Gan.AI

Personalized videos at scale.

Integrate the Gan.AI API with the Python API

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

Create Videos with the Gan.AI API

Creates videos in bulk by passing tags and values. Requires a project ID. 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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Overview of Gan.AI

Gan.AI is a dynamic API that leverages the power of generative adversarial networks (GANs) to create synthetic datasets, simulate user behaviors, and generate realistic images or text. With Gan.AI, developers can enhance their applications by integrating AI-generated content that improves user engagement and simulates various scenarios for testing or training models. Using Pipedream, you can automate workflows involving Gan.AI to process data, trigger AI-based actions, and connect outputs to other apps for extended functionality.

Connect Gan.AI

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    gan_ai: {
      type: "app",
      app: "gan_ai",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.gan.ai/projects/v2`,
      headers: {
        Authorization: `Bearer ${this.gan_ai.$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

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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}}