@subhajit-gorai/react-native-mediapipe-llm/src/hooks/useLlmInference.ts

React Native binding for Google AI Edge Gallery's MediaPipe on-device LLM inference engine

import { useState, useCallback } from 'react';
import { LlmOptions, LlmInferenceHook } from '../types';

export const useLlmInference = (): LlmInferenceHook => {
  const [isInitialized, setIsInitialized] = useState(false);
  const [isLoading, setIsLoading] = useState(false);

  const initialize = useCallback(async (options: LlmOptions): Promise<boolean> => {
    setIsLoading(true);
    try {
      await new Promise(resolve => setTimeout(resolve, 2000));
      setIsInitialized(true);
      return true;
    } catch (error) {
      return false;
    } finally {
      setIsLoading(false);
    }
  }, []);

  const generateResponse = useCallback(async (
    prompt: string, 
    partialCallback?: (partial: string) => void
  ): Promise<string> => {
    if (!isInitialized) {
      throw new Error('LLM not initialized');
    }

    setIsLoading(true);
    
    try {
      const responses = [
        `Hello! I'm Gemma 3N, your AI assistant. You asked: "${prompt}". How can I help you today?`,
        `That's an interesting question about "${prompt}"! Let me think about that...`,
        `Based on your input "${prompt}", I would suggest the following approach:`,
        `I understand you're asking about "${prompt}". Here's what I know:`,
        `Thank you for your question about "${prompt}". Let me provide you with a detailed response:`,
      ];
      
      const baseResponse = responses[Math.floor(Math.random() * responses.length)];
      const words = baseResponse.split(' ');
      let currentResponse = '';
      
      for (let i = 0; i < words.length; i++) {
        currentResponse += (i > 0 ? ' ' : '') + words[i];
        if (partialCallback) {
          partialCallback(words[i] + (i < words.length - 1 ? ' ' : ''));
        }
        await new Promise(resolve => setTimeout(resolve, 100));
      }
      
      return currentResponse;
    } finally {
      setIsLoading(false);
    }
  }, [isInitialized]);

  return {
    generateResponse,
    initialize,
    isInitialized,
    isLoading,
  };
};