Classify Text with MonkeyLearn API on Random item from multiple RSS feeds from RSS API

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Random item from multiple RSS feeds from the RSS API

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Classify Text with the MonkeyLearn API

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Getting Started#

This integration creates a workflow with a RSS trigger and MonkeyLearn action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

Select this integration
Configure the Random item from multiple RSS feeds trigger
1. Connect your RSS account
2. Configure timer
3. Configure Feed URLs
Configure the Classify Text action
1. Connect your MonkeyLearn account
2. Select a Classifier Id
3. Configure Data
4. Optional- Configure Production Model
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#

Random item from multiple RSS feeds on RSS

Description:Emit a random item from multiple RSS feeds

Version:0.2.7

Key:rss-random-item-in-multiple-feeds

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 rss from "../../app/rss.app.mjs";
import { defineSource } from "@pipedream/types";
import rssCommon from "../common/common.mjs";
export default defineSource({
    ...rssCommon,
    key: "rss-random-item-in-multiple-feeds",
    name: "Random item from multiple RSS feeds",
    type: "source",
    description: "Emit a random item from multiple RSS feeds",
    version: "0.2.7",
    props: {
        ...rssCommon.props,
        urls: {
            propDefinition: [
                rss,
                "urls",
            ],
        },
    },
    dedupe: "unique",
    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.
            for (const url of this.urls) {
                await this.rss.fetchAndParseFeed(url);
            }
        },
    },
    async run() {
        const items = [];
        for (const url of this.urls) {
            const feedItems = await this.rss.fetchAndParseFeed(url);
            items.push(...feedItems);
        }
        const item = items[Math.floor(Math.random() * items.length)];
        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 URLs	`urls`	`string[]`	Enter either one or multiple URLs from any public RSS feed

Trigger Authentication#

The RSS API does not require authentication.

About RSS#

Real Simple Syndication

Action#

Classify Text on MonkeyLearn

Description:Classifies texts with a given classifier. [See the docs here](https://monkeylearn.com/api/v3/#classify)

Version:0.0.1

Key:monkeylearn-classify-text

View on GitHub

MonkeyLearn Overview#

MonkeyLearn is a text analysis platform that employs machine learning to extract and process data from chunks of text. By leveraging the MonkeyLearn API on Pipedream, you can automate the categorization of text, extract specific data, analyze sentiment, and more, all in real-time. This enables the development of powerful custom workflows that can analyze customer feedback, automate email processing, or provide insightful analytics on textual data from various sources.

Action Code#

import app from "../../monkeylearn.app.mjs";
import { ConfigurationError } from "@pipedream/platform";

export default {
  key: "monkeylearn-classify-text",
  name: "Classify Text",
  description: "Classifies texts with a given classifier. [See the docs here](https://monkeylearn.com/api/v3/#classify)",
  version: "0.0.1",
  type: "action",
  props: {
    app,
    classifierId: {
      propDefinition: [
        app,
        "classifierId",
      ],
    },
    data: {
      propDefinition: [
        app,
        "data",
      ],
    },
    productionModel: {
      propDefinition: [
        app,
        "productionModel",
      ],
    },
  },
  async run({ $ }) {
    const {
      classifierId,
      data,
      productionModel,
    } = this;
    if (!data || !Array.isArray(data) || data.length === 0) {
      throw new ConfigurationError("Data array is required and must have at least one string to be classified.");
    }
    const response = await this.app.classifyText($, classifierId, data, productionModel);
    $.export("$summary", "Successfully classified all elements");
    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
MonkeyLearn	`app`	`app`	This component uses the MonkeyLearn app.
Classifier Id	`classifierId`	`string`	Select a value from the drop down menu.
Data	`data`	`string[]`	A list of up to 500 data elements. Each element must be a string with the text.
Production Model	`productionModel`	`boolean`	Indicates if the extractions are performed by the production model. Only use this parameter on custom models. Note that you first need to deploy your model to production.

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Popular Triggers#

New Item in Feed from the RSS API

Emit new items from an RSS feed

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New Item From Multiple RSS Feeds from the RSS API

Emit new items from multiple RSS feeds

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Random item from multiple RSS feeds from the RSS API

Emit a random item from multiple RSS feeds

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Popular Actions#

Merge RSS Feeds with the RSS API

Retrieve multiple RSS feeds and return a merged array of items sorted by date See documentation

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Classify Text with the MonkeyLearn API

Classifies texts with a given classifier. See the docs here

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Extract Text with the MonkeyLearn API

Extracts information from texts with a given extractor. See the docs here

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Upload Training Data with the MonkeyLearn API

Uploads data to a classifier. This component can be used to upload new data to a classifier, to update the tags of texts that have already been uploaded, or both. See the docs here

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