Tag: #embeddings
36 packages • ⭐ 48,162 total stars
LLM-powered framework for deep document understanding, semantic retrieval, and context-aware answers using RAG paradigm.
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
LangChain4j is an open-source Java library that simplifies the integration of LLMs into Java applications through a unified API, providing access to popular LLMs and vector databases. It makes impleme
AutoRAG: An Open-Source Framework for Retrieval-Augmented Generation (RAG) Evaluation & Optimization with AutoML-Style Automation
Memory library for building stateful agents
A Markdown-first memory system, a standalone library for any AI agent. Inspired by OpenClaw.
RESTai is an AIaaS (AI as a Service) open-source platform. Supports many public and local LLM suported by Ollama/vLLM/etc. Precise embeddings usage, tuning, analytics etc. Built-in image/audio generat
Cognitive memory for AI agents — FSRS-6 spaced repetition, 29 brain modules, 3D dashboard, single 22MB Rust binary. MCP server for Claude, Cursor, VS Code, Xcode, JetBrains.
MAGI: Markdown for Agent Guidance & Instruction - A next-generation markdown extension designed specifically for AI systems. MAGI enhances standard markdown with structured metadata, embedded AI instr
Turn AI into a persistent, memory-powered collaborator. Universal MCP Server (supports HTTP, STDIO, and WebSocket) enabling cross-platform AI memory, multi-agent coordination, and context sharing. Bui
A modern desktop application for exploring, managing, and analyzing vector databases
The Go client for Chroma vector database
The AI Operating System for Delphi. 100% native framework with RAG 2.0 for knowledge retrieval, autonomous agents with semantic memory, visual workflow orchestration, and universal LLM connector. Supp
Persistent project knowledge graph for coding agents. MCP server with semantic search, in-process embeddings, and web explorer.
On-device context engine and memory for AI agents. Claude Code, Hermes and OpenClaw. Hooks + MCP server + hybrid RAG search.
Build, deploy, and orchestrate event-driven agents natively on Apache Flink® and Apache Kafka®
A lightweight, embeddable vector database library for Go AI projects.
MCP server for semantic search using local Qdrant vector database and OpenAI embeddings
The memory system your AI agent deserves. 4-stage hybrid retrieval — Vector + BM25 + Knowledge Graph + Neural Reranker — in <150ms. Self-hosted, $0/query, built for agents that need to actually rememb
AI-first, zero-dependency JavaScript database. Vector search, agent memory, MCP server, and encryption built in. Node.js, Bun, Deno, browsers, and edge runtimes.
Universal memory layer for AI applications. Self-host in minutes. Open source.
A lock-free, in-memory fuzzy search engine for Kotlin Multiplatform. L2-normalized sparse vector embeddings with O(1) cosine similarity — handles typos, transpositions, and blind continuation. Zero-al
The highest-scoring AI memory system ever benchmarked that isn't reliant on LLM reranking. And it's free & burns less tokens.
🧠 Transform documentation chaos into a structured memory system with Mnemos, your self-hosted, multi-context knowledge server for developers.
🛒 Build a leading-edge e-commerce recommendation system using RAG architecture, Groq Llama 3, LangChain, and AstraDB, deployed on Kubernetes for scalability.
🧠 Enhance AI conversations with Cognio, a persistent memory server that retains context and enables meaningful semantic search across sessions.
Self-hostable RAG platform - document ingestion, embedding, and vector search behind a simple REST API
🤖 Recommend TV shows by matching favorites, averaging embeddings, and finding similar titles using fuzzy search and vector similarity.
🛠️ Master 27 AI Agent Skills for effective semantic code search with GrepAI, enhancing installation, configuration, and integration.
🚀 Build memory and retrieval infrastructure for ReasonKit, enhancing data management and access for your applications with ease and efficiency.
🧠 Capture and manage your team's knowledge effortlessly with Eywa, ensuring no valuable memory is ever lost.
🚀 Enhance retrieval with REFRAG, using micro-chunking and fast indexing for optimized RAG systems that improve efficiency and effectiveness.
No description
No description
Detect physical hits on your laptop and play audio responses using sensors in a lightweight, cross-platform binary.
Build semantic vector databases from code and docs to enable AI agents to understand and navigate your entire codebase effectively.