Awesome GitHub RepositoriesKnowledge Graphs

Ruflo is an AI agent orchestration platform and workflow automation tool designed to decompose high-level goals into executable action plans. It functions as a manager for multi-agent swarms, organizing autonomous entities into collaborative topologies that utilize shared consensus to complete complex tasks. The framework distinguishes itself through a retrieval-augmented generation layer and knowledge graphs for reasoning over linked data. It incorporates a trajectory-based learning loop that analyzes previous execution paths to refine cognitive patterns and improve future reasoning accuracy

AgentMemory is a persistent knowledge store and memory server designed to provide AI coding agents with long-term memory. It functions as a knowledge graph engine and vector database store that saves and recalls project context, architectural decisions, and patterns across different sessions. The system distinguishes itself by using a tiered-memory consolidation pipeline that compresses raw observations into episodic, semantic, and procedural layers to optimize token usage. It employs a hybrid retrieval strategy combining keyword matching, vector embeddings, and graph traversal to surface rel

R2R is an agentic retrieval-augmented generation platform that uses reasoning agents to perform multi-step data fetching for context-aware answering. It functions as a multimodal vector database manager and knowledge graph engine designed to ground artificial intelligence responses in verified factual knowledge. The platform distinguishes itself by combining reasoning agents for complex research automation with a knowledge graph that maps entity relationships. This allows the system to perform structured data traversal alongside unstructured vector search to resolve complex questions from int

QASystemOnMedicalKG is a medical knowledge graph question answering system designed to retrieve disease-centered information from a structured data store. It functions as both a constructor for building medical knowledge graphs and a retrieval system that extracts answers regarding symptoms, causes, and treatments. The system employs a pipeline that converts unstructured medical web data into a graph database using dictionary-based entity segmentation. It utilizes query-based intent classification to parse natural language inputs and maps these queries to specific nodes and edges within the g

Org-roam is an Emacs-based note-taking system that builds a bidirectional network of plain-text notes, functioning as a personal knowledge base manager. It maintains both forward and backlink references in a SQLite database, automatically updated on file save, and uses persistent unique identifiers for notes instead of file paths to enable stable links across renames and moves. The system integrates directly with Emacs through custom interactive commands and hooks that access the database and buffer state, and it generates static graphs of note interconnections using Graphviz to reveal relati

This project is a self-hosted system for discovering, browsing, and receiving personalized recommendations from academic papers on arXiv. It combines an arXiv API client that downloads paper metadata and PDFs with a TF-IDF document similarity engine and an SVM-based recommendation system that trains a classifier per user based on their preferences. The system provides a web interface for browsing, searching, and filtering recent arXiv submissions, alongside personalized paper recommendations generated from individual user signals. It also includes a Twitter mention tracker that periodically p

Qodo Cover is an engineering governance platform and AI-powered assistant designed for automated code review and unit test generation. It utilizes an abstract syntax tree codebase knowledge graph to map dependencies and architectural relationships, allowing it to analyze pull requests and enforce organizational coding standards. The system distinguishes itself through a multi-agent analysis pipeline that performs architectural reasoning and identifies bugs beyond the immediate diff. It features a model context protocol server to expose codebase intelligence to external tools and can automatic

KnowledgeGraphData 是一个结构化数据集与语料库集合，旨在为认知智能与人工智能系统提供基础层。它主要由大规模中文知识图谱数据集组成，包括用于驱动语义理解与自动问答的实体关系数据与 NLP 训练集。 该项目专注于海量实体-属性-值图谱的构建与导出，将知识组织为可移植的格式。它提供专门的领域划分，以针对医疗、军事与公共安全等专业领域定制信息检索。 该仓库涵盖了广泛的能力，包括中文自然语言处理、语义搜索与认知对话系统。其工具集涵盖了语言分析、实体提取、情感检测与文本摘要，以及用于网站审计的视觉内容分析与语音转文字转换。

Huatuo-Llama-Med-Chinese 是一个专门用于处理和生成中文自然语言文本的医学大语言模型。它是一个指令微调系统，旨在通过利用专门的医学知识库来回答专业的医疗保健问题。 该模型集成了结构化医学文献和知识图谱，以确保响应生成过程中的临床准确性。它采用知识图谱增强推理，将结构化实体关系与神经网络输出相结合。 该系统通过特定领域的权重适配、跨语言模型迁移和监督微调流水线开发而成。这些过程将通用语言模式与专业临床标准和专门的中文医学术语进行了对齐。

auto-dev 是一款 AI 原生软件工程工具和多代理开发平台，旨在自动化整个软件开发生命周期。它作为一个自主编排器，通过声明式代理链管理 AI 驱动的编码、测试和基础设施配置。该项目基于 Kotlin Multiplatform AI 框架构建，允许代理逻辑在不同的环境和设备界面上运行。 该平台实现了模型上下文协议，以与外部 AI 服务交换工具和项目信息。它通过使用检索增强生成管道和基于树的代码图分析脱颖而出，这些分析抽象语法树和调用链以压缩项目上下文并减少幻觉。交互式开发画布提供 UML 图、OpenAPI 规范和代码差异的实时同步。 功能领域涵盖自主软件开发，包括动态任务规划、迭代测试驱动修复和遗留代码迁移。该系统还处理 Docker 和 CI/CD 配置的基础设施即代码自动化、AI 驱动的代码审查，以及跨团队协调共享 AI 个性和提示规范。 核心逻辑使用 Kotlin Multiplatform 实现，以确保跨平台代理部署的一致性。

TypeDB 是一款强类型图数据库和知识图谱管理系统。它作为多模型数据存储，将关系、文档和图结构统一到一个环境中，既充当 ACID 兼容数据库，又充当声明式查询引擎。 该系统通过使用 n 元超图建模和多态类型层级脱颖而出。它采用强类型模式来强制执行结构规则并验证数据完整性，允许在查询执行期间自动解析复杂关系的基于类型的多态推理和基于角色的接口多态性。 该平台涵盖了广泛的功能，包括通过制表（tabling）计算递归关系、快照隔离事务和声明式数据检索。它还通过基于共识的集群复制、基于角色的访问控制以及与 AI 代理的集成以进行结构化数据检索，支持高可用性。 管理通过命令行界面支持，系统提供用于可视化图模式和审计管理活动的工具。

Starspace 是一个向量嵌入框架，旨在训练文本和图像的高维表示。它作为一种机器学习系统，用于神经排序、文本分类和知识图谱嵌入，将不同的对象类型映射到共享的数值空间中，以促进检索和预测任务。 该系统包含用于知识图谱补全和链接预测的专用工具，通过在多关系向量空间中表示实体及其关系来实现。它还通过将输入映射到目标标签或候选项目，提供了语义内容推荐和大规模文本分类功能。 该框架涵盖了广泛的功能领域，包括基于相似度的实体排序、从文档或 n-gram 中提取向量嵌入，以及使用基于随机游走的训练。为了管理大数据集，它集成了基于磁盘的压缩数据加载和负采样优化。

This project is an educational curriculum and architectural framework for building autonomous AI agents and multi-agent systems. It provides a structured learning path focused on the development of independent software components capable of planning, executing tasks, and utilizing external tools to achieve high-level goals. The framework emphasizes multi-agent system orchestration through distributed architectures where specialized agents collaborate using standardized communication protocols. It details specific design patterns such as dual-memory systems for maintaining short-term plans and

Helix DB is a distributed graph database and knowledge graph platform that persists nodes and edges on object storage for durable and unlimited scaling. It operates as an ACID-compliant system, ensuring data consistency through serializable snapshot isolation during concurrent operations. The project distinguishes itself by combining a vector search engine and a property graph, utilizing hybrid vector and full-text search to locate entry points for graph traversals. It enables dynamic graph querying through a domain-specific language, allowing complex logic and recursive queries to be execute

Memary is a memory-augmented agent framework that stores and retrieves contextual information from a knowledge graph to personalize responses and maintain long-term memory across interactions. It automatically captures all agent interactions and stores them as structured memories without requiring explicit instrumentation, then injects top-ranked user entities and themes into the active context window to tailor agent responses dynamically. The framework distinguishes itself through a multi-retriever memory search that combines COLBERT reranking with recursive graph queries across databases, e

Simple Graph is a lightweight graph database engine that utilizes SQLite to persist nodes and edges. It functions as a relational graph engine by mapping graph structures into standard database tables, allowing for the storage of both structured data and flexible, schema-less information through JSON document embedding. The system provides a utility for performing complex graph traversals and path discovery by leveraging recursive common table expressions. This approach enables the exploration of deep connections and sequences of connected nodes within the stored data network. The project su

Hyper-Extract is a framework designed for automated knowledge extraction, graph construction, and retrieval-augmented generation. It functions as a command-line tool that transforms unstructured text into structured knowledge graphs and hypergraphs, enabling users to build interconnected, searchable, and machine-readable data repositories from their documents. The system distinguishes itself through its focus on personal knowledge management and incremental processing. It allows users to update existing knowledge bases by processing only new document deltas, avoiding redundant computation. Th