Would like to build nodeJS SDK for rasa.

Here’s my first step - formAction SDK for rasa on NodeJS - NPM

To suggest changes or report issues: Issues · rohitnairtech/nodejs-formaction-sdk-rasa · GitHub

Hi there, I’m also new on Rasa, I’ve been “playing” with spaCy for some weeks to train a HR machine learning model, then now I’m going to use Rasa with this model to make some kind of recruitment assistant. The project is to allow multiple tasks like :

  • Allow user to ask company specific question(based on a FAQ db linked to each company)
  • Allow user to search for job and return them some jobs based on their replies and properties collected
  • Be able to pre-fill application forms from Rasa collected Datas (and add Rasa chat logs to the application meta-datas)

In future, I’m going to add a “login” interface to allow user to logged in, and then have some kind of a personal assistant.

So here is my project with Rasa. Of course all of this will be used on as full gitlab with CI/CD pipeline on Kubernetes cluster.

Hello everyone! Please find below this project completed at ISS-Software Hive, Lebanon:
Digital Assistant Robot: Helping ISS Software Hive employees manage their leave and visa requests
Digital Assistant Robot (DAR) is a digital employee, built using Rasa, that manages all leave and visa requests at ISS Software Hive.

The chatbot helps employees submit leave requests through WhatsApp or Telegram. Employees can also view their submitted requests, track requests, view pending tasks, and respond directly to tasks.

The chatbot offers employees the convenience of submitting a visa request directly from their mobile device, without opening the browser.

DAR is integrated with Nintex Workflow Cloud (NWC), a cloud-first automation platform that integrates with systems of record and existing tools to accelerate digital transformation. Using Nintex Workflow Cloud, the leave management process and visa request application workflow are streamlined and automated to improve productivity and increase efficiency.

Employees’ requests are analyzed and classified using a document image classifier engine based on machine learning technology.

Languages supported: Arabic, English.

You can find below a demo:

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story: check_confirmation path steps: checkpoint: check_asked_question intent: greet action: utter_greet intent: mood_great action: utter_happy intent: worktime action: action_check_confirmation intent: check_confirmation

Hi. I’m working on a project of implement the telegram inline functionality. I’ll share the code on github and I want to write a tutorial ifor the blog. I annexed an example conversation with IMDBpy.



We are working on a proof-of-concept to help local UK councils serve their citizens with answers to everything “recycling”. This leverages many features in RASA including:

  • DIET Classifier and Entity Extraction
  • Real-time Website scraping for dynamic, up to date information
  • Complex disambiguation with entities e.g. home addresses for bin collections
  • Simple FAQs through to complex dialogues
  • Memory to help pre-populate information in different conversations
  • Users can drive the conversation using natural language and/or buttons (where appropriate)

We have created a video of it in action below. Built using RASA 2.7.



YouTube Video: Local Council Recycling Bot

More Information here: Bertie the Local Council Recycling Bot