ИИ-агенты
bisheng
Enterprise LLM app platform: GenAI workflows, RAG, agents, model management, evaluation, fine-tuning.
★ 12,0 тыс. звёздApache-2.0
Смотреть руководство →evals — проект с открытым исходным кодом из категории «ИИ-агенты» от strands-agents (strands-agents/evals на GitHub). У него 230 звёзд на GitHub и 71 форк, он распространяется по лицензии Apache-2.0 и последний раз обновлялся на GitHub 7 октября 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.
Google's modular toolkit that lets AI coding agents hunt, reproduce, and patch vulnerabilities autonomously.
Другие проекты из категории «ИИ-агенты» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если evals вам не подходит.
A personal AI that really does things — on any OS, with your data staying yours.
An agentic skills framework & software development methodology that works.
Agent harness optimization system with skills, memory and security for Claude Code, Codex and more
The agent that grows with you — a Python framework for adaptive AI agents.
DeepSeek's plugin-based agent harness where everything is a plugin.
Соседние проекты из категории «ИИ-агенты» в каталоге, ближайшие по числу звёзд к evals — продолжайте изучать полку по обе стороны от него.
WorkArena: ServiceNow's benchmark for how well web agents handle everyday knowledge-work tasks.
An MCP-native AI coding agent and runtime in a single binary.
Benchmark computer-use agents on long, real-world desktop tasks.
A benchmark for comparing AI agent memory systems head-to-head.
Agentic memory for LLM agents, from a published research project.
A voice-driven multi-agent assistant that orchestrates in realtime.
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.