Currently, we are building a ChatBot which will be called NestorGR. It is a experimental try on the tech, since our team for the project (consisting currently of:

  • me as a Intern/back-end dev. I had never really made nothing “real” with python, so LOTS of stuff to learn. NICE! :smiley:
  • my mentor, who is the deploy/back-end guy (i started to take on the back-end tasks so he could focus on the kubernetes stuff for now)
  • a front-end dev for the user interface.

The idea as of now is to build a robust and scalable app based on microservices and implement it on our company website. We are a company of about 40ish devs and handle lots of projects for our city port (IIRC, brazil’s biggest), so there is lots of contact via our website/phone regarding status on the multiple projects.

NestorGR should handle most of the information about them, so we won’t need to allocate a person specifically to deal with this kind of conversation, and in last case guide the user to the proper sector dealing with it.

In future, we plan to integrate our company Facebook page to the AI, and with it stable enough, start to provide the service as an extra for our clients, using their APIs/whatsoever.

One of our main roadblocks as of now, and I would be very thankful if you guys have some suggestions are on how to:

  • Deal with him learning new stuff as users talk to the AI (I thought on saving every conversation on a postgres db and from times to times update our models - is it the right approach?)
  • Optimize our docker containers to proper good practices, since we are handling docker/docker-compose/kubernetes for the first time, so there are images of 1.xGb, which i guess that can be reduced a lot with alpine
  • Build a UI interface to improve workflow (we had some issues with rasa-ui, but are still using it for basics)
  • Apply good practices on Python codes. As it is my first time coding with python and coming from a JS-mainly background, there are some stuff i would like to improve.

If any of you guys have real-life examples with open-source code for me to study the workflow, file structure and such, I would be thankful. I’m loving it like never before, so I want to provide the best code i can offer! hahaha

cheers and keep on the good work, mates!


Our company have an app and web based e-commerce platform. So we are planing to build a bot which can help user to look for different product with the help of chat bot. For a use case, we are planing for user authentication through the bot. So my first question is , it it feasible or right use case for a chatbot. I was exploring different e-commerce chatbots for shopping. But all of them were based on contextual -UI . Is it practical to implement a shopping workflow from product search to checkout using RASA NLU and RASA core or any contextual AI framework.


I am not able to pass values from cmdline to the custom action script written in Python. Any idea on what am I missing or how to resolve it ?

Hi @jkc.kiran This is not a thread to ask these kind of questions. Create a new topic and add more details about your issue! Good luck!

Thanks @Akshit

I am working with Lichess Team (Chess playing website) to create a chatbot that works with Chess bots. Its still experimental but I got a very crude version of it working with NLU + Core.

The idea is that each chess bot can have its own bot and answers accordingly. So creating a framework for chess bot makers to make their own chatbot using Rasa’s tech.


Since I know Kubernetes and its packager Helm I’m working on a simple chart that will make possible to deploy on a cluster a simple chatbot given a github repository for nlu, stories and custom actions.

I already developed a chart that, when installed in the Kubernetes cluster, download stories, actions and nlu and use them to train a Rasa model.

In past I also developed simple Bot for Telegram using BotKit.

The idea would be to have a out-of-the-box Rasa chart to create and deploy self-service Bots.

I’m just wondering:

  • if this contribution can be a good idea and
  • to look if some is interested in the creation of the bot (nodeJS with BotKit and Rasa interaction)

Let me know if some is interested. Bye


Does Anyone Else Want a Search Engine API?

I was trying to make my own personal assistant chatbot with Rasa and I reaslised I don’t have access to information - like the weather, traffic, random trivia, random jokes and fun facts, recipes, news, sports results, etc. etc. - basically anything I would like to ask it.

So I decided I would make an information retrieval API for these fetching these kind of things and I think there could be a lot of people using Rasa that could use it. You can check it out at, we’ll be releasing an Alpha version soon.

If you’re interesting in using something like this, could you please heart this post :slight_smile: If people wanted to give more information, I would love to know:

  • what kind of device you are building?
  • how would people like to interact with it?
  • what kind of information do other people need?

Thanks all!


I have created couple of bots using (Webex teams+botkit) and (Webex Teams+dialogueflow). Now planning to use RASA stack for compliance reason and using AI capability of RASA. So appreciate you suggestion on below questions. Is RASA 1.0.1 provides integration with Webex Teams? If yes can I just add webex team token details in credentials.yml file ?

If no is it good idea to use botkit along with Webex Teams and Rasa stack ?


We’ve released an Alpha version of ‘The Search Engine for Artificial Intelligence’ at :tada: :clinking_glasses:

You can see a blog post showing how to integrate it with Rasa here:

It’s still in Alpha and needs a lot of work so any feedback you guys can give would be amazing! :pray:


Hi @Andrew-Murtagh. Wow, this is very cool!

Thanks @Juste, hopefully it will help some people build their bots :smiley:

Hello all, this is Ranjith from India/Tamil nadu /tirupur . I’m absolutely newbie for RASA. I have started few days ago. really its an interesting to learn and do chat bots. I like RASA X very much because without coding anything we can make a chat bot. thanks for entire team for make this.

Hey I’m working on developing a chatbot for a website . The bot respond for the user queries. The bot search in the website for user queries

I am new to Rasa and was hoping to get some guidelines on how to recreate a simplified version of Symptom Checker, Check Your Symptoms in Real Time | Buoy just for learning purposes.

What I’d like to achieve is a dialogue flow in which the user initially specifies one symptom (or is instructed to provide a symptom), the assistant retrieves a few associated symptoms from some external service (associated symptoms model) and asks the user about those all symptoms as follow up questions. Once the followup questions are all answered, then the assistant passes all the symptoms present (and not present) to some disease prediction model based on the symptoms to output some potential diagnoses.

For now I would just like to keep things simple with either yes the symptom is present, or no the symptom is not present (as I’m not sure how to handle if a user were unsure whether the symptom is present).

Example conversation:

input> I think I have a cough

#the entity is recognized as cough either from or a symptoms.txt lookup table

output> let’s determine some potential diagnoses

output> do you have a fever?

input> yes/no (or if this is possible via buttons then great)

output> do you feel dizzy?

output>possible diagnoses: bronchitis, benign cough, allergies, etc

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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.

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