Retry with exponential backoff for the command line.
Retry with exponential backoff for the command line.
Retry with exponential backoff for the command line.
Retries a function that returns a promise, leveraging the power of the retry module.
A utility to retry failed async methods.
Abstraction for exponential and custom retry strategies for failed operations.
TypeScript definitions for retry
Check whether a request can be retried based on the `error.code`
Retrying made simple, easy and async
Retries a function that returns a promise, leveraging the power of the retry module.
An exchange for operation retry support in urql
Retry a promise-returning or async function
Axios plugin that intercepts failed requests and retries them whenever posible.
Retry HTTP requests with Axios.
Retry a request.
Extend any fetch library with retry functionality
Retry a failed promise
TypeScript definitions for async-retry
Automatic retry plugin for octokit
retry for functions returning a promise
A webpack plugin to retry loading of chunks that failed to load
Abstraction for exponential and custom retry strategies for failed operations.
AWS SDK for JavaScript Proton Client for Node.js, Browser and React Native
TypeScript definitions for promise-retry
General purpose retry cli program for anything
Ravanello is the cli for analyze keys in redis and size of it's values. Example of usage: ```bash gem install ravanello ravanello --version REDIS_URL="redis://localhost/db" ravanello analyze --rules rules.yml ``` The rules files specifies the structure of the redis keys (splitted by :) and should looks like this: ```yml rules: resque: - 'delayed' - 'resque-retry' - 'timestamps' - 'lock' - 'meta' ``` After analyzing you will get the report in console: ``` Q-ty Size Key (sample) 4 24 * (hello) 1 6 denormalized:companies:* (denormalized:companies:99585213) ```
RCrewAI is a powerful Ruby framework for creating autonomous AI agent crews that collaborate to solve complex tasks. Build intelligent workflows with reasoning agents, tool usage, memory systems, and human oversight. Key Features: • Multi-Agent Orchestration: Create crews of specialized AI agents that work together • Multi-LLM Support: OpenAI GPT-4, Anthropic Claude, Google Gemini, Azure OpenAI, Ollama • Rich Tool Ecosystem: Web search, file operations, SQL databases, email, code execution, PDF processing • Agent Memory: Short-term and long-term memory for learning from past executions • Human-in-the-Loop: Interactive approval workflows and collaborative decision making • Advanced Task Management: Dependencies, retries, async execution, and context sharing • Hierarchical Teams: Manager agents that coordinate and delegate to specialist agents • Production Ready: Security controls, error handling, comprehensive logging, and monitoring • Ruby-First Design: Built specifically for Ruby developers with idiomatic patterns • CLI Tools: Command-line interface for creating and managing AI crews
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