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环境设置

关于如何安装及配置Anaconda Python发行版,详情请参阅:此文档中的Python相关章节。

使用conda创建新的env

由于最近ustc(中科大镜像源)出现了429 (Too Many Requests)的异常,因此我们需要更换镜像源。 这里建议使用清华大学的镜像源,具体操作如下:

# 首先将conda的channels进行重置
conda config --remove-key channels
# 接下来依次导入清华大学的channels
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/conda-forge/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/msys2/

接下来我们就可以创建一个新的env了:

conda env create -f ACTAgent.yml

※请注意,ACTAgent.yml中的PREFIX字段指定了新的conda环境(即:ACTAgent)在系统上的存储位置 这里默认是以我的WSL2位置进行存储,因此您需要修改为:$CONDA_HOME/env/ACTAgent 这里的$CONDA_HOME指的是您系统上的conda的安装位置,通常它位于:/home/<$USER_NAME>/anaconda3/ 或者 /home/<$USER_NAME>/miniconda3/

激活环境

conda activate ACTAgent
# 请记得在环境变量中添加OPENAI_API_KEY
export OPENAI_API_KEY=sk-xxxxxx

或者在~/.bashrc或者~/.zshrc中添加:

export OPENAI_API_KEY=sk-xxxxxx

进行测试

python TestingScript.py

对于测试的结果您可以,您可以在LLM执行完成后检查其项目根目录下的TestingResult.json以核查LLM 生成的准确性。届时,您也可以自行修改Cases.json以定制您的特化测试用例,每个单独的用例问题请以回车分隔。

Todo List

  • 针对国服玩家的环境创建单独的Agent。

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