How to Build an AI Chat App Using React Native

How do you build an AI chat app in React Native?

Build an AI chat app in React Native using a message state manager, streaming API integration, and a conversational UI component. This requires handling real-time responses, message history, and provider switching. AI Mobile Launcher's Chat Module implements this complete solution in under 100 lines of code.

AI chat applications have become the most requested feature in mobile apps. This comprehensive guide walks you through building a production-ready AI chat app from scratch, covering architecture, UI design, and deployment best practices.

What architecture should you use for an AI chat app?

A robust AI chat app requires these architectural layers:

• Presentation Layer - Chat UI components: message bubbles, input field, typing indicators
• State Management - Message history, loading states, error handling with Zustand or Context
• API Layer - Secure backend endpoints that communicate with AI providers
• Persistence Layer - AsyncStorage or SQLite for conversation history
• Streaming Handler - Real-time response streaming for better UX

// Architecture Overview
src/
├── features/
│   └── chat/
│       ├── components/
│       │   ├── ChatScreen.tsx
│       │   ├── MessageBubble.tsx
│       │   ├── ChatInput.tsx
│       │   └── TypingIndicator.tsx
│       ├── hooks/
│       │   ├── useChat.ts
│       │   └── useStreamingResponse.ts
│       ├── stores/
│       │   └── chatStore.ts
│       └── types/
│           └── chat.types.ts
├── api/
│   └── ai.api.ts
└── utils/
    └── storage.ts

How do you implement the chat state management?

Use Zustand for efficient, type-safe state management:

// stores/chatStore.ts
import { create } from 'zustand';
import { persist, createJSONStorage } from 'zustand/middleware';
import AsyncStorage from '@react-native-async-storage/async-storage';

interface Message {
  id: string;
  role: 'user' | 'assistant' | 'system';
  content: string;
  timestamp: number;
}

interface ChatState {
  messages: Message[];
  isLoading: boolean;
  error: string | null;
  addMessage: (message: Omit<Message, 'id' | 'timestamp'>) => string;
  updateMessage: (id: string, content: string) => void;
  setLoading: (loading: boolean) => void;
  setError: (error: string | null) => void;
  clearChat: () => void;
}

export const useChatStore = create<ChatState>()(
  persist(
    (set, get) => ({
      messages: [],
      isLoading: false,
      error: null,
      
      addMessage: (message) => {
        const id = Date.now().toString();
        set((state) => ({
          messages: [...state.messages, {
            ...message,
            id,
            timestamp: Date.now(),
          }],
        }));
        return id;
      },
      
      updateMessage: (id, content) => {
        set((state) => ({
          messages: state.messages.map((msg) =>
            msg.id === id ? { ...msg, content } : msg
          ),
        }));
      },
      
      setLoading: (isLoading) => set({ isLoading }),
      setError: (error) => set({ error }),
      clearChat: () => set({ messages: [], error: null }),
    }),
    {
      name: 'chat-storage',
      storage: createJSONStorage(() => AsyncStorage),
    }
  )
);

How do you create a beautiful chat UI in React Native?

Build an accessible, responsive chat interface:

// components/ChatScreen.tsx
import { FlatList, KeyboardAvoidingView, Platform } from 'react-native';
import { useChatStore } from '../stores/chatStore';
import { MessageBubble } from './MessageBubble';
import { ChatInput } from './ChatInput';
import { TypingIndicator } from './TypingIndicator';

export function ChatScreen() {
  const { messages, isLoading, sendMessage } = useChatStore();
  const flatListRef = useRef<FlatList>(null);

  const scrollToBottom = () => {
    flatListRef.current?.scrollToEnd({ animated: true });
  };

  useEffect(() => {
    scrollToBottom();
  }, [messages]);

  return (
    <KeyboardAvoidingView
      behavior={Platform.OS === 'ios' ? 'padding' : 'height'}
      style={{ flex: 1 }}
      keyboardVerticalOffset={90}
    >
      <FlatList
        ref={flatListRef}
        data={messages}
        keyExtractor={(item) => item.id}
        renderItem={({ item }) => (
          <MessageBubble message={item} />
        )}
        contentContainerStyle={{ padding: 16 }}
        ListFooterComponent={
          isLoading ? <TypingIndicator /> : null
        }
      />
      <ChatInput onSend={sendMessage} disabled={isLoading} />
    </KeyboardAvoidingView>
  );
}

// components/MessageBubble.tsx
import { View, Text, StyleSheet } from 'react-native';
import Animated, { FadeInUp } from 'react-native-reanimated';

export function MessageBubble({ message }) {
  const isUser = message.role === 'user';
  
  return (
    <Animated.View
      entering={FadeInUp.duration(300)}
      style={[
        styles.bubble,
        isUser ? styles.userBubble : styles.assistantBubble,
      ]}
    >
      <Text style={[
        styles.text,
        isUser ? styles.userText : styles.assistantText,
      ]}>
        {message.content}
      </Text>
    </Animated.View>
  );
}

const styles = StyleSheet.create({
  bubble: {
    maxWidth: '80%',
    padding: 12,
    borderRadius: 16,
    marginVertical: 4,
  },
  userBubble: {
    alignSelf: 'flex-end',
    backgroundColor: '#007AFF',
    borderBottomRightRadius: 4,
  },
  assistantBubble: {
    alignSelf: 'flex-start',
    backgroundColor: '#E9E9EB',
    borderBottomLeftRadius: 4,
  },
  text: { fontSize: 16, lineHeight: 22 },
  userText: { color: '#FFFFFF' },
  assistantText: { color: '#000000' },
});

How do you implement streaming responses?

Streaming provides real-time feedback as the AI generates responses:

// hooks/useStreamingChat.ts
import { useCallback } from 'react';
import { useChatStore } from '../stores/chatStore';

export function useStreamingChat() {
  const { 
    messages, 
    addMessage, 
    updateMessage, 
    setLoading,
    setError 
  } = useChatStore();

  const sendMessage = useCallback(async (content: string) => {
    // Add user message
    addMessage({ role: 'user', content });
    
    // Create placeholder for assistant message
    const assistantId = addMessage({ role: 'assistant', content: '' });
    setLoading(true);
    setError(null);

    try {
      const response = await fetch('/api/chat', {
        method: 'POST',
        headers: { 'Content-Type': 'application/json' },
        body: JSON.stringify({
          messages: messages.map(m => ({
            role: m.role,
            content: m.content,
          })),
        }),
      });

      if (!response.ok) throw new Error('API request failed');

      const reader = response.body?.getReader();
      const decoder = new TextDecoder();
      let accumulatedContent = '';

      while (reader) {
        const { done, value } = await reader.read();
        if (done) break;

        const chunk = decoder.decode(value, { stream: true });
        accumulatedContent += chunk;
        
        // Update message with accumulated content
        updateMessage(assistantId, accumulatedContent);
      }
    } catch (error) {
      setError(error instanceof Error ? error.message : 'Unknown error');
      updateMessage(assistantId, 'Sorry, an error occurred. Please try again.');
    } finally {
      setLoading(false);
    }
  }, [messages, addMessage, updateMessage, setLoading, setError]);

  return { sendMessage };
}

What advanced features should you add?

• Message Reactions - Let users thumbs up/down responses for feedback
• Copy to Clipboard - Long-press to copy message content
• Regenerate Response - Button to regenerate the last AI response
• Conversation Branching - Edit previous messages and create new branches
• Voice Input - Speech-to-text for hands-free messaging
• Image Attachments - Send images for vision AI analysis

People Also Ask

Get Started with AI Mobile Launcher

Building a production-ready AI chat app from scratch takes 80+ hours. AI Mobile Launcher includes everything shown in this guide—plus advanced features like voice input, image analysis, and offline support—ready to use out of the box.

For Developers: Download AI Mobile Launcher and ship your AI chat app this week.

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