ATScribe - AI Powered ATS compatible resume generator

ATScribe is a command line tool that uses AI to generate ATS (Applicant Tracking System) compatible resumes. It leverages the power of LLM to create resumes that are optimized for ATS systems, ensuring that your resume gets noticed by recruiters and hiring managers.

Features🚀

• AI Powered ATS compatible resume generator.
• Supports both Gemini and Ollama

Technology Stack🚀

• Python 3.13
• uv package management
• Langchain for LLM and vector store integration
• Gemini AI for llm inference
• Ollama for running models locally

How it works🚀

• Create your existing resume in PDF format.
• Create the job description in PDF format.
• Run the CLI tool and provide the paths to your resume and job description PDFs.

Installation🚀

• Install the uv package manager: https://docs.astral.sh/uv/getting-started/installation/
• Download the whl binary from the releases page
• Add environment variables to your .bashrc or .zshrc file or equivalent shell configuration file:

GOOGLE_API_KEY: Your Google API key, required if `USE_OLLAMA` is set to false.
USE_OLLAMA: Set to `true` if you want to use Ollama, otherwise set to `false`.
MODEL_NAME: The name of the model you want to use (e.g., `gemini-2.0-flash`).

• Set up a virtual environment using uv or python3:

uv venv --python 3.13 # Or simply 'uv venv' if it uses a Python >=3.13 interpreter
OR
python3 -m venv .venv # Ensure your python3 is version 3.13+

• Add the virtual environment to your .bashrc or .zshrc or equivalent shell configuration file:

source .venv/bin/activate

• Install the package using pip:

uv pip install atscribe-0.1.0-py3-none-any.whl

• Run the CLI tool:

atscribe path/to/resume.pdf path/to/job_description.pdf

OR

To install globally, do the following steps:

• Clone the repository
• Add the following to your .bashrc, .zshrc, or equivalent shell configuration file, then source it (e.g., source ~/.bashrc) or open a new terminal session:

# Replace /PATH_TO_YOUR_CLONED_ATSCRIBE_REPO/ with the actual path to the repository
export PATH=/PATH_TO_YOUR_CLONED_ATSCRIBE_REPO/bin/:$PATH

AND set environment variables in the same file:

GOOGLE_API_KEY: Your Google API key, required if `USE_OLLAMA` is set to false.
USE_OLLAMA: Set to `true` if you want to use Ollama, otherwise set to `false`.
MODEL_NAME: The name of the model you want to use (e.g., `gemini-2.0-flash`).

• Run atscribe from the command line:

atscribe path/to/resume.pdf path/to/job_description.pdf

OR

• Clone the repository
• Setup .env file:

cp .env.example .env

• Edit the .env file to configure the following environment variables:

  • GOOGLE_API_KEY: Your Google API key, required if USE_OLLAMA is set to false.
  • USE_OLLAMA: Set to true if you want to use Ollama, otherwise set to false.
  • MODEL_NAME: The name of the model you want to use (e.g., gemini-2.0-flash).

• Install the uv package manager: https://docs.astral.sh/uv/getting-started/installation/

• Install the package using uv:

uv sync

• Run the CLI tool:

bin/atscribe path/to/resume.pdf path/to/job_description.pdf

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References🚀

• Python 3.13 Documentation
• Langchain Documentation
• Gemini AI Documentation
• uv Documentation