Fast, Accurate, Lightweight Python library to make State of the Art Embedding
- embeddings
- openai
- rag
- retrieval
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Fast, Accurate, Lightweight Python library to make State of the Art Embedding
AI Search & RAG Without Moving Your Data. Get instant answers from your company's knowledge across 100+ apps while keeping data secure. Deploy in minutes, not months.
The code used to train and run inference with the ColVision models, e.g. ColPali, ColQwen2, and ColSmol.
All-in-one platform for search, recommendations, RAG, and analytics offered via API
[ACL2026] "MiniRAG: Making RAG Simpler with Small and Open-Sourced Language Models"
NVIDIA AI Blueprint for video search and summarization (VSS) is a GPU-accelerated reference architecture for building video analytics agents with real-time verified alerts, visual Q&A, and automated reporting. The VSS Blueprint uses vision language models (VLMs) such as NVIDIA Cosmos, LLMs such as NVIDIA Nemotron, RAG, and NVIDIA NIMs.
WFGY is heading toward WFGY 5.0 Polaris Protocol, a major open-source release for AI reasoning, RAG, agents, and real-world workflows. Includes Problem Map, Global Debug Card, WFGY 4.0, and the CFV Easter Egg.
The official implementation of RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval
This repository includes the official implementation of OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs.
This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
Cache-Augmented Generation: A Simple, Efficient Alternative to RAG
A toolkit to create optimal Production-readyRetrieval Augmented Generation(RAG) setup for your data
List of software that allows searching the web with the assistance of AI: https://hf.co/spaces/felladrin/awesome-ai-web-search
OctoTools: An agentic framework with extensible tools for complex reasoning
Comprehensive guide to learn RAG from basics to advanced.
😎 Awesome list of Retrieval-Augmented Generation (RAG) applications in Generative AI.
A code repository indexing tool to supercharge your LLM experience.
Ontology-Augmented Generation for AI agents.
RAG over GitHub issues, with a hand-reviewed eval set and an audit of the judge itself. Reports the interval, not just the best number.
LLM and agent evaluation for Java & Kotlin. Runs in JUnit and CI. Spring AI, LangChain4j, Koog, Embabel, and any LLM client.