zhengguanyu/KGB-RAG
KGB-RAG是一个基于neo4j图数据库和其他图数据库的知识图谱检索系统，它可以根据用户的自然语句提问，从原数据库获取相关实体信息，并通过知识图谱检索技术以及结合大模型自身能力来增强回答用户的自然语言提问。
This tool helps businesses, researchers, or anyone with large, interconnected datasets to get quick, accurate answers to complex questions. It takes natural language questions (text, image, or voice) and uses a knowledge graph (like Neo4j) to find relevant facts, then leverages large language models to provide comprehensive and personalized answers. It's ideal for domain experts who need to query their specific, private knowledge bases efficiently.
No commits in the last 6 months.
Use this if you have a complex dataset stored as a knowledge graph and need to ask nuanced, multi-faceted questions in plain language to get precise answers from your own data.
Not ideal if your data is not structured as a knowledge graph or if you only need simple keyword-based searches.
Stars
64
Forks
6
Language
Python
License
Apache-2.0
Category
Last pushed
Dec 20, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/rag/zhengguanyu/KGB-RAG"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
neo4j/neo4j-graphrag-python
Neo4j GraphRAG for Python
microsoft/graphrag
A modular graph-based Retrieval-Augmented Generation (RAG) system
Hawksight-AI/semantica
Semantica 🧠 — A framework for building semantic layers, context graphs, and decision...
FalkorDB/GraphRAG-SDK
Build fast and accurate GenAI apps with GraphRAG SDK at scale.
getzep/graphiti
Build Real-Time Knowledge Graphs for AI Agents