85bf1341f3
Frontend Enhancements: - Complete React TypeScript frontend with modern UI components - Distributed workflows management interface with real-time updates - Socket.IO integration for live agent status monitoring - Agent management dashboard with cluster visualization - Project management interface with metrics and task tracking - Responsive design with proper error handling and loading states Backend Infrastructure: - Distributed coordinator for multi-agent workflow orchestration - Cluster management API with comprehensive agent operations - Enhanced database models for agents and projects - Project service for filesystem-based project discovery - Performance monitoring and metrics collection - Comprehensive API documentation and error handling Documentation: - Complete distributed development guide (README_DISTRIBUTED.md) - Comprehensive development report with architecture insights - System configuration templates and deployment guides The platform now provides a complete web interface for managing the distributed AI cluster with real-time monitoring, workflow orchestration, and agent coordination capabilities. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
70 lines
2.6 KiB
JavaScript
70 lines
2.6 KiB
JavaScript
let random = async bytes => crypto.getRandomValues(new Uint8Array(bytes))
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let customAlphabet = (alphabet, defaultSize = 21) => {
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// First, a bitmask is necessary to generate the ID. The bitmask makes bytes
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// values closer to the alphabet size. The bitmask calculates the closest
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// `2^31 - 1` number, which exceeds the alphabet size.
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// For example, the bitmask for the alphabet size 30 is 31 (00011111).
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// `Math.clz32` is not used, because it is not available in browsers.
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let mask = (2 << (Math.log(alphabet.length - 1) / Math.LN2)) - 1
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// Though, the bitmask solution is not perfect since the bytes exceeding
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// the alphabet size are refused. Therefore, to reliably generate the ID,
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// the random bytes redundancy has to be satisfied.
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// Note: every hardware random generator call is performance expensive,
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// because the system call for entropy collection takes a lot of time.
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// So, to avoid additional system calls, extra bytes are requested in advance.
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// Next, a step determines how many random bytes to generate.
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// The number of random bytes gets decided upon the ID size, mask,
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// alphabet size, and magic number 1.6 (using 1.6 peaks at performance
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// according to benchmarks).
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// `-~f => Math.ceil(f)` if f is a float
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// `-~i => i + 1` if i is an integer
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let step = -~((1.6 * mask * defaultSize) / alphabet.length)
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return async (size = defaultSize) => {
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let id = ''
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while (true) {
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let bytes = crypto.getRandomValues(new Uint8Array(step))
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// A compact alternative for `for (var i = 0; i < step; i++)`.
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let i = step | 0
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while (i--) {
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// Adding `|| ''` refuses a random byte that exceeds the alphabet size.
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id += alphabet[bytes[i] & mask] || ''
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if (id.length === size) return id
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}
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}
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}
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}
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let nanoid = async (size = 21) => {
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let id = ''
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let bytes = crypto.getRandomValues(new Uint8Array((size |= 0)))
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// A compact alternative for `for (var i = 0; i < step; i++)`.
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while (size--) {
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// It is incorrect to use bytes exceeding the alphabet size.
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// The following mask reduces the random byte in the 0-255 value
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// range to the 0-63 value range. Therefore, adding hacks, such
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// as empty string fallback or magic numbers, is unneccessary because
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// the bitmask trims bytes down to the alphabet size.
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let byte = bytes[size] & 63
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if (byte < 36) {
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// `0-9a-z`
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id += byte.toString(36)
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} else if (byte < 62) {
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// `A-Z`
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id += (byte - 26).toString(36).toUpperCase()
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} else if (byte < 63) {
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id += '_'
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} else {
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id += '-'
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}
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}
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return id
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}
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module.exports = { nanoid, customAlphabet, random }
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