Hugging Face

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

Integrate the Hugging Face API with the MongoDB API

Setup the Hugging Face API trigger to run a workflow which integrates with the MongoDB API. Pipedream's integration platform allows you to integrate Hugging Face and MongoDB remarkably fast. Free for developers.

Image Classification with Hugging Face API on New Collection from MongoDB API
MongoDB + Hugging Face
 
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Document Question Answering with Hugging Face API on New Collection from MongoDB API
MongoDB + Hugging Face
 
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Document Question Answering with Hugging Face API on New Database from MongoDB API
MongoDB + Hugging Face
 
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Document Question Answering with Hugging Face API on New Document from MongoDB API
MongoDB + Hugging Face
 
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Document Question Answering with Hugging Face API on New Field in Document from MongoDB API
MongoDB + Hugging Face
 
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New Collection from the MongoDB API

Emit new an event when a new collection is added to a database

 
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New Database from the MongoDB API

Emit new an event when a new database is added

 
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New Document from the MongoDB API

Emit new an event when a new document is added to a collection

 
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New Field in Document from the MongoDB API

Emit new an event when a new field is added to a document

 
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Document Question Answering with the Hugging Face API

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.

 
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Create New Document with the MongoDB API

Create a new document in a collection of your choice. See the docs here

 
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Image Classification with the Hugging Face API

This task reads some image input and outputs the likelihood of classes. This action allows you to classify images into categories. See the docs.

 
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Delete a Document with the MongoDB API

Delete a single document by ID. See the docs here

 
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Language Translation with the Hugging Face API

This task is well known to translate text from one language to another. See the docs.

 
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Overview of Hugging Face

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.

Connect Hugging Face

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    hugging_face: {
      type: "app",
      app: "hugging_face",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://huggingface.co/api/whoami-v2`,
      headers: {
        Authorization: `Bearer ${this.hugging_face.$auth.access_token}`,
      },
    })
  },
})

Overview of MongoDB

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.

Connect MongoDB

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import mongodb from 'mongodb'

export default defineComponent({
  props: {
    mongodb: {
      type: "app",
      app: "mongodb",
    },
    collection: {
      type: "string"
    },
    filter: {
      type: "object"
    }
  },
  async run({steps, $}) {
    const MongoClient = mongodb.MongoClient
    
    const {
      database,
      hostname,
      username,
      password,
    } = this.mongodb.$auth
    
    const url = `mongodb+srv://${username}:${password}@${hostname}/test?retryWrites=true&w=majority`
    const client = await MongoClient.connect(url, { 
      useNewUrlParser: true, 
      useUnifiedTopology: true 
    })
    
    const db = client.db(database)

    const results = await db.collection(this.collection).find(this.filter).toArray();
    $.export('results', results);
    
    await client.close()
  },
})