Analyze Text with Tisane Labs API on New Item in Feed from RSS API

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New Item in Feed from the RSS 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 RSS 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 Item in Feed trigger
1. Connect your RSS account
2. Configure timer
3. Configure Feed URL
4. Configure Published After
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 Item in Feed on RSS

Description:Emit new items from an RSS feed

Version:1.2.7

Key:rss-new-item-in-feed

View on GitHub

RSS Overview#

The RSS app allows users to automatically fetch and parse updates from web feeds. This functionality is pivotal for staying abreast of content changes or updates from websites, blogs, and news outlets that offer RSS feeds. With Pipedream, you can harness the RSS API to trigger workflows that enable a broad range of automations, like content aggregation, monitoring for specific keywords, notifications, and data synchronization across platforms.

Trigger Code#

import { defineSource } from "@pipedream/types";
import rss from "../../app/rss.app.mjs";
import rssCommon from "../common/common.mjs";
export default defineSource({
    ...rssCommon,
    key: "rss-new-item-in-feed",
    name: "New Item in Feed",
    description: "Emit new items from an RSS feed",
    version: "1.2.7",
    type: "source",
    dedupe: "unique",
    props: {
        ...rssCommon.props,
        url: {
            propDefinition: [
                rss,
                "url",
            ],
        },
        publishedAfter: {
            type: "string",
            label: "Published After",
            description: "Emit items published after the specified date in ISO 8601 format .e.g `2022-12-07T12:57:10+07:00`",
            default: new Date(Date.now() - 24 * 60 * 60 * 1000).toISOString(), // default to one day ago
        },
    },
    hooks: {
        async activate() {
            // Try to parse the feed one time to confirm we can fetch and parse.
            // The code will throw any errors to the user.
            await this.rss.fetchAndParseFeed(this.url);
        },
    },
    methods: {
        ...rssCommon.methods,
        generateMeta: function (item) {
            return {
                id: this.rss.itemKey(item),
                summary: item.title,
                ts: Date.now(),
            };
        },
    },
    async run() {
        const items = await this.rss.fetchAndParseFeed(this.url);
        for (const item of items.reverse()) {
            const publishedAfter = +new Date(this.publishedAfter);
            const ts = this.rss.itemTs(item);
            if (Number.isNaN(publishedAfter) || publishedAfter > ts) {
                continue;
            }
            const meta = this.generateMeta(item);
            this.$emit(item, meta);
        }
    },
});

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
RSS	`rss`	`app`	This component uses the RSS app.
	`timer`	`$.interface.timer`	How often you want to poll the feed for new items
Feed URL	`url`	`string`	Enter the URL for any public RSS feed
Published After	`publishedAfter`	`string`	Emit items published after the specified date in ISO 8601 format .e.g `2022-12-07T12:57:10+07:00`

Trigger Authentication#

The RSS API does not require authentication.

About RSS#

Real Simple Syndication

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" }`