milvus

18 projetos partilham este topic do GitHub

Linhas conectam membros que estão mensuravelmente relacionados entre si. O tamanho do ponto reflete estrelas.

🧬 Membros

Langchain-Chatchat

Langchain-Chatchat（原Langchain-ChatGLM）基于 Langchain 与 ChatGLM, Qwen 与 Llama 等语言模型的…

★ 38.6k

langchain4j

LangChain4j is an idiomatic, open-source Java library for building LLM-powered applications on the JVM. It…

★ 13k

all-in-rag

🔍大模型应用开发实战一：RAG 技术全栈指南，在线阅读地址：https://datawhalechina.gith…

★ 10.7k

deep-searcher

Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.

★ 8.2k

GPTCache

Semantic cache for LLMs. Fully integrated with LangChain and llama_index.

★ 8.2k

Yuxi

可私有部署的多租户知识智能体平台：统一 RAG、知识图谱、多智能体、MCP/Skills、沙…

★ 6.6k

towhee

Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

★ 3.5k

attu

The Best GUI for Milvus

★ 3k

memsearch

A persistent, unified memory layer for all your AI agents (e.g. Claude Code, Codex, DSH), backed by Markdown…

★ 2.5k

bootcamp

Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video…

★ 2.4k

pymilvus

Python SDK for Milvus Vector Database

★ 1.4k

EnterpriseAgentFramework

ReachAI企业级智能体开发平台：快速、安全完成已有业务系统智能化改造，让 AI 在…

★ 629

stashbase

Turn local files into searchable context for AI agents.

★ 505

vector-graph-rag

Graph RAG with pure vector search, achieving SOTA performance in multi-hop reasoning scenarios.

★ 244

RustyRAG

Production-grade RAG API built in Rust. Hybrid search with HNSW dense vectors and BM25 sparse matching,…

★ 152

mfs

A context harness for AI agents: all your scattered context — code, memory, docs, databases, SaaS — in…

★ 133

Educational_RAG_System

End-to-end educational RAG system: dual-engine retrieval (BM25 + BGE-M3 hybrid vector search), adaptive query…

★ 126

ai-agent-platform

企业级 AI Agent 平台 | Spring Boot 3 + LangChain4j | ReAct 推理 + 多路召回 RAG + 语义缓存 +…

★ 114

Medido a partir dos tópicos do GitHub compartilhados por ambos os projetos, ponderado pela raridade de cada tópico.