AI Agents
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PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute t…
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View guide →The Ruby-native AI framework. Chats, agents, tools, images, audio, and video through one consistent API, in plain Ruby or Rails.
ruby_llm is an open-source ai agents project by crmne (crmne/ruby_llm on GitHub). It has 4,428 GitHub stars and 510 forks, is released under the MIT license, and was last updated on GitHub on 3 October 2026.
Research, coding, browsing, or ops — agents work best with a clear goal.
From no-code builders to code-first SDKs, match complexity to the task.
Web search, code execution, and APIs are what make agents useful.
Watch the trace, approve consequential actions, iterate.
Large language models drive its smartest features, locally or via API.
Agents call real tools: browsers, terminals, APIs.
Benchmarks keep agent quality measurable.
Run agents on your infra with your keys.
Swap frontier models as better ones appear.
Traces show exactly what the agent did and why.
Download the source and move into the project folder.
git clone https://github.com/crmne/ruby_llm.git
cd ruby_llmEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is an open-source project at crmne/ruby_llm with 510 forks. Check the repo's contributors and recent commits to see how active maintenance is.
MIT licensed — use it commercially, no strings attached.
For bounded tasks with supervision, yes. Fully autonomous money-moves still need guardrails.
Sandboxing, approval gates, and least-privilege credentials.
Builders exist, but code-first frameworks go further.
PraisonAI 🦞 — Hire a 24/7 AI Workforce. Stop writing boilerplate and start shipping autonomous self-improving agents that research, plan, code, and execute t…
A visual playground for agentic workflows: Iterate over your agents 10x faster
A股多Agent投研框架 — 适配A股数据源(龙虎榜/游资/解禁等)，7位分析师基于A股规则的辩论决策，基于TradingAgents深度改造，适配大A。A-share multi-agent investment research framework — 7 AI analysts, bull/bear deb…
A TypeScript toolkit for building agents: unified LLM API, loop, TUI, and CLI.
An open-source platform for AI-native application development — assistants, tools, RAG and models in one API.
Framework-agnostic, git-native standard for defining and sharing AI agents.
The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if ruby_llm is not the right fit.
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Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Free and open — grab the source, star the repo, and start creating.