Botpress

Automate complex conversations, tasks, and workflows — reliably.

Integrate the Botpress API with the Python API

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

Run Python Code with Python API on New Bot Event Created from Botpress API
Botpress + Python
 
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New Bot Event Created from the Botpress API

Emit new event from bot is created. See the documentation

 
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Add Participant To Conversation with the Botpress API

Adds a participant to a conversation. 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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List Conversations with the Botpress API

List conversations. See the documentation

 
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Overview of Botpress

Botpress is a powerful, open-source chatbot platform that enables developers to create intelligent, conversational bots. With its natural language understanding (NLU) capabilities, users can design bots that can interpret human language and respond appropriately. Utilizing the Botpress API on Pipedream allows you to automate interactions, analyze chat data, and integrate with various other services to enhance the functionality of your bots.

Connect Botpress

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    botpress: {
      type: "app",
      app: "botpress",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.botpress.cloud/v1/chat/users`,
      headers: {
        Authorization: `Bearer ${this.botpress.$auth.identity_token}`,
        "Content-Type": `application/json`,
        "x-bot-id": `${this.botpress.$auth.bot_id}`,
      },
    })
  },
})

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

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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}}