Integrate the Koala AI API with the Python API

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

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Popular Koala AI and Python Actions#

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 Koala AI#

The Koala AI API enables intelligent analysis of text and conversation data, offering insights and automation capabilities. With Koala AI API on Pipedream, you can craft serverless workflows that respond to data in real-time. Use it to analyze sentiment, categorize content, extract entities, and more. Build workflows that trigger on new data, process it through Koala AI, and act on the insights gained, like updating a database, sending notifications, or enriching CRM information.

Connect Koala AI#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    koala_ai: {
      type: "app",
      app: "koala_ai",
    }
  },
  async run({steps, $}) {
    const data = {
      "targetKeyword": `What is Pipedream?`,
      "gptVersion": `gpt-3.5`,
    }
    return await axios($, {
      method: "post",
      url: `https://koala.sh/api/articles/`,
      headers: {
        Authorization: `Bearer ${this.koala_ai.$auth.api_key}`,
        "Content-Type": `application/json`,
      },
      data,
    })
  },
})

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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