Use Google Vertex AI with AI Agents

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Google Vertex AI is a managed machine learning platform that enables users to build, deploy, and scale ML models quickly. It provides a fully-managed end-to-end ML pipeline and supports multiple ML frameworks and programming languages.

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🔗 Connect and Use Google Vertex AI

1. 🔑 Connect your Google Vertex AI

2. ✅ Select an action

3. 🚀 Go live with the agent

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API actions for Google Vertex AI for AI assitants/agents

Language

PYTHON

Framework

Create Model

Create a new machine learning model in Google Vertex AI.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.CREATE_MODEL])

Train Model

Initiate the training process for a specified machine learning model.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.TRAIN_MODEL])

Deploy Model

Deploy a trained model to an endpoint for serving predictions.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.DEPLOY_MODEL])

Make Prediction

Use a deployed model to make predictions on new data.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.MAKE_PREDICTION])

Create Dataset

Create a new dataset in Vertex AI for training or batch prediction.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.CREATE_DATASET])

Import Data

Import data into a Vertex AI dataset from various sources.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.IMPORT_DATA])

Export Data

Export data from a Vertex AI dataset to various destinations.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.EXPORT_DATA])

Delete Model

Remove a specific model from Vertex AI.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.DELETE_MODEL])

Update Model

Update the properties or metadata of an existing model.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.UPDATE_MODEL])

List Models

Retrieve a list of all models in the Vertex AI project.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.LIST_MODELS])

Get Model Details

Fetch detailed information about a specific model.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.GET_MODEL_DETAILS])

Create Endpoint

Create a new endpoint for model deployment in Vertex AI.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.CREATE_ENDPOINT])

Delete Endpoint

Remove a specific endpoint from Vertex AI.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.DELETE_ENDPOINT])

Create Pipeline

Create a new ML pipeline for automating workflows in Vertex AI.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.CREATE_PIPELINE])

Run Pipeline

Execute a predefined ML pipeline in Vertex AI.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.RUN_PIPELINE])

Create Hyperparameter Tuning Job

Initiate a hyperparameter tuning job to optimize model performance.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.CREATE_HP_TUNING_JOB])

Create Batch Prediction Job

Start a batch prediction job using a deployed model.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.CREATE_BATCH_PREDICTION_JOB])

Create Feature Store

Create a new feature store for managing and serving ML features.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.CREATE_FEATURE_STORE])

Import Features

Import features into a Vertex AI feature store.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.IMPORT_FEATURES])

Create AutoML Training Job

Initiate an AutoML training job for automated model creation.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.CREATE_AUTOML_JOB])

Model Training Completed

Triggered when a model training job is completed.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.MODEL_TRAINING_COMPLETED])

Model Deployment Completed

Triggered when a model is successfully deployed to an endpoint.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.MODEL_DEPLOYMENT_COMPLETED])

Batch Prediction Job Completed

Triggered when a batch prediction job finishes processing.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.BATCH_PREDICTION_COMPLETED])

Dataset Import Completed

Triggered when data import into a dataset is finished.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.DATASET_IMPORT_COMPLETED])

Pipeline Execution Completed

Triggered when an ML pipeline execution is completed.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.PIPELINE_EXECUTION_COMPLETED])

Hyperparameter Tuning Completed

Triggered when a hyperparameter tuning job is finished.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.HP_TUNING_COMPLETED])

AutoML Job Completed

Triggered when an AutoML training job is completed.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.AUTOML_JOB_COMPLETED])

Model Performance Threshold Reached

Triggered when a model's performance reaches a specified threshold.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.MODEL_PERFORMANCE_THRESHOLD])

Feature Store Update Completed

Triggered when features in a feature store are successfully updated.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.FEATURE_STORE_UPDATE_COMPLETED])

Model Version Created

Triggered when a new version of a model is created.

from composio_langchain import ComposioToolSet, Action tool_set = ComposioToolSet() tools = tool_set.get_tools(actions=[Action.MODEL_VERSION_CREATED])

Frequently asked questions

What is Composio.dev?

Composio.dev is a platform for building AI applications, designed to make the process of developing AI solutions super easy and fun! It provides a comprehensive set of tools and libraries that simplify the process of developing AI solutions, allowing you to focus on the creative aspects of your project without getting bogged down by the technical details.

How does Composio.dev support Google Vertex AI?

Composio.dev seamlessly integrates with Google Vertex AI, allowing you to leverage its capabilities within the Composio.dev platform. You can utilize Google Vertex AI to call functions across various platforms, including Google, GitHub, and others, making it a breeze to incorporate different services into your AI applications. Additionally, it supports user authentication via OAuth2 and can work in conjunction with other popular frameworks like LangChain and CrewAI, giving you the flexibility to build truly innovative AI solutions.

What models can I use with Google Vertex AI?

With Google Vertex AI, you have access to a wide range of state-of-the-art language models, including GPT-4o (OpenAI), GPT-3.5 (OpenAI), GPT-4 (OpenAI), Claude (Anthropic), PaLM (Google), LLaMA and LLaMA 2 (Meta), Gemini, and many others. This flexibility allows you to choose the model that best suits your specific use case, whether you're building a chatbot, a content creation tool, or any other AI-powered application. You can experiment with different models and find the one that delivers the best performance for your project.

How can I integrate Google Vertex AI into my project?

Composio.dev provides a seamless integration for Google Vertex AI, making it super easy to incorporate this powerful framework into your projects. You can leverage the Composio.dev API to call functions from Google Vertex AI, allowing you to tap into its capabilities with just a few lines of code. The SDK is available in Python, JavaScript, and TypeScript, so you can work with your preferred programming language and integrate Google Vertex AI into your projects seamlessly.

What is the pricing for Google Vertex AI?

Google Vertex AI is completely free to use, with a generous free tier that allows up to 1000 requests per month. This makes it accessible for developers and organizations of all sizes to explore and experiment with this powerful tool without any upfront costs. Whether you're a student working on a personal project or a startup building the next big thing, you can get started with Google Vertex AI without worrying about breaking the bank.

What kind of authentication is supported for Google Vertex AI?

Google Vertex AI supports OAuth2 authentication, ensuring secure and authorized access to its functionalities. You can leverage the Composio.dev API to handle authentication and call functions from Google Vertex AI seamlessly. The SDK is available in Python, JavaScript, and TypeScript for your convenience, making it easy to integrate authentication into your projects and keep your users' data safe and secure.

Can I add Google Vertex AI to my project?

Absolutely! You can easily incorporate Google Vertex AI into your project by utilizing the Composio.dev API. This API allows you to call functions from Google Vertex AI, enabling you to leverage its capabilities within your application. The SDK is available in Python, JavaScript, and TypeScript to facilitate integration, so you can work with the language you're most comfortable with and add Google Vertex AI to your project with ease.

What is the accuracy of Google Vertex AI?

Google Vertex AI is designed to provide highly accurate and reliable results, ensuring that your AI applications perform at their best. The integration with Composio.dev ensures precise function calls, enabling you to build robust and powerful AI applications with confidence. Google Vertex AI's comprehensive framework and the ability to leverage state-of-the-art models ensure reliable and accurate outcomes for your AI development needs, whether you're working on a chatbot, a content creation tool, or any other AI-powered project.

What are some common use cases for Google Vertex AI?

Google Vertex AI can be used for a wide range of AI applications, making it a versatile tool for developers and creators alike. Some common use cases include natural language processing, text generation, question answering, sentiment analysis, and more. It's particularly useful for building chatbots, virtual assistants, content creation tools, and other AI-powered applications that can help you automate tasks, engage with users, and create compelling content. Whether you're working on a personal project or building a product for your startup, Google Vertex AI can help you bring your ideas to life.

How does Google Vertex AI handle data privacy and security?

Data privacy and security are crucial considerations when working with AI systems, and Google Vertex AI takes these issues seriously. It follows industry best practices and adheres to strict data protection regulations, ensuring that your data is kept safe and secure. Google Vertex AI provides robust security measures, such as encryption and access controls, to ensure the confidentiality and integrity of your data. You can rest assured that your sensitive information is protected when using Google Vertex AI for your AI development needs.