Automatically Publish Models to Firebase ML

This sample demonstrates how to automatically publish models to Firebase ML for each TensorFlow Lite file that is uploaded to Firebase Storage.

Functions Code

See file functions/index.js for the model publishing code.

The dependencies are listed in functions/package.json.

Trigger rules

The function triggers on upload of any file to your Firebase project's default Cloud Storage bucket.

Deploy and test

To deploy and test the sample:

• Create a Firebase project on the Firebase Console and visit the Storage tab.
• Clone this repo: git clone https://github.com/firebase/functions-samples.
• Open this sample's directory: cd functions-samples/publish-model
• Setup your project by running firebase use --add and select the project you had created.
• Install dependencies in the functions directory: cd functions; npm install; cd -
• Deploy your project using firebase deploy
• Go to your project's Cloud Console > IAM & admin > IAM, Find the App Engine default service account.
• Add the Service Account Token Creator role to that member. This will allow your app to create signed public URLs to the models.
• Add the Firebase ML Kit Admin role to that member. This will allow your app to manage Firebase ML models.
• Add the Firebase Admin SDK Administrator Service Agent role to that member. This will allow your app to manage models with the Firebase Admin SDK.
• Go to the Firebase Console Storage tab and upload a Tensorflow Lite model (*.tflite). After a short time a model with same file name will be published to Firebase ML.
• Go to the Firebase Console ML Kit (Custom) tab and see that a new model with file name has been created.