{"repo":"FrancescoStabile/omnigent","free":true,"listed":false,"github":"https://github.com/FrancescoStabile/omnigent","clone":"git clone https://github.com/FrancescoStabile/omnigent.git","description":"Universal autonomous agent framework with ReAct loop, multi-provider LLM routing, reasoning graph, and MCP integration, domain-agnostic for building specialized AI agents.","language":"Python","stars":30,"topics":["agent-architecture","agent-framework","ai-agent","ai-orchestration","autonomous-agent","claude","deepseek","hierarchical-planning","langchain-alternative","llm"],"license":"MIT","category":"ai-agents","readme_excerpt":"Omnigent The universal scaffold for building autonomous AI agents. Build any AI agent — security, code analysis, DevOps, compliance, research — on a production-proven foundation. Extracted from a real-world agent with 17k+ LOC and 320 tests. Architecture · Examples · Contributing --- What is Omnigent? Most AI agent frameworks give you wrappers around LLM APIs. Omnigent gives you the entire brain . It's the domain-agnostic architecture of a production autonomous agent — the ReAct loop, multi-provider LLM routing, structured memory, hierarchical planning, reasoning graphs, error recovery, reflection, and plugin system. Everything you need to build a real agent, not a chatbot with tools. You bring the domain. Omnigent brings the intelligence. Why Omnigent? Problem Omnigent Solution --------- ------------------- Agents that loop forever Circuit breaker + loop detection (hash-based, blocks on first repeat) + rate limiting (per-iteration and total caps) Context window overflow 3-level smart trimming preserving atomic message groups + semantic compression via LLM \"Just a tool caller\" Reasoning Graph chains findings into multi-step escalation paths No methodology Hierarchical Planner with phase-based execution, LLM refinement, skip conditions, and macro-reflection at phase end Blind tool execution Extractors auto-parse results → structured memory → async reflection Failures crash the agent Error recovery patterns with retry strategies and graceful degradation Vendor lock-in 4 LLM pro","default_branch":null,"files":null,"tree":[],"storefront":"/r/FrancescoStabile","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/FrancescoStabile/omnigent/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}