Analyze Text with Tisane Labs API on New Command Received (Instant) from Discord API

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New Command Received (Instant) from the Discord 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 Discord 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 Command Received (Instant) trigger
1. Connect your Discord account
2. Configure Channels
3. Configure discordApphook
4. Configure Commands
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 Command Received (Instant) on Discord

Description:Emit new event for each command posted to one or more channels in a Discord server

Version:0.0.3

Key:discord-new-command-received

View on GitHub

Discord Overview#

The Discord API interacts seamlessly with Pipedream, empowering you to craft customized automations and workflows for your Discord server. With this powerful integration, you can automate tasks like message posting, user management, and notifications, based on a myriad of triggers and actions from different apps. These automations can enhance the Discord experience for community moderators and members, by synchronizing with external tools, organizing community engagement, and streamlining notifications.

Trigger Code#

import discord from "../../discord.app.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  type: "source",
  key: "discord-new-command-received",
  name: "New Command Received (Instant)",
  description: "Emit new event for each command posted to one or more channels in a Discord server",
  version: "0.0.3",
  dedupe: "unique",
  props: {
    discord,
    channels: {
      type: "$.discord.channel[]",
      appProp: "discord",
      label: "Channels",
      description: "Select the channel(s) you'd like to be notified for",
    },
    // eslint-disable-next-line pipedream/props-label,pipedream/props-description
    discordApphook: {
      type: "$.interface.apphook",
      appProp: "discord",
      async eventNames() {
        return this.channels || [];
      },
    },
    commands: {
      label: "Commands",
      description: "List of commands to listen. E.g. `[\"/hi\", \"/hello\"]`",
      type: "string[]",
    },
  },
  async run(event) {
    if (event.guildID != this.discord.$auth.guild_id) {
      return;
    }

    const command = event.content.split(" ")[0];

    if (typeof this.commands === "string") {
      this.commands = JSON.parse(this.commands);
    }

    if (!this.commands.includes(command)) {
      return;
    }

    this.$emit(event, {
      id: event.id,
      summary: `New command posted with ID ${event.id}`,
      ts: Date.parse(event.createdTimestamp),
    });
  },
  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
Discord	`discord`	`app`	This component uses the Discord app.
Channels	`channels`	`$.discord.channel[]`	Select the channel(s) you'd like to be notified for
	`discordApphook`	`$.interface.apphook`
Commands	`commands`	`string[]`	List of commands to listen. E.g. `["/hi", "/hello"]`

Trigger Authentication#

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

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

botemailidentifyguilds

About Discord#

Use this app to create a Discord source that emits messages from your guild to a Pipedream workflow.

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 Command Received (Instant) from Discord API

Pipedream makes it easy to connect APIs for Tisane Labs, Discord and 2,000+ other apps remarkably fast.

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

Developers ♥ Pipedream

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