Integrate the Rasa API with the Python API

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

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Popular Rasa 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 Rasa#

Rasa is an open-source platform for building conversational AI applications, including chatbots and voice assistants. It offers robust API endpoints for training models, managing conversations, and interpreting user messages, thus enabling the development of sophisticated AI-driven communication tools. When used with Pipedream, Rasa can automate dialogue flow, extract insights from conversation data, or trigger actions in other apps based on conversational cues.

Connect Rasa#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    rasa: {
      type: "app",
      app: "rasa",
    }
  },
  async run({steps, $}) {
    const data = {
      "key": `${this.rasa.$auth.key}`,
    }
    return await axios($, {
      method: "post",
      url: `https://api.rasa.io/v1/tokens`,
      headers: {
        "accept": `application/json`,
        "Content-type": `application/json`,
      },
      auth: {
        username: `${this.rasa.$auth.username}`,
        password: `${this.rasa.$auth.password}`,
      },
      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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