semvec/pypi-packages huggingface dataset:
pyzemrpc 1.2.1
zeptools zem remote api.
License: MIT
Requires Python: >=3.11
Keywords: SEM, Calibration, Utilities

![pyzemrpc Banner](./doc/pyzemrpc_banner.png)

# pyzemrpc

**ZEM远程控制接口（python版本）**

`pyzemrpc` 是安徽泽攸科技（ZEPTOOLS）扫描电镜（SEM）的Python远程控制接口与工具集。它提供了一套Python API，允许开发者通过代码控制SEM设备，以及一个图形用户界面（GUI）用于交互式操作。

---

## ✨ 特性 (Features)

*   **远程控制**: 支持对ZEM系列扫描电镜的远程操作与监控。
*   **Python API**: 提供友好的Python接口，便于集成到自动化脚本或第三方软件中。
*   **图形界面**: 内置 `pyzemrpc` GUI 工具，开箱即用。
*   **配置灵活**: 基于 YAML 和 数据库 的灵活配置管理。

## 🚀 安装 (Installation)

### 依赖环境
*   Python 3.10+
*   Windows / Linux / MacOS

### 安装步骤

1.  克隆仓库：
    ```bash
    git clone https://gitee.com/zeyou-anhui/pyzemrpc.git
    cd pyzemrpc
    ```

2.  安装依赖并安装包：
    ```bash
    pip install .
    ```

    或者使用开发模式安装：
    ```bash
    pip install -e .
    ```

3.  或者使用pypi安装
    ```bash
    pip install pyzemrpc
    ```



## 🖥️ 使用 (Usage)

### 启动 GUI
安装完成后，可以直接在终端运行以下命令启动图形界面：
```bash
pyzemrpc
```

### 命令行工具
查看相关信息：
```bash
pyzemrpc_info
```

### Python 开发
在您的 Python 脚本中导入 `zemrpc`：

```python
import zemrpc
from zemrpc import app_cfg

# 示例代码 (具体API参考文档)
print(f"pyzemrpc version: {app_cfg.version}")
```

## 📄 文档 (Documentation)
更多详细文档和配置说明，请查阅 [doc](./doc) 目录。

## 🤝 贡献 (Contributing)
欢迎提交 Issue 或 Pull Request 来改进本项目。

## 📃 许可证 (License)
本项目采用 [MIT License](LICENSE) 开源。

---
Copyright © 2024-2026 ZEPTOOLS
bilbystats 0.1.8
Python Packages of functions for performing stats for bilby
License: MIT
Requires Python: >=3.9
Keywords: LLMs, Transformers

# BilbyStats

## A collection of statistical and machine learning functions for use in the Bilby pipeline

### Install the package

#### Pip installation
```bash
pip install bilbystats
```

#### Alternative: local installation
To pull the repo run

```bash
git clone --depth=1 https://github.com/bilbyai/bilbystats/
```
Navigate to the root directory of the package and run

```bash
uv pip install .
```

or just 
```bash
pip install .
```
if you don't have uv install.

### Set up API keys
API keys must be added in order to call LLMs. To do so they must be added to the environment. The simplest way to do so is to add lines of the following form to your .bashrc or .zshrc file. 

```bash
export OPENROUTER_API_KEY=exampleapikey
export OPENAI_API_KEY=exampleapikey
export CLAUDE_API_KEY=exampleapikey
```

Where you should replace exampleapikey with the corresponding API key in each case. 

### Importing the package

Then the package can be imported from within python via e.g.

```bash
import bilbystats as bs
```

### Setting local defaults
In order to set local defaults. E.g. for checkpoint saving etc. You'll need to navigate to 

cp bilbystats/defaults/local_defaults_example.env bilbystats/defaults/local_defaults.env

and then change the default parameters and reinstall the package.

### Run local LLMs using Ollama

If you'd like to use the Ollama functions which allow you to call LLMs on your local machine you'll need to install [Ollama](https://ollama.com/).
Once you've installed ollama you can download LLMs such as llama3.2

```bash
ollama run llama3.2
```

or deepseek-r1:7b

```bash
ollama run deepseek-r1:7b
```

See https://ollama.com/search for a full list of the available models.

To call the LLM programmatically using bilbystats you can run

```
bs.llm_api('test call', 'you are an llm', 'llama3.2')
```

or

```
bs.llm_api('test call', 'you are an llm', 'deepseek-r1:7b')
```

Or in general use the model name in any llm related function such as bs.translate.