Core

We're excited to introduce langchain-azure-storage, the first official Azure Storage integration package built by Microsoft for LangChain 1.0. As part...

AI21 Maestro’s Structured RAG fixes RAG’s accuracy gaps with hybrid retrieval—delivering reliable, auditable answers for enterprise compliance and reporting.

Strategies and parameters you can tune to improve the performance of Retrieval-Augmented Generation (RAG) applications for production.

LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.

Explore how semantic chunking enhances RAG systems by improving context, precision, and performance through optimized chunking strategies and advanced tools.

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont...

Explore the top Retrieval-Augmented Generation (RAG) techniques of 2025, including Traditional RAG, Long RAG, Self-RAG, and more.

Docs, Snippets, Guides. Contribute to cohere-ai/cohere-developer-experience development by creating an account on GitHub.

Relerance feedback: from ancient history to LLMs Why relevance feedback techniques are good on paper but not popular in neural search and what we can do about it

Contribute to labdmitriy/llm-rag development by creating an account on GitHub.

Learn about the Query Agent, our new agentic search service that redefines how you interact with Weaviate’s database!

Document Index System for Reasoning-Based RAG

Connecting Claude Desktop to Your Documentation Through MCP and Qdrant

This repository shares end-to-end notebooks on how to use various Weaviate features and integrations! - weaviate/recipes

Two months ago user durable-racoon posted about DocumentContextExtractor, their iteration on a technique for improving the accuracy of RAG that both and had made demo implementations of. Contextual Retrieval improves the… — LlamaIndex 🦙 (@llama_index)

Here are 8 notebooks you should know about: 1. Vanilla vector search: 2. Image similarity search: 3. Hybrid search: 4. Local RAG… — Leonie (@helloiamleonie)

This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems. - athina-ai/rag-cookbooks

Everything you need to know to build your own RAG application - bRAGAI/bRAG-langchain

Here’s a cheat sheet of 7 of the most popular RAG architectures. Which variants did we miss? — Weaviate • vector database (@weaviate_io)

Discover how QueryGPT revolutionizes SQL query generation at Uber! Learn about the cutting-edge AI that turns natural language prompts into efficient SQL queries, boosting productivity at Uber. Dive into our journey of innovation and transformation.

Learn to build an agentic RAG system with LangChain, MyScaleDB, VoyageAI, and Tavily for dynamic Q&A that adapts to real-time data and knowledge base searches.

LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.

LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models (LLMs).

We’re publishing 2 full-length tutorial videos showing you how to implement various agentic RAG techniques - adding LLM layers to reason over inputs and post… | 12 comments on LinkedIn