Integrate the Claid AI API with the Python API

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

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Popular Claid AI and Python Actions#

Correct Color & Lighting with the Claid AI API

Automatically adjusts the color and lighting of an image by applying HDR. The result is an enhancement of the dynamic range in dark or overexposed images. 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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Remove Background with the Claid AI API

Easily erases the image's background, effectively isolating the main subject. See the documentation

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Upscale Image with the Claid AI API

Enlarges the selected image in order to improve its resolution. By running this action, users can obtain clearer and sharper images. See the documentation

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Overview of Claid AI#

Claid AI API provides tools for image enhancement, including resizing, cropping, increasing resolution, and optimizing for web use. It's suitable for automating image processing tasks in applications like e-commerce, real estate, and content management. On Pipedream, you can create serverless workflows that use the Claid AI API to process images in response to various triggers, such as new file uploads or webhooks, and then pass the processed images to other services or store them.

Connect Claid AI#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    claid_ai: {
      type: "app",
      app: "claid_ai",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.claid.ai/v1-beta1/storage/storages`,
      headers: {
        Authorization: `Bearer ${this.claid_ai.$auth.api_key}`,
      },
    })
  },
})

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}}

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