gitresume 0.1.0

Generate professional resumes from your GitHub repositories.

🚀 GitResume

Transform your GitHub repositories into professional, ATS-optimized resumes using AI.

GitResume is a CLI tool that analyzes your local or remote repositories, extracts technical achievements, and generates impactful resume bullet points, tech stack summaries, and interview preparation materials.

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✨ Features

• 🔍 Deep Analysis: Uses Tree-sitter to parse your code and understand the actual technical complexity.
• 🤖 Multi-LLM Support: Integrates with Gemini, OpenAI, Anthropic, and Groq via LiteLLM.
• 📄 Multiple Formats: Generates resumes in Markdown and structured JSON.
• 💻 Local-First: No need to upload your code to a 3rd party service. Analysis happens on your machine.
• 📊 Web Dashboard: View your generated resumes and analysis history in a beautiful local web interface.
• 🎯 Job Tailoring: Provide a job description to generate targeted achievements.

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🚀 Quick Start

Installation

Choose your preferred installation method:

1. Via uv (Recommended)

uv tool install gitresume

2. Via pip

pip install gitresume

3. Via Docker

docker pull whoisjayd/gitresume

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📖 Usage

1. Analyze a Repository

Point GitResume at any local folder or clone a remote repo to create an analysis artifact.

# Local
gitresume analyze ./my-awesome-project

# Docker
docker run -v $(pwd):/app/data -e GEMINI_API_KEY=$GEMINI_API_KEY whoisjayd/gitresume analyze /app/data/my-project

2. Generate a Resume

Use the analysis to generate a polished resume. You can optionally provide a job description for better targeting.

gitresume generate ./artifacts/my-awesome-project-run-id --jd "Senior Backend Engineer at Google"

3. View in Dashboard

Start the local dashboard to browse your artifacts and view your resumes.

gitresume web

4. Bulk Processing

Process multiple repositories at once using a text file, JSON, or CSV containing paths or URLs.

# Analyze multiple repos in parallel
gitresume bulk repos.txt --mode analyze --concurrency 10

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🔧 Configuration

GitResume uses environment variables for API keys. You can set them in your shell or use an .env or env.yaml file.

See the Configuration Guide for a full list of environment variables.

Variable	Description
GEMINI_API_KEY	Required for Gemini models (Default)
OPENAI_API_KEY	Required for OpenAI models
ANTHROPIC_API_KEY	Required for Claude models
GITRESUME_MODEL	Model string (e.g., gemini/gemini-1.5-flash)

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🏗 CLI Reference

For detailed command usage, see the CLI Reference.

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📄 Documentation

• Installation & Setup
• Configuration Guide
• Security & Data Handling
• Release Process

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🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

📜 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Created with ❤ by Jaydeep Solanki.