with Slack and MonkeyLearn?
Emit new events on new Slack interactivity events sourced from Block Kit interactive elements, Slash commands, or Shortcuts
Emit new event when a specific keyword is mentioned in a channel
Emit new event when a new message is posted to one or more channels
Emit new event when a member has added an emoji reaction to a message
Suspend the workflow until approved by a Slack message. See the documentation
Extracts information from texts with a given extractor. See the docs here
The Pipedream app for Slack enables you to build event-driven workflows that interact with the Slack API. Once you authorize the app's access to your workspace, you can use Pipedream workflows to perform common Slack actions or write your own code against the Slack API.
The Pipedream app for Slack is not a typical app. You don't interact with it directly as a bot, and it doesn't add custom functionality to your workspace out of the box. It makes it easier to automate anything you'd typically use the Slack API for, using Pipedream workflows.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
slack_v2: {
type: "app",
app: "slack_v2",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://slack.com/api/users.profile.get`,
headers: {
Authorization: `Bearer ${this.slack_v2.$auth.oauth_access_token}`,
},
})
},
})
MonkeyLearn is a text analysis platform that employs machine learning to extract and process data from chunks of text. By leveraging the MonkeyLearn API on Pipedream, you can automate the categorization of text, extract specific data, analyze sentiment, and more, all in real-time. This enables the development of powerful custom workflows that can analyze customer feedback, automate email processing, or provide insightful analytics on textual data from various sources.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
monkeylearn: {
type: "app",
app: "monkeylearn",
}
},
async run({steps, $}) {
const data = {
"data": [
"This is a great tool!",
]
}
return await axios($, {
method: "post",
url: `https://api.monkeylearn.com/v3/classifiers/cl_pi3C7JiL/classify/`,
headers: {
"Authorization": `Token ${this.monkeylearn.$auth.api_key}`,
"Content-Type": `application/json`,
},
data,
})
},
})