Getting Started

Latest Android SDK version: 3.3.1 — see the Changelog for release notes. The SDK is published on Maven Central as ai.passio.passiosdk:nutrition-ai.

Overview

The Passio Nutrition AI Android SDK (ai.passio.passiosdk:nutrition-ai) provides food recognition and nutrition intelligence for Android apps.

At a high level, this SDK gives you:

• Camera integration (CameraX-backed) for live capture and barcode scanning.

• Remote food recognition from images.

• Nutrition/food search and food item retrieval.

• Speech-to-meal parsing.

• Meal suggestions and meal plan generation.

• Nutrition Advisor conversational APIs.

• Food reporting and user-submitted food APIs.

Requirements

Requirement	Value
Android min SDK	26 (Android 8.0+)
Compile SDK	35 (recommended)
CameraX	1.4.0
ML Kit text recognition	19.0.0
ML Kit barcode scanning	18.3.0
Camera permission	Required for scanner/preview workflows
Internet access	Required for license/token and most APIs
Passio SDK key	Required for production use

Core Concepts

1. PassioSDK.instance

• Singleton entry point for all SDK functionality.

• All calls should be made from the main thread; results are delivered on the main thread.

1. PassioConfiguration

• Startup configuration object passed to configure(...).

• Key options: sdkDownloadsModels, remoteOnly, proxyUrl, proxyHeaders.

1. PassioStatus / PassioMode

• Returned by configure(...).

• Modes: NOT_READY, FAILED_TO_CONFIGURE, IS_BEING_CONFIGURED, IS_DOWNLOADING_MODELS, IS_READY_FOR_DETECTION.

1. PassioResult<T>

• Sealed result wrapper: PassioResult.Success(value) or PassioResult.Error(message).

1. PassioFoodItem

• Primary nutrition model for fully resolved food data.

• Includes amounts, serving units, ingredients, and nutrient accessors.

Quick Start Flow

1. Add the SDK dependency to your app.

2. Request camera permission at runtime.

3. Configure the SDK with PassioConfiguration.

4. Wait for PassioMode.IS_READY_FOR_DETECTION.

5. Start camera with a PassioCameraViewProvider.

6. Call APIs like recognizeImageRemote, searchForFood, fetchFoodItemForRefCode, or startBarcodeScanning.

Minimal Setup Example

import ai.passio.passiosdk.core.config.PassioConfiguration
import ai.passio.passiosdk.core.config.PassioMode
import ai.passio.passiosdk.passiofood.PassioSDK

private fun configurePassio(applicationContext: Context, key: String) {
    val config = PassioConfiguration(applicationContext, key).apply {
        sdkDownloadsModels = true
        debugMode = 1
    }

    PassioSDK.instance.configure(config) { status ->
        when (status.mode) {
            PassioMode.IS_READY_FOR_DETECTION -> {
                // SDK ready
            }
            PassioMode.IS_DOWNLOADING_MODELS -> {
                // Models are downloading
            }
            PassioMode.FAILED_TO_CONFIGURE -> {
                // Check status.error and status.debugMessage
            }
            PassioMode.IS_BEING_CONFIGURED,
            PassioMode.NOT_READY -> Unit
        }
    }
}

Read Next

• Adding Passio SDK to your project

• Initialize and configure the SDK

• Quick Start Guide

• API Reference

• Classes and Properties

• Changelog