![]() ![]() These env vars are necessary for using the WA API v2. Obtaining WA environment variablesīelow, we listed the environment variables (env vars) related to IBM Watson STT on our source code: To start working with the chatbot, download the JSON file at skills_assistant/OpenSource-Release-dialog.json, and navigate to the Skill dashboard as shown in this picture:Īfter that, choose "Create Skill", and there should be a button on the following page to upload a skill - upload the JSON file there. The chatbot used in this challenge is a Dialog Skill. There are three types of skills available at this time of writing: Action, Dialog, and Search. You then associate a given skill with your assistant. When you create your own Watson Assistant, you would see that it works by adding Skills. For example, if you said "hi" to a friend, that might be the start node in your conversation, which would then flow into a catching-up node as you ask your friend about their day. ![]() As seen in the next image image, talking to a chatbot can be thought of as interacting with a dialog tree, in which different nodes represent different stages in a conversation. ![]() The documentation has lots of helpful tips for working with WA. Watson Assistant (or WA) is the IBM Cloud service that actually implements the chatbot technology. On this page, you will find more information about Watson Services and how to obtain their API keys, which are necessary information to proceed to test and deploy the app. Based on research, we can affirm that Watson STT and TTS catalyze user engagement and make the chatbot more efficacious in talking, informing, and collecting data. The Watson Services are valuable tools for enhancing the effectiveness of conversational user interfaces. The AI components of the application, contained in the lilac box, were developed with IBM Watson Services: Watson Assistant, Watson Speech-to-Text, and Watson Text-to-Speech, part of the IBM technologies. Voice and Text Chatbot designed for WhatsApp and Telegram Watson ServicesĪs shown in the application architecture below, we built the app based on IBM technologies, such as Watson Assistant, Object Storage, and Code Engine. ![]()
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