Integrate the Originality.ai API with the Python API

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

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Popular Originality.ai and Python Actions#

Detect AI Content with the Originality.ai API

Scans a string for AI content. 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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Detect AI From URL with the Originality.ai API

Scans a webpage for AI generated content. See the documentation

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Scan Content for Plagiarism and Readability with the Originality.ai API

Scans a string for plagiarism as well as readability. See the documentation

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Overview of Originality.ai#

The Originality.ai API provides functionality to check content for potential plagiarism and AI-generated text. Within Pipedream's serverless environment, you can construct workflows that automate the process of evaluating originality in large volumes of text, integrate plagiarism checks into content pipelines, and flag content for further review. By leveraging this API in Pipedream, you can harness event-driven, scalable workflows to ensure content integrity across various platforms.

Connect Originality.ai#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    originality_ai: {
      type: "app",
      app: "originality_ai",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.originality.ai/api/v1/account/credits/balance`,
      headers: {
        "X-OAI-API-KEY": `${this.originality_ai.$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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