Integrate Hugging Face and Firestore
Connect Hugging Face and Firestore nodes in your workflow. Integrate with any tool or database and ship powerful backend logic and APIs instantly - No code required!
Node stack
Supported Hugging Face and Firestore Nodes
Add any other tools or your preferred database nodes. If an integration is not available generate your own using AI
Caption Image
Generate caption for the image using Hugging Face's [Salesforce/blip-image-captioning-large](https://huggingface.co/Salesforce/blip-image-captioning-large) model for image captioning pretrained on COCO dataset - base architecture (with ViT large backbone).
Image Classification
Get classification labels for your image using Hugging Face's [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) model which is a transformer encoder model (BERT-like) pretrained on a large collection of images in a supervised fashion, namely ImageNet-21k, at a resolution of 224x224 pixels. Next, the model was fine-tuned on ImageNet (also referred to as ILSVRC2012), a dataset comprising 1 million images and 1,000 classes, also at resolution 224x224.
Text Summarization
Summarize long text using Hugging Face's [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) model which is a transformer encoder-encoder (seq2seq) model with a bidirectional (BERT-like) encoder and an autoregressive (GPT-like) decoder. BART is pre-trained by (1) corrupting text with an arbitrary noising function, and (2) learning a model to reconstruct the original text.
Text-To-Image
Generate image from text, using Hugging Face's [openskyml/dalle-3-xl](https://huggingface.co/openskyml/dalle-3-xl) test model very similar to Dall•E 3.
Text-To-Music
Generate music from text using Hugging Face's [facebook/musicgen-small](https://huggingface.co/facebook/musicgen-small) model capable of generating high-quality music samples conditioned on text descriptions or audio prompts.
Add Object to Firestore Array
Adds an object to an existing array in a Firestore document
Collection Query
Get documents of a query in Firestore with multiple filters (with support for document reference).
Create Document
Creates or updates a document in a specified Firestore collection (with document reference field type support).
Delete Firestore Document
Delete a document from a Firestore collection
Firestore Document Count
Get the count of documents in a collection for a given filter
Firestore Field Average
This is blank script node to help you get started. [Full Documentation](https://docs.buildship.com/core-nodes/script).
Firestore Field Sum
Sum of field in collection for given filter
Firestore Query Count
Get server count of a query in Firestore with multiple filters
Get Document Field Value
Fetches a specific field value from a document in a Firestore collection
Get Firestore Document
Fetch a document from Firestore by its collection name and ID
Get User Data With Email
Fetch user data from Firebase Auth based given their email
Update Document
Updates an entire Firestore document with a given object
Update Field Value
Updates a field value in a Firestore document with a given object
Quick start
How to integrate Hugging Face and Firestore
Step 1 — Add the nodes to your workflow
Create a new workflow in BuildShip, click “Add node”, and select the Hugging Face and Firestore actions you want to use.
Step 2 — Configure each node
Go to each node to authenticate (or add your API key) and fill in the required parameters.
Step 3 — Connect the nodes
Each node in BuildShip can connect to others by using their output variables. When you reference a variable from one node in another, BuildShip automatically links them in the workflow.
Step 4 — Test your workflow
Define your starting data in the Inputs node and choose what to do with the result in the Flow Output node. Finally, run a test to see your workflow in action.
blog posts & tutorials
Recommended Reads
Below are recommneded blogs that will help in your journey
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