Integrate the Wonderchat API with the Python API

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

Popular Wonderchat 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.

Try it

Overview of Wonderchat#

The Wonderchat API lets you automate interactions with your Wonderchat account, streamlining conversations and enhancing customer engagement. On Pipedream, you can build workflows that trigger on specific events and automate tasks like sending messages, managing contacts, or integrating with CRMs. By coupling the Wonderchat API with Pipedream’s capabilities, you get a powerful synergy where you can seamlessly connect various apps and services, run serverless code, and manipulate data with ease.

Connect Wonderchat#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    wonderchat: {
      type: "app",
      app: "wonderchat",
    }
  },
  async run({steps, $}) {
    const data = {
      "apiKey": `${this.wonderchat.$auth.api_key}`,
      "chatbotId": `{{your_chatbot_id}}`,
      "question": `{{your_queston}}`,
      "chatlogId": `{{your_chatlog_id}}`,
      "context": `{{your_context}}`,
    }
    return await axios($, {
      method: "POST",
      url: `https://app.wonderchat.io/api/v1/chat`,
      headers: {
        "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}}