Search Results for "personal knowledge"

...By recomputing embeddings during queries and using compact graph-based indexing structures, LEANN can maintain high search accuracy while minimizing disk usage. It aims to act as a unified personal knowledge layer that connects different types of data such as documents, code, images, and other local files into a searchable context for language models.

...Unlike monolithic systems where memory management is ad-hoc, SimpleMem formalizes a memory lifecycle—write, index, retrieve, refine—so applications can handle user history, document collections, or dynamic contextual state systematically. It supports customizable embedding models, efficient vector indexes, and relevance weighting, making it practical for building assistants, personal agents, or domain-specific retrieval systems that need persistent knowledge.

The chatgpt-retrieval-plugin repository implements a semantic retrieval backend that lets ChatGPT (or GPT-powered tools) access private or organizational documents in natural language by combining vector search, embedding models, and plugin infrastructure. It can serve as a custom GPT plugin or function-calling backend so that a chat session can “look up” relevant documents based on user queries, inject those results into context, and respond more knowledgeably about a private knowledge...