In this Quickstart we are setting up our first source, listen to conversations, and consume directly from Kafka
We are going to use Airy's Live Chat Plugin as our first source. We then use the plugin to send messages, and check them out in the UI, your terminal and directly in Apache Kafka.
Airy's Live Chat Plugin can be connected both through API request and the UI. This document covers both options.
- Step 1: Set up your first source
- Step 2: Send messages via the Chat Plugin
- Step 3: Use the HTTP API to list conversations
- Step 4: Consume directly from Apache Kafka
Did you already install the Airy CLI?
To get going with the Quickstart, you must install Airy first. Once the CLI is up and running you are good to go.
The ID from the response is the
channel_id. It is required for
the next steps, so note it down.
Alternatively, you can connect an Airy's Live Chat Plugin channel via the UI.
On your instance's Airy Core UI, click on the 'Channels' icon on the left sidebar menu. Then, click on the button displaying a + icon next to the Airy Live Chat channel.
Next, click on the blue button "Connect Airy Live Chat".
Enter a display name and optionally an image URL in the respective fields. The display name will be used as the conversation's name while the image URL will be used as its icon in the Inbox UI. A fallback image will be used if you do not enter a valid image URL. Click on the Save button.
This will bring you to a page where you can edit or disconnect each channel. Click on 'Edit'.
Click on the 'Install app' tab. Here you will find the
channel_id, which is located in the sample code (highlighted in the screenshot above). It is required for the next steps, so note it down.
channel_id as a query parameter when opening the demo page in your
browser. This authenticates the chat plugin and enables you to send messages
You can now type a message in the text box and send it 🎉
To see how messages are flowing through the system, list conversations for the channel you have just created. it should return the message you have just sent.
You can also consume the messages directly from the Kafka