Upload Training Data with MonkeyLearn API on New Message In Channels (Instant) from Slack API

Pipedream makes it easy to connect APIs for MonkeyLearn, Slack and 2,000+ other apps remarkably fast.

Trigger workflow on

New Message In Channels (Instant) from the Slack API

Next, do this

Upload Training Data with the MonkeyLearn API

No credit card required

▶

Watch us build a workflow

4 min

Watch now ➜

Trusted by 800,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

Getting Started#

This integration creates a workflow with a Slack trigger and MonkeyLearn action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the New Message In Channels (Instant) trigger
1. Connect your Slack account
2. Optional- Select one or more Channels
3. Configure slackApphook
4. Optional- Configure Resolve Names
5. Optional- Configure Ignore Bots
6. Optional- Configure Ignore replies in threads
Configure the Upload Training Data action
1. Connect your MonkeyLearn account
2. Select a Classifier Id
3. Configure Data Array
4. Optional- Select a Input Duplicates Strategy
5. Optional- Select a Existing Duplicates Strategy
Deploy the workflow
Send a test event to validate your setup
Turn on the trigger

Details#

This integration uses pre-built, source-available components from Pipedream's GitHub repo. These components are developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Trigger#

New Message In Channels (Instant) on Slack

Description:Emit new event when a new message is posted to one or more channels

Version:1.0.14

Key:slack-new-message-in-channels

View on GitHub

Slack Overview#

The Pipedream Slack app enables you to build event-driven workflows that interact with the Slack API. When you authorize the Pipedream 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 Slack app 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.

Automate posting updates to your team channels
Create a bot to answer common questions
Integrate with your existing tools and services
And much more!

Trigger Code#

import common from "../common/base.mjs";
import sampleEmit from "./test-event.mjs";
import constants from "../common/constants.mjs";

export default {
  ...common,
  key: "slack-new-message-in-channels",
  name: "New Message In Channels (Instant)",
  version: "1.0.14",
  description: "Emit new event when a new message is posted to one or more channels",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    conversations: {
      propDefinition: [
        common.props.slack,
        "conversation",
      ],
      type: "string[]",
      label: "Channels",
      description: "Select one or more channels to monitor for new messages.",
      optional: true,
    },
    // eslint-disable-next-line pipedream/props-description,pipedream/props-label
    slackApphook: {
      type: "$.interface.apphook",
      appProp: "slack",
      async eventNames() {
        return this.conversations || [
          "message",
        ];
      },
    },
    resolveNames: {
      propDefinition: [
        common.props.slack,
        "resolveNames",
      ],
    },
    ignoreBot: {
      propDefinition: [
        common.props.slack,
        "ignoreBot",
      ],
    },
    ignoreThreads: {
      type: "boolean",
      label: "Ignore replies in threads",
      description: "Ignore replies to messages in threads",
      optional: true,
    },
  },
  methods: {
    ...common.methods,
    getSummary() {
      return "New message in channel";
    },
    async processEvent(event) {
      if (event.type !== "message") {
        console.log(`Ignoring event with unexpected type "${event.type}"`);
        return;
      }
      if (event.subtype && !constants.ALLOWED_MESSAGE_IN_CHANNEL_SUBTYPES.includes(event.subtype)) {
        // This source is designed to just emit an event for each new message received.
        // Due to inconsistencies with the shape of message_changed and message_deleted
        // events, we are ignoring them for now. If you want to handle these types of
        // events, feel free to change this code!!
        console.log("Ignoring message with subtype.");
        return;
      }
      if ((this.ignoreBot) && (event.subtype == "bot_message" || event.bot_id)) {
        return;
      }
      console.log(event.s);
      // There is no thread message type only the thread_ts field
      // indicates if the message is part of a thread in the event.
      if (this.ignoreThreads && event.thread_ts) {
        console.log("Ignoring reply in thread");
        return;
      }
      if (this.resolveNames) {
        if (event.user) {
          event.user_id = event.user;
          event.user = await this.getUserName(event.user);
        } else if (event.bot_id) {
          event.bot = await this.getBotName(event.bot_id);
        }
        event.channel_id = event.channel;
        event.channel = await this.getConversationName(event.channel);
        if (event.team) {
          event.team_id = event.team;
          event.team = await this.getTeamName(event.team);
        }
      }
      return event;
    },
  },
  sampleEmit,
};

Trigger Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.

Label	Prop	Type	Description
Slack	`slack`	`app`	This component uses the Slack app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Channels	`conversations`	`string[]`	Select a value from the drop down menu.
	`slackApphook`	`$.interface.apphook`
Resolve Names	`resolveNames`	`boolean`	Instead of returning `channel`, `team`, and `user` as IDs, return their human-readable names.
Ignore Bots	`ignoreBot`	`boolean`	Ignore messages from bots
Ignore replies in threads	`ignoreThreads`	`boolean`	Ignore replies to messages in threads

Trigger Authentication#

Slack uses OAuth authentication. When you connect your Slack account, Pipedream will open a popup window where you can sign into Slack and grant Pipedream permission to connect to your account. Pipedream securely stores and automatically refreshes the OAuth tokens so you can easily authenticate any Slack API.

Pipedream requests the following authorization scopes when you connect your account:

bookmarks:writecalls:readcalls:writechannels:historychannels:readchannels:writednd:readdnd:writeemoji:readfiles:readgroups:historygroups:readgroups:writeim:historyim:readim:writelinks:readlinks:writempim:historympim:readmpim:writepins:readpins:writereactions:readreactions:writereminders:readreminders:writeremote_files:readremote_files:sharestars:readstars:writeteam:readusergroups:readusergroups:writeusers:readusers:read.emailusers:writechat:write:botchat:write:usercommandsfiles:write:userusers.profile:writeusers.profile:readsearch:read

About Slack#

Slack is a channel-based messaging platform. With Slack, people can work together more effectively, connect all their software tools and services, and find the information they need to do their best work — all within a secure, enterprise-grade environment.

Action#

Upload Training Data on MonkeyLearn

Description:Uploads data to a classifier. This component can be used to upload new data to a classifier, to update the tags of texts that have already been uploaded, or both. [See the docs here](https://monkeylearn.com/api/v3/#upload-classifier-data)

Version:0.0.1

Key:monkeylearn-upload-training-data

View on GitHub

MonkeyLearn Overview#

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.

Action Code#

import app from "../../monkeylearn.app.mjs";
import common from "../common/common.mjs";
import { ConfigurationError } from "@pipedream/platform";

export default {
  key: "monkeylearn-upload-training-data",
  name: "Upload Training Data",
  description: "Uploads data to a classifier. This component can be used to upload new data to a classifier, to update the tags of texts that have already been uploaded, or both. [See the docs here](https://monkeylearn.com/api/v3/#upload-classifier-data)",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    classifierId: {
      propDefinition: [
        app,
        "classifierId",
      ],
    },
    dataObjectArray: {
      propDefinition: [
        app,
        "dataObjectArray",
      ],
    },
    inputDuplicatesStrategy: {
      propDefinition: [
        app,
        "inputDuplicatesStrategy",
      ],
    },
    existingDuplicatesStrategy: {
      propDefinition: [
        app,
        "existingDuplicatesStrategy",
      ],
    },
  },
  async run({ $ }) {
    const {
      classifierId,
      dataObjectArray,
      inputDuplicatesStrategy,
      existingDuplicatesStrategy,
    } = this;
    const data = common.formatObjectArray(dataObjectArray);
    if (!data || !Array.isArray(data) || data.length === 0) {
      throw new ConfigurationError("Data must to be an array and must have at least one object.");
    }
    const params = {
      data,
      input_duplicates_strategy: inputDuplicatesStrategy,
      existing_duplicates_strategy: existingDuplicatesStrategy,
    };
    const response = await this.app.uploadClassifierTrainingData($, classifierId, params);
    $.export("$summary", "Successfully uploaded training data");
    return response;
  },
};

Action Configuration#

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI.

Label	Prop	Type	Description
MonkeyLearn	`app`	`app`	This component uses the MonkeyLearn app.
Classifier Id	`classifierId`	`string`	Select a value from the drop down menu.
Data Array	`dataObjectArray`	`string[]`	A list of data objects. Example: `[{ "text": "first text", "tags": ["tag_id_1", "tag_name"], "markers": ["any_marker", "other_marker"] }]`
Input Duplicates Strategy	`inputDuplicatesStrategy`	`string`	Select a value from the drop down menu:`{ "label": "Merge", "value": "merge" }{ "label": "Keep first", "value": "keep_first" }{ "label": "Keep last", "value": "keep_last" }`
Existing Duplicates Strategy	`existingDuplicatesStrategy`	`string`	Select a value from the drop down menu:`{ "label": "Overwrite", "value": "overwrite" }{ "label": "Ignore", "value": "ignore" }`

Action Authentication#

MonkeyLearn uses API keys for authentication. When you connect your MonkeyLearn account, Pipedream securely stores the keys so you can easily authenticate to MonkeyLearn APIs in both code and no-code steps.

MonkeyLearn requires that you authenticate by sending an API Key with each request to grant you access to the API. See docs.

About MonkeyLearn#

Text Analysis

More Ways to Connect MonkeyLearn + Slack#

Other Popular Integrations#

Classify Text with MonkeyLearn API on New Star Added To Message (Instant) from Slack API

Slack + MonkeyLearn

Upload Training Data with MonkeyLearn API on New Message In Channels (Instant) from Slack API

Pipedream makes it easy to connect APIs for MonkeyLearn, Slack and 2,000+ other apps remarkably fast.

Trusted by 800,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

1-24of2,000+apps by most popular

1
-
24
of
2,000+
apps by most popular