Create Social Media Post with TextCortex 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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Create Social Media Post with the TextCortex API

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Getting Started#

This integration creates a workflow with a RSS trigger and TextCortex 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 Create Social Media Post action
1. Connect your TextCortex account
2. Configure Context
3. Optional- Configure Keywords
4. Optional- Configure Max Tokens
5. Select a Mode
6. Optional- Select a Model
7. Optional- Configure N
8. Optional- Select a Source Language
9. Optional- Select a Target Language
10. Optional- Configure Temperature
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#

Create Social Media Post on TextCortex

Description:Create a social media post. [See the documentation](https://docs.textcortex.com/api/paths/texts-social-media-posts/post)

Version:0.0.1

Key:textcortex-create-social-media-post

View on GitHub

TextCortex Overview#

The TextCortex API enables automated creation of human-like text, making it a powerful tool for a variety of text generation tasks like drafting emails, creating content, or generating product descriptions. With Pipedream, you can integrate TextCortex into serverless workflows to harness AI writing assistance, trigger content creation based on events, or enhance data with generated text. The API's capability enhances automation and can be combined with other apps for more complex tasks.

Action Code#

import app from "../../textcortex.app.mjs";
import constants from "../../common/constants.mjs";

export default {
  key: "textcortex-create-social-media-post",
  name: "Create Social Media Post",
  description: "Create a social media post. [See the documentation](https://docs.textcortex.com/api/paths/texts-social-media-posts/post)",
  type: "action",
  version: "0.0.1",
  props: {
    app,
    context: {
      type: "string",
      label: "Context",
      description: "The context of the social media post.",
    },
    keywords: {
      type: "string[]",
      label: "Keywords",
      description: "Keywords to be included in the post.",
      optional: true,
    },
    maxTokens: {
      propDefinition: [
        app,
        "maxTokens",
      ],
    },
    mode: {
      type: "string",
      label: "Mode",
      description: "The platform, e.g. `twitter` to generate a Tweet. Allowed values: `twitter`, `linkedin`",
      options: Object.values(constants.SOCIAL_MEDIA_MODE),
    },
    model: {
      propDefinition: [
        app,
        "model",
      ],
    },
    n: {
      propDefinition: [
        app,
        "n",
      ],
    },
    sourceLang: {
      propDefinition: [
        app,
        "sourceLang",
      ],
    },
    targetLang: {
      propDefinition: [
        app,
        "targetLang",
      ],
    },
    temperature: {
      propDefinition: [
        app,
        "temperature",
      ],
    },
  },
  methods: {
    createSocialMediaPost(args = {}) {
      return this.app.post({
        path: "/texts/social-media-posts",
        ...args,
      });
    },
  },
  async run({ $: step }) {
    const {
      createSocialMediaPost,
      context,
      keywords,
      maxTokens,
      mode,
      model,
      n,
      sourceLang,
      targetLang,
      temperature,
    } = this;

    const response = await createSocialMediaPost({
      step,
      data: {
        context,
        keywords,
        max_tokens: maxTokens,
        mode,
        model,
        n,
        source_lang: sourceLang,
        target_lang: targetLang,
        temperature,
      },
    });

    step.export("$summary", `Successfully created social media post with status \`${response.status}\``);

    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
TextCortex	`app`	`app`	This component uses the TextCortex app.
Context	`context`	`string`	The context of the social media post.
Keywords	`keywords`	`string[]`	Keywords to be included in the post.
Max Tokens	`maxTokens`	`integer`	The maximum number of tokens to generate.
Mode	`mode`	`string`	Select a value from the drop down menu:`twitterlinkedin`
Model	`model`	`string`	Select a value from the drop down menu:`velox-1aecus-1alta-1sophos-1chat-sophos-1`
N	`n`	`integer`	The number of outputs to generate.
Source Language	`sourceLang`	`string`	Select a value from the drop down menu:`{ "label": "English (Default)", "value": "en" }{ "label": "The API will attempt to detect the language of the text and translate it.", "value": "auto" }{ "label": "Bulgarian", "value": "bg" }{ "label": "Czech", "value": "cs" }{ "label": "Danish", "value": "da" }{ "label": "German", "value": "de" }{ "label": "Greek", "value": "el" }{ "label": "Spanish", "value": "es" }{ "label": "Estonian", "value": "et" }{ "label": "Finnish", "value": "fi" }{ "label": "French", "value": "fr" }{ "label": "Hungarian", "value": "hu" }{ "label": "Indonesian", "value": "id" }{ "label": "Italian", "value": "it" }{ "label": "Japanese", "value": "ja" }{ "label": "Korean", "value": "ko" }{ "label": "Lithuanian", "value": "lt" }{ "label": "Latvian", "value": "lv" }{ "label": "Norwegian", "value": "nb" }{ "label": "Dutch", "value": "nl" }{ "label": "Polish", "value": "pl" }{ "label": "Portuguese (all Portuguese varieties mixed)", "value": "pt" }{ "label": "Romanian", "value": "ro" }{ "label": "Russian", "value": "ru" }{ "label": "Slovak", "value": "sk" }{ "label": "Slovenian", "value": "sl" }{ "label": "Swedish", "value": "sv" }{ "label": "Turkish", "value": "tr" }{ "label": "Ukrainian", "value": "uk" }{ "label": "Chinese", "value": "zh" }`
Target Language	`targetLang`	`string`	Select a value from the drop down menu:`{ "label": "English (Default)", "value": "en" }{ "label": "The API will attempt to detect the language of the text and translate it.", "value": "auto" }{ "label": "Bulgarian", "value": "bg" }{ "label": "Czech", "value": "cs" }{ "label": "Danish", "value": "da" }{ "label": "German", "value": "de" }{ "label": "Greek", "value": "el" }{ "label": "Spanish", "value": "es" }{ "label": "Estonian", "value": "et" }{ "label": "Finnish", "value": "fi" }{ "label": "French", "value": "fr" }{ "label": "Hungarian", "value": "hu" }{ "label": "Indonesian", "value": "id" }{ "label": "Italian", "value": "it" }{ "label": "Japanese", "value": "ja" }{ "label": "Korean", "value": "ko" }{ "label": "Lithuanian", "value": "lt" }{ "label": "Latvian", "value": "lv" }{ "label": "Norwegian", "value": "nb" }{ "label": "Dutch", "value": "nl" }{ "label": "Polish", "value": "pl" }{ "label": "Portuguese (all Portuguese varieties mixed)", "value": "pt" }{ "label": "Romanian", "value": "ro" }{ "label": "Russian", "value": "ru" }{ "label": "Slovak", "value": "sk" }{ "label": "Slovenian", "value": "sl" }{ "label": "Swedish", "value": "sv" }{ "label": "Turkish", "value": "tr" }{ "label": "Ukrainian", "value": "uk" }{ "label": "Chinese", "value": "zh" }`
Temperature	`temperature`	`string`	The sampling temperature to be used in text generation. The higher the temperature, the higher the risk of the output to sound "made up".