Connect-Chain composes a connect middleware from a chain of middlewares to be called in series.
Substrate-connect to Smoldot clients. Using either substrate extension with predefined clients or an internal smoldot client based on chainSpecs provided.
Substrate-connect well known chain specifications
Node.js implementation of a proxy server (think Squid) with support for SSL, authentication, upstream proxy chaining, and protocol tunneling.
Light client that connects to Polkadot and Substrate-based blockchains
Connect middleware that composes a new middleware from a chain of middlewares. Supports conditional chaining.
`JsonRpcProvider` to connect to a chain via Smoldot.
Chain functions, generators, Node streams, and Web streams into a pipeline with backpressure support.
HANDLE CONFIGURATION ONCE AND FOR ALL
TypeScript definitions for connect
The safe way to handle the `connect` socket event
React hooks and providers for integrating PULSE into AppKit, wagmi, and Stacks apps.
A utility for managing a prototype chain
OpenTelemetry instrumentation for `connect` http middleware framework
High performance middleware framework
Ethereum Provider for WalletConnect Protocol
WalletConnect SDK module for connecting to Web3-Onboard. Web3-Onboard makes it simple to connect Ethereum hardware and software wallets to your dapp. Features standardised spec compliant web3 providers for all supported wallets, framework agnostic modern
API for combining call site modifiers
TypeScript definitions for stream-chain
## Local Development
OKX Connect Universal Provider
MetaMask Connect multichain client — CAIP multichain API, session management, and transport negotiation
MetaMask Connect EVM adapter — EIP-1193 provider over the multichain client
<p align="center"> <img src="./public/logos/celo-saver.png" height="80" alt="CeloSaver" /> <img src="./public/logos/proof-pay.png" height="80" alt="ProofPay" /> <img src="./public/logos/market-pu
Proxy connections in Ruby via the Node package proxy-chain
LLM Chain is a powerful Ruby framework that provides tools for building sophisticated LLM-powered applications. It includes support for prompt management, conversation chains, memory systems, vector storage integration, and seamless LLM provider connections. Key features: • Chain-based conversation flows • Memory management with Redis • Vector storage with Weaviate • Multiple LLM provider support • Prompt templating and management • Easy integration with existing Ruby applications
Zokor is an HTTP proxy tunnelling tool that collapses multiple HTTP proxies into one. It's useful when you want to send traffic through a chain of two HTTP proxies where the first supports the CONNECT verb. Zokor presents a local server that transparently tunnels packets through the first proxy as though clients were directly connected to the second proxy. It optionally uses TLS to connect to the second proxy.
The WEBFLEET.connect API connects software applications with the Webfleet fleet management solution. Via WEBFLEET.connect you can enhance the value of all types of business solutions, including routing and scheduling optimization, ERP, Transport Management System (TMS), supply chain planning, asset management, and much more.
rails_ai_promptable makes it easy to integrate AI-driven features into your Rails application. It allows you to define promptable methods, chain context, and connect with AI APIs like OpenAI, Anthropic, or local LLMs with minimal setup.
In computer science, a disjoint-set data structure, also called a union–find data structure or merge–find set, is a data structure that keeps track of a set of elements partitioned into a number of disjoint (non-overlapping) subsets. It provides near-constant-time operations (bounded by the inverse Ackermann function) to add new sets, to merge existing sets, and to determine whether elements are in the same set. In addition to many other uses (see the Applications section), disjoint-sets play a key role in Kruskal's algorithm for finding the minimum spanning tree of a graph. A disjoint-set forest consists of a number of elements each of which stores an id, a parent pointer, and, in efficient algorithms, a value called the "rank". The parent pointers of elements are arranged to form one or more trees, each representing a set. If an element's parent pointer points to no other element, then the element is the root of a tree and is the representative member of its set. A set may consist of only a single element. However, if the element has a parent, the element is part of whatever set is identified by following the chain of parents upwards until a representative element (one without a parent) is reached at the root of the tree. Forests can be represented compactly in memory as arrays in which parents are indicated by their array index. Disjoint-set data structures model the partitioning of a set, for example to keep track of the connected components of an undirected graph. This model can then be used to determine whether two vertices belong to the same component, or whether adding an edge between them would result in a cycle. The Union–Find algorithm is used in high-performance implementations of unification. This data structure is used by the Boost Graph Library to implement its Incremental Connected Components functionality. It is also a key component in implementing Kruskal's algorithm to find the minimum spanning tree of a graph. Note that the implementation as disjoint-set forests doesn't allow the deletion of edges, even without path compression or the rank heuristic. Sharir and Agarwal report connections between the worst-case behavior of disjoint-sets and the length of Davenport–Schinzel sequences, a combinatorial structure from computational geometry.
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