Markdown example You can use some markdown in your replies for the Web channel. Use this flow to take some inspiration! ``` You should go to [Tiledesk](https://www.tiledesk.com) Or https://www.tiledesk.com **This is bold** *Italic here* or _italic here too_ Manufacturing in AI 2025 (A table) | Year | Adoption AI (%) | Cost Reduction (%) | Productivity Increment (%) | Reduced Issues (%) | average Revenue from AI (M€) | |------|-----------------|----------------------|--------------------------|---------------------|----------------------------| | 2020 | 12 | 5 | 4 | 3 | 1,2 | | 2021 | 20 | 8 | 7 | 6 | 2,8 | | 2022 | 33 | 12 | 11 | 10 | 5,5 | | 2023 | 45 | 18 | 16 | 14 | 9,7 | | 2024 | 58 | 24 | 21 | 19 | 15,3 | | 2025 | 70 | 30 | 28 | 25 | 22,6 | <br> **A List** - One - Two - Three & a urls [Tiledesk](https://www.tiledesk.com) https://www.tiledesk.com Markdown Image  ```

In the Dynamic branch we set (using Set Attribute) this array of JSON values (suppose coming from a shop web service): <img src="https://tiledesk-html-site-tiledesk.replit.app/images/carousel1.png" alt="Products JSON" width="1000"> ``` [ { "name": "Product 1", "description": "Top notch, best price", "imageURL": "https://t4.ftcdn.net/jpg/01/86/85/71/360_F_186857190_s4dfc0wfT6jcEcr7e3vzrFuUdysg6Gpp.jpg" }, { "name": "Product 2", "description": "On Sale", "imageURL": "https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTz1i9qjMUbhwRSaCOzNKTH00O_bfpp9SHV-g&s" } ] ``` Then we used a dynamic carousel with this JSON structure: <img src="https://tiledesk-html-site-tiledesk.replit.app/images/carousel2.png" alt="JSON Gallery" width="1000"> ``` [ {% for item in results limit:10 %} { "preview": { "src": {{item.imageURL | json}} }, "title": {{item.name | json}}, "description": {{item.description | json}}, "buttons": [{"type": "url","value": "Buy","link": {{item.imageURL | json}}}] }{% unless forloop.last %},{% endunless %} {% endfor %} ] ``` If everying works fine you should have a carousel rendered correctly: <img src="https://tiledesk-html-site-tiledesk.replit.app/images/carousel3.png" alt="JSON Gallery" width="1000">

Use this project to set up a chatbot using the Replace Bot action with the new slug property. See more documentation here: https://gethelp.tiledesk.com/articles/enhancing-conversation-flows-with-replace-bot-action/

With this chatbot you will have a good base to create a conversation where you can use ChatGPT (and generative AI in general) to manage the Named Entity Recognition (NER) in a new, fancy and seamless way powered by Generative-AI. Please read this article on our blog to fully discover more on this piece of art! : ) https://tiledesk.com/engineering/named-entity-recognition-with-generative-ai/ Bye

### Tutorial: Integrating ActiveCampaign with Tiledesk This tutorial will guide you through integrating ActiveCampaign with Tiledesk to send WhatsApp messages triggered by an automation workflow. Follow these steps: --- #### Step 1: Create a New Bot in Tiledesk 1. Log in to your **Tiledesk Dashboard**. 2. Create a new bot: - You can either build a bot from scratch or import this Bot. 3. Once the bot is set up, proceed to configure actions. --- #### Step 2: Configure the WhatsApp Action in Tiledesk 1. Navigate to the **Actions Menu** within your bot settings. 2. Select the action **Send WhatsApp** from the list. 3. Populate the following required information: - **Phone Number ID**: Obtain this ID from the **Meta for Developers** platform where you’ve installed your WhatsApp app. You can find it in the **API Configuration** section, as shown below: *(Insert relevant image here)* - **WhatsApp Template**: Choose any pre-approved WhatsApp template you've created in Meta. If you need help with creating templates, [see more about templates here](https://gethelp.tiledesk.com/articles/how-to-use-whatsapp-templates-with-tiledesk/). - **Variables**: Insert the relevant placeholders, such as the recipient's phone number and first name, for dynamic messaging. --- #### Step 3: Create an Automation in ActiveCampaign 1. Log in to your **ActiveCampaign** account. 2. Go to the **Automation** section and create a new workflow. 3. Select your desired **Trigger** and choose the **Webhook** option from the workflow list. This will allow ActiveCampaign to call Tiledesk when the trigger conditions are met. --- #### Step 4: Set Up the Webhook URL in ActiveCampaign To integrate ActiveCampaign with Tiledesk, you need to generate a Webhook URL for your bot: 1. Use the base URL: ``` https://api.tiledesk.com/v3/modules/tilebot/ ``` 2. Append the following details to complete the Webhook URL: - **Project ID**: Your Tiledesk project ID. - **Chatbot ID**: The ID of the chatbot you want to trigger. - **Block Name**: The name of the block to activate (usually `"start"`). The final URL format should look like this: ``` https://api.tiledesk.com/v3/modules/tilebot/block/PROJECT-ID/CHATBOT-ID/start ``` 3. Insert this Webhook URL into ActiveCampaign’s webhook field in your automation workflow. --- #### Example: Complete Webhook URL Suppose your: - Project ID: `12345` - Chatbot ID: `67890` Your Webhook URL will look like this: ``` https://api.tiledesk.com/v3/modules/tilebot/block/12345/67890/start ``` --- With this integration, you’ve successfully linked ActiveCampaign and Tiledesk. Now, whenever the automation trigger fires in ActiveCampaign, your Tiledesk bot will send a WhatsApp message using the configured template. --- If you have any questions or run into issues, feel free to [reach out to the Tiledesk Community](https://github.com/Tiledesk) for support!

Sometimes the "else" branch doesn't behave as expected. Simply add a further GPT Task to analyze the user question and the KB reply and ask GPT to find out if the two really fit together.

Find more info here: https://gethelp.tiledesk.com/articles/mix-multiple-knowledge-bases-outcomes/

This chatbot shows how to use the Set Attribute Action to create a simple message counter createing an expression like counter = counter + 1

The most easy and straightforward experience to create and interact with your OpenAI Assistants. <center> <img width="900" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/chatGPT-assistant-preview.png"> </center> <br> With Tiledesk you can easily setup and interact with your ChatGPT Assistants on multiple channels (Whatsapp, Facebook etc.). With a single drag & drop! See docs here [OpenAI Assistants](https://gethelp.tiledesk.com/articles/chatgpt-assistant-action-beta/)

A very simple Chatbot A/B test with Code Action using a random value <center> <image width="1200" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/ABtest/AB-test-chatbot.png"> </center> Use the Code Action to set a random attribute that will be used by the following Condition Action to choose a corrispondent flow path

A very simple Chatbot A/B test with Code Action using a random value

This template provides a simple flow to always trigger the "start" block on the first end-user message, whatever he writes. This flow is useful when you send a push Whatsapp message through APIs and you previously enabled a bot on the corresponding Whatsapp department. When you configure a department for Whatsapp, as soon as you send a message (using APIs) to the end-user on Whatsapp he can start to interact with you. If a chatbot is configured on the Whatsapp department the user will interact with the chatbot. If you want the end-user to start interaction always from the "start" block, whatever he writes (i.e. to always show the start menu), this flow is for you. <br> <br> <center> <image width="550" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/whatsapp-start/whatsapp-first-message-schema.png"/> <br>First message sequence </center> <br> Simply import the chatbot and feel free to modify adding additional blocks to implement your own logic. If you need support feel free to write to support@tiledesk.com <br> <br> Have fun with Tiledesk 🥰

A simple template demonstrating how to manage buttons-by-title-typing selection

Simple hello using GPT Task Action

Use this template to understand how the Code Action actually works. I hope this is self-explanatory, while we'll be out with the documentation. The basics are: The language is actually Javascript. Use **context.attributes.KEY** or **context.attributes[KEY]** to read the value of a flow attribute Ex. ``` let age = context.attributes.age; ``` Use **context.setAttribute(KEY, VALUE)** to set the value of an attribute Ex. ``` context.setAttribute('age', 35); ```

Multi language chatbot using Globals section to host all the translations in JSON format. <br/> <center> <img width="1200" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/multi_language_1/multi_language_2.png"> </center> <br/> Create a JSON object with translations hosted in Globals section of the chatbot. <br/> <center> <img width="1200" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/multi_language_1/globals.png"> </center> <br/> The should have a structure like the following (keep in mind that this is only a suggested structure, you're free to implement the JSON object that best fits your needs): ``` { "en": { "welcome": "Welcome", "support_button": "Support", "sales_button": "Sales", "welcome_support": "Welcome to support", "welcome_sales": "Welcome to sales", "fallback_message": "I didn't understand" }, "it": { "welcome": "Welcome IT", "support_button": "Support IT", "sales_button": "Sales IT", "welcome_support": "Welcome to support IT", "welcome_sales": "Welcome to sales IT", "fallback_message": "Non ho capito" }, "es": { "welcome": "Welcome ES", "support_button": "Support ES", "sales_button": "Sales ES", "welcome_support": "Welcome to support ES", "welcome_sales": "Welcome to sales ES", "fallback_message": "No entendía" } } ``` Import and enjoy the simplicity!

This multi-language chatbot is able to send text in multiple languages based on the browser language. It uses an approach based on [Reply Filters](https://gethelp.tiledesk.com/articles/reply-action/). The basic idea is that you can use some available attribute to "filter" in (or out) some replies' components (i.e. text, images etc.). The Filter feature is available on each reply component. When we work with languages we can use the [user_language](https://gethelp.tiledesk.com/articles/flow-attributes/#most-used-attributes) attribute that always represents the ISO language of the user on the channel he's using to communicate on Tiledesk. Take a look at the whole chatbot design. It is made up of four total replies. <center> <br/> <image width="1000" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/multi_language_1/multi_language_basic_chatbot_schema.png"> </center> <br/> <br/> 1. Welcome reply (greet the user in three supported languages) 2. Sales specific welcome message 3. Support specific welcome message 4. Fallback message Each reply is managed "multi language", supporting three total languages: 1. English (iso code "en"). It also acts as **pivot language** (the fallback language used when there is no support for the user-language by the chatbot) 2. Italian (iso code "it") 3. Spanish (iso code "es") Focus on the welcome block. It's made up of one Reply action, "composed" by three different messages. Each one is filtered based on the user language got from the communicating channel. We "filtered" each text reply adding a filter condition on each one. The filters are basically all the same, as you can see in the figure, except for the "en" part of the reply. We want english to be also the defalt language so we must add another condition on it useing the special regex "matches" condition". <br/> <center> <br/> <image width="1000" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/multi_language_1/multi_language_1.png"> <br/> </center> We used the regex: ``` ^((?!it|es).)*$ ``` We use this regex to get a "true" condition when the user language is different by the other two that we know are supported. As you can see the languages are represented by their iso codes "it" and "es". <center> <br/> <image width="1000" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/multi_language_1/multi_language_pivot_regex.png"> <br/> </center> If you support other languages different by the pivot one, you should add them here, adding them like in the following example: <br/> ``` ^((?!it|es|fr|ru).)*$ ``` In the previous expression we also added support for French (iso code "fr") and Russian (iso code "ru").

A simple chatbot showing how you can chain multiple actions to get multiple user data using the Capture User Reply and the Reply action together. <center> <br/> <br/> <image width="1000" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/capture_reply_chain_shema.png" /> <br/> <br/> </center> Please refer to the [Capture User Reply](https://gethelp.tiledesk.com/articles/capture-user-reply-action/) official documentation for more info.

A simple chatbot demonstrating the Capture User Reply. Please refer to official documentation to learn how to use the Capture User Reply action [Capture user reply documentation](https://gethelp.tiledesk.com/articles/capture-user-reply-action/)

This chatbot demonstrates how you can mix some useful rest APIs (www.wetherapi.com) with ChatGPT to create a dynamic and beautiful welcome messages. Enjoy!

This chatbot shows how to invoke https://www.weatherapi.com/ APIs to get weather info. <br/> <center> <image width="1100" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/weather_tutorial/weather_flow.png"> </center> <br/> It uses the HTTP GET method to invoke the APIS, getting back the conditions JSON and whowing the rusults. Keep in mind that you must create an API KEY on the website after signup. Put the API KEY in GLobals section and name it *www_weather_com_api_key*: <br/> <center> <img width="600" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/weather_tutorial/weather_apikey.png"> </center>

<br/> <center> <img width="1300" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/hubspot_webrequest/hubspot-webrequest-banner.png"> </center> <br/> This simple chatbot gets user data through a dyna-form and then creates (or updates) a Contact on [Hubspot](https://www.hubspot.com/). To use this integration you need a **Hubspot Access token**. We'll learn how to create one. We use the "Capture user reply" action to ask the follwing data, creating the corresponding chatbot attributes: * User first name. Attribute: _firstname_ * User full name. Attribute: _lastname_ * User email. Attribute: _userEmail_ Once the form is configured you can move to the next step, sending contact's data to Hubspot. To achieve this goal first [create a new Private App](https://developers.hubspot.com/docs/api/migrate-an-api-key-integration-to-a-private-app#create-a-new-private-app) on Hubspot. In this way you will get a new **Access token** to connect to their APIs. ## Hubspot Private app When asked, select the "scope" of your app, taking care of selectiong "contacts" and assigning at least the Write permission (that we use for our chatbot). <img width="800" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/hubspot_webrequest/hubspot_permissions1.png"> Once created you can go to the App's details page where you can get your **Access token**. We'll use this later. <img width="800" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/hubspot_webrequest/hs_apikey2.png"> ## Configure your connection Now back to our chatbot. Add the Hubspot APIKEY to the Globals section of your chatbot. <img width="800" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/hubspot_webrequest/hs_globals2.png"> Now add a _WebRequest_ Action from the side menu. The WebRequest Action simply executes an HTTP call to the Hubspot "create a contact" REST API. See related [https://developers.hubspot.com/docs/api/crm/contacts](https://developers.hubspot.com/docs/api/crm/contacts) documentation. <img width="800" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/hubspot_webrequest/webrequest_auth3.png"> Setup the HTTP url with the documented API endpoint using the **POST** HTTP method. Hubspot contact's **API endpoint**: ``` https://api.hubapi.com/crm/v3/objects/contacts ``` Then setup all the HTTP headers fields as in the picture, taking care to add or customize the **Authorization** header field with your own **Access token**. **Contact JSON body**: ``` { "properties": { "email": "{{userEmail}}", "firstname": "{{firstname}}", "lastname": "{{lastname}}" } } ``` Well, now press _Test it out_ to see the chatbot in action: <img width="400" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/hubspot_webrequest/final5.png"> As soon as the conversation ends The WebRequest action sends all the contact data to Hubspot Contacts. You we'll see your updated contact in the Hubspot's Contact center: <img width="800" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/hubspot_webrequest/final6.png"> Hope you enjoy this simple chatbot 🤖 If you need any help please feel free to contact me at _andrea_ _at_ _tiledesk.com_ 🤓

This chatbot will decode entities like **email** and **fullname** directly from the user text with a simple ChatGPT prompt. <br/> <br/> <center> <img width="700" alt="Designer ChatGPT" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/ner_gpt/GPTNERimage2.png"> </center> <br/> In this chatbot I used a special prompt to ask ChatGPT to reply me with a JSON structure with the entites I asked it to decode from the user text. <br/> <br/> <center> <img width="700" alt="Designer ChatGPT Prompt" src="https://tiledesk-html-site-tiledesk.replit.app/images/public/ner_gpt/GPTNERimage2.png"> </center> <br/> The used prompt: <br/> <br/> ``` The user provided the info in the "user reply" section below. Can you detect thei fullname and email? Once detected please reply with the following JSON structure, fufilled with the detected entities. Please when the user don't provide some of the previous info fulfill the corrispondent one with null. { "userName":"the detected username", "userEmail": "the detected email" } User reply: {{user_reply}} ``` <br/> The prompt will reply with a JSON strcture fulfilled with the requested key/values. I asked to use "null" values when entities are not recognised, so the corrispondent form fields are automatically triggered. The returned JSON is automatically converted to a JSON object. The GPT Task action always checks if the returned GPT response has a JSON structure. In this case the returned payload is automatically converted to a JSON object. Decoded entities are then moved into the conversation attributes as "flat" attributes, so they can be used within a form. The form will ask the user for all the missing entities automatically. Feel free to contact me at support@tiledesk.com

This template demonstrates how to use Conditions for branching inside a chatbot flow Video tutorial available here:

A simple chatbot with a very simple form asking your visitors some useful data 🙂 It's just a very simple chatbot with a basic form, asking data as soon as a conversation starts (before any interaction will take place). Enjoy the simplicity of Tiledesk forms!

A simple "quiz on Javascript" submitted through a Chatbot 🤓 You can use this chatbot to submit a simple test to your audience. This test makes wide use of "attributes" and "conditions" (aka the "flow"). ## Quiz Design The test uses "attributes". Attributes are a great way to manage your chatbot flow, and they are especially useful to store some in-flow data that can be also used later to manage your flow with conditions (you can use your attributes in any actions). <img width="900" alt="image" src="https://user-images.githubusercontent.com/32564846/229458815-17de81e8-55b1-403e-8773-d2e584514b77.png"> The test starts with the “Start quiz” button in the **“start” block**. Set up the _total_ attribute to his initial value of zero when the button is pressed. > TIP: Button’s “Attributes” option allows you to set up as many attributes as you want on a single button pressure. <img width="700" alt="image" src="https://user-images.githubusercontent.com/32564846/229460968-d180dc71-e92d-464b-88ce-79f7b61139c1.png"> <img width="528" alt="image" src="https://user-images.githubusercontent.com/32564846/229474089-13f48286-2c11-4d36-8803-1668f9a2412a.png"> The first question (**question1 block**) simply proposes four possible replies (plus a "Cancel test" option), where only one is true. We always use the Button's Attributes feature to set the current test score. Every time the user pressed the correct reply's botton the total score increases of the corresponding amount. When an incorrect reply is selected the score is set to zero. <img width="1132" alt="image" src="https://user-images.githubusercontent.com/32564846/229462520-f656e68e-5912-45b0-b9d4-63ef91e61ae4.png"> <img width="900" alt="image" src="https://user-images.githubusercontent.com/32564846/229464270-bbdce1af-7efb-4095-8a34-52009384e0f0.png"> Now move to **question2**. From now on, until the last question, each question will have the same identical structure. On each question we simply increase the "total" score adding the current reply's score coming from the previuos button press. <img width="900" alt="image" src="https://user-images.githubusercontent.com/32564846/229466456-b72a3dc9-b3f6-44a8-9aa2-a6c83de5c199.png"> The first action of each question always computes the new total, adding the actual question score - the one you got by pressing the choosen reply-button. After all, it’s a simple _add_ operation: ``` total = total + score ``` On the last question, as soon as the test comes to the end, the chatbot will branch on specific replies, based on your total score. Take a look at the branh_result block. It's made by threee condition-actions. Each action will move to the reply specific for the score. <img width="900" alt="image" src="https://user-images.githubusercontent.com/32564846/229618419-6f4a3b93-e556-473a-acb8-6820e56742d8.png"> And the result... <img width="300" alt="image" src="https://user-images.githubusercontent.com/32564846/229619734-f3863691-d384-4b7e-824c-d9e1e76ff938.png"> ## Proactive rules We also created a rule to proactively engage your visitors to open and complete the test. <img width="300" alt="image" src="https://user-images.githubusercontent.com/32564846/229613928-601a56e4-971d-4e0e-b6c8-6b89b80013d7.png"> Setup your proactive rule in the rules section: <img width="300" alt="image" src="https://user-images.githubusercontent.com/32564846/228898518-fab82c21-422b-435d-b18b-76a3104e39ca.png"> This rule simply states that whatever link you open the proactive block will be invoked: <img width="900" alt="image" src="https://user-images.githubusercontent.com/32564846/229614324-c0665ce9-de02-4132-95fd-a2e6b24b61f4.png"> ## Ask visitor name We also used "forms" to ask your visitor's data (his name). You can find the Form setup in the "start" block. <img width="900" alt="image" src="https://user-images.githubusercontent.com/32564846/229614743-e6004919-750c-43b5-af7d-379de1f83de6.png"> ## Whatsapp It also works on Whatsapp! Just push the green button et...voilà, it's ready to run on Whatsapp! <img width="300" alt="image" src="https://user-images.githubusercontent.com/32564846/229617345-f2e406ed-3a61-442b-8fd0-333769a328fc.png"> ## Conclusions Feel free to import and modify this test as you prefer. Let us know if you have some questions about this template writing a message to *andrea@tiledesk.com*

A simple chatbot that gives the option to move your widget conversation to a Whatsapp number.

Gives a suggestion for the selected Assignment

Replace the current bot with the browser language bot. The pivot-language bot is added when no matching language is available.

A simple chatbot that moves you to the first available agent only when there is someone online. When there are no available agents the chatbot will reply with a notice message.

A basic chatbot that asks for your customer's contact info in more natural way thanks to a conversational form that is highly customizable.

En grundläggande chatbot med start- och reservavsikter. Det inledande hälsningsmeddelandet är på engelska såväl som det förinställda återgångsmeddelandet. Det första meddelandet tränas också med en minimal uppsättning träningsfraser. Bra att implementera din logik från början.

Başlangıç ve geri dönüş amaçlarına sahip temel bir sohbet robotu. İlk selamlama mesajı, defaultFallback mesajının yanı sıra İngilizce'dir. İlk mesaj aynı zamanda minimum sayıda eğitim cümlesi ile eğitilir. Mantığınızı sıfırdan uygulamak güzel.

Un chatbot básico con las intenciones de inicio y respaldo. El mensaje de bienvenida inicial está en inglés, así como el predeterminado. El mensaje inicial también se entrena con un conjunto mínimo de frases de entrenamiento. Es bueno implementar tu lógica desde cero.

Базовый чат-бот с начальным и резервным намерениями. Начальное приветственное сообщение на английском языке, а также по умолчанию. Исходное сообщение также обучается на минимальном наборе обучающих фраз. Хорошо реализовать свою логику с нуля.

Un chatbot de bază cu intenții de pornire și de rezervă. Mesajul inițial de salut este în engleză, precum și cel implicitFallback. Mesajul inițial este, de asemenea, antrenat cu un set minim de fraze de antrenament. Bine să-ți implementezi logica de la zero.

Um chatbot básico com as intenções de início e retorno. A mensagem de saudação inicial está em inglês, assim como a defaultFallback. A mensagem inicial também é treinada com um conjunto mínimo de frases de treinamento. É bom implementar sua lógica do zero.

En grunnleggende chatbot med start- og fallback-hensikter. Den første hilsenen er på engelsk, så vel som den standard tilbakegangsmeldingen. Den første meldingen trenes også med et minimalt sett med treningsfraser. Godt å implementere logikken fra bunnen av.

Alapvető chatbot, indulási és visszaállítási szándékkal. A kezdeti üdvözlő üzenet angol nyelvű, valamint az alapértelmezett Fallback üzenet. A kezdeti üzenetet a képzési kifejezések minimális halmazával is betanítják. Jó megvalósítani a logikáját a semmiből.

Ein einfacher Chatbot mit den Start- und Fallback-Intents. Die anfängliche Begrüßungsnachricht ist ebenso wie die defaultFallback-Nachricht auf Englisch. Die anfängliche Nachricht wird auch mit einem minimalen Satz von Trainingsphrasen trainiert. Gut, um Ihre Logik von Grund auf neu zu implementieren.

Un chatbot de base avec les intentions de démarrage et de secours. Le message d'accueil initial est en anglais ainsi que celui par défaut. Le message initial est également entraîné avec un ensemble minimal de phrases d'entraînement. Bon pour mettre en œuvre votre logique à partir de zéro.

Perus-chatbot, jolla on aloitus- ja palautustarkoitukset. Ensimmäinen tervehdysviesti on englanniksi sekä oletusarvoinen Fallback-viesti. Alkuviesti opetetaan myös pienillä harjoituslauseilla. Hyvä toteuttaa logiikkasi tyhjästä.

Een basischatbot met de start- en terugvalintenties. Het eerste begroetingsbericht is in het Engels, evenals het standaardFallback-bericht. Het eerste bericht wordt ook getraind met een minimale set trainingszinnen. Goed om je logica vanaf nul te implementeren.

En grundlæggende chatbot med start- og fallback-hensigter. Den indledende hilsen er på engelsk såvel som standardtilbagegangsbeskeden. Den indledende besked er også trænet med et minimalt sæt træningssætninger. Godt at implementere din logik fra bunden.

A basic chatbot with the start and fallback intents. The initial greet message is in english as well as the defaultFallback one. The initial message is also trained with a minimal set of training phrases. Good to implement your logic from scratch.

Un chatbot molto semplice che dispone solo degli intent start e defaultFallback. Il saluto iniziale è in italiano, così come il messaggio per il fallback. Il messaggio di saluto iniziale è addestrato con un minimo set di possibili frasi utente (ex. Ciao, buongiorno...). Ottimo per implementare la tua logica partendo dal minimo indispensabile.