Welcome to the Slack Mention Poem Generator template! This template allows you to create an app that listens for mentions on Slack and responds with a custom-generated poem based on the user's message. It's a fun and interactive way to engage with your team or community on Slack.
To get started, simply click Start with this Template on the Lazy platform. This will set up the template in your Lazy Builder interface, and you'll be ready to customize it to your liking.
Before you can use this template, you'll need to set up two environment secrets:
These tokens are essential for authenticating your app with Slack. Here's how to obtain and set them:
No external integrations are required for this template beyond setting up the Slack app and obtaining the necessary tokens as described above.
After setting up your environment secrets, you can use the Test button to deploy your app. The Lazy CLI will guide you through any additional user input that may be required. Once the app is running, you'll be able to interact with it directly in your Slack workspace.
When someone mentions your app in a Slack channel, the app will acknowledge the mention and then use the built-in 'abilities' module to generate a poem based on the message content. The poem will be posted as a reply in the same thread.
Once your app is deployed and running, here's how to use it:
@your_app_name
followed by a message.Enjoy engaging with your Slack community in a creative and entertaining way with your very own AI-powered poem generator!
If you need further assistance or have any questions, please reach out to our customer support team. We're here to help you make the most of your Lazy experience!
This app allows users to interact with a Slack bot, ask a question about the data in a table or request the table schema, and then uses the latest ChatGPT to generate a query that is executed on BigQuery to return the results. The app includes a retry mechanism for query generation in case of an error (up to two retries) and provides the LLM with the table info to generate more accurate queries. The table schema is only printed if it is successfully retrieved. All errors from retries are now passed to the LLM. The generated query is printed before the results, and the results are displayed in a pretty table format. The bot uses the Slack API to send and receive messages and parses the user's message to determine the action to take. The bot always responds in a thread to the original message.