Document Question Answering with Hugging Face API on New Item From Multiple RSS Feeds from RSS API

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New Item From Multiple RSS Feeds from the RSS API

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Document Question Answering with the Hugging Face API

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Getting Started#

This integration creates a workflow with a RSS trigger and Hugging Face 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 From Multiple RSS Feeds trigger
1. Connect your RSS account
2. Configure timer
3. Configure Feed URLs
4. Optional- Configure Max per Feed
Configure the Document Question Answering action
1. Connect your Hugging Face account
2. Select a Model ID
3. Configure Image URL
4. Configure Question
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 From Multiple RSS Feeds on RSS

Description:Emit new items from multiple RSS feeds

Version:1.2.7

Key:rss-new-item-from-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-new-item-from-multiple-feeds",
    name: "New Item From Multiple RSS Feeds",
    type: "source",
    description: "Emit new items from multiple RSS feeds",
    version: "1.2.7",
    props: {
        ...rssCommon.props,
        urls: {
            propDefinition: [
                rss,
                "urls",
            ],
            description: "Enter one or multiple URLs from any public RSS feed. To avoid timeouts, 5 or less URLs is recommended.",
        },
        max: {
            type: "integer",
            label: "Max per Feed",
            description: "Maximum number of posts per feed to retrieve at one time. Defaults to 20.",
            optional: true,
            default: 20,
        },
    },
    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))?.slice(0, this.max);
            console.log(`Retrieved items from ${url}`);
            items.push(...feedItems);
        }
        this.rss.sortItems(items).forEach((item) => {
            const meta = this.generateMeta(item);
            this.$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 one or multiple URLs from any public RSS feed. To avoid timeouts, 5 or less URLs is recommended.
Max per Feed	`max`	`integer`	Maximum number of posts per feed to retrieve at one time. Defaults to 20.

Trigger Authentication#

The RSS API does not require authentication.

About RSS#

Real Simple Syndication

Action#

Document Question Answering on Hugging Face

Description:Want to have a nice know-it-all bot that can answer any question?. This action allows you to ask a question and get an answer from a trained model. [See the docs](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#questionanswer).

Version:0.0.1

Key:hugging_face-document-question-answering

View on GitHub

Hugging Face Overview#

The Hugging Face API provides access to a vast range of machine learning models, primarily for natural language processing (NLP) tasks like text classification, translation, summarization, and question answering. It lets you leverage pre-trained models and fine-tune them on your data. Using the API within Pipedream, you can automate workflows that involve language processing, integrate AI insights into your apps, or respond to events with AI-generated content.

Action Code#

import app from "../../hugging_face.app.mjs";
import tag from "../common/tag.mjs";

export default {
  key: "hugging_face-document-question-answering",
  name: "Document Question Answering",
  description: "Want to have a nice know-it-all bot that can answer any question?. This action allows you to ask a question and get an answer from a trained model. [See the docs](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#questionanswer).",
  type: "action",
  version: "0.0.1",
  props: {
    app,
    modelId: {
      propDefinition: [
        app,
        "modelId",
        () => ({
          tagFilter: tag.DOCUMENT_QUESTION_ANSWERING,
        }),
      ],
    },
    imageUrl: {
      description: "The image url to use for answering the question.",
      propDefinition: [
        app,
        "imageUrl",
      ],
    },
    question: {
      type: "string",
      label: "Question",
      description: "The question to ask.",
    },
  },
  async run({ $: step }) {
    const {
      modelId,
      imageUrl,
      question,
    } = this;

    const image = await this.app.getBinaryFromUrl(imageUrl);

    const response = await this.app.inference({
      step,
      modelId,
      data: {
        inputs: {
          image,
          question,
        },
      },
    });

    step.export("$summary", `Successfully answered question with score ${response[0].score}`);

    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
Hugging Face	`app`	`app`	This component uses the Hugging Face app.
Model ID	`modelId`	`string`	Select a value from the drop down menu.
Image URL	`imageUrl`	`string`	The image url to use for answering the question.
Question	`question`	`string`	The question to ask.

Action Authentication#

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

To retrieve your Access Tokens,

Navigate to your Hugging Face account and sign in
Go to “Settings” > “Access Tokens”

About Hugging Face#

Build, train and deploy state of the art models powered by the reference open source in machine learning.

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