Phildram1/myantfarm-ai
Multi-Agent LLM Orchestration for High-Quality Incident Response - 100% actionable recommendations vs 1.7% for single-agent
When critical IT incidents strike, getting actionable recommendations quickly is paramount. This project helps Site Reliability Engineers (SREs), DevOps teams, or IT Operations managers evaluate and implement multi-agent AI systems that process incident alerts and generate concrete, high-quality steps to resolve issues. It takes incident scenarios as input and produces a detailed list of actionable recommendations for resolution.
Use this if you are building or evaluating AIOps tools for incident response and need to benchmark the effectiveness of multi-agent LLM approaches for generating highly actionable remediation plans.
Not ideal if you are looking for a standalone incident response tool ready for production use, as this is an experimental framework for research and evaluation.
Stars
8
Forks
1
Language
TeX
License
MIT
Category
Last pushed
Feb 04, 2026
Commits (30d)
0
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