Agentes de IA
WorkArena
WorkArena: ServiceNow's benchmark for how well web agents handle everyday knowledge-work tasks.
★ 275 estrelasNOASSERTION
Ver o guia →AgentBench é um projeto de agentes de IA de código aberto de THUDM (THUDM/AgentBench no GitHub). Tem 3.765 estrelas no GitHub e 288 forks, é publicado sob a licença Apache-2.0 e foi atualizado pela última vez no GitHub em 8 de fevereiro de 2026.
A rigorous benchmark for LLMs acting as agents.
Pick one concrete task so you can judge whether the project fits.
Clone the repo and check the prerequisites listed in the README.
Install what it needs and configure credentials or model access.
Run a minimal example end to end before wiring it into your stack.
Tests models as actors in environments.
Peer-reviewed benchmark design.
Diverse tasks beyond static QA.
From a leading academic lab.
Runnable evaluation code.
Permissive licensing.
Download the source and move into the project folder.
git clone https://github.com/THUDM/AgentBench.git
cd AgentBenchSet up a virtual environment and install dependencies.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtEvaluate a model on a task subset per the docs.
# see README for the task runnersIt is maintained by THUDM at THUDM/AgentBench, with 288 forks.
Yes. It is released under the Apache-2.0 license, which permits commercial use, modification, and redistribution. Read the LICENSE file for the exact terms.
You need model access to evaluate; the harness itself is free.
AgentBench covers diverse agentic environments; SWE-bench targets real-world software engineering specifically.
Follow the repo docs to run a task subset against your model.
WorkArena: ServiceNow's benchmark for how well web agents handle everyday knowledge-work tasks.
High-performance serving for the LLMs that power your agents.
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Open-source red-teaming framework that stress-tests LLMs and AI agents.
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Uber's ADR: discover, observe, benchmark, and detect threats across enterprise AI agents, deployed at Uber.
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Projetos de Agentes de IA próximos no catálogo, os mais próximos em estrelas de AgentBench: continue explorando dos dois lados dele.
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Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.