Skip to main content

Generate professional resumes from your GitHub repositories.

Project description

🚀 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.

GitResume CLI Demo

(Placeholder for Rich UI Screenshot)

PyPI version Python License: MIT Build Status Docker Image Version GitHub Issues


✨ 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.

🚀 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

📖 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

🔧 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)

🏗 CLI Reference

For detailed command usage, see the CLI Reference.


📄 Documentation


🤝 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.


Created with ❤ by Jaydeep Solanki.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

gitresume-0.0.1.tar.gz (256.8 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

gitresume-0.0.1-py3-none-any.whl (36.6 kB view details)

Uploaded Python 3

File details

Details for the file gitresume-0.0.1.tar.gz.

File metadata

  • Download URL: gitresume-0.0.1.tar.gz
  • Upload date:
  • Size: 256.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for gitresume-0.0.1.tar.gz
Algorithm Hash digest
SHA256 1a23973e1807f0072aacfe5f2662be92918a010a16d4f4dd6a5cc9314f719498
MD5 5dca7a06680dc15037e75281702be152
BLAKE2b-256 818b3107ddfca3e08dbe5854a22c1f20c74c175ff6b0502df49dc2d92d0e7fd0

See more details on using hashes here.

File details

Details for the file gitresume-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: gitresume-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 36.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for gitresume-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 c994365bd4bc754a04c34066cce3ecd290cde58c5f69b52368e71d2970189bf3
MD5 b8a9c9488929ca986f667ccf0aef9b05
BLAKE2b-256 aa88d289d319123668a6accea5c8cb6b0e86fd69cf85d382e28299f941fc3a2c

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page