Quickstart: Generate text using the Vertex AI Gemini API (original) (raw)

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In this quickstart, you send the following multimodal requests to the Vertex AI Gemini API and view the responses:

You can complete this quickstart by using a programming language SDK in your local environment or the REST API.

Prerequisites

Completing this quickstart requires you to:

Set up a Google Cloud project

Set up your Google Cloud project and enable the Vertex AI API.

  1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.
  2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
    Go to project selector
  3. Make sure that billing is enabled for your Google Cloud project.
  4. Enable the Vertex AI API.
    Enable the API
  5. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.
    Go to project selector
  6. Make sure that billing is enabled for your Google Cloud project.
  7. Enable the Vertex AI API.
    Enable the API

Set up the Google Cloud CLI

On your local machine, set up and authenticate with the Google Cloud CLI. If you are familiar with the Gemini API in Google AI Studio, note that the Vertex AI Gemini API uses Identity and Access Management instead of API keys to manage access.

  1. Install and initialize the Google Cloud CLI.
  2. If you previously installed the gcloud CLI, ensure yourgcloud components are updated by running this command.
    gcloud components update
  3. To authenticate with the gcloud CLI, generate a local Application Default Credentials (ADC) file by running this command. The web flow launched by the command is used to provide your user credentials.
    gcloud auth application-default login
    For more information, see Set up Application Default Credentials.

Set up the SDK for your programming language

On your local machine, click one of the following tabs to install the SDK for your programming language.

Gen AI SDK for Python

Install and update the Gen AI SDK for Python by running this command.

pip install --upgrade google-genai

Gen AI SDK for Go

Install and update the Gen AI SDK for Go by running this command.

go get google.golang.org/genai

Gen AI SDK for Node.js

Install and update the Gen AI SDK for Node.js by running this command.

npm install @google/genai

Gen AI SDK for Java

Install and update the Gen AI SDK for Java:

Maven

Add the following to your pom.xml:

<dependencies>
  <dependency>
    <groupId>com.google.genai</groupId>
    <artifactId>google-genai</artifactId>
    <version>0.7.0</version>
  </dependency>
</dependencies>

C#

Install the Google.Cloud.AIPlatform.V1 package from NuGet. Use your preferred method of adding packages to your project. For example, right-click the project in Visual Studio and choose Manage NuGet Packages....

REST

  1. Configure your environment variables by entering the following. ReplacePROJECT_ID with the ID of your Google Cloud project.
    MODEL_ID="gemini-2.0-flash-001"
    PROJECT_ID="PROJECT_ID"
  2. Use Google Cloud CLI to provision the endpoint by running this command.
    gcloud beta services identity create --service=aiplatform.googleapis.com --project=${PROJECT_ID}

Send a prompt to the Vertex AI Gemini API

Use the following code to send a prompt to the Vertex AI Gemini API. This sample returns a list of possible namesfor a specialty flower store.

You can run the code from the command line, by using an IDE, or by including the code in your application.

Gen AI SDK for Python

Install

pip install --upgrade google-genai

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

Gen AI SDK for Go

Learn how to install or update the Gen AI SDK for Go.

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

Gen AI SDK for Node.js

Install

npm install @google/genai

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

Gen AI SDK for Java

Learn how to install or update the Gen AI SDK for Java.

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

C#

To send a prompt request, create a C# file (.cs) and copy the following code into the file. Set your-project-id to your Google Cloud project ID. After updating the values, run the code.

REST

To send this prompt request, run the curl command from the command line or include the REST call in your application.

curl -X POST
-H "Authorization: Bearer $(gcloud auth print-access-token)"
-H "Content-Type: application/json"
https://aiplatform.googleapis.com/v1/projects/${PROJECT_ID}/locations/global/publishers/google/models/${MODEL_ID}:generateContent -d
$'{ "contents": { "role": "user", "parts": [ { "text": "What's a good name for a flower shop that specializes in selling bouquets of dried flowers?" } ] } }'

The model returns a response. Note that the response is generated in sections with each section separately evaluated for safety.

Send a prompt and an image to the Vertex AI Gemini API

Use the following code to send a prompt that includes text and an image to the Vertex AI Gemini API. This sample returns a description of theprovided image(image for Java sample).

Gen AI SDK for Python

Install

pip install --upgrade google-genai

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

Gen AI SDK for Go

Learn how to install or update the Gen AI SDK for Go.

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

Gen AI SDK for Node.js

Install

npm install @google/genai

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

Gen AI SDK for Java

Learn how to install or update the Gen AI SDK for Java.

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

Node.js

Before trying this sample, follow the Node.js setup instructions in theVertex AI quickstart using client libraries. For more information, see theVertex AI Node.js API reference documentation.

To authenticate to Vertex AI, set up Application Default Credentials. For more information, seeSet up authentication for a local development environment.

Java

Before trying this sample, follow the Java setup instructions in theVertex AI quickstart using client libraries. For more information, see theVertex AI Java API reference documentation.

To authenticate to Vertex AI, set up Application Default Credentials. For more information, seeSet up authentication for a local development environment.

C#

To send a prompt request, create a C# file (.cs) and copy the following code into the file. Set your-project-id to your Google Cloud project ID. After updating the values, run the code.

REST

You can send this prompt request from from your IDE, or you can embed the REST call into your application where appropriate.

curl -X POST
-H "Authorization: Bearer $(gcloud auth print-access-token)"
-H "Content-Type: application/json"
https://aiplatform.googleapis.com/v1/projects/${PROJECT_ID}/locations/global/publishers/google/models/${MODEL_ID}:generateContent -d
$'{ "contents": { "role": "user", "parts": [ { "fileData": { "mimeType": "image/jpeg", "fileUri": "gs://generativeai-downloads/images/scones.jpg" } }, { "text": "Describe this picture." } ] } }'

The model returns a response. Note that the response is generated in sections with each section separately evaluated for safety.

Send a prompt and a video to the Vertex AI Gemini API

Use the following code to send a prompt that includes text, audio, and video to the Vertex AI Gemini API. This sample returns a description of theprovided video, including anything important from the audio track.

You can send this prompt request by using the command line, using your IDE, or by including the REST call in your application.

Gen AI SDK for Python

Install

pip install --upgrade google-genai

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

Gen AI SDK for Go

Learn how to install or update the Gen AI SDK for Go.

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

Gen AI SDK for Node.js

Install

npm install @google/genai

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

Gen AI SDK for Java

Learn how to install or update the Gen AI SDK for Java.

To learn more, see the SDK reference documentation.

Set environment variables to use the Gen AI SDK with Vertex AI:

Replace the GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_LOCATION values

with appropriate values for your project.

export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT export GOOGLE_CLOUD_LOCATION=global export GOOGLE_GENAI_USE_VERTEXAI=True

Node.js

Before trying this sample, follow the Node.js setup instructions in theVertex AI quickstart using client libraries. For more information, see theVertex AI Node.js API reference documentation.

To authenticate to Vertex AI, set up Application Default Credentials. For more information, seeSet up authentication for a local development environment.

Java

Before trying this sample, follow the Java setup instructions in theVertex AI quickstart using client libraries. For more information, see theVertex AI Java API reference documentation.

To authenticate to Vertex AI, set up Application Default Credentials. For more information, seeSet up authentication for a local development environment.

C#

To send a prompt request, create a C# file (.cs) and copy the following code into the file. Set your-project-id to your Google Cloud project ID. After updating the values, run the code.

REST

curl -X POST
-H "Authorization: Bearer $(gcloud auth print-access-token)"
-H "Content-Type: application/json"
https://aiplatform.googleapis.com/v1/projects/${PROJECT_ID}/locations/global/publishers/google/models/${MODEL_ID}:generateContent -d
$'{ "contents": { "role": "user", "parts": [ { "fileData": { "mimeType": "video/mp4", "fileUri": "gs://cloud-samples-data/generative-ai/video/pixel8.mp4" } }, { "text": "Provide a description of the video. The description should also contain anything important which people say in the video." } ] } }'

The model returns a response. Note that the response is generated in sections with each section separately evaluated for safety.

What's next

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Last updated 2025-06-12 UTC.