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VectorDB

6 articles · Page 1 of 1
Linyb Geek Road
Linyb Geek Road
Sep 2, 2026 · Artificial Intelligence

Where Does an Agent’s Long‑Term Memory Live? Update and Deletion Strategies Explained

The article explains why AI agents need a memory layer, categorizes memory into semantic, episodic and procedural types, describes a dual‑layer design of short‑term sliding‑window and long‑term vector‑database storage, and details practical management operations (ADD, UPDATE, DELETE, NOOP) with conflict detection, TTL expiration and privacy‑compliant deletion.

LLMLong-TermMem0
0 likes · 9 min read
Where Does an Agent’s Long‑Term Memory Live? Update and Deletion Strategies Explained
James' Growth Diary
James' Growth Diary
Apr 12, 2026 · Artificial Intelligence

Build a Complete Private Knowledge Base with RAG: A Hands‑On Guide

This article walks through a complete, production‑ready Retrieval‑Augmented Generation pipeline that lets AI answer a company’s private documents, covering chunking strategies, embedding model choices, vector‑database selection, retrieval methods, full LangChain chain assembly, and common pitfalls to avoid.

EmbeddingLangChainPromptEngineering
0 likes · 18 min read
Build a Complete Private Knowledge Base with RAG: A Hands‑On Guide
Tencent Cloud Developer
Tencent Cloud Developer
Mar 11, 2025 · Artificial Intelligence

Fine‑Tuning Local LLaMA‑Factory Models and Building Networked AI Applications

The article walks through preparing a GPU‑enabled environment, downloading and LoRA‑fine‑tuning a DeepSeek model with LLaMA‑Factory, merging the adapter, then wrapping the model in a web UI that queries a ChromaDB vector store via crawled web data, illustrating security‑focused use cases and forecasting domain‑specific LLM adoption.

AILLMLLaMA-Factory
0 likes · 17 min read
Fine‑Tuning Local LLaMA‑Factory Models and Building Networked AI Applications
System Architect Go
System Architect Go
Nov 19, 2024 · Artificial Intelligence

Retrieval Augmented Generation (RAG) System Overview and Implementation with LangChain, Redis, and llama.cpp

This article explains the concept, architecture, and step‑by‑step implementation of Retrieval Augmented Generation (RAG), covering indexing, retrieval & generation processes, a practical LangChain‑Redis‑llama.cpp example on Kubernetes, code snippets, test results, challenges, and references.

AIEmbeddingLLM
0 likes · 6 min read
Retrieval Augmented Generation (RAG) System Overview and Implementation with LangChain, Redis, and llama.cpp