Search Results for "squid-graph"
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Showing 2123 open source projects for "squid-graph"
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Graph Node
Graph Node indexes data from blockchains such as Ethereum
The Graph is an indexing protocol for querying networks like Ethereum and IPFS. Anyone can build and publish open APIs, called subgraphs, making data easily accessible. Subgraphs can be composed into a global graph of all the world's public information. This data can be transformed, organized, and shared across applications for anyone to query with just a few keystrokes. -
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Graph Notebook
Library extending Jupyter notebooks to integrate with Apache TinkerPop
The graph notebook provides an easy way to interact with graph databases using Jupyter notebooks. Using this open-source Python package, you can connect to any graph database that supports the Apache TinkerPop, openCypher or the RDF SPARQL graph models. These databases could be running locally on your desktop or in the cloud. Graph databases can be used to explore a variety of use cases including knowledge graphs and identity graphs. -
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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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Code-Graph-RAG
The ultimate RAG for your monorepo
Code-Graph-RAG is an advanced retrieval-augmented generation system designed specifically for understanding and interacting with large, multi-language codebases by transforming them into structured knowledge graphs. It uses Tree-sitter to parse source code into abstract syntax trees, extracting relationships between functions, classes, and modules to build a graph-based representation of the entire codebase. -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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NLP-Knowledge-Graph
Research and application of technologies such as nl processing
...It includes curated materials covering key topics such as knowledge graph construction, entity recognition, relation extraction, graph embeddings, and semantic reasoning. By combining NLP techniques with graph-based data models, knowledge graphs allow systems to represent complex relationships between entities and improve tasks such as question answering, information retrieval, and recommendation systems. -
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code-review-graph
Local-first code intelligence graph for MCP and CLI
Code Review Graph is a local-first code intelligence tool that builds a persistent structural map of a software repository. It parses source files with Tree-sitter and stores functions, classes, imports, calls, inheritance, and test relationships in a SQLite graph. When code changes, blast-radius analysis identifies the callers, dependents, and tests most likely to be affected. -
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react-native-graph
Beautiful, high-performance Graphs and Charts for React Native
react-native-graph is a Line Graph implementation based on the high-performance 2D graphics rendering engine "Skia". It's used in the Pink Panda Wallet app to power thousands of token graphs every day. Animations are ran using the Skia animation system and are fully natively interpolated to ensure best possible performance. If animated is false, a light-weight implementation of the graph renderer will be used, which is optimal for displaying a lot of graphs in large lists. -
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CogDB
Micro Graph Database for Python Applications
Cog is a lightweight, embedded graph database for Go that provides a simple interface for storing and querying graph-based data structures, making it useful for knowledge representation and graph analytics. -
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Graph NotebookAmazon GameLift Unity
Access GameLift resources and integrate GameLift into your Unity game
The Amazon GameLift Plugin for Unity contains libraries and native UI that makes it easier to access GameLift resources and integrate GameLift into your Unity game. You can use the GameLift Unity Plugin to access GameLift APIs and deploy AWS CloudFormation templates for common gaming scenarios. Auth Only, this scenario creates a game backend service that performs only player authentication and no game server capability. It creates a Cognito user pool to store player authentication... -
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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G6
A Graph Visualization Framework in JavaScript
G6 is graph visualization engine with simplicity and convenience. Based on the ability to customize, it provides a set of elegant graph visualization solutions and helps developers to build up applications for graph visualization, graph analysis, and graph editor. G6 is a complete graph visualization engine, which focuses on relational data. -
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AgensGraph
AgensGraph, a transactional graph database based on PostgreSQL
AgensGraph is a multi-model database that extends PostgreSQL with graph database capabilities, enabling users to work with both relational and graph data within a single system. It supports the Cypher query language alongside SQL, making it ideal for hybrid workloads. -
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Apache AGE
Graph database optimized for fast analysis
Apache AGE (A Graph Extension) is a PostgreSQL extension that adds support for graph database functionality using the openCypher query language. AGE allows users to store and query graph-structured data alongside traditional relational data in a single database. Built for performance and scalability, it brings the power of graph queries to the robustness of PostgreSQL, making it suitable for use cases like social networks, recommendation systems, and fraud detection. -
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Google DeepMind GraphCast and GenCast
Global weather forecasting model using graph neural networks and JAX
GraphCast, developed by Google DeepMind, is a research-grade weather forecasting framework that employs graph neural networks (GNNs) to generate medium-range global weather predictions. The repository provides complete example code for running and training both GraphCast and GenCast, two models introduced in DeepMind’s research papers. GraphCast is designed to perform high-resolution atmospheric simulations using the ERA5 dataset from ECMWF, while GenCast extends the approach with diffusion-based ensemble forecasting for probabilistic weather prediction. ... -
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AI Powered Knowledge Graph Generator
AI Powered Knowledge Graph Generator
AI-Powered Knowledge Graph is an open-source project focused on building knowledge graph systems that integrate artificial intelligence and machine learning to represent complex relationships between data entities. Knowledge graphs organize information as networks of nodes and relationships, allowing applications to analyze connections between concepts, datasets, or real-world entities. -
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gping
Ping, but with a graph
Graphical Ping displays a color-coded realtime graph of continuous pings to a specified host. No warranties are provided on this program, it is completely free to use. Graph the execution time for a list of commands rather than pinging hosts. Resolve ping targets to IPv4 address. Resolve ping targets to IPv6 address. Uses dot characters instead of braille. Determine the number of seconds to display in the graph. -
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HugeGraph
A graph database that supports more than 100+ billion data
HugeGraph is a convenient, efficient, and adaptable graph database compatible with the Apache TinkerPop3 framework and the Gremlin query language. HugeGraph supports fast import performance in the case of more than 10 billion Vertices and Edges Graph, millisecond-level OLTP query capability, and can be integrated into big data platforms like Hadoop or Spark for OLAP analysis. The main scenarios of HugeGraph include correlation search, fraud detection, and knowledge graph. ... -
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nano-graphrag
A simple, easy-to-hack GraphRAG implementation
...The system extracts entities and relationships from documents using language models and organizes them into graph structures that can be queried during generation. Developers can integrate different storage backends and embedding engines, including vector databases and graph databases such as Neo4j, allowing flexible experimentation with hybrid retrieval methods. -
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codebase-memory-mcp
High-performance code intelligence MCP server
...It ships as a single static binary for macOS, Linux, and Windows with no shared library dependencies. It also includes semantic search, BM25 search, graph visualization, auto-indexing, and cross-repository intelligence. -
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Graphs.jl
An optimized graphs package for the Julia programming language
The goal of Graphs.jl is to offer a performant platform for network and graph analysis in Julia, following the example of libraries such as NetworkX in Python. Offers a set of simple, concrete graph implementations – SimpleGraph (for undirected graphs) and SimpleDiGraph (for directed graphs), an API for the development of more sophisticated graph implementations under the AbstractGraph type, and a large collection of graph algorithms with the same requirements as this API. -
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KuzuDB
Embeddable property graph database management system
KuzuDB is a high-performance graph database optimized for analytical queries, built from the ground up with a columnar storage engine. It is designed to efficiently process large-scale graph workloads, making it ideal for data science, machine learning, and knowledge graph applications. -
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rtabmap
RTAB-Map library and standalone application
RTAB-Map (Real-Time Appearance-Based Mapping) is a RGB-D, Stereo and Lidar Graph-Based SLAM approach based on an incremental appearance-based loop closure detector. The loop closure detector uses a bag-of-words approach to determine how likely a new image comes from a previous location or a new location. When a loop closure hypothesis is accepted, a new constraint is added to the map’s graph, then a graph optimizer minimizes the errors in the map. -
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DGL
Python package built to ease deep learning on graph
...We want to make it easy to implement graph neural networks model family. We also want to make the combination of graph based modules and tensor based modules (PyTorch or MXNet) as smooth as possible. DGL provides a powerful graph object that can reside on either CPU or GPU. It bundles structural data as well as features for a better control. We provide a variety of functions for computing with graph objects including efficient and customizable message passing primitives for Graph Neural Networks. -
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Plotly Graphing Library for MATLAB
Plotly Graphing Library for MATLAB
Create interactive charts in your web browser with MATLAB® and Plotly. -
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GraphEmbedding
Implementation and experiments of graph embedding algorithms
GraphEmbedding is an open-source Python project for implementing and experimenting with graph embedding algorithms. It follows a simple “graph in, embedding out” design. The library uses NetworkX graphs as input and produces vector representations for graph nodes. It includes implementations of DeepWalk, LINE, Node2Vec, SDNE, and Struc2Vec. Users can configure walks, embedding dimensions, training windows, epochs, and other model-specific parameters. -
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dockprom
Docker hosts and containers monitoring with Prometheus, Grafana, etc.
...The Docker Host Dashboard shows key metrics for monitoring the resource usage of your server. Server uptime, CPU idle percent, number of CPU cores, available memory, swap and storage. System load average graph, running and blocked by IO processes graph, interrupts graph. CPU usage graph by mode (guest, idle, iowait, irq, nice, softirq, steal, system, user). Memory usage graph by distribution (used, free, buffers, cached). IO usage graph (read Bps, read Bps and IO time). Network usage graph by device (inbound Bps, Outbound Bps).
