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Building an Interactive Kids Story Generator with React Native and Hugging Face API

Linda Hamilton
Release: 2024-11-25 15:35:11
Original
1024 people have browsed it

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

  1. Interactive Story Generation: User input guides the AI to create engaging children’s stories.
  2. Summarization and Visualization: The story is summarized and displayed alongside an AI-generated image.
  3. Smooth UI Animation: Animations adapt the UI for keyboard input.
  4. 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
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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

Building an Interactive Kids Story Generator with React Native and Hugging Face API

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"
     >



<h3>
  
  
  Key Components of Home.js
</h3>

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


<hr>

<h3>
  
  
  Step 3: Displaying Story and Image on the Detail Screen
</h3>

<p><img src="https://img.php.cn/upload/article/000/000/000/173252011696327.jpg" alt="Building an Interactive Kids Story Generator with React Native and Hugging Face API" /></p>

<p>The Detail screen retrieves the generated story, summarizes it, and displays an AI-generated cartoon image related to the story.</p><h4>
  
  
  Detail.js Code
</h4>



<pre class="brush:php;toolbar:false">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>



<h3>
  
  
  Wrapping Up
</h3>

<p>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.</p>


          

            
        
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