← Microsoft Teams + Tisane Labs integrations

Analyze Text with Tisane Labs API on New Channel Message from Microsoft Teams API

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

Trigger workflow on
New Channel Message from the Microsoft Teams 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 Microsoft Teams trigger and Tisane Labs action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

  1. Select this integration
  2. Configure the New Channel Message trigger
    1. Connect your Microsoft Teams account
    2. Configure Polling interval
    3. Select a Team
    4. Select a Channel
  3. 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
  4. Deploy the workflow
  5. Send a test event to validate your setup
  6. 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

Description:Emit new event when a new message is posted in a channel
Version:0.0.6
Key:microsoft_teams-new-channel-message

Microsoft Teams Overview

The Microsoft Teams API on Pipedream allows you to automate tasks, streamline communication, and integrate with other services to enhance the functionality of Teams as a collaboration hub. With this API, you can send messages to channels, orchestrate complex workflows based on Teams events, and manage Teams' settings programmatically.

Trigger Code

import base from "../common/base.mjs";

export default {
  ...base,
  key: "microsoft_teams-new-channel-message",
  name: "New Channel Message",
  description: "Emit new event when a new message is posted in a channel",
  version: "0.0.6",
  type: "source",
  dedupe: "unique",
  props: {
    ...base.props,
    team: {
      propDefinition: [
        base.props.microsoftTeams,
        "team",
      ],
    },
    channel: {
      propDefinition: [
        base.props.microsoftTeams,
        "channel",
        (c) => ({
          teamId: c.team,
        }),
      ],
    },
  },
  methods: {
    ...base.methods,
    async getResources(lastCreated) {
      return this.getNewPaginatedResources(
        this.microsoftTeams.listChannelMessages,
        {
          teamId: this.team,
          channelId: this.channel,
        },
        lastCreated,
      );
    },
    generateMeta(message) {
      return {
        id: message.id,
        summary: `New Message ${message.id}`,
        ts: Date.parse(message.createdDateTime),
      };
    },
  },
};

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.
LabelPropTypeDescription
Microsoft TeamsmicrosoftTeamsappThis component uses the Microsoft Teams app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
Polling intervaltimer$.interface.timer

Pipedream will poll the YouTube API on this schedule

TeamteamstringSelect a value from the drop down menu.
ChannelchannelstringSelect a value from the drop down menu.

Trigger Authentication

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

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

User.Reademailoffline_accessopenidprofileChat.ReadChat.ReadWriteChatMessage.SendChannel.ReadBasic.AllChannelMessage.SendTeam.ReadBasic.AllSchedule.Read.All

About Microsoft Teams

Microsoft Teams has communities, events, chats, channels, meetings, storage, tasks, and calendars in one place.

Action

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

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.

LabelPropTypeDescription
Tisane LabstisaneLabsappThis component uses the Tisane Labs app.
LanguagelanguagestringSelect a value from the drop down menu.
Contentcontentstring

The content to analyze

FormatformatstringSelect 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 SpellcheckdisableSpellcheckboolean

Determines whether the automatic spellchecking is to be disabled. Default: false

Lowercase Spellcheck OnlylowercaseSpellcheckOnlyboolean

Determines whether the automatic spellchecking is only to be applied to words in lowercase. Default: false

Minimum Generic FrequencyminGenericFrequencyinteger

Allows excluding more esoteric terms; The valid values are 0 thru 10.

Subscopesubscopeboolean

Enables sub-scope parsing, for scenarios like hashtag, URL parsing, and obfuscated content (e.g. ihateyou). Default: false

Abuseabuseboolean

Output instances of abusive conten. Default: true

Sentimentsentimentboolean

Output sentiment-bearing snippets. Default: true

Document SentimentdocumentSentimentboolean

output document-level sentiment. Default: false

Entitiesentitiesboolean

Output entities. Default: true

Topicstopicsboolean

Output topics. Default: true

Wordswordsboolean

Output the lexical chunks / words for every sentence. Default: false

Fetch DefinitionsfetchDefinitionsboolean

Include definitions of the words in the output. Only relevant when the words setting is true. Default: `false

Parseparsesboolean

Output parse forests of phrases

Deterministicdeterministicboolean

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

Snippetssnippetsboolean

Include the text snippets in the abuse, sentiment, and entities sections. Default: false

Explainexplainboolean

If true, a reasoning for the abuse and sentiment snippets is provided when possible

Feature StandardfeatureStandardstringSelect 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 StandardtopicStandardstringSelect 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 TypesentimentAnalysisTypestringSelect 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" }

Action Authentication

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

Sign in and copy your API key directly from your dashboard.

About Tisane Labs

Home of cutting edge, explainable AI software that turns unstructured content into meaningful insights.

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