Integrate the ChatBot API with the Python API

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

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Popular Ways to Connect ChatBot with Python#

Run Python Code with Python API on New Event from ChatBot API

ChatBot + Python

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Popular ChatBot and Python Triggers#

New Event from the ChatBot API

Emit new event for event received. Need to be configured in the ChatBot UI flow to emit events. See docs here

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Popular ChatBot and Python Actions#

Create User with the ChatBot API

Creates new user. See docs here

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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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Get Users with the ChatBot API

Get a list of users. See docs here

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Overview of ChatBot#

Leverage the ChatBot API on Pipedream to automate conversations, streamline customer service, and connect chat functionality with various apps for rich, responsive interaction. With this API, you can programmatically send messages, manage chat histories, and implement chatbots that react to user input in real-time. By integrating with Pipedream, these capabilities can be augmented with thousands of apps, enabling seamless data flow and complex automations.

Connect ChatBot#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    chatbot: {
      type: "app",
      app: "chatbot",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.chatbot.com/stories`,
      headers: {
        Authorization: `Bearer ${this.chatbot.$auth.developer_access_token}`,
      },
    })
  },
})

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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