Analyze Text with Tisane Labs API on New Row Added from Supabase API

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New Row Added from the Supabase 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 Supabase 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 Row Added trigger
1. Connect your Supabase account
2. Configure Table
3. Optional- Configure Row Identifier
4. Optional- Configure Column
5. Optional- Select a Filter
6. Optional- Configure Value
7. Configure Order By
8. Optional- Select a Sort Order
9. Configure timer
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 Row Added on Supabase

Description:Emit new event for every new row added in a table. [See documentation here](https://supabase.com/docs/reference/javascript/select)

Version:0.0.1

Key:supabase-new-row-added

View on GitHub

Supabase Overview#

Supabase is a real-time backend-as-a-service that provides developers with a suite of tools to quickly build and scale their applications. It offers database storage, authentication, instant APIs, and real-time subscriptions. With the Supabase API, you can perform CRUD operations on your database, manage users, and listen to database changes in real time. When integrated with Pipedream, you can automate workflows that react to these database events, synchronize data across multiple services, or streamline user management processes.

Trigger Code#

import base from "../common/base.mjs";
import {
  DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
  ConfigurationError,
} from "@pipedream/platform";
import constants from "../../common/constants.mjs";

export default {
  key: "supabase-new-row-added",
  name: "New Row Added",
  description: "Emit new event for every new row added in a table. [See documentation here](https://supabase.com/docs/reference/javascript/select)",
  version: "0.0.1",
  type: "source",
  props: {
    ...base.props,
    column: {
      propDefinition: [
        base.props.supabase,
        "column",
      ],
      optional: true,
    },
    filter: {
      propDefinition: [
        base.props.supabase,
        "filter",
      ],
      optional: true,
    },
    value: {
      propDefinition: [
        base.props.supabase,
        "value",
      ],
      optional: true,
    },
    orderBy: {
      propDefinition: [
        base.props.supabase,
        "column",
      ],
      label: "Order By",
      description: "Column name to order by",
    },
    sortOrder: {
      propDefinition: [
        base.props.supabase,
        "sortOrder",
      ],
    },
    db: "$.service.db",
    timer: {
      type: "$.interface.timer",
      default: {
        intervalSeconds: DEFAULT_POLLING_SOURCE_TIMER_INTERVAL,
      },
    },
  },
  methods: {
    _getOffset() {
      return this.db.get("offset") || 0;
    },
    _setOffset(offset) {
      this.db.set("offset", offset);
    },
  },
  async run() {
    const {
      table,
      column,
      filter,
      value,
      orderBy,
      sortOrder,
      rowIdentifier,
    } = this;

    if ((column || filter || value) && !(column && filter && value)) {
      throw new ConfigurationError("If `column`, `filter`, or `value` is used, all three must be entered");
    }

    const offset = this._getOffset();
    const client = await this.supabase._client();
    const query = client
      .from(table)
      .select()
      .order(orderBy, {
        ascending: sortOrder,
      })
      .range(offset, offset + constants.MAX_OFFSET);

    if (filter) {
      const filterMethod = this.supabase[filter];
      filterMethod(query, column, value);
    }

    const { data } = await query;
    this._setOffset(offset + data.length);

    for (const row of data) {
      let summary = "New row in table";
      if (row[rowIdentifier]) {
        summary = `${summary}: ${row[rowIdentifier]}`;
      }
      this.$emit(row, {
        summary,
      });
    }
  },
};

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
Supabase	`supabase`	`app`	This component uses the Supabase app.
Table	`table`	`string`	The name of the table to watch for new rows
Row Identifier	`rowIdentifier`	`string`	The column name to use as the row identifier
Column	`column`	`string`	Column name to search by
Filter	`filter`	`string`	Select a value from the drop down menu:`{ "label": "Equal", "value": "equalTo" }{ "label": "Not Equal", "value": "notEqualTo" }{ "label": "Greater Than", "value": "greaterThan" }{ "label": "Greater Than or Equal To", "value": "greaterThanOrEqualTo" }{ "label": "Less Than", "value": "lessThan" }{ "label": "Less Than or Equal To", "value": "lessThanOrEqualTo" }{ "label": "Contains (Case Sensitive)", "value": "patternMatch" }{ "label": "Contains (Case Insensitive)", "value": "patternMatchCaseInsensitive" }`
Value	`value`	`string`	Value of the column specified to search for
Order By	`orderBy`	`string`	Column name to order by
Sort Order	`sortOrder`	`string`	Select a value from the drop down menu:`ascendingdescending`
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`

Trigger Authentication#

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

Supabase provides a Service Key to get started. You can find the service_role in the API Settings page.

Finding the Supabase subdomain

About Supabase#

Supabase is an open source Firebase alternative.

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" }`

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.

About Tisane Labs#

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

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Popular Triggers#

New Row Added from the Supabase API

Emit new event for every new row added in a table. See documentation here

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New Webhook Event (Instant) from the Supabase API

Emit new event for every insert, update, or delete operation in a table. This source requires user configuration using the Supabase website. More information in the README. Also see documentation here

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