Integrate the LiveChat API with the Python API

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

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Popular LiveChat 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 LiveChat#

LiveChat API unlocks the capability to integrate your customer service system with powerful automation and data processing. Through Pipedream, you can harness this API to create workflows that trigger actions within LiveChat, synchronize data with other services, and analyze customer interactions to improve support experiences. Pipedream's serverless platform allows you to connect LiveChat with hundreds of other apps with minimal setup, enabling your customer support to be as responsive and informed as possible.

Connect LiveChat#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    livechat: {
      type: "app",
      app: "livechat",
    }
  },
  async run({steps, $}) {
    const data = {
      "all": `true`,
    }
    return await axios($, {
      method: "post",
      url: `https://api.livechatinc.com/v3.5/configuration/action/list_channels `,
      headers: {
        Authorization: `Bearer ${this.livechat.$auth.oauth_access_token}`,
        "Content-Type": `application/json`,
      },
      params: {
        organization_id: `${this.livechat.$auth.organization_id}`,
      },
      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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