Actions
| Name | Description |
|---|---|
document_question_answeringAnswer questions from document images using Hugging Face models | Answer questions from document images using Hugging Face models |
language_translationTranslate text between languages using specialized Hugging Face translation models | Translate text between languages using specialized Hugging Face translation models |
text_classificationClassify text into categories using Hugging Face models - includes zero-shot classification for custom categories | Classify text into categories using Hugging Face models - includes zero-shot classification for custom categories |
text_summarizationGenerate abstractive summaries of long text using Hugging Face models - optimized for business content | Generate abstractive summaries of long text using Hugging Face models - optimized for business content |
chat_completionGenerate assistant replies using chat-style LLMs - perfect for FAQ bots, support agents, and content generation | Generate assistant replies using chat-style LLMs - perfect for FAQ bots, support agents, and content generation |
create_imageGenerate stunning images from text prompts using state-of-the-art diffusion models - perfect for marketing, product design, and creative content | Generate stunning images from text prompts using state-of-the-art diffusion models - perfect for marketing, product design, and creative content |
object_detectionDetect and locate objects in images with precise bounding boxes - perfect for inventory management, content moderation, and automated tagging | Detect and locate objects in images with precise bounding boxes - perfect for inventory management, content moderation, and automated tagging |
image_classificationClassify images with pre-trained models or custom categories - perfect for content moderation, automated tagging, and smart asset management | Classify images with pre-trained models or custom categories - perfect for content moderation, automated tagging, and smart asset management |
Quick Start
import { WeavzClient } from '@weavz/sdk'
const weavz = new WeavzClient({ apiKey: 'wvz_...' })
const result = await weavz.actions.execute({
integrationName: 'hugging-face',
actionName: 'document_question_answering',
input: { /* ... */ },
connectionId: 'conn_id',
workspaceId: 'ws_id',
})Related Integrations
Works well with
Frequently Asked Questions
How do I connect Hugging Face to my app?
Use Weavz Hosted Connect for API Key authentication. Install the SDK, create a connection through the connect portal or API, then execute actions programmatically.
What actions does Hugging Face support?
Hugging Face supports 8 actions including Document Question Answering, Language Translation, Text Classification, Text Summarization, Chat Completion, and more.
Can I use Hugging Face with AI agents?
Yes. Add Hugging Face to an MCP server in TOOLS mode or CODE mode. CODE mode provides 80-98% context reduction with 3 meta-tools for efficient agent access.
What authentication does Hugging Face use?
Hugging Face uses API Key. Weavz handles token management, refresh, and secure credential storage automatically.
How much does the Hugging Face integration cost?
The Hugging Face integration is included on all Weavz plans including the free tier with 1,000 actions per month. No credit card required.
Connect Hugging Face in 2 minutes
Get 1,000 free actions every month. No credit card required.