Skip to content

Latest commit

 

History

History
39 lines (31 loc) · 2.55 KB

README.md

File metadata and controls

39 lines (31 loc) · 2.55 KB
Raw

Simple CLI Retrieval Augmented Generation Scanner

Aim of the project: A showcase of a RAG scanner written in Java and using Spring AI, which scans the targeted documents and you can ask questions to the LLM regarding the given documents.

Disclaimer

This tool is intended for educational and productivity purposes only. It is designed to assist users in managing and querying their own documents. Any illegal or unethical use of this software is strictly prohibited.

Requirements

  1. Java 21 installed on your device
  2. Docker
  3. An environment variable named GOOGLE_API_KEY and add your Google Gemini API key

Installation

  1. Navigate to the project directory
  2. Open CMD/Powershell/Terminal
  3. For Windows Run ./mvnw clean install, for Linux/Mac run ./mvn clean install

How to use:

  1. Run docker-compose up in your CMD/Powershell/Terminal
  2. Run the project using maven, on Windows: ./mvnw spring-boot:run, on Linux/Mac run ./mvn spring-boot:run.
  3. When the shell opens type collection-size 768 (for Gemini 768 is compatible).
  4. Place your files in a directory, copy the full path of the directory, and run something like this load /your/path, wait till the files are chunked and loaded to Qdrant vector database.
  5. Finally in the shell write ask "your question here" and that's it.

Notes

It's a simple project, needs a lot of improvements like:

  1. Improve chunking documents (Currently chunked by token size)
  2. Support more file types (Currently supports txt, HTML, JSON, MD, docx, ppt, pdf, and a lot more)
  3. Support other Chat models like GPT, Ollama, etc... (currently supports Gemini version gemini-1.5-flash-latest, the reason I decided to use Gemini is because it has a good free tier)
  4. Support to make it a standalone executable and a jar file, (Currently you can build it yourself and run it, it has no problem, but I will simplify it)
  5. Support other vector databases ( Currently supports Qdrant, to be honest, it's good enough)
  6. Support custom System Context and custom similar returned documents in DB (Default, for now, is 5.)

Rabbit hole

Don't try to retrieve an API key from older .git versions, it's a rabbit hole :)

Please create an Issue, if something is wrong I will look into it, and feel free to contribute to the project.