Agent Eval 评估器
Agent 能力评估框架（agent-eval CLI）——基于 Agent-Driven 架构，支持课件生成、
代码生成、RAG、对话等多类 Agent 评估。
安装（发布后）
pip install ai-eval-scope # 基础：规则评估（无 LLM 依赖）
pip install "ai-eval-scope[llm]" # + LLM Judge（OpenAI/Anthropic 兼容）
pip install "ai-eval-scope[agent]" # + ExecutionAgent 执行引擎（DeepAgents 底座）
pip install "ai-eval-scope[vision]" # + 视觉评估（playwright 截图渲染）
pip install "ai-eval-scope[datasets]" # + 数据集下载（HuggingFace/ModelScope）
uv tool install "ai-eval-scope[agent]" # uv：全局 CLI 工具安装
uvx --from "ai-eval-scope[agent]" agent-eval --help # 一次性运行，不落盘
包名
ai-eval-scope，import 名agent_eval，CLI 命令agent-eval（命令名≠包名）。 Python ≥ 3.11。LLM 与凭证配置见 CLI 使用教程。
开发
cd evaluator
uv sync --group dev # 开发依赖组（PEP 735，含 llm/vision 测试依赖）
uv run playwright install chromium # 下载 Chromium 浏览器二进制（~150MB，装到用户缓存）
uv run agent-eval --help
配置
交互式向导（推荐）
uv run agent-eval models login
向导流程：
- 选择提供商：
anthropic/openai/deepseek/custom（自定义 OpenAI 兼容端点） - API Base URL：按提供商给默认值（anthropic 缺省
https://api.moonshot.cn/anthropic，即 Kimi 的 Anthropic 协议端点；openai 缺省https://api.openai.com/v1；deepseek 缺省https://api.deepseek.com/v1） - API Key：隐藏输入
- 逐角色确认模型：
text— 文本 LLM Judge（默认必配）vision— 视觉评估模型（用视觉规则集时需要）agent— 执行侧模型（run/pipeline驱动被测 Agent 用；未配置时自动回退text）
查看与验证
uv run agent-eval models list # 查看（API Key 脱敏显示 前4…后4）
uv run agent-eval models test # 对每个已配角色真实调用一次，打印时延
uv run agent-eval models logout # 删除配置（含 key）
运行
uv run agent-eval eval \
--package-dir workspace/packages/<包目录>/ \
--package courseware
验证是否真正执行：产物中出现 *.png 截图、评估耗时显著增加（视觉渲染 + 视觉 LLM 调用），
且日志无「视觉跳过」「Chromium 启动失败」字样。缓存命中时会跳过视觉重算，调试时加
--no-cache 强制重评。
1 maintainer
Metadata
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