly Azure AD) and has a configurable lifetime.
*
* @return TokenCredential instance that provides Azure access tokens
*/
@Bean
public TokenCredential tokenCredential() {
return tokenRequestContext ->
Mono.just(new AccessToken(azureAuthenticationService.fetchAccessToken(),
OffsetDateTime.now().plus(ofHours(tokenLifetime))));
}
/**
* Creates an OpenAIClientBuilder configured with endpoint, credentials, and service options.
* This builder is used to establish connections to Azure OpenAI services.
*
* @return OpenAIClientBuilder instance ready for creating OpenAI clients.
*/
@Bean
public OpenAIClientBuilder openAIClientBuilder() {
return new OpenAIClientBuilder()
.endpoint(chatModelEndpoint)
.credential(tokenCredential())
.serviceVersion(V2023_05_15)
.clientOptions(new ClientOptions().setApplicationId("spring-ai"));
}
/**
* Configures an AzureOpenAiChatModel with appropriate deployment settings and parameters.
*
* @param openAIClientBuilder The builder used to establish connections to Azure OpenAI.
* @return AzureOpenAiChatModel instance with specified deployment settings
*/
@Bean
public AzureOpenAiChatModel azureOpenAiChatModel(OpenAIClientBuilder openAIClientBuilder) {
return AzureOpenAiChatModel.builder()
.openAIClientBuilder(openAIClientBuilder)
.defaultOptions(AzureOpenAiChatOptions.builder()
.deploymentName(chatModelDeploymentName)
.build())
.build();
}
/**
* Creates a ChatClient that provides a high-level interface for interacting with Azure OpenAI.
*
* @param azureOpenAiChatModel the configured model to use for chat completions.
* @return ChatClient instance ready for sending prompts and receiving completions
*/
@Bean
public ChatClient chatClient(AzureOpenAiChatModel azureOpenAiChatModel) {
return ChatClient.create(azureOpenAiChatModel);
}
/**
* Creates an OpenAIClient configured with endpoint, credentials, and service options.
* This client is used for embedding operations with Azure OpenAI services.
*
* @return OpenAIClient instance ready for embedding operations.
*/
@Bean
public OpenAIClient openAIClient() {
return new OpenAIClientBuilder()
.endpoint(embeddingModelEndpoint)
.credential(tokenCredential())
.serviceVersion(V2023_05_15)
.clientOptions(new ClientOptions().setApplicationId("spring-ai")).buildClient();
}
/**
* Configures an AzureOpenAiEmbeddingModel with appropriate deployment settings and parameters.
* This model is used for generating vector embeddings from text, which are essential for
* document similarity search and retrieval operations.
*
* @param openAIClient The OpenAI client used to connect to Azure OpenAI services
* @return AzureOpenAiEmbeddingModel instance configured for text embedding operations
*/
@Bean
public AzureOpenAiEmbeddingModel embeddingModel(OpenAIClient openAIClient) {
return new AzureOpenAiEmbeddingModel(
openAIClient,
EMBED,
AzureOpenAiEmbeddingOptions.builder()
.deploymentName(embeddingModelDeploymentName)
.user("user-6")
.build(),
NOOP);
}
/**
* Creates and configures an STGroup bean for template processing.
*
* @return STGroup instance initialized with the specified template file.
*/
@Bean
public STGroup promptTemplateGroup() {
STGroup compositeGroup = new STGroup();
for (String path : templateFilePaths) {
compositeGroup.importTemplates(new STGroupFile(path.trim()));
}
return compositeGroup;
}
}
Подробнее здесь: https://stackoverflow.com/questions/796 ... ions-setup
