From beb39f79194682e1ddd355219760adeedd4c0f1a Mon Sep 17 00:00:00 2001 From: Jaycee Li Date: Tue, 19 May 2026 11:37:58 -0700 Subject: [PATCH] docs: Update the README PiperOrigin-RevId: 917942076 --- README.md | 64 +++++++++++++++++++++++++++---------------------------- 1 file changed, 32 insertions(+), 32 deletions(-) diff --git a/README.md b/README.md index 47233672678..f7f309fbdf6 100644 --- a/README.md +++ b/README.md @@ -16,7 +16,7 @@ If you're using Maven, add the following to your dependencies: com.google.genai google-genai - 1.47.0 + 1.53.0 ``` @@ -29,8 +29,8 @@ SDK for Java. ### Create a client The Google Gen AI Java SDK provides a Client class, simplifying interaction -with both the Gemini API and Vertex AI API. With minimal configuration, -you can seamlessly switch between the 2 backends without rewriting +with both the Gemini API and Gemini Enterprise Agent Platform API. With minimal +configuration, you can seamlessly switch between the 2 backends without rewriting your code. #### Instantiate a client that uses Gemini API @@ -42,7 +42,7 @@ import com.google.genai.Client; Client client = Client.builder().apiKey("your-api-key").build(); ``` -#### Instantiate a client that uses Vertex AI API +#### Instantiate a client that uses Gemini Enterprise Agent Platform API ##### Using project and location @@ -50,24 +50,24 @@ Client client = Client.builder().apiKey("your-api-key").build(); import com.google.genai.Client; // Use Builder class for instantiation. Explicitly set the project and location, -// and set `vertexAI(true)` to use Vertex AI backend. +// and set `enterprise(true)` to use Gemini Enterprise Agent Platform backend. Client client = Client.builder() .project("your-project") .location("your-location") - .vertexAI(true) + .enterprise(true) .build(); ``` -##### Using API key on Vertex AI (GCP Express Mode) +##### Using API key on Gemini Enterprise Agent Platform (GCP Express Mode) ```java import com.google.genai.Client; -// Explicitly set the `apiKey` and `vertexAI(true)` to use Vertex AI backend +// Explicitly set the `apiKey` and `enterprise(true)` to use Gemini Enterprise Agent Platform backend // in express mode. Client client = Client.builder() .apiKey("your-api-key") - .vertexAI(true) + .enterprise(true) .build(); ``` @@ -75,7 +75,7 @@ Client client = Client.builder() You can create a client by configuring the necessary environment variables. Configuration setup instructions depends on whether you're using the Gemini -Developer API or the Gemini API in Vertex AI. +Developer API or the Gemini API in Gemini Enterprise Agent Platform. **Gemini Developer API:** Set the `GOOGLE_API_KEY`. It will automatically be picked up by the client. Note that `GEMINI_API_KEY` is a legacy environment @@ -86,15 +86,16 @@ variable, it's recommended to use `GOOGLE_API_KEY` only. But if both are set, export GOOGLE_API_KEY='your-api-key' ``` -**Gemini API on Vertex AI:** Set `GOOGLE_GENAI_USE_VERTEXAI`, +**Gemini API on Gemini Enterprise Agent Platform:** Set `GOOGLE_GENAI_USE_ENTERPRISE`, `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION`, or `GOOGLE_API_KEY` for -Vertex AI express mode. It's recommended that you set only project & location, -or API key. But if both are set, project & location takes precedence. +Gemini Enterprise Agent Platform express mode. It's recommended that you set +only project & location, or API key. But if both are set, project & location +takes precedence. ```bash -export GOOGLE_GENAI_USE_VERTEXAI=true +export GOOGLE_GENAI_USE_ENTERPRISE=true -// Set project and location for Vertex AI authentication +// Set project and location for Gemini Enterprise Agent Platform authentication export GOOGLE_CLOUD_PROJECT='your-project-id' export GOOGLE_CLOUD_LOCATION='us-central1' // or API key for express mode @@ -117,7 +118,7 @@ preview features in the APIs. The stable API endpoints can be selected by setting the API version to `v1`. To set the API version use `HttpOptions`. For example, to set the API version to -`v1` for Vertex AI: +`v1` for Gemini Enterprise Agent Platform: ```java import com.google.genai.Client; @@ -126,7 +127,7 @@ import com.google.genai.types.HttpOptions; Client client = Client.builder() .project("your-project") .location("your-location") - .vertexAI(true) + .enterprise(true) .httpOptions(HttpOptions.builder().apiVersion("v1")) .build(); ``` @@ -284,10 +285,10 @@ import com.google.genai.types.Part; public class GenerateContentWithImageInput { public static void main(String[] args) { - // Instantiate the client using Vertex API. The client gets the project and + // Instantiate the client using Gemini Enterprise Agent Platform API. The client gets the project and // location from the environment variables `GOOGLE_CLOUD_PROJECT` and // `GOOGLE_CLOUD_LOCATION`. - Client client = Client.builder().vertexAI(true).build(); + Client client = Client.builder().enterprise(true).build(); // Construct a multimodal content with quick constructors Content content = @@ -563,7 +564,7 @@ public class CountTokens { ``` The `computeTokens` method returns the Tokens Info that contains tokens and -token IDs given your prompt. This method is only supported in Vertex AI. +token IDs given your prompt. This method is only supported in Gemini Enterprise Agent Platform. ```java package ; @@ -573,7 +574,7 @@ import com.google.genai.types.ComputeTokensResponse; public class ComputeTokens { public static void main(String[] args) { - Client client = Client.builder().vertexAI(true).build(); + Client client = Client.builder().enterprise(true).build(); ComputeTokensResponse response = client.models.computeTokens("gemini-2.5-flash", "What is your name?", null); @@ -586,7 +587,7 @@ public class ComputeTokens { #### Embed Content The `embedContent` method allows you to generate embeddings for words, phrases, -sentences, and code, as well as multimodal content like images or videos via Vertex AI. +sentences, and code, as well as multimodal content like images or videos via Gemini Enterprise Agent Platform. ```java package ; @@ -604,8 +605,8 @@ public class EmbedContent { System.out.println("Embedding response: " + response); - // Multimodal embedding with Vertex AI - Client vertexClient = Client.builder().vertexAI(true).build(); + // Multimodal embedding with Gemini Enterprise Agent Platform + Client enterpriseClient = Client.builder().enterprise(true).build(); EmbedContentConfig config = EmbedContentConfig.builder() .outputDimensionality(10) @@ -614,7 +615,7 @@ public class EmbedContent { .build(); EmbedContentResponse mmResponse = - vertexClient.models.embedContent( + enterpriseClient.models.embedContent( "gemini-embedding-2-exp-11-2025", Content.fromParts( Part.fromText("Hello"), @@ -669,7 +670,7 @@ public class GenerateImages { #### Upscale Image The `upscaleImage` method allows you to upscale an image. This feature is only -supported in Vertex AI. +supported in Gemini Enterprise Agent Platform. ```java package ; @@ -681,7 +682,7 @@ import com.google.genai.types.UpscaleImageResponse; public class UpscaleImage { public static void main(String[] args) { - Client client = Client.builder().vertexAI(true).build(); + Client client = Client.builder().enterprise(true).build(); Image image = Image.fromFile("path/to/your/image"); @@ -712,7 +713,7 @@ The `editImage` method lets you edit an image. You can input reference images addition to a text prompt to guide the editing. This feature uses a different model than `generateImages` and `upscaleImage`. It -is only supported in Vertex AI. +is only supported in Gemini Enterprise Agent Platform. ```java package ; @@ -731,7 +732,7 @@ import java.util.ArrayList; public class EditImage { public static void main(String[] args) { - Client client = Client.builder().vertexAI(true).build(); + Client client = Client.builder().enterprise(true).build(); Image image = Image.fromFile("path/to/your/image"); @@ -986,10 +987,9 @@ The Google Gen AI Java SDK will accept contributions in the future. Apache 2.0 - See [LICENSE][license] for more information. [gemini-api-doc]: https://ai.google.dev/gemini-api/docs -[vertex-api-doc]: https://cloud.google.com/vertex-ai/generative-ai/docs/learn/overview +[gemini-enterprise-agent-platform-doc]: https://docs.cloud.google.com/gemini-enterprise-agent-platform [maven-version-image]: https://img.shields.io/maven-central/v/com.google.genai/google-genai.svg [maven-version-link]: https://central.sonatype.com/artifact/com.google.genai/google-genai [javadoc-image]: https://img.shields.io/badge/JavaDoc-Online-green [javadoc-link]: https://googleapis.github.io/java-genai/javadoc/ -[license]: https://github.com/googleapis/java-genai/blob/main/LICENSE - +[license]: https://github.com/googleapis/java-genai/blob/main/LICENSE \ No newline at end of file