Rago

Rago is a lightweight framework for RAG.

• Software License: BSD 3 Clause
• Documentation: https://osl-incubator.github.io/rago

Features

• Vector Database support
  • FAISS
• Retrieval features
  • Support pdf extraction via langchain
• Augmentation (Embedding + Vector Database Search)
  • Support for Sentence Transformer (Hugging Face)
  • Support for Open AI
  • Support for SpaCy
• Generation (LLM)
  • Support for Hugging Face
  • Support for llama (Huggin FAce)
  • Support for OpenAI
  • Support for Gemini

Installation

If you want to install it for cpu only, you can run:

$ pip install rago[cpu]

But, if you want to install it for gpu (cuda), you can run:

$ pip install rago[gpu]

Setup

Llama 3

In order to use a llama model, visit its page on huggingface and request your access in its form, for example: https://huggingface.co/meta-llama/Llama-3.2-1B.

After you are granted access to the desired model, you will be able to use it with Rago.

You will also need to provide a hugging face token in order to download the models locally, for example:

animals_data = [
    "The Blue Whale is the largest animal ever known to have existed, even "
    "bigger than the largest dinosaurs.",
    "The Peregrine Falcon is renowned as the fastest animal on the planet, "
    "capable of reaching speeds over 240 miles per hour.",
    "The Giant Panda is a bear species endemic to China, easily recognized by "
    "its distinctive black-and-white coat.",
    "The Cheetah is the world's fastest land animal, capable of sprinting at "
    "speeds up to 70 miles per hour in short bursts covering distances up to "
    "500 meters.",
    "The Komodo Dragon is the largest living species of lizard, found on "
    "several Indonesian islands, including its namesake, Komodo.",
]

rag = Rago(
    retrieval=StringRet(animals_data),
    augmented=SentenceTransformerAug(top_k=2),
    generation=LlamaGen(apikey=HF_TOKEN),
)
rag.prompt('What is the faster animal on Earth?')