What do you want to automate
with Hugging Face and Data Stores?
Prompt, edit and deploy AI agents that connect to Hugging Face, Data Stores and 2,500+ other apps in seconds.
Trusted by 1,000,000+ developers from startups to Fortune 500 companies
Popular Hugging Face and Data Stores Actions#
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
Add or update a single record in your Pipedream Data Store
This task reads some image input and outputs the likelihood of classes. This action allows you to classify images into categories. See the docs
Add or update multiple records to your Pipedream Data Store
This task is well known to translate text from one language to another. See the docs
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#
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 Data Stores#
Data Stores are a key-value store that allow you to persist state and share data across workflows. You can perform CRUD operations, enabling dynamic data management within your serverless architecture. Use it to save results from API calls, user inputs, or interim data; then read, update, or enrich this data in subsequent steps or workflows. Data Stores simplify stateful logic and cross-workflow communication, making them ideal for tracking process statuses, aggregating metrics, or serving as a simple configuration store.
Connect Data Stores#
export default defineComponent({
props: {
myDataStore: {
type: "data_store",
},
},
async run({ steps, $ }) {
await this.myDataStore.set("key_here","Any serializable JSON as the value")
return await this.myDataStore.get("key_here")
},
})Trusted by 1,000,000+ developers from startups to Fortune 500 companies