Alternatives

Products that do what Rag Framework does

A scalable centralized embeddings platform for efficient embedding and retrieval to build RAG applications faster

1WC
We cut RAG latency ~2× by switching embedding model▲27
Nov 2025 · myclone.is
2WA
Wikipedia2Vec – A tool for learning embeddings of words and entities▲105
2018 · wikipedia2vec.github.io
3AU
A Unified Embed API▲11
2014 · embedkit.com
4ET
[Embedditor] - the Open-source Microsoft Word for Vector Embeddings▲7
2023 · github.com
5DA
Demystifying Advanced RAG Pipelines▲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:…
2023 · github.com
6ML
Model2vec – Lightning-fast Static Embeddings for RAG/Semantic Search▲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…
2024 · github.com
7EA
Embeddinghub: A vector database built for Machine Learning embeddings▲118
2021 · github.com
8IM
I'm building an API that allows you to train semantic search for RAGs▲6
When your embedding provider is good, but could be better for your use-case.
2024 · zoplabs.com
9SF
Supabase for Embeddings▲9
2023 · github.com
10RA
RAG App Example with Self-hosted Embedding and LLM Services▲5
2024 · github.com
11BS
Blabr – Scientific Computing for the Web▲106
2015 · blabr.io
12SA
SimilaritySearchKit – A package for local text embeddings with CoreML▲7
2023 · github.com
13EA
EmbedBox, an Open-Source UI to Get Your Embed Code Installed▲75
2016 · embedbox.io
14AF
A file-based agent memory framework that works like skill▲11
Hi HN, We’ve been building [memU](https://github.com/NevaMind-AI/memU), an open-source memory framework for AI agents that supports both classic RAG and LLM-based direct file reading. RAG has become the default in LLM systems, but many of its failures don’t come from the model — they come from the retrieval assumptions. Embedding-based retrieval is fundamentally an approximation over semantic similarity. It works well for fuzzy recall, but it often breaks when relevance ≠ correctness, which is common in real systems. From a retrieval perspective, RAG struggles with: -…
Jan 2026 · github.com
15PF
Playground for comparing embedding models on Wikipedia+book retrieval▲5
Introducing embeds.ai: an embedding playground to compare how embedding models work on a real world use case (retrieval augmented generation for Wikipedia articles + Elad Gil's High growth handbook) A few weeks ago, Shreyan and I were looking for an embedding model to use for RAG. We eventually came across the MTEB leaderboard, but we struggled to understand the benchmark scores. We wanted a tool to test various embedding models with example queries on real-world datasets. After unsuccessfully looking for such a “playground”, we decided to just build one ourselves! We embedded HuggingFace’s…
2023 · embeds.ai
16LS
Local Search Agent – RAG replacement, no embeddings, free tier▲5
Jul 2026 · github.com
17SV
Superlinked – Vector Embeddings for Structured and Unstructured Data▲7
Hi HN, I'm Daniel from Superlinked! We have built an open-source framework that improves vector search relevance and usefulness by combining structured metadata with unstructured data in your embeddings. We included self-hostable API server that sits between your data sources and vector database. Docs: https://docs.superlinked.com/ We're launching our cloud offering soon where you can use Superlinked to orchestrate high-performance retrieval for RAG, Search & Recommendation apps in your own cloud. Looking for feedback and happy to answer questions!
2024 · github.com
18AE
APIembed - Embeddable API Code Snippets in Multiple Languages▲14
2015 · apiembed.com
19VV
Veml – Vector Embedding Markup Language▲8
2023 · github.com
20LA
Lark, a modern parsing library with Earley and LALR(1) implementations▲15
2017 · github.com
21MM
Multi-modal RAG with ColQwen in a single line of Code▲5
Hi HN, we're Arnav and Adi, and we're building DataBridge - a multi-modal database built from the ground up with AI use cases in mind. We recently launched support for ColPali-style image embeddings and late-interaction retrieval. We've implemented a hamming distance version of retrieval which helps this approach scale significantly more when compared with the regular late-interaction similarity scoring. These embeddings provide a significantly better retrieval accuracy, with ColQwen achieving around an 89% average score on the ViDoRe benchmark, compared to around 67% for traditional parsing…
2025 · github.com
22AE
An Embedding-Based Search Service over ShowHN, AskHN, GitHub, More▲7
Hey folks, Elias here. Excited to unveil my latest project. Why I Built This: Traditional keyword search isn't cutting it. I've used LLM-embeddings to provide more nuanced, relevant results. How It Works: LLM-embedding similarity on curated datasets for semantically similar results. No need to iterate over keywords any more. Current Datasets: - YC Companies - Show HN Posts, - Ask HN Posts - ProductHunt Startups - Github Top 200k Repos Use Cases: - Validate a product idea's existence - Check if someone already Asked HN something - Have fun - search random terms and see what pops up Want to…
2023 · payperrun.com
23SQ
SatoriDB – Query 1B vectors on a laptop (SQLite for embeddings, Rust)▲5
Dec 2025 · github.com
24CY
Can you think like a word vector? A game for exploring word embeddings▲8
2018 · robotmindmeld.com

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