Automated Resume Customizer (ARC)

An intelligent system that tailors your resume to specific job applications by analyzing the job description and selecting the most relevant content from your base resume.

Overview

ARC creates customized resumes through a multi-step workflow:

1. Researches the company to enhance the job description with additional context
2. Selects relevant responsibility and accomplishment groups for each role in your resume
3. Constructs polished, targeted sentences that highlight your relevant experience
4. Reviews sentences for clarity, grammar, and readability
5. Reviews the overall content for relevance and narrative flow
6. Creates a tailored resume summary that aligns with the job requirements

Requirements

• Python 3.8+
• An OpenAI API key for core functionality
• A Perplexity API key (default) or Tavily API key for company research

Installation

1. Clone this repository:

   git clone https://github.com/openfinesse/arc.git
   cd arc

2. Install the required packages:

   pip install -r requirements.txt

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

   OPENAI_API_KEY=your_openai_api_key
   PERPLEXITY_API_KEY=your_perplexity_api_key
   # Or alternatively:
   # TAVILY_API_KEY=your_tavily_api_key
   # RESEARCH_API_PROVIDER=tavily
   

   Additional configuration options:

   # Control how long company research is cached (in days)
   # COMPANY_CACHE_DAYS=30
   

Company Research Caching

ARC now automatically caches company research results to improve performance and reduce API usage. When you run ARC for a job at a specific company, the system will:

1. First check if research for this company already exists in the cache
2. Use the cached research if it's available and not expired
3. Perform new research only when necessary and cache the results

This caching mechanism helps you:

• Save on API costs when applying to multiple positions at the same company
• Speed up the customization process for repeat applications
• Reduce unnecessary API calls

The cache is stored in the cache/company_research directory. By default, cached research expires after 30 days, but you can adjust this by setting the COMPANY_CACHE_DAYS environment variable.

Preparing Your Resume

ARC uses a modular YAML format for your base resume, which allows the system to mix and match content effectively. You have two options:

1. Create a resume.yaml file manually following the structure in the example files
2. Let ARC create one for you by running the system without specifying a resume file

For the second option, ARC will run a modularization process to create a structured YAML file from your inputs.

Usage

Run ARC with a job description to create a customized resume:

python -m src.main --job-description path/to/job_description.txt --output path/to/output/resume.md

For a specific resume file:

python -m src.main --resume path/to/your/resume.yaml --job-description path/to/job_description.txt --output path/to/output/resume.md

Command Line Arguments

• --job-description: Path to the job description text file (required)
• --output: Path to save the customized resume (required)
• --resume: Path to your resume YAML file (optional, defaults to input/resume.yaml)
• --skip-modularizer: Skip checking for and creating a modular resume (optional)
• --clear-company-cache: Clear all cached company research data (optional)
• --list-cached-companies: List all companies in the research cache (optional)

Managing Company Research Cache

You can manage the company research cache using the following commands:

# List all companies in the cache
python -m src.main --list-cached-companies

# Clear the entire company research cache
python -m src.main --clear-company-cache

Resume YAML Format

Your resume should follow this structure:

basics:
  name: "Your Name"
  email: "[email protected]"
  # Other personal details
  
work:
  - title_variables:
      - "Job Title"
      - "Alternative Title"
    start_date: "Jan 2020"
    end_date: "Present"
    company: "Company Name"
    location: "City, State"
    responsibilities_and_accomplishments:
      group_1:
        modular_sentence: "Accomplished {X} by doing {Y} which resulted in {Z}"
        variables:
          X:
            - "option 1 for X" 
            - "option 2 for X"
          Y:
            - "option 1 for Y"
            - "option 2 for Y"
          Z:
            - "option 1 for Z"
            - "option 2 for Z"
      # More groups...
  # More work experiences...

See input/resume_example.yaml for a complete example.

Output

ARC generates a customized resume in Markdown format, which you can:

• Convert to PDF using tools like Pandoc
• Import into word processors
• Use with Markdown-based resume templates

The output includes a tailored professional summary and selectively highlighted experience based on the job requirements.