Tagged "retrieval-augmented-generation"
6 articles tagged retrieval-augmented-generation, 16 February 2026 to 30 June 2026. Newest first.
-
Meet EverOS: An Open Source Markdown-First Agent Memory Runtime With Hybrid BM25 + Vector Retrieval
A new open-source framework provides markdown-based agent memory management with hybrid semantic and keyword search capabilities, enabling self-evolving AI agents that can run locally.
-
Agentic AI Community Focus: Building Local Agents in 2026
The emerging agentic AI community shares resources and frameworks for building autonomous agents with local LLM backends. Focus areas include memory systems, tool integration, and edge deployment of multi-step reasoning tasks.
-
Llama 8B Matches 70B Performance on Multi-Hop QA Using Structured Prompting
Structured prompting techniques with Graph RAG enable smaller Llama 8B models to match 70B model performance on complex multi-hop question answering without fine-tuning. Research reveals reasoning, not retrieval, is the actual bottleneck.
-
RAG vs. Skill vs. MCP vs. RLM: Comparing LLM Enhancement Patterns
A comparative analysis of four major architectural patterns for augmenting LLMs with external knowledge and capabilities, helping developers choose the right approach for their local deployment needs.
-
Building a Privacy-Preserving RAG System in the Browser
A guide for implementing retrieval-augmented generation entirely in the browser using local models, maintaining complete data privacy. Demonstrates advanced local LLM architectures running entirely client-side.
-
InitRunner: YAML-Based AI Agent Framework with RAG and Memory
InitRunner is a new open-source framework that lets developers define AI agents using simple YAML configuration, including support for RAG, memory management, and API endpoints.