@thecodingwhale/cv-processor/dist/index_new.js

CV Processor to extract structured data from PDF resumes using TypeScript

#!/usr/bin/env node
"use strict";
/**
 * Optimized CV Processor CLI
 * Usage: npx cv-processor-ts input.pdf
 * Output: Creates output JSON file with extracted CV data
 */
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      desc = { enumerable: true, get: function() { return m[k]; } };
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}) : (function(o, m, k, k2) {
    if (k2 === undefined) k2 = k;
    o[k2] = m[k];
}));
var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
    Object.defineProperty(o, "default", { enumerable: true, value: v });
}) : function(o, v) {
    o["default"] = v;
});
var __importStar = (this && this.__importStar) || (function () {
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        __setModuleDefault(result, mod);
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})();
Object.defineProperty(exports, "__esModule", { value: true });
const commander_1 = require("commander");
const dotenv = __importStar(require("dotenv"));
const fs = __importStar(require("fs"));
const path = __importStar(require("path"));
const AICVProcessorX_1 = require("./AICVProcessorX");
const AIProviderFactory_1 = require("./ai/AIProviderFactory");
// Load environment variables
dotenv.config();
// CLI config
const program = new commander_1.Command();
program
    .name('cv-processor-ts')
    .description('Extract structured data from CV/resume PDF')
    .version('2.0.0')
    .argument('<pdf-file>', 'Path to the CV/resume PDF file')
    .option('-o, --output <file>', 'Output JSON file (defaults to output directory)')
    .option('-v, --verbose', 'Verbose output')
    .option('--use-ai [provider]', 'AI provider (openai, azure, gemini, etc.)', 'openai')
    .option('--ai-model <model>', 'AI model to use')
    .action(async (pdfFile, options) => {
    try {
        if (!fs.existsSync(pdfFile)) {
            console.error(`❌ Error: Input file not found: ${pdfFile}`);
            process.exit(1);
        }
        const outputDir = path.resolve(__dirname, '../output');
        if (!fs.existsSync(outputDir))
            fs.mkdirSync(outputDir);
        const outputFile = options.output ||
            `${path.basename(pdfFile, path.extname(pdfFile))}.json`;
        const outputPath = path.join(outputDir, outputFile);
        // const providerType = options.useAi as AIProviderType
        // console.log(`🧠 Using AI provider: ${providerType}`)
        // Use the default provider (based on CLI args or environment vars)
        const defaultProvider = process.env.DEFAULT_AI_PROVIDER || 'gemini';
        let apiProviderType = defaultProvider;
        // Get API key from environment variables
        const apiKeyEnvVar = apiProviderType === 'aws'
            ? 'AWS_ACCESS_KEY_ID'
            : `${apiProviderType.toUpperCase()}_API_KEY`;
        const apiKey = process.env[apiKeyEnvVar];
        if (!apiKey) {
            console.error(`Error: API key not found in environment variables (${apiKeyEnvVar})`);
            console.error('Please set it in your .env file or environment');
            throw new Error(`Missing API key for provider: ${apiProviderType}`);
        }
        // Configure AI provider
        let aiConfig = {
            apiKey,
            model: 'gemini',
        };
        const aiProvider = AIProviderFactory_1.AIProviderFactory.createProvider(apiProviderType, aiConfig);
        // const aiProvider = AIProviderFactory.createProvider('gemini', {
        //   model: options.aiModel,
        // })
        const processor = new AICVProcessorX_1.AICVProcessorX(aiProvider, options.verbose);
        const start = Date.now();
        const cvData = await processor.processCv(pdfFile);
        const duration = (Date.now() - start) / 1000;
        console.log(`✅ Processing completed in ${duration.toFixed(2)} seconds`);
        fs.writeFileSync(outputPath, JSON.stringify(cvData, null, 2));
        console.log(`💾 Saved output to ${outputPath}`);
    }
    catch (err) {
        console.error(`❌ Failed to process CV: ${err.message}`);
        process.exit(1);
    }
});
program.parse(process.argv);