Integrate the One AI API with the Python API

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

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Popular One AI and Python Actions#

Find Text in Clusters with the One AI API

Find clusters with a similar meaning of a given text. 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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Summarize Text with the One AI API

Summarize a given text. See the documentation.

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Overview of One AI#

One AI API enables users to leverage advanced language AI to analyze and process text. On Pipedream, you can integrate One AI into serverless workflows to automate tasks like content summarization, emotion detection, or keyword extraction. By tapping into One AI's capabilities via Pipedream, you can enrich data, glean insights, and streamline content-centric operations with ease and efficiency.

Connect One AI#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    one_ai: {
      type: "app",
      app: "one_ai",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.oneai.com/api/v0/org/info`,
      headers: {
        "api-key": `${this.one_ai.$auth.api_key}`,
        "Accept": `application/json`,
      },
    })
  },
})

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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