Integrate the Google Vertex AI API with the Python API

Setup the Google Vertex AI API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Google Vertex AI and Python remarkably fast. Free for developers.

Popular Google Vertex AI and Python Actions#

Analyze Image/Video with the Google Vertex AI API

Examines an image or video following given instructions. Results will contain the analysis findings. See the documentation

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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Analyze Text Sentiment with the Google Vertex AI API

Analyzes a specified text for its underlying sentiment. See the documentation

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Classify Text with the Google Vertex AI API

Groups a provided text into predefined categories. See the documentation

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Overview of Google Vertex AI#

With the Google Vertex AI API, you can tap into a robust suite of AI tools offered by Google Cloud to build, deploy, and scale machine learning models. Whether you're processing data, training custom models, or using pre-trained ones, Vertex AI provides a unified platform for AI development. In Pipedream, you can create serverless workflows that interact with Vertex AI, allowing you to automate tasks like model training, prediction, and resource management without provisioning your own infrastructure.

Connect Google Vertex AI#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    google_vertex_ai: {
      type: "app",
      app: "google_vertex_ai",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://www.googleapis.com/oauth2/v1/userinfo`,
      headers: {
        Authorization: `Bearer ${this.google_vertex_ai.$auth.oauth_access_token}`,
      },
    })
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}