Search Results for "knowledge graph"
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30 projects for "knowledge graph" with 2 filters applied:
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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NLP-Knowledge-Graph
Research and application of technologies such as nl processing
NLP-Knowledge-Graph is an open educational repository that collects resources, research materials, and tutorials focused on the intersection of natural language processing and knowledge graph technologies. The project aims to help researchers and developers understand how structured knowledge representations can enhance language processing systems. -
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fireworks-tech-graph
Claude Code skill for generating production-quality SVG+PNG technical
...The system likely leverages AI techniques for entity extraction, relationship mapping, and graph construction, enabling automated knowledge organization. It can be used to power recommendation systems, research tools, or intelligent assistants that require contextual understanding of technical topics. The project emphasizes scalability and adaptability, allowing it to handle large datasets and evolving knowledge bases. By structuring information into graph form, it enables more meaningful navigation and discovery compared to traditional document-based systems. -
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Youtu-GraphRAG
Vertically Unified Agents for Graph Retrieval-Augmented Reasoning
Youtu-GraphRAG is a research framework developed by Tencent for performing complex reasoning using graph-based retrieval-augmented generation. The system combines knowledge graphs, retrieval mechanisms, and agent-based reasoning into a unified architecture designed to handle knowledge-intensive tasks. Instead of relying solely on text retrieval, the framework organizes information into structured graph schemas that represent entities, relationships, and attributes. ... -
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SAG
SQL-Driven RAG Engine
...These vectors allow the system to identify relationships between concepts and construct a graph representation of knowledge at runtime. The architecture also includes a three-stage retrieval pipeline consisting of recall, expansion, and reranking steps to improve search accuracy. The engine integrates semantic vector similarity with traditional full-text search to improve both recall and precision. Because the knowledge graph is generated dynamically, the system can adapt to new information without requiring manual graph maintenance. -
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kg-gen
Knowledge Graph Generation from Any Text
...The framework addresses common problems in automatic knowledge graph construction, particularly sparsity and duplication of entities, by applying a clustering and entity-resolution process that merges semantically similar nodes. This allows the generated graphs to be denser, more coherent, and easier to use for downstream tasks such as retrieval-augmented generation, semantic search, and reasoning systems. -
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Basic Memory
Persistent AI memory using local Markdown knowledge graphs
...Basic Memory creates a semantic knowledge graph by linking related ideas, making it easier to retrieve, expand, and connect information over time. With a local-first design, your data stays private and portable, while optional cloud sync enables cross-device access. It combines simplicity with powerful indexing and search, giving you a flexible way to build long-term memory for projects, research, and workflows. -
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Graphify
AI coding assistant skill (Claude Code, Codex, OpenCode, OpenClaw)
...It is particularly useful in domains such as network analysis, knowledge graphs, and system architecture visualization. The architecture emphasizes flexibility, enabling users to customize how data is mapped and displayed. It may also include analytical features to explore patterns, clusters, or anomalies within the graph. Overall, Graphify serves as a bridge between raw data and visual insight. -
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LEANN
Local RAG engine for private multimodal knowledge search on devices
LEANN is an open source system designed to enable retrieval-augmented generation (RAG) and semantic search across personal data while running entirely on local devices. It focuses on dramatically reducing the storage overhead typically required for vector search and embedding indexes, enabling efficient large-scale knowledge retrieval on consumer hardware. LEANN introduces a storage-efficient approximate nearest neighbor index combined with on-the-fly embedding recomputation to avoid storing large embedding vectors. By recomputing embeddings during queries and using compact graph-based indexing structures, LEANN can maintain high search accuracy while minimizing disk usage. ... -
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Understand Anything
Turn any codebase into an interactive knowledge graph
Understand-Anything is an AI-driven tool designed to help users deeply understand any topic by generating structured explanations, summaries, and breakdowns. It focuses on transforming complex or unfamiliar subjects into clear, step-by-step explanations that are easier to grasp. The system leverages language models to provide layered insights, allowing users to explore topics at different levels of detail. It is particularly useful for learning, research, and quick comprehension of new... -
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KG-LLM-Papers
Papers integrating knowledge graphs (KGs) and large language models
KG-LLM-Papers is a curated academic resource that collects and organizes research papers exploring the intersection between knowledge graphs and large language models. The repository functions as a continuously updated index of scholarly work that investigates how structured knowledge representations can enhance the reasoning, factual accuracy, and interpretability of language models. It includes surveys, benchmark studies, and cutting-edge research that examine topics such as knowledge graph-guided prompting, retrieval-augmented generation, reasoning over structured data, and hybrid architectures combining symbolic and neural systems. ... -
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PipesHub
Workplace AI platform for enterprise search and workflow automation
PipesHub AI is an open-source, enterprise-grade workplace AI platform designed to unify search, knowledge management, and workflow automation across distributed organizational systems. It connects to a wide range of enterprise tools such as Google Workspace, Slack, Jira, and Confluence, aggregating data into a centralized knowledge layer that can be queried using natural language. The platform uses knowledge graphs and ranking algorithms to provide context-rich answers along with traceable... -
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The Machine & Deep Learning Compendium
List of references in my private & single document
The Machine & Deep Learning Compendium is an open-source knowledge repository that compiles summaries, references, and learning materials related to machine learning and deep learning. The project functions as a comprehensive compendium that organizes hundreds of topics covering algorithms, frameworks, research areas, and practical machine learning workflows. Originally created as a personal knowledge base, the repository evolved into a public educational resource designed to help learners explore the rapidly expanding machine learning ecosystem. ... -
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openbench
Provider-agnostic, open-source evaluation infrastructure
openbench is an open-source, provider-agnostic evaluation infrastructure designed to run standardized, reproducible benchmarks on large language models (LLMs), enabling fair comparison across different model providers. It bundles dozens of evaluation suites — covering knowledge, reasoning, math, code, science, reading comprehension, long-context recall, graph reasoning, and more — so users don’t need to assemble disparate datasets themselves. With a simple CLI interface (e.g. bench eval <benchmark> --model <model-id>), you can quickly evaluate any model supported by Groq or other providers (OpenAI, Anthropic, HuggingFace, local models, etc.). openbench also supports private/local evaluations: you can integrate your own custom benchmarks or data (e.g. internal test suites, domain-specific tasks) to evaluate models in a privacy-preserving way. -
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CSGHub
CSGHub is a brand-new open-source platform for managing LLMs
CSGHub is an open-source framework designed for collaborative scientific research and content generation. It enables researchers to utilize AI-driven tools for literature review, hypothesis generation, and automated writing assistance, streamlining the scientific discovery process. -
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Obsidian Skills
Agent skills for Obsidian
...These skills are markdown-driven specifications that teach Claude Code (or similar agents) how to perform context-aware tasks within Obsidian’s unique environment, such as interpreting different file types and workflows, automating workflows tied to notes, or enhancing agent responses with structured knowledge. By providing formal descriptions of patterns, conventions, and workflows common to Obsidian users, the skills empower AI tools to give more relevant suggestions, generate content that adheres to user conventions, or execute complex multi-step operations that respect the knowledge graph and file relationships. -
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Mini Agent
A minimal yet professional single agent demo project
...The project exposes an Anthropic-compatible API interface and fully supports interleaved thinking, letting the agent alternate between reasoning steps and tool invocations during long, complex tasks. It includes a basic toolset for file-system operations and shell commands, plus integrations with MCP tools such as web search and knowledge graph access. Mini-Agent also comes with “Claude Skills”-style predefined skills for tasks like document processing, design work, and testing, packaged as reusable behaviors that can be invoked by the agent as needed. -
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Agent Framework
Framework for building, orchestrating, and deploying AI agents
Microsoft Agent Framework is an open source framework designed to help developers build, orchestrate, and deploy AI agents and multi-agent systems. It provides a unified programming model that supports both Python and .NET implementations, allowing developers to create agent-driven applications in multiple programming environments. It includes tools and abstractions for constructing simple conversational agents as well as complex workflows where multiple agents collaborate to complete tasks.... -
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Kodezi Chronos
Kodezi Chronos is a debugging-first language model
...Unlike general-purpose language models that focus primarily on code generation, Chronos is built to diagnose and repair bugs by analyzing complex relationships across files within a codebase. The project introduces architectural techniques such as Adaptive Graph-Guided Retrieval, which allows the system to navigate large repositories and retrieve relevant debugging information from multiple sources. Another component, Persistent Debug Memory, allows the system to learn patterns from past debugging sessions and apply that knowledge to future problems. The repository mainly contains research documentation, evaluation benchmarks, and experimental frameworks rather than the full proprietary model implementation. -
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The Algorithms - C++ #
Collection of various algorithms in mathematics, machine learning
...The project is part of the broader “The Algorithms” initiative, which maintains algorithm implementations in several programming languages to support education and knowledge sharing. Within the C++ repository, contributors implement algorithms across a wide range of fields including sorting, graph theory, number theory, machine learning, cryptography, and data structures. Each implementation is designed to be readable and well documented so that learners can understand the logic and structure behind each algorithm. ... -
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MemMachine
Universal memory layer for AI Agents
MemMachine is a universal memory layer designed for AI agents that provides persistent, rich memory storage and retrieval capabilities so autonomous agent systems can recall context, personal preferences, and long-term interaction history across sessions, models, and use cases. Unlike ephemeral LLM prompt state, MemMachine supports distinct memory types—short-term conversational context, long-term persistent knowledge, and profile memory for personalized facts—persisted in optimized stores (e.g., graph databases for episodic lines of reasoning and SQL for user facts) to support robust, context-aware intelligence in agents. It offers flexible APIs, a Python SDK, REST interfaces, and MCP (Model Context Protocol) connectivity to integrate seamlessly with agent frameworks receiving and storing memories over time, effectively boosting relevance, continuity, and tailored behavior. -
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Hindsight
Hindsight: Agent Memory That Learns
Hindsight is an advanced, open-source memory system for AI agents designed to enable long-term learning, reasoning, and consistency across interactions by treating memory as a first-class component of intelligence rather than a simple retrieval layer. It addresses one of the core limitations of modern AI agents, which is their inability to retain and meaningfully use past experiences over time, by introducing a structured, biomimetic memory architecture inspired by how human memory works.... -
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AI_Tutorial
A selection of learning materials, search, recommendation, advertising
...The curated content includes topics like recommendation systems, search engine architecture, neural networks, graph neural networks, and modern deep learning techniques. The goal of the project is to reduce information fragmentation by organizing valuable AI resources into structured sections that can be explored easily by learners and practitioners. -
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MiroFlow
Agent framework that enables tool-use agent tasks
MiroFlow is a high-performance open-source framework designed for building intelligent AI agents capable of solving complex reasoning and research tasks. The system introduces a hierarchical architecture that organizes components into control, agent, and foundation layers, allowing developers to manage agent orchestration and tool interactions in a structured manner. One of the core innovations of MiroFlow is its use of agent graphs, which enable flexible orchestration of multiple sub-agents... -
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Knowledge + Chat
Knowledge is a tool for saving, searching, accessing, and chatting
Knowledge is an open-source desktop application designed for organizing, exploring, and interacting with information gathered from websites, documents, and other digital sources. The platform allows users to collect knowledge from multiple formats including web pages, PDF files, videos, and other documents and organize them into structured projects and subprojects. -
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funNLP
Resources, corpora, and tools for Chinese natural language processing
FunNLP is a large, curated collection of resources, corpora, and tools for Chinese natural language processing (NLP). It aggregates datasets, lexicons, wordlists, sentiment dictionaries, knowledge graphs, and pretrained model references, serving as a one-stop resource hub for Chinese NLP practitioners. The repository is organized into categories such as sentiment analysis, text classification, named entity recognition, knowledge graphs, and various lexicons (e.g. sensitive words, emotion...
