@masuidrive/bloom-local-rag/dist/commands/init.js

RAG (Retrieval-Augmented Generation) system for local directories - Index and search your documents with AI-powered answers

import { resolve } from 'path';
import chalk from 'chalk';
import { saveConfig, saveMetadata, ensureBloomDir } from '../lib/config.js';
import { VectorStoreManager } from '../lib/vectorStore.js';
import { Indexer } from '../lib/indexer.js';
export async function initCommand(options = {}) {
    try {
        const targetDir = options.directory ? resolve(options.directory) : resolve('.');
        console.log(chalk.blue(`Initializing bloom-local-rag in ${targetDir}...`));
        // Set API key from option if provided
        if (options.apiKey) {
            if (options.embeddingProvider === 'openai' || options.llmProvider === 'openai') {
                process.env.OPENAI_API_KEY = options.apiKey;
            }
            else {
                process.env.GOOGLE_API_KEY = options.apiKey;
            }
        }
        // Create configuration
        const config = {
            version: '1.0',
            directory: targetDir,
            extensions: options.extensions || ['.md', '.mdx', '.txt', '.js', '.ts', '.jsx', '.tsx', '.yaml', '.yml'],
            exclude: options.exclude || [],
            embedding: {
                provider: options.embeddingProvider || 'gemini',
                model: options.embeddingModel || (options.embeddingProvider === 'openai' ? 'text-embedding-3-small' : 'text-embedding-004'),
                chunkSize: options.chunkSize || 1000,
                chunkOverlap: options.chunkOverlap || 200,
            },
            llm: {
                provider: options.llmProvider || 'gemini',
                model: options.llmModel || (options.llmProvider === 'openai' ? 'gpt-4o-mini' : 'gemini-2.0-flash-exp'),
                temperature: 0.7,
            },
        };
        // Ensure bloom directory exists
        await ensureBloomDir(targetDir);
        // Save configuration
        await saveConfig(targetDir, config);
        console.log(chalk.green('✓ Configuration saved'));
        // Initialize vector store
        console.log(chalk.blue('Initializing vector database...'));
        const vectorStore = new VectorStoreManager(config);
        await vectorStore.initialize(targetDir);
        // Perform initial indexing
        console.log(chalk.blue('Scanning and indexing files...'));
        const indexer = new Indexer(config, vectorStore);
        const result = await indexer.index(targetDir);
        console.log(chalk.green(`✓ Indexed ${result.added.length} files with ${result.totalChunks} chunks`));
        // Save metadata
        const metadata = {
            indexedAt: new Date().toISOString(),
            fileCount: result.added.length,
            totalChunks: result.totalChunks,
            dbSize: 'N/A', // Would need to calculate actual size
        };
        await saveMetadata(targetDir, metadata);
        console.log(chalk.green('\n✨ Initialization complete!'));
        console.log(chalk.gray(`\nYou can now search this directory with:`));
        console.log(chalk.white(`  npx @masuidrive/bloom-local-rag query "your search query"`));
    }
    catch (error) {
        console.error(chalk.red('Error during initialization:'), error);
        process.exit(1);
    }
}
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