Beyond-Naive-RAG--Practical-Advanced-Methods.pdf
RAG
Introducing langchain-azure-storage: Azure Storage integrations for LangChain | Microsoft Community Hub
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 accuracy fix for RAG’s blind spots
AI21 Maestro’s Structured RAG fixes RAG’s accuracy gaps with hybrid retrieval—delivering reliable, auditable answers for enterprise compliance and reporting.
cohere-developer-experience/notebooks/guides/embed-v4-pdf-search/embed-v4-pdf-search.ipynb at main · cohere-ai/cohere-developer-experience
Docs, Snippets, Guides. Contribute to cohere-ai/cohere-developer-experience development by creating an account on GitHub.
A Guide on 12 Tuning Strategies for Production-Ready RAG Applications
Strategies and parameters you can tune to improve the performance of Retrieval-Augmented Generation (RAG) applications for production.
RAG is dead, long live agentic retrieval — LlamaIndex - Build Knowledge Assistants over your Enterprise Data
LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.
Semantic Chunking for RAG: Better Context, Better Results
Explore how semantic chunking enhances RAG systems by improving context, precision, and performance through optimized chunking strategies and advanced tools.
NirDiamant/RAG_Techniques: This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and contextually rich responses.
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...
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The 2025 Guide to Retrieval-Augmented Generation (RAG)
Explore the top Retrieval-Augmented Generation (RAG) techniques of 2025, including Traditional RAG, Long RAG, Self-RAG, and more.
athina-ai/rag-cookbooks: This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems. - athina-ai/rag-cookbooks
Relevance Feedback in Informational Retrieval
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
RAG from Scratch
Contribute to labdmitriy/llm-rag development by creating an account on GitHub.
Introducing the Weaviate Query Agent | Weaviate
Learn about the Query Agent, our new agentic search service that redefines how you interact with Weaviate’s database!
VectifyAI/PageIndex: Document Index System for Reasoning-Based RAG
Document Index System for Reasoning-Based RAG
Building Your Own RAG System: Enhancing Claude with Your Documentation
Connecting Claude Desktop to Your Documentation Through MCP and Qdrant
RAG with Streaming
Design and Develop a RAG Solution - Azure Architecture Center
How to plan a RAG project
Evaluating Chunking Strategies for Retrieval | Chroma Research
recipes/weaviate-features/generative-search/generative_search_anthropic/rag_with_anthropic_citations.ipynb at main · weaviate/recipes
This repository shares end-to-end notebooks on how to use various Weaviate features and integrations! - weaviate/recipes
Open source: it works!
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)
The recipes repo is such an underrated developer resource.
Here are 8 notebooks you should know about:
1. Vanilla vector search:
2. Image similarity search:
3. Hybrid search:
4. Local RAG…
— Leonie (@helloiamleonie)
Advanced RAG Techniques ebook
GitHub - bRAGAI/bRAG-langchain: Everything you need to know to build your own RAG application
Everything you need to know to build your own RAG application - bRAGAI/bRAG-langchain
QueryGPT - Natural Language to SQL using Generative AI | Uber Blog
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.
Agentic RAG with VoyageAI, Gemini and LangGraph
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.
RAG Context Refinement Agent — LlamaIndex - Build Knowledge Assistants over your Enterprise Data
LlamaIndex is a simple, flexible framework for building knowledge assistants using LLMs connected to your enterprise data.
Building Blocks of LLM Report Generation: Beyond Basic RAG — LlamaIndex, Data Framework for LLM Applications
LlamaIndex is a simple, flexible data framework for connecting custom data sources to large language models (LLMs).
LlamaIndex on LinkedIn: We’re publishing 2 full-length tutorial videos showing you how to… | 12 comments
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
Building an Advanced RAG System With Self-Querying Retrieval | MongoDB
It’s related to BundesFlow.
RAG Developer Attention! 🔔 Docling is a new library from that efficiently parses PDF, DOCX, and PPTX and exports them to Markdown and JSON. It supports advanced PDF understanding and seamless integration with and .
TL;DR:
🗂️ Parses numerous…
— Philipp Schmid (@_philschmid)