{"repo":"louisbrulenaudet/ragoon","free":true,"listed":false,"github":"https://github.com/louisbrulenaudet/ragoon","clone":"git clone https://github.com/louisbrulenaudet/ragoon.git","description":"High level library for batched embeddings generation, blazingly-fast web-based RAG and quantized indexes processing ⚡","language":"Jupyter Notebook","stars":70,"topics":["ai","generative-ai","groq","groqapi","llama","llama-index","rag","retrieval-augmented-generation","vector-database","embeddings"],"license":"Apache-2.0","category":"ai-agents","readme_excerpt":"RAGoon : High level library for batched embeddings generation, blazingly-fast web-based RAG and quantized indexes processing ⚡ RAGoon is a set of NLP utilities for multi-model embedding production, high-dimensional vector visualization, and aims to improve language model performance by providing contextually relevant information through search-based querying, web scraping and data augmentation techniques. Quick install The reference page for RAGoon is available on the official page of PyPI: RAGoon. Usage This section provides an overview of different code blocks that can be executed with RAGoon to enhance your NLP and language model projects. Embeddings production This class handles loading a dataset from Hugging Face, processing it to add embeddings using specified models, and provides methods to save and upload the processed dataset. You can also embed a single text using multiple models: Similarity search and index creation The SimilaritySearch class is instantiated with specific parameters to configure the embedding model and search infrastructure. The chosen model, louisbrulenaudet/tsdae-lemone-mbert-base , is likely a multilingual BERT model fine-tuned with TSDAE (Transfomer-based Denoising Auto-Encoder) on a custom dataset. This model choice suggests a focus on multilingual capabilities and improved semantic representations. The cuda device specification leverages GPU acceleration, crucial for efficient processing of large datasets. The embedding dimension of 768 is ty","default_branch":null,"files":null,"tree":[],"storefront":"/r/louisbrulenaudet","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/louisbrulenaudet/ragoon/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}