Rag Framework

What it does

🚀 Scale your RAG pipeline using Ragswift: A scalable centralized embeddings management platform - shivamsanju/ragswift

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  Demystifying Advanced RAG Pipelines2023 · github.com · ▲131

  I've built an advanced RAG (Retrieval-Augmented Generation) pipeline from scratch to demystify the complex mechanics of modern LLM-powered Question Answering systems. This repository features: -- An implementation of a sub-question query engine from scratch to answer complex user questions. -- Illustrative explanations that unveil the inner workings of the system. -- An analysis of the challenges I faced while working with the system, like prompt engineering and cost estimation. -- Qualitative comparison with similar frameworks like LlamaIndex, offering a broader perspective. Key Takeaway:…

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  Model2vec – Lightning-fast Static Embeddings for RAG/Semantic Search2024 · github.com · ▲28

  We’ve recently open-sourced Model2vec, a method to distill sentence transformers into static embeddings that outperform all previous approaches by a large margin on MTEB. Our new models set a new state-of-the-art for static embeddings. Main features: - Our best model (potion-base-8M) has only 8M parameters, which is ~30mb on disk - Inference is ~500x faster than the distilled base model (bge-base), on a CPU - New models can be distilled in 30 seconds on a CPU without requiring a dataset - just a vocabulary - Numpy-only inference: The packaged can be install the package with minimal…

• IM
  I'm building an API that allows you to train semantic search for RAGs2024 · zoplabs.com · ▲6

  When your embedding provider is good, but could be better for your use-case.

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  RAG App Example with Self-hosted Embedding and LLM Services2024 · github.com · ▲5
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  Embeddinghub2021 · github.com · ▲118

  An open-source database for machine learning

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  Embeddinghub: A vector database built for Machine Learning embeddings2021 · github.com · ▲118

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