semvec/pypi-packages huggingface dataset:
yltk 0.1.1
---

# Yoruba Language Took Kit

The Yoruba language toolkit was developed as a tool for processing and preprocessing Yoruba language.
In the similitude of how the NLTK works, where stopwords, stem, lemmas are handle while processing languages, the YLTK is also equipped with various tools ranging from the stopwords in Yoruba and other things are under development.

- [Installation](#installation)
- [Usage](#usage)
- [Features](#features)
- [Contributing](#contributing)
- [License](#license)
- [Authors](#authors)

## Installation
Clone the repository:
   ```bash
   git clone https://github.com/username/project-name.git
   ```
Activate virtual environment
   ```bash
    YLTK\Scripts\activate
   ```
Install requirement
   ```bash
    pip install -r requirements.txt
   ```

Add you API_KEY
```bash
   export API_KEY='your-api-key-here'
   ```

## Usage
Run the script:
   ```bash
    python detect.py --url https://example.com
   ```

## Features
- Batch processing of large text to extract Yoruba texts alone with the method `extract_yoruba_words`.
- Frequency count for each words with the method `word_frequency_count`.
- Generate Stop words that is higher than a specified frequency with the method `stop_words`.
- Batch Stop words removal from a large Yoruba text using the method `remove_stopwords`

## Contributing
Contributions are welcome! Please follow these steps:
1. Fork the repository.
2. Create a feature branch: `git checkout -b feature-name`.
3. Commit your changes: `git commit -m "Add feature-name"`.
4. Push the branch: `git push origin feature-name`.
5. Submit a pull request.

## Testing
Run the tests using:
   ```bash
   pytest tests/
   ```

## License
This project is licensed under the MIT License. See the LICENSE file for details.

## Authors
1. Kolade Atanseiye: koladeatanseiye@gmail.com
ai-benchmarks 0.1.6
HS-QA
Requires Python: <4.0,>=3.9

# LLM 推理服务基准测试

本仓库包含了测试常见推理服务吞吐的代码以及相关的测试结果。

## 安装说明

### 基础环境

- Python 3.9 或以上版本
- Poetry (非必须)

请使用以下命令安装 Poetry：
```bash
pip install poetry
```

## 运行方式

### [通过 pip 线上安装运行]

    pip install ai_benchmarks
    run-benchmark -h
    run-app

### [通过 pip手动构建安装运行]

1. **构建包或以其他方式获取：**
    ```bash
    cd ai-benchmarks && poetry build
    ```

2. **安装包：**
    ```bash
    pip install ai_benchmarks-x.x.x.tar.gz
    ```

3. **接口运行方式：**
   - 启动后可访问 [127.0.0.1:8012/docs](http://127.0.0.1:8012/docs) 查看接口文档。
    ```bash
    run-app
    ```

4. **直接运行方式,-h查看帮助，默认执行配置文件默认测试端点：**
    ```bash
    run-benchmark -h
    ```

### [通过代码运行]

1. **安装依赖：**
    ```bash
    cd ai-benchmarks
    poetry安装
    poetry lock && poetry install
    requirements安装
    pip install -i https://mirrors.aliyun.com/pypi/simple/   -r .\requirements.txt
    ```

2. **`benchmark.py`** 是主要的压测脚本，采用 asyncio、AsyncOpenAI 和 ProcessPoolExecutor等 实现多端压测框架。

3. **直接运行压测：**
    ```bash
    poetry run python -m inference.benchmark
    ```

4. **启动接口压测：**
   - 启动后可访问 [127.0.0.1:8012/docs](http://127.0.0.1:8012/docs) 查看接口文档。
    ```bash
    poetry run python -m inference.main
    ```

5. **测试报告和结果：**
   - 测试报告输出到 `inference/report` 文件夹。
   - 原始测试结果数据输出到 `inference/results` 文件夹，可使用 `draw.ipynb` 进行绘图。

## 配置文件说明

```yaml
[section]                  # 支持多section
endpoint:                  # *必须提供一个有效的 endpoint
api_key:                   # 认证KEY
concurrent_requests:       # 同时并发的请求数
batch:                     # 执行批次
duration_enabled:          # 启用持续请求的时间限制（开启后不执行 concurrent_requests）[True/False]
duration_time:             # 请求持续时间，默认为 1 秒
duratio_interval:          # 持续/请求间隔，默认0.2秒
duration_batch:            # 请求持续时间内每次并发数量，默认为 10
ip:                        # 用户查询机器资源占用
username:                  # 用户名
password:                  # 密码
timeout:                   # 超时时间，默认 60 秒
max_retries:               # 最大重试次数，默认 1
max_connections:           # 最大连接数
max_keepalive_connections: # 最大保持活动连接数
model:                     # 自动获取，可手动添加
owned_by:                  # 自动获取，可手动添加
stream:                    # 流式回复默认关闭[True/False]
prompts:                   # 问题, 为空自动匹配默认问题, 格式 [{"id": 1, "prompt": "Output from 1 to 100"}, {"id": 2, "prompt": "List the top 10 most important people in history."},]
create-pipenv-project 1.0
A CLI tool for creating Python projects with Pipenv workflow.
Requires Python: >=3.11

# create_pipenv_project
A CLI tool for creating Python projects with Pipenv workflow.

## Extra Features
- ✅ **Type Checking:**
Preinstalled with [mypy](https://mypy-lang.org/) + `mypy.ini` configuration file.
- 📝 **Logging:**
Available with nice and colorful format + some other debugging tools.
Uncaught exceptions are also captured to allow error logging for the entire program.
- 🔁 **asyncio:**
Asynchronous programming out of the box using [uvloop](https://github.com/MagicStack/uvloop).
No need to setup your own event loop.
- 🧪 **pytest:**
Run tests with [coverage](https://coverage.readthedocs.io/) + [pytest](https://pytest.org/).
- ✨ **Formatter:**
Preinstalled with [Black](https://pypi.org/project/black/)
Python code formatter for codebase consistency.
- 🐍 **And more!**

## Installation
```bash
pip install create_pipenv_project
```

## Usage
```bash
create_pipenv_project
```