Meta Agents Research Environments is a comprehensive platform designed to evaluate AI agents in dynamic, realistic scenarios. Unlike static benchmarks, this platform introduces evolving environments where agents must adapt their strategies as new information becomes available, mirroring real-world challenges.
$ git clone https://github.com/facebookresearch/meta-agents-research-environments.git[ICML 2024] TrustLLM: LLM trustworthiness evaluation across truthfulness, safety, fairness, robustness, privacy and ethics. Python/CLI toolkit for local models, compatible APIs and AI agent orchestration.
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💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
A community-driven collection of RAG (Retrieval-Augmented Generation) frameworks, projects, and resources. Contribute and explore the evolving RAG ecosystem.
[ICLR 2025] Benchmarking Agentic Workflow Generation
[ACL 2024] Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology View
DialOp: Decision-oriented dialogue environments for collaborative language agents
Data from GitHub · snapshot Nov 13, 2026