In this post, we’ll walk through building a React Native app that generates children’s stories based on prompts and age ranges, using Hugging Face's powerful AI models. The app allows users to enter a prompt, select an age range, and then see a custom story along with a cartoonish image summarizing the story.

Features

Interactive Story Generation: User input guides the AI to create engaging children’s stories.
Summarization and Visualization: The story is summarized and displayed alongside an AI-generated image.
Smooth UI Animation: Animations adapt the UI for keyboard input.
Navigation and Styling: Using Expo Router for easy navigation and custom styles for an attractive UI.

Let’s break down each part!

Step 1: Setting Up React Native and Hugging Face API

Start by creating a new React Native project with Expo:

npx create-expo-app@latest KidsStoryApp
cd KidsStoryApp

Set up Expo Router in your app for easy navigation, and install any additional dependencies you may need, like icons or animations.

Step 2: Creating the Story Generator Home Screen

In the Home.js file, we set up a screen where users can select an age range, enter a story prompt, and press a button to generate a story.

Home.js Code

import React, { useEffect, useRef, useState } from "react";
import {
  View,
  Text,
  TouchableOpacity,
  StyleSheet,
  TextInput,
  Animated,
  ActivityIndicator,
} from "react-native";
import useKeyboardOffsetHeight from "../hooks/useKeyboardOffsetHeight";
import { HUGGING_FACE_KEY } from "../env";
import { useRouter } from "expo-router";

const Home = () => {
  const ageRanges = ["0-3", "4-6", "7-9"];
  const [selectedAgeRange, setSelectedAgeRange] = useState("0-3");
  const [textInput, setTextInput] = useState("");
  const [isLoading, setIsLoading] = useState(false);
  const keyboardOffsetHeight = useKeyboardOffsetHeight();
  const animatedValue = useRef(new Animated.Value(0)).current;
  const router = useRouter();

  useEffect(() => {
    Animated.timing(animatedValue, {
      toValue: keyboardOffsetHeight ? -keyboardOffsetHeight * 0.5 : 0,
      duration: 500,
      useNativeDriver: true,
    }).start();
  }, [keyboardOffsetHeight]);

  const handleAgeRangeSelect = (range) => setSelectedAgeRange(range);

  const handleShowResult = () => {
    if (textInput.length > 5) {
      fetchStory();
    } else {
      alert("Please enter a bit more detail.");
    }
  };

  async function fetchStory() {
    setIsLoading(true);
    try {
      let message = `Write a simple story for kids about ${textInput} ${
        selectedAgeRange ? "for age group " + selectedAgeRange : ""
      }, in plain words. Only provide the story content without any headings, titles, or extra information.`;

      const response = await fetch(
        "https://api-inference.huggingface.co/models/meta-llama/Llama-3.2-3B-Instruct/v1/chat/completions",
        {
          method: "POST",
          headers: {
            Authorization: `Bearer ${HUGGING_FACE_KEY}`,
            "Content-Type": "application/json",
          },
          body: JSON.stringify({
            model: "meta-llama/Llama-3.2-3B-Instruct",
            messages: [{ role: "user", content: message }],
            max_tokens: 500,
          }),
        }
      );

      if (!response.ok) throw new Error("Failed to fetch story");

      const data = await response.json();
      const storyContent = data.choices[0].message.content;

      // Summarize the story
      const summaryResponse = await fetch(
        "https://api-inference.huggingface.co/models/meta-llama/Llama-3.2-3B-Instruct/v1/chat/completions",
        {
          method: "POST",
          headers: {
            Authorization: `Bearer ${HUGGING_FACE_KEY}`,
            "Content-Type": "application/json",
          },
          body: JSON.stringify({
            model: "meta-llama/Llama-3.2-3B-Instruct",
            messages: [
              { role: "user", content: `Summarize this story in a line: "${storyContent}"` },
            ],
            max_tokens: 30,
          }),
        }
      );

      if (!summaryResponse.ok) throw new Error("Failed to fetch summary");

      const summaryData = await summaryResponse.json();
      const summaryContent = summaryData.choices[0].message.content;

      router.push({
        pathname: "/detail",
        params: { story: storyContent, summary: summaryContent },
      });
    } catch (error) {
      console.error("Error fetching story or summary:", error);
      alert("Error fetching story. Please try again.");
    } finally {
      setIsLoading(false);
    }
  }

  return (
    <Animated.ScrollView
      bounces={false}
      keyboardShouldPersistTaps="handled"
      keyboardDismissMode="on-drag"
      style={{ transform: [{ translateY: animatedValue }] }}
      contentContainerStyle={styles.container}
    >
      <Text style={styles.header}>Select Age Range</Text>
      <View style={styles.checkboxContainer}>
        {ageRanges.map((range, index) => (
          <TouchableOpacity
            key={index}
            style={[
              styles.checkbox,
              selectedAgeRange === range && styles.selectedCheckbox,
            ]}
            onPress={() => handleAgeRangeSelect(range)}
          >
            <Text style={styles.checkboxLabel}>{range}</Text>
          </TouchableOpacity>
        ))}
      </View>
      <TextInput
        style={styles.textInput}
        placeholder="Enter story topic..."
        placeholderTextColor="#888"
        value={textInput}
        onChangeText={setTextInput}
        multiline
      />
      <TouchableOpacity style={styles.showButton} onPress={handleShowResult} disabled={isLoading}>
        {isLoading ? <ActivityIndicator color="#fff" /> : <Text style={styles.showButtonText}>Generate</Text>}
      </TouchableOpacity>
    </Animated.ScrollView>
  );
};

const styles = StyleSheet.create({
  container: { flex: 1, padding: 20, alignItems: "center", backgroundColor: "#1c1c1c" },
  header: { fontSize: 20, fontWeight: "bold", color: "#fff", marginVertical: 10 },
  checkboxContainer: { flexDirection: "row", flexWrap: "wrap", justifyContent: "center", marginBottom: 20 },
  checkbox: { width: 60, height: 60, borderRadius: 30, backgroundColor: "#333", alignItems: "center", justifyContent: "center", margin: 10 },
  selectedCheckbox: { backgroundColor: "#1fb28a" },
  checkboxLabel: { color: "#fff", fontSize: 14, fontWeight: "bold" },
  textInput: { width: "100%", height: 150, backgroundColor: "#333", color: "#fff", borderRadius: 8, padding: 10, marginVertical: 20, fontSize: 16 },
  showButton: { backgroundColor: "#1fb28a", borderRadius: 8, paddingVertical: 10, paddingHorizontal: 20, marginTop: 10 },
  showButtonText: { color: "#fff", fontSize: 16, fontWeight: "bold" },
});

export default Home;

Key Components of `Home.js`

Text Input and Age Selector: Allows the user to select an age range and enter a story prompt.
Fetch Story: fetchStory interacts with the Hugging Face API to generate and summarize a story based on the input.
Navigation: If a story and summary are successfully fetched, the app navigates to the Detail screen to display the results.

Step 3: Displaying Story and Image on the Detail Screen

The Detail screen retrieves the generated story, summarizes it, and displays an AI-generated cartoon image related to the story.

Detail.js Code

import React, { useEffect, useState } from "react";
import { StyleSheet, View, Text, TouchableOpacity, ActivityIndicator, Image, ScrollView } from "react-native";
import { useLocalSearchParams, useRouter } from "expo-router";
import { HUGGING_FACE_KEY } from "../env";
import Ionicons from "@expo/vector-icons/Ionicons";

const Detail = () => {
  const params = useLocalSearchParams();
  const { story, summary } = params;
  const [imageUri, setImageUri] = useState(null);
  const [loading, setLoading] = useState(false);
  const router = useRouter();

  useEffect(() => {
    const fetchImage = async () => {
      setLoading(true);
      try {
        const response = await fetch("https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0", {
          method: "POST",
          headers: { Authorization: `Bearer ${HUGGING_FACE_KEY}`, "Content-Type": "application/json" },
          body: JSON.stringify

({ inputs: `Cartoonish ${summary}`, target_size: { width: 300, height: 300 } }),
        });

        if (!response.ok) throw new Error(`Request failed: ${response.status}`);

        const blob = await response.blob();
        const base64Data = await blobToBase64(blob);
        setImageUri(`data:image/jpeg;base64,${base64Data}`);
      } catch (error) {
        console.error("Error fetching image:", error);
      } finally {
        setLoading(false);
      }
    };

    fetchImage();
  }, []);

  const blobToBase64 = (blob) => {
    return new Promise((resolve, reject) => {
      const reader = new FileReader();
      reader.onloadend = () => resolve(reader.result.split(",")[1]);
      reader.onerror = reject;
      reader.readAsDataURL(blob);
    });
  };

  return (
    <ScrollView style={styles.container}>
      <TouchableOpacity onPress={() => router.back()}>
        <Ionicons name="arrow-back-circle-sharp" size={50} color="yellow" />
      </TouchableOpacity>
      {loading ? (
        <ActivityIndicator size="large" color="#ffffff" />
      ) : imageUri ? (
        <Image source={{ uri: imageUri }} style={styles.image} />
      ) : (
        <Text style={styles.text}>No image generated yet.</Text>
      )}
      <Text style={styles.header}>{story}</Text>
    </ScrollView>
  );
};

export default Detail;

const styles = StyleSheet.create({
  container: { flex: 1, padding: 16, backgroundColor: "#1c1c1c" },
  header: { fontSize: 24, color: "#ffffff", marginVertical: 16 },
  text: { color: "#ffffff" },
  image: { width: 300, height: 300, marginTop: 20, borderRadius: 10, alignSelf: "center" },
});

Wrapping Up

This app is a great way to combine user input with AI models to create a dynamic storytelling experience. By using React Native, Hugging Face API, and Expo Router, we’ve created a simple yet powerful storytelling app that can entertain kids with custom-made stories and illustrations.

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