← MongoDB + Hugging Face integrations

Image Classification with Hugging Face API on New Collection from MongoDB API

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Trigger workflow on
New Collection from the MongoDB API
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Image Classification with the Hugging Face API
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Getting Started

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

  1. Select this integration
  2. Configure the New Collection trigger
    1. Connect your MongoDB account
    2. Configure Polling Interval
    3. Select a Database
  3. Configure the Image Classification action
    1. Connect your Hugging Face account
    2. Select a Model ID
    3. Configure Image URL
  4. Deploy the workflow
  5. Send a test event to validate your setup
  6. 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

Description:Emit new an event when a new collection is added to a database
Version:0.0.7
Key:mongodb-new-collection

MongoDB Overview

The MongoDB API provides powerful capabilities to interact with a MongoDB database, allowing you to perform CRUD (Create, Read, Update, Delete) operations, manage databases, and execute sophisticated queries. With Pipedream, you can harness these abilities to automate tasks, sync data across various apps, and react to events in real-time. It’s a combo that’s particularly potent for managing data workflows, syncing application states, or triggering actions based on changes to your data.

Trigger Code

import common from "../common/base.mjs";

export default {
  ...common,
  key: "mongodb-new-collection",
  name: "New Collection",
  description: "Emit new an event when a new collection is added to a database",
  version: "0.0.7",
  type: "source",
  dedupe: "unique",
  props: {
    ...common.props,
    database: {
      propDefinition: [
        common.props.mongodb,
        "database",
      ],
    },
  },
  methods: {
    ...common.methods,
    _getCollectionIds() {
      return this.db.get("collectionIds");
    },
    _setCollectionIds(collectionIds) {
      this.db.set("collectionIds", collectionIds);
    },
    isRelevant(uuid, collectionIds) {
      return !collectionIds.includes(uuid);
    },
    async processEvent(client, ts) {
      const collectionIds = this._getCollectionIds() || [];
      const collections = await this.mongodb.listCollections(client, this.database);
      for (const collection of collections) {
        const uuid = JSON.stringify(collection.info.uuid);
        if (!this.isRelevant(uuid, collectionIds)) {
          continue;
        }
        collectionIds.push(uuid);
        this.emitEvent(collection, ts);
      }
      this._setCollectionIds(collectionIds);
    },
    generateMeta({
      info, name,
    }, ts) {
      return {
        id: info.uuid,
        summary: name,
        ts,
      };
    },
  },
};

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.
LabelPropTypeDescription
MongoDBmongodbappThis component uses the MongoDB app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
Polling Intervaltimer$.interface.timer

Pipedream will poll the API on this schedule

DatabasedatabasestringSelect a value from the drop down menu.

Trigger Authentication

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

Before you connect to your Mongo database from Pipedream, please make sure your database is accessible from the public internet. You may need to add a firewall rule allowing connections from 0.0.0.0/0.

Then, enter the details of your Mongo host / database below.

About MongoDB

MongoDB is an open source NoSQL database management program.

Action

Description:This task reads some image input and outputs the likelihood of classes. This action allows you to classify images into categories. [See the docs](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#imageclassification).
Version:0.0.1
Key:hugging_face-image-classification

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-image-classification",
  name: "Image Classification",
  description: "This task reads some image input and outputs the likelihood of classes. This action allows you to classify images into categories. [See the docs](https://huggingface.co/docs/huggingface.js/inference/classes/HfInference#imageclassification).",
  type: "action",
  version: "0.0.1",
  props: {
    app,
    modelId: {
      propDefinition: [
        app,
        "modelId",
        () => ({
          tagFilter: tag.IMAGE_CLASSIFICATION,
        }),
      ],
    },
    imageUrl: {
      description: "The image url to use for classification.",
      propDefinition: [
        app,
        "imageUrl",
      ],
    },
  },
  async run({ $: step }) {
    const {
      modelId,
      imageUrl,
    } = this;

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

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

    step.export("$summary", "Successfully classified image");

    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.

LabelPropTypeDescription
Hugging FaceappappThis component uses the Hugging Face app.
Model IDmodelIdstringSelect a value from the drop down menu.
Image URLimageUrlstring

The image url to use for classification.

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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