Agents IA
bisheng
Enterprise LLM app platform: GenAI workflows, RAG, agents, model management, evaluation, fine-tuning.
★ 12,0 k étoilesApache-2.0
Voir le guide →evals est un projet de agents IA open source, créé par strands-agents (strands-agents/evals sur GitHub). Il compte 230 étoiles sur GitHub et 71 forks, il est publié sous la licence Apache-2.0 et a été mis à jour pour la dernière fois sur GitHub le 7 octobre 2026.
A complete evaluation toolkit for AI agents.
Write down the job you will use the project for before touching any code.
Download the source and read the README's setup section first.
Run the install steps and add any required API keys or config.
Follow the example in the docs to confirm everything works.
Measure agent quality systematically.
Covers multiple evaluation dimensions.
Works for agents and LLM apps alike.
From the Strands Agents team.
Fits Python agent workflows.
Permissive licensing.
Download the source and move into the project folder.
git clone https://github.com/strands-agents/evals.git
cd evalsSet up a virtual environment and install dependencies.
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtExecute a first eval per the README.
# see README for the eval runnersIt is maintained by the Strands Agents team at strands-agents/evals, with 71 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.
The framework is free; evaluations consume model calls through your own keys.
Compare on metrics, workflow, and how tightly each fits your agent stack.
Follow the README to run a first evaluation against your agent.
Enterprise LLM app platform: GenAI workflows, RAG, agents, model management, evaluation, fine-tuning.
Build voice-based LLM agents with a modular, open-source toolkit.
Test prompts, agents and RAGs — LLM evals, red teaming and model comparisons from the CLI
Observability and evaluation for AI apps — see what your agents do.
Policy, identity, and sandboxing guardrails for AI agents.
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.