Analyze Text with Tisane Labs API on New Message In Channels (Instant) from Slack API

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New Message In Channels (Instant) from the Slack API

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Analyze Text with the Tisane Labs API

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Getting Started#

This integration creates a workflow with a Slack trigger and Tisane Labs 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 Analyze Text action
1. Connect your Tisane Labs account
2. Select a Language
3. Configure Content
4. Optional- Select a Format
5. Optional- Configure Disable Spellcheck
6. Optional- Configure Lowercase Spellcheck Only
7. Optional- Configure Minimum Generic Frequency
8. Optional- Configure Subscope
9. Optional- Configure Abuse
10. Optional- Configure Sentiment
11. Optional- Configure Document Sentiment
12. Optional- Configure Entities
13. Optional- Configure Topics
14. Optional- Configure Words
15. Optional- Configure Fetch Definitions
16. Optional- Configure Parse
17. Optional- Configure Deterministic
18. Optional- Configure Snippets
19. Optional- Configure Explain
20. Optional- Select a Feature Standard
21. Optional- Select a Topic Standard
22. Optional- Select a Sentiment Analysis Type
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:1.0.22

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

export default {
  ...common,
  key: "slack-new-message-in-channels",
  name: "New Message In Channels (Instant)",
  version: "1.0.22",
  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;
      }
      // 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#

Analyze Text on Tisane Labs

Description:Analyze text for language, entities, sentiment, and other insights. [See the documentation](https://docs.tisane.ai/#561264c5-6dbe-4bde-aba3-7defe837989f)

Version:0.0.1

Key:tisane_labs-analyze-text

View on GitHub

Tisane Labs Overview#

The Tisane Labs API offers advanced text analysis capabilities, focusing on abusive content detection and linguistic insights. With it, you can automate content moderation, extract entities, detect the sentiment, and identify the language of the text. In Pipedream, Tisane Labs API can be integrated into workflows to process text from various sources such as user comments, support tickets, or social media posts. By leveraging Pipedream's serverless platform, you can create real-time, event-driven applications that respond to text analyses, connect with other services, and perform actions based on the insights gained from the Tisane Labs API.

Action Code#

import tisaneLabs from "../../tisane_labs.app.mjs";

export default {
  key: "tisane_labs-analyze-text",
  name: "Analyze Text",
  description: "Analyze text for language, entities, sentiment, and other insights. [See the documentation](https://docs.tisane.ai/#561264c5-6dbe-4bde-aba3-7defe837989f)",
  version: "0.0.1",
  type: "action",
  props: {
    tisaneLabs,
    language: {
      propDefinition: [
        tisaneLabs,
        "language",
      ],
    },
    content: {
      type: "string",
      label: "Content",
      description: "The content to analyze",
    },
    format: {
      propDefinition: [
        tisaneLabs,
        "format",
      ],
    },
    disableSpellcheck: {
      type: "boolean",
      label: "Disable Spellcheck",
      description: "Determines whether the automatic spellchecking is to be disabled. Default: `false`",
      default: false,
      optional: true,
    },
    lowercaseSpellcheckOnly: {
      type: "boolean",
      label: "Lowercase Spellcheck Only",
      description: "Determines whether the automatic spellchecking is only to be applied to words in lowercase. Default: `false`",
      default: false,
      optional: true,
    },
    minGenericFrequency: {
      type: "integer",
      label: "Minimum Generic Frequency",
      description: "Allows excluding more esoteric terms; The valid values are 0 thru 10.",
      min: 0,
      max: 10,
      optional: true,
    },
    subscope: {
      type: "boolean",
      label: "Subscope",
      description: "Enables sub-scope parsing, for scenarios like hashtag, URL parsing, and obfuscated content (e.g. ihateyou). Default: `false`",
      default: false,
      optional: true,
    },
    abuse: {
      type: "boolean",
      label: "Abuse",
      description: "Output instances of abusive conten. Default: `true`",
      default: true,
      optional: true,
    },
    sentiment: {
      type: "boolean",
      label: "Sentiment",
      description: "Output sentiment-bearing snippets. Default: `true`",
      default: true,
      optional: true,
    },
    documentSentiment: {
      type: "boolean",
      label: "Document Sentiment",
      description: "output document-level sentiment. Default: `false`",
      default: false,
      optional: true,
    },
    entities: {
      type: "boolean",
      label: "Entities",
      description: "Output entities. Default: `true`",
      default: true,
      optional: true,
    },
    topics: {
      type: "boolean",
      label: "Topics",
      description: "Output topics. Default: `true`",
      default: true,
      optional: true,
    },
    words: {
      type: "boolean",
      label: "Words",
      description: "Output the lexical chunks / words for every sentence. Default: `false`",
      default: false,
      optional: true,
    },
    fetchDefinitions: {
      type: "boolean",
      label: "Fetch Definitions",
      description: "Include definitions of the words in the output. Only relevant when the `words` setting is `true`. Default: `false",
      default: false,
      optional: true,
    },
    parses: {
      type: "boolean",
      label: "Parse",
      description: "Output parse forests of phrases",
      optional: true,
    },
    deterministic: {
      type: "boolean",
      label: "Deterministic",
      description: "Whether the n-best senses and n-best parses are to be output in addition to the detected sense. If `true`, only the detected sense will be output. Default: `true`",
      default: true,
      optional: true,
    },
    snippets: {
      type: "boolean",
      label: "Snippets",
      description: "Include the text snippets in the abuse, sentiment, and entities sections. Default: `false`",
      default: false,
      optional: true,
    },
    explain: {
      type: "boolean",
      label: "Explain",
      description: "If `true`, a reasoning for the abuse and sentiment snippets is provided when possible",
      optional: true,
    },
    featureStandard: {
      propDefinition: [
        tisaneLabs,
        "featureStandard",
      ],
    },
    topicStandard: {
      propDefinition: [
        tisaneLabs,
        "topicStandard",
      ],
    },
    sentimentAnalysisType: {
      propDefinition: [
        tisaneLabs,
        "sentimentAnalysisType",
      ],
    },
  },
  async run({ $ }) {
    const response = await this.tisaneLabs.analyzeText({
      data: {
        language: this.language,
        content: this.content,
        settings: {
          format: this.format,
          disable_spellcheck: this.disableSpellcheck,
          lowercase_spellcheck_only: this.lowercaseSpellcheckOnly,
          min_generic_frequency: this.minGenericFrequency,
          subscope: this.subscope,
          abusse: this.abuse,
          sentiment: this.sentiment,
          document_sentiment: this.documentSentiment,
          entities: this.entities,
          topics: this.topics,
          words: this.words,
          fetch_definitions: this.fetchDefinitions,
          parses: this.parses,
          deterministic: this.deterministic,
          snippets: this.snippets,
          explain: this.explain,
          feature_standard: this.featureStandard,
          topic_standard: this.topicStandard,
          sentiment_analysis_type: this.sentimentAnalysisType,
        },
      },
      $,
    });

    if (response) {
      $.export("$summary", "Successfully analyzed text.");
    }

    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
Tisane Labs	`tisaneLabs`	`app`	This component uses the Tisane Labs app.
Language	`language`	`string`	Select a value from the drop down menu.
Content	`content`	`string`	The content to analyze
Format	`format`	`string`	Select a value from the drop down menu:`{ "label": "Review", "value": "review" }{ "label": "Dialog", "value": "dialog" }{ "label": "Shortpost", "value": "shortpost" }{ "label": "Longform", "value": "longform" }{ "label": "Proofread", "value": "proofread" }{ "label": "Alias", "value": "alias" }{ "label": "Search", "value": "search" }`
Disable Spellcheck	`disableSpellcheck`	`boolean`	Determines whether the automatic spellchecking is to be disabled. Default: `false`
Lowercase Spellcheck Only	`lowercaseSpellcheckOnly`	`boolean`	Determines whether the automatic spellchecking is only to be applied to words in lowercase. Default: `false`
Minimum Generic Frequency	`minGenericFrequency`	`integer`	Allows excluding more esoteric terms; The valid values are 0 thru 10.
Subscope	`subscope`	`boolean`	Enables sub-scope parsing, for scenarios like hashtag, URL parsing, and obfuscated content (e.g. ihateyou). Default: `false`
Abuse	`abuse`	`boolean`	Output instances of abusive conten. Default: `true`
Sentiment	`sentiment`	`boolean`	Output sentiment-bearing snippets. Default: `true`
Document Sentiment	`documentSentiment`	`boolean`	output document-level sentiment. Default: `false`
Entities	`entities`	`boolean`	Output entities. Default: `true`
Topics	`topics`	`boolean`	Output topics. Default: `true`
Words	`words`	`boolean`	Output the lexical chunks / words for every sentence. Default: `false`
Fetch Definitions	`fetchDefinitions`	`boolean`	Include definitions of the words in the output. Only relevant when the `words` setting is `true`. Default: `false
Parse	`parses`	`boolean`	Output parse forests of phrases
Deterministic	`deterministic`	`boolean`	Whether the n-best senses and n-best parses are to be output in addition to the detected sense. If `true`, only the detected sense will be output. Default: `true`
Snippets	`snippets`	`boolean`	Include the text snippets in the abuse, sentiment, and entities sections. Default: `false`
Explain	`explain`	`boolean`	If `true`, a reasoning for the abuse and sentiment snippets is provided when possible
Feature Standard	`featureStandard`	`string`	Select a value from the drop down menu:`{ "label": "Universal Dependencies tags", "value": "ud" }{ "label": "Penn treebank tags", "value": "penn" }{ "label": "Tisane native feature codes", "value": "native" }{ "label": "Tisane native feature descriptions", "value": "description" }`
Topic Standard	`topicStandard`	`string`	Select a value from the drop down menu:`{ "label": "IPTC topic taxonomy code", "value": "iptc_code" }{ "label": "IPTC topic taxonomy description", "value": "iptc_description" }{ "label": "IAB topic taxonomy code", "value": "iab_code" }{ "label": "IAB topic taxonomy description", "value": "iab_description" }{ "label": "Tisane domain description, coming from the family description", "value": "native" }`
Sentiment Analysis Type	`sentimentAnalysisType`	`string`	Select a value from the drop down menu:`{ "label": "Products and Services", "value": "products_and_services" }{ "label": "Entity", "value": "entity" }{ "label": "Creative Content Review", "value": "creative_content_review" }{ "label": "Political Essay", "value": "political_essay" }`

Analyze Text with Tisane Labs API on New Message In Channels (Instant) from Slack API

Pipedream makes it easy to connect APIs for Tisane Labs, Slack and 2,400+ other apps remarkably fast.

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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