This page shows you how to send chat prompts to a Gemini model by using the Google Cloud console, REST API, and supported SDKs.
To learn how to add images and other media to your request, see Image understanding.
For a list of languages supported by Gemini, see Language support.
To explore the generative AI models and APIs that are available on Vertex AI, go to Model Garden in the Google Cloud console.
If you're looking for a way to use Gemini directly from your mobile and web apps, see the Firebase AI Logic client SDKs for Swift, Android, Web, Flutter, and Unity apps.
Generate text
For testing and iterating on chat prompts, we recommend using the Google Cloud console. To send prompts programmatically to the model, you can use the REST API, Google Gen AI SDK, Vertex AI SDK for Python, or one of the other supported libraries and SDKs.
You can use system instructions to steer the behavior of the model based on a specific need or use case. For example, you can define a persona or role for a chatbot that responds to customer service requests. For more information, see the system instructions code samples.
You can use the Google Gen AI SDK to send requests if you're using Gemini 2.0 Flash.
Here is a simple text generation example.
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
Streaming and non-streaming responses
You can choose whether the model generates streaming responses or non-streaming responses. For streaming responses, you receive each response as soon as its output token is generated. For non-streaming responses, you receive all responses after all of the output tokens are generated.
Here is a streaming text generation example.
Python
Before trying this sample, follow the Python setup instructions in the Vertex AI quickstart using client libraries. For more information, see the Vertex AI Python API reference documentation.
To authenticate to Vertex AI, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.
What's next
Learn how to send multimodal prompt requests:
Learn about responsible AI best practices and Vertex AI's safety filters.