Search results for "rag"
LLM-powered framework for deep document understanding, semantic retrieval, and context-aware answers using RAG paradigm.
Nornicdb is a low-latency, Graph + Vector, Temporal MVCC with all sub-ms HNSW search, graph traversal, and writes. Uses Neo4j Bolt/Cypher and qdrant's gRPC drivers so you can switch with no changes. T
A lightweight, embeddable vector database library for Go AI projects.
♾️ Private Agent Fleet with Spec Coding. Each agent gets their own GPU-accelerated desktop. Run Claude, Codex, Gemini and open models on a full private AI Stack ♾️
Get up and running with Kimi-K2.5, GLM-5, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models.
The Maestro App Factory: a highly-opinionated multi-agent orchestration tool for app development that emulates the workflow of high-functioning human development teams using AI agents
Open-source Agentic AI framework in Go for building, orchestrating, and deploying intelligent agents. LLM-agnostic, event-driven, with multi-agent workflows, MCP tool discovery, and production-grade o
Weaviate is an open-source vector database that stores both objects and vectors, allowing for the combination of vector search with structured filtering with the fault tolerance and scalability of a c
mkdir beats vector DB. B-tree NeuronFS: 0-byte folders govern AI — ₩0 infrastructure, ~200x token efficiency. OS-native constraint engine for LLM agents.
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
OasisDB: A minimal and lightweight vector database
The cognitive database. A new class of data storage. Not a vector store, not a graph DB, not a RAG wrapper. Ebbinghaus decay, Hebbian learning, and Bayesian confidence are engine-native primitives.
trpc-agent-go is a powerful Go framework for building intelligent agent systems using large language models (LLMs) and tools.
LocalAI is the open-source AI engine. Run any model - LLMs, vision, voice, image, video - on any hardware. No GPU required.
AI-native HTAP database with Git-for-Data and built-in vector search, serving as the data and memory backbone for intelligent agents and applications.
A minimal, lightweight structured data store designed for small applications, scripts and automation workflows. Built for simplicity, portability and low overhead.
A selective learning and memory substrate for agentic systems — typed, revisable, decayable memory with competence learning and trust-aware retrieval.
A Slack bot and MCP client acts as a bridge between Slack and Model Context Protocol (MCP) servers. Using Slack as the interface, it enables large language models (LLMs) to connect and interact with v