ai-resume-parser 1.0.4

AI-powered resume parser with parallel processing for multiple file formats (PDF, DOCX, images, etc.)

ResumeParser Pro 🚀

Production-ready AI-powered resume parser with parallel processing capabilities. Extract structured data from resumes in PDF, DOCX, TXT, images, and more, using state-of-the-art language models.

🌟 Features

• 🤖 AI-Powered: Uses advanced language models (GPT, Gemini, Claude, etc.).
• ⚡ Parallel Processing: Process multiple resumes simultaneously.
• 📊 Structured Output: Returns clean, validated JSON data.
• 🎯 High Accuracy: Extracts 20+ fields with intelligent categorization.
• 📁 Multi-Format Support: Parses PDFs, DOCX, TXT, images (PNG, JPG), HTML, and ODT files.
• 🔌 Easy Integration: Simple API with just a few lines of code.

🚀 Quick Start

Installation

Core installation (for PDF, DOCX, TXT) pip install ai-resume-parser

To include support for all file types pip install ai-resume-parser[full]

See the "Supported File Formats" section for installing specific file handlers.

Basic Usage

from resumeparser_pro import ResumeParserPro

Initialize parser parser = ResumeParserPro( provider="google_genai", model_name="gemini-2.0-flash", api_key="your-api-key" )

Parse single resume (supports .pdf, .docx, .png, etc.) result = parser.parse_resume("path/to/your/resume.pdf")

if result.success: print(f"Name: {result.resume_data.contact_info.full_name}") print(f"Experience: {result.resume_data.total_experience_months} months")

📁 Supported File Formats

ResumeParser Pro supports a wide range of file formats. Core dependencies handle PDF, DOCX, and TXT. For other formats, install the optional extras.

Format	Extensions	Required Installation Command
Core Formats	.pdf, .docx, .txt	pip install ai-resume-parser
Images (OCR)	.png, .jpg, .jpeg	pip install ai-resume-parser[ocr]
HTML	.html, .htm	pip install ai-resume-parser[html]
OpenDocument	.odt	pip install ai-resume-parser[odt]

❗️ Important Note for Image Parsing: To parse images, you must have the Google Tesseract OCR engine installed on your system. This is a separate step from the pip installation.

• Tesseract Installation Guide

🎯 Supported AI Providers

Since ai-resume-parser uses LangChain's init_chat_model, it supports all LangChain-compatible providers:

Provider	Example Models	Setup
Google	Gemini 2.0 Flash, Gemini Pro, Gemini 1.5	provider="google_genai"
OpenAI	GPT-4o, GPT-4o-mini, GPT-4 Turbo	provider="openai"
Anthropic	Claude 3.5 Sonnet, Claude 3 Opus	provider="anthropic"

... (and others like Azure, Bedrock, Ollama, etc.)

Full list: See LangChain Model Providers for complete provider support.

📈 Performance

• Speed: ~3-5 seconds per resume (depending on the LLM).
• Parallel Processing: 5-10x faster for batch operations.
• Accuracy: 95%+ field extraction accuracy.

🛠️ Advanced Features

Custom Configuration

parser = ResumeParserPro( provider="openai", model_name="gpt-4o-mini", api_key="your-api-key", max_workers=10, # Parallel processing workers temperature=0.1 # Model consistency )

🤝 Contributing

Contributions are welcome! Please read our contributing guidelines.

📄 License

MIT License - see LICENSE file for details.