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Awesome GitHub RepositoriesKnowledge Graph Builders

Tools for processing interaction data into organized facts, vector embeddings, and knowledge graph triples.

Distinct from Knowledge Graph Indexers: Distinct from Knowledge Graph Indexers: focuses on the construction and extraction of knowledge from raw logs rather than just indexing.

Explore 43 awesome GitHub repositories matching data & databases · Knowledge Graph Builders. Refine with filters or upvote what's useful.

Awesome Knowledge Graph Builders GitHub Repositories

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  • garrytan/gbraingarrytan 的头像

    garrytan/gbrain

    23,848在 GitHub 上查看↗

    gbrain is an agent framework and retrieval-augmented generation system that combines a durable task queue, a git-synced vector store, and a knowledge graph engine. It provides a foundation for building AI agents that interact with structured knowledge bases using the Model Context Protocol. The system synchronizes markdown files from a git repository into a database for high-performance semantic retrieval and creates typed edges between data pages by extracting entity references and wikilinks. It uses a database-backed queue to execute persistent background jobs and tool loops, ensuring relia

    Automatically creates typed edges between pages by extracting entity references from markdown and wikilinks.

    TypeScript
    在 GitHub 上查看↗23,848
  • recommenders-team/recommendersrecommenders-team 的头像

    recommenders-team/recommenders

    21,769在 GitHub 上查看↗

    This project is a recommendation system framework designed for building, evaluating, and operationalizing personalized item suggestion engines. It provides a comprehensive toolkit for implementing collaborative filtering and content-based algorithms, supported by an end-to-end machine learning pipeline for preparing datasets and deploying predictive models. The framework distinguishes itself through the integration of knowledge graphs to provide richer context for recommendations and the use of industry-specific patterns to accelerate system deployment. It also includes a specialized model ev

    Generates recommendations by leveraging structured knowledge graph data to explore entity relationships.

    Pythonaiartificial-intelligencedata-science
    在 GitHub 上查看↗21,769
  • memorilabs/memoriMemoriLabs 的头像

    MemoriLabs/Memori

    15,358在 GitHub 上查看↗

    Memori is an AI agent memory middleware platform designed to provide persistent, context-aware recall for language models. It functions as a non-intrusive layer that intercepts outbound model requests to automatically capture interaction history and execution traces, ensuring that agents maintain continuity across sessions without requiring modifications to existing application logic. The platform distinguishes itself through a dual-model storage architecture that maintains information as both structured relational primitives for precise fact retrieval and rolling narrative summaries for situ

    Extracts structured facts and semantic relationships from interaction data to build a queryable knowledge base for AI models.

    Pythonagentaiaiagent
    在 GitHub 上查看↗15,358
  • nesquena/hermes-webuinesquena 的头像

    nesquena/hermes-webui

    14,912在 GitHub 上查看↗

    Hermes-webui is a self-hosted AI orchestrator and web interface for managing autonomous agents. It serves as a multi-provider gateway that connects cloud and local large language models, providing a central hub to execute scheduled background jobs, run shell commands, and manage agent memory on private hardware. The system distinguishes itself through a persistent memory manager that utilizes knowledge graphs and markdown files for long-term context across sessions. It features a model context protocol host for extending agent capabilities with standardized tools and supports the orchestratio

    Builds a structured knowledge graph of facts that accumulates across different projects and sessions for long-term recall.

    Pythonagentai-agentshermes
    在 GitHub 上查看↗14,912
  • open-metadata/openmetadataopen-metadata 的头像

    open-metadata/OpenMetadata

    14,213在 GitHub 上查看↗

    OpenMetadata is an enterprise data catalog, metadata platform, and governance suite that functions as a knowledge graph for data assets. It serves as an AI-ready metadata layer, providing governed context and organizational memory to large language model agents via the Model Context Protocol. The platform distinguishes itself by capturing institutional knowledge, linking conversations, decisions, and remediation notes directly to data assets to preserve tribal knowledge. It integrates AI agents to automate metadata governance, such as suggesting descriptions and identifying sensitive data thr

    Constructs a knowledge graph connecting technical assets, people, and business concepts.

    TypeScriptcontextcontext-layerdata-catalog
    在 GitHub 上查看↗14,213
  • blinkospace/blinkoblinkospace 的头像

    blinkospace/blinko

    10,601在 GitHub 上查看↗

    Blinko is a personal knowledge management system and an LLM-powered knowledge base that enables users to capture and organize thoughts through a bi-directional knowledge graph. It functions as a RAG-enabled note-taking application and a self-hosted Markdown editor, allowing for the creation of permanent documentation and fleeting notes. The project distinguishes itself by integrating retrieval-augmented generation to provide conversational querying and AI-powered analysis of private document libraries. It supports both cloud-based and local AI model integration, enabling users to perform sema

    Connects ideas through reciprocal links to build a structured knowledge graph.

    TypeScriptmarkdownmemosnextjs
    在 GitHub 上查看↗10,601
  • elemefe/node-interviewElemeFE 的头像

    ElemeFE/node-interview

    10,491在 GitHub 上查看↗

    This project is a structured catalog of server-side development questions and advanced Node.js concepts designed for senior-level interview preparation. It focuses on backend engineering topics including architecture, performance, and system design, while also covering Node.js internals, async patterns, and production debugging. The resource organizes interview topics into a navigable knowledge graph of interconnected concepts and subtopics, with explicit cross-references linking related ideas together. Content is presented through a question-driven learning path that guides the learner from

    Organises interview topics into a navigable graph of interconnected concepts and subtopics.

    HTMLinterviewnodejs
    在 GitHub 上查看↗10,491
  • k-dense-ai/claude-scientific-skillsK-Dense-AI 的头像

    K-Dense-AI/claude-scientific-skills

    8,907在 GitHub 上查看↗

    This project is a scientific agent framework and workflow orchestrator designed to extend large language models with specialized tools for genomic, chemical, and biological research. It provides a system for planning research hypotheses and executing automated workflows by integrating scientific databases with dynamic code execution. The framework includes a cheminformatics modeling suite for predicting molecular bioactivity and performing virtual screening, alongside a bioinformatics analysis toolkit for processing genomic sequences and single-cell data. It also features an academic document

    Maps protein interactions and biological pathways by linking gene lists to structured scientific databases.

    Pythonai-scientistbioinformaticschemoinformatics
    在 GitHub 上查看↗8,907
  • openspg/kagOpenSPG 的头像

    OpenSPG/KAG

    8,548在 GitHub 上查看↗

    KAG is a graph-augmented retrieval augmented generation system and knowledge graph engine. It functions as a framework that integrates large language models with graph retrieval and numerical calculation to resolve natural language queries. The system creates unified knowledge representations by aligning unstructured data and expert rules through semantic mapping. It maintains mutual indexing between graph structures and original text blocks to ensure that reasoning processes remain linked to verifiable source data. The project provides capabilities for semantic information integration, grap

    Combines unstructured data and expert rules through semantic alignment to build comprehensive knowledge graphs.

    Pythonknowledge-graphlarge-language-modellogical-reasoning
    在 GitHub 上查看↗8,548
  • norvig/paip-lispnorvig 的头像

    norvig/paip-lisp

    7,465在 GitHub 上查看↗

    This project is a comprehensive Lisp AI implementation library that provides reference implementations for various artificial intelligence paradigms and symbolic algorithms. It functions as a multi-purpose toolkit containing a logic programming engine, a natural language processing suite, and a symbolic mathematics toolkit. The library is distinguished by its diverse architectural frameworks, including a Prolog-style execution engine that uses unification and goal-driven backtracking, and a system for simulating human decision-making through expert system shells and certainty factors. It also

    Implements production rules that map clinical observations and patient attributes to probabilities of specific identities.

    Common Lisp
    在 GitHub 上查看↗7,465
  • dendronhq/dendrondendronhq 的头像

    dendronhq/dendron

    7,436在 GitHub 上查看↗

    Dendron is a markdown knowledge management system designed for organizing linked files into a hierarchical personal knowledge base. It functions as a git-backed note manager that stores data as plaintext markdown files to ensure data persistence and ownership. The system distinguishes itself through schema-based organization, which applies structural templates and autocomplete hints to maintain consistency across large sets of documents. It also provides bi-directional linking and an interactive graph view to visualize relationships between notes, alongside a static site generator that export

    Creates reciprocal links between documents to enable navigation via backlinks and graph visualizations.

    TypeScriptdendronmarkdownmarkdown-editor
    在 GitHub 上查看↗7,436
  • liuhuanyong/qasystemonmedicalkgliuhuanyong 的头像

    liuhuanyong/QASystemOnMedicalKG

    7,313在 GitHub 上查看↗

    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

    Provides tools to process medical entities and relations into a structured knowledge graph.

    Python
    在 GitHub 上查看↗7,313
  • microsoft/vscode-docsmicrosoft 的头像

    microsoft/vscode-docs

    6,549在 GitHub 上查看↗

    This repository contains the comprehensive documentation for a code editor focused on AI-assisted software development and remote development workflows. It covers the implementation of AI agents and language models used for autonomous code generation, large-scale refactoring, and task iteration. The project is distinguished by its deep integration of autonomous AI agents capable of web navigation, application logic validation, and orchestrating multi-step development processes. It provides specialized frameworks for tailoring AI behavior through custom instructions, model context protocols, a

    Analyzes Markdown files to detect and report broken references to local files and headers.

    Markdownvscode
    在 GitHub 上查看↗6,549
  • standardnotes/appstandardnotes 的头像

    standardnotes/app

    6,519在 GitHub 上查看↗

    Creates clickable links between notes for navigating related content like a personal wiki.

    TypeScriptencryptedevernotemarkdown
    在 GitHub 上查看↗6,519
  • keyvanakbary/learning-noteskeyvanakbary 的头像

    keyvanakbary/learning-notes

    6,412在 GitHub 上查看↗

    This project is a curated repository of technical learning materials and a personal knowledge base. It consists of version-controlled Markdown summaries covering software architecture, engineering literature, research papers, and professional talks. The collection functions as a digital garden, using bidirectional linking and cross-references to map relationships between technical concepts. Content is distilled from various sources, including technical books, conference talks, and foundational computer science papers, into concise summaries to facilitate recall and study. The system is organ

    Implements a digital garden with bidirectional linking to map relationships between technical concepts.

    SCSSbook-notes
    在 GitHub 上查看↗6,412
  • cocoindex-io/cocoindexcocoindex-io 的头像

    cocoindex-io/cocoindex

    6,117在 GitHub 上查看↗

    Cocoindex is an incremental data processing engine that builds and maintains live indexes for AI agents, with a core focus on codebase indexing and knowledge graph extraction. The engine uses a function-graph execution model where user-defined Python functions are composed into a directed acyclic graph, and it processes data incrementally so only changed source records or code paths are re-computed, avoiding full recomputation at any scale. It supports automatic schema inference from transformation pipeline type annotations and provides full data lineage tracing, tagging every output record wi

    Builds real-time knowledge graphs with incremental updates and high-performance graph queries from documents.

    Rustagentic-data-frameworkaiai-agents
    在 GitHub 上查看↗6,117
  • org-roam/org-roamorg-roam 的头像

    org-roam/org-roam

    5,980在 GitHub 上查看↗

    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

    Displays backlinks, reference links, and unlinked references for the current note in a dedicated buffer that updates as the cursor moves.

    Emacs Lisphacktoberfestmemexorg-mode
    在 GitHub 上查看↗5,980
  • epwalsh/obsidian.nvimepwalsh 的头像

    epwalsh/obsidian.nvim

    5,910在 GitHub 上查看↗

    Obsidian.nvim is a Neovim plugin that brings Obsidian vault management and markdown note-taking directly into the editor. It models each Obsidian vault as a local directory with configurable settings, note paths, and attachment folders, bridging vault operations through Neovim's Lua API and user-defined keybindings. The plugin handles core vault workflows including note creation with template insertion, daily notes management with configurable date formats, and navigation by following wiki-style and markdown links. It provides asynchronous full-text and filename search across vault notes usin

    Follows wiki and markdown links to other notes in the vault by pressing a key, opening the target file.

    Luaneovimneovim-luaneovim-plugin
    在 GitHub 上查看↗5,910
  • pbek/qownnotespbek 的头像

    pbek/QOwnNotes

    5,792在 GitHub 上查看↗

    QOwnNotes is a desktop note editor that stores each note as a plain-text Markdown file on the local filesystem, avoiding proprietary formats and enabling direct file access. It functions as a Nextcloud Notes client, syncing notes and metadata with Nextcloud or ownCloud servers through a companion API service for versioning and sharing. The application also integrates with AI providers and exposes a local MCP server for external agents to search and fetch notes, and includes a companion browser extension for capturing web content, bookmarks, and screenshots. The editor distinguishes itself thr

    Creates and follows links to other notes using note, noteid, and file protocols with custom styling.

    C++
    在 GitHub 上查看↗5,792
  • cri-o/cri-ocri-o 的头像

    cri-o/cri-o

    5,629在 GitHub 上查看↗

    CRI-O is an open-source container runtime that implements the Kubernetes Container Runtime Interface (CRI) to manage container images, pods, and containers on cluster nodes using OCI-compatible runtimes. It serves as a node-level container manager that handles image pulling, container lifecycle, and resource monitoring for Kubernetes clusters, running containers according to the Open Container Initiative specifications. The runtime distinguishes itself through live configuration reloading that applies changes to runtime definitions, registry mirrors, and TLS certificates without restarting th

    Displays whether the binary is linked dynamically or statically in the version output.

    Go
    在 GitHub 上查看↗5,629
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  1. Home
  2. Data & Databases
  3. Knowledge Graph Indexers
  4. Knowledge Graph Builders

探索子标签

  • Bi-Directional Note Linking3 个子标签The creation of reciprocal links between documents to form a navigable knowledge graph. **Distinct from Knowledge Graph Builders:** Closest candidate is about building graphs from logs; this is about user-defined reciprocal links in notes.
  • Biological Pathway MappingMapping protein interactions and biological pathways using structured knowledge graphs. **Distinct from Knowledge Graph Builders:** Focuses on biological pathway and protein interaction mapping rather than general knowledge graph construction from logs.
  • Infrastructure Knowledge GraphsGraph-based representations of physical and virtual infrastructure to map dependencies and operational relationships. **Distinct from Knowledge Graph Builders:** Focuses specifically on mapping hybrid cloud estates and infrastructure dependencies, not general knowledge triples or codebase symbols.
  • Infrastructure Topology GraphsKnowledge graphs specifically used to map and visualize cloud infrastructure dependencies and topologies. **Distinct from Knowledge Graph Builders:** Focuses on infrastructure topology and operational remediation rather than generic data processing or codebase reasoning
  • Interview Topic GraphsNavigable graphs that organize interview topics into interconnected concepts and subtopics with explicit cross-references. **Distinct from Knowledge Graph Builders:** Distinct from Knowledge Graph Builders: focuses on structuring educational interview content rather than processing interaction data into facts or embeddings.
  • Knowledge Graph RecommendationsRecommendation strategies that use structured knowledge graphs to discover relationships between entities. **Distinct from Knowledge Graph Builders:** Focuses on using the graph for generating recommendations rather than the construction of the graph itself.
  • Link PredictionThe analytical process of predicting missing connections between entities in a graph. **Distinct from Knowledge Graph Builders:** Focuses on the predictive analysis of missing links rather than the construction of the graph triples.
  • Logical Rule Expansion1 个子标签Systems that use expert-defined logical rules to derive new facts and relationships within a knowledge graph. **Distinct from Knowledge Graph Builders:** Focuses on the logical derivation of new facts via expert rules rather than just the initial construction of the graph from data.
  • Real-TimeTools for constructing knowledge graphs with incremental updates and high-performance graph queries. **Distinct from Knowledge Graph Builders:** Distinct from Knowledge Graph Builders: adds real-time incremental updates and query performance as primary design goals.
  • Response InjectorsWrites final agent outputs directly into an existing knowledge graph to enrich it with new information. **Distinct from Knowledge Graph Builders:** Distinct from Knowledge Graph Builders: focuses on injecting agent responses into an existing graph, not building from raw logs.
  • Self-Evolving Knowledge GraphsKnowledge graphs that automatically distill session data into facts and reusable agent skills. **Distinct from Knowledge Graph Builders:** Focuses on the self-evolution of the graph from session data into skills, not just building the graph
  • Session Log DistillersTools that transform raw interaction logs into semantic knowledge graph topologies. **Distinct from Knowledge Graph Builders:** Specific to distilling session logs into a queryable topology for AI context, rather than general graph building.
  • Standardized Knowledge AbstractionsMethods for representing diverse information sources as a uniform set of entities and relationships. **Distinct from Knowledge Graph Builders:** Focuses on the abstraction and standardization of various sources into a common format, rather than the low-level process of building triples from logs.