Resume Parser API

API that accepts PDF or DOCX resumes converts them to text and uses OpenRouter API to extract structured information.

Used by Resume Yay | Free AI Resume Builder

Why

Resume parsing is expensive and requires monthly fees. For low volume, it can cost around $0.10 per resume. Using this API, the cost is at least 100x cheaper with no monthly commitment.

Limitations

As it is LLM-based, results might be inconsistent or missing some info; use with caution.

The parsing time is longer than the traditional resume parser, based on resume length, model TPS (Tokens Per Second), and model load.

Setup

1. Create a virtual environment and activate it:

python -m venv venv
source venv/bin/activate

2. Install dependencies:

pip install -r requirements.txt

3. Create a .env file in the root directory with your OpenRouter API key:

OPENROUTER_API_KEY=your_api_key_here

Usage

1. Start the server:

python app.py

2. Send a POST request to /parse endpoint with a resume file:

curl -X POST -F "file=@path/to/resume.pdf" http://localhost:5000/parse

The API accepts both PDF and DOCX files and returns a structured JSON response containing the parsed resume information.

Response Format

The API returns a JSON object based on the schema in the config.yml file. The default one would return the following structure:

• basics (name, contact info, location, etc.)
• work experience
• education
• skills
• languages
• interests
• certifications
• awards
• publications
• projects
• volunteer work
• references
• custom sections
• metadata

Error Handling

The API returns appropriate error messages for:

• Missing files
• Invalid file types
• File processing errors
• AI processing errors

File Size Limit

The maximum file size is 16MB. It can be changed from the config.yml file.