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with Hugging Face and Google Cloud?

Prompt, edit and deploy AI agents that connect to Hugging Face, Google Cloud and 2,500+ other apps in seconds.

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Document Question Answering with Hugging Face API on New Pub/Sub Messages from Google Cloud API
Google Cloud + Hugging Face
 
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Image Classification with Hugging Face API on New Pub/Sub Messages from Google Cloud API
Google Cloud + Hugging Face
 
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Language Translation with Hugging Face API on New Pub/Sub Messages from Google Cloud API
Google Cloud + Hugging Face
 
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Object Detection with Hugging Face API on New Pub/Sub Messages from Google Cloud API
Google Cloud + Hugging Face
 
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Text Classification with Hugging Face API on New Pub/Sub Messages from Google Cloud API
Google Cloud + Hugging Face
 
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New Pub/Sub Messages from the Google Cloud API

Emit new Pub/Sub topic in your GCP account. Messages published to this topic are emitted from the Pipedream source.

 
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BigQuery - New Row from the Google Cloud API

Emit new events when a new row is added to a table

 
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BigQuery - Query Results from the Google Cloud API

Emit new events with the results of an arbitrary query

 
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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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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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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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Object Detection with the Hugging Face API

This task reads some image input and outputs the likelihood of classes and bounding boxes of detected objects. See the docs

 
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Bigquery Insert Rows with the Google Cloud API

Inserts rows into a BigQuery table. See the docs and for an example here

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

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 Google Cloud

The Google Cloud API opens a world of possibilities for enhancing cloud operations and automating tasks. It empowers you to manage, scale, and fine-tune various services within the Google Cloud Platform (GCP) programmatically. With Pipedream, you can harness this power to create intricate workflows, trigger cloud functions based on events from other apps, manage resources, and analyze data, all in a serverless environment. The ability to interconnect GCP services with numerous other apps enriches automation, making it easier to synchronize data, streamline development workflows, and deploy applications efficiently.

Connect Google Cloud

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module.exports = defineComponent({
  props: {
    google_cloud: {
      type: "app",
      app: "google_cloud",
    }
  },
  async run({steps, $}) {
    // Required workaround to get the @google-cloud/storage package
    // working correctly on Pipedream
    require("@dylburger/umask")()
    
    const { Storage } = require('@google-cloud/storage')
    
    const key = JSON.parse(this.google_cloud.$auth.key_json)
     
    const storage = new Storage({
      projectId: key.project_id,
      credentials: {
        client_email: key.client_email,
        private_key: key.private_key,
      }
    })
    
    await storage.authClient.getCredentials()
    return {
      status: "success",
      authenticated: true,
      projectId: key.project_id,
      serviceAccount: key.client_email
    }
  },
})

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

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SAS logo
Scale AI logo
Webflow logo
Warner Bros. logo
Adyen logo
Appcues logo
Bandwidth logo
Checkr logo
ChartMogul logo
Dataminr logo
Gopuff logo
Gorgias logo
LinkedIn logo
Logitech logo
Replicated logo
Rudderstack logo
SAS logo
Scale AI logo
Webflow logo
Warner Bros. logo