semvec/pypi-packages huggingface dataset:
nebuia-copilot-python 0.0.16
NebuIA Copilot python integration
Requires Python: >=3.8

# Nebuia Integration Library

This library provides an interface to interact with the Nebuia API, allowing operations for document processing, custom brain searching, and batch management.

## Key Features

- Integrator initialization with API credentials
- Custom brain searching
- Document management (retrieve, clear, delete)
- Batch handling (create, get documents, add files)
- Document type retrieval

## Installation

[Specific installation instructions for each language]

## Basic Usage

```[language]
# Integrator initialization
integrator = Integrator(with_base='http://nebuia.instance/api/v1', key='api_key', secret='api_secret')

# Usage example: Custom brain search
results = integrator.search_in_brain(search_params=SearchParameters(batch="brain_id", param="flu", k=2, type_search="literal"))

# Usage example: Get documents by status
docs = integrator.get_documents_by_status(status=StatusDocument.ERROR_LINK)

# Usage example: Create a new batch
status, batch_id = integrator.create_batch("name_batch", batch_type=BatchType.TESTING)
```

## API Reference

### Integrator Class

#### Main Methods:

- `search_in_brain(search_params: SearchParameters) -> dict`
- `get_documents_by_status(status: StatusDocument) -> list`
- `clear_document_by_uuid(uuid: str) -> dict`
- `delete_document(uuid: str) -> dict`
- `get_documents_by_batch_id(batch_id: str) -> BatchDocuments`
- `append_to_batch(batch_id: str, files: list[File]) -> dict`
- `get_document_types() -> list[DocumentType]`
- `create_batch(name: str, batch_type: BatchType) -> tuple[bool, str]`

### Data Structures

- `File`: Represents a file to process
- `SearchParameters`: Parameters for brain searching
- `StatusDocument`: Enumeration of document statuses
- `BatchType`: Enumeration of batch types

## Error Handling

The library uses the Loguru logger to log information and errors. Make sure to configure Loguru appropriately in your application.

## Implementation Notes

- The library should handle API responses and convert them into appropriate data structures for each language.
- Input validations should be implemented for method parameters.
- Error handling should be consistent across all methods, using specific exceptions when appropriate.

## Contributions

[Instructions for contributing to the project]

## License

[License information]
binaryBHexp 1.0.4
The binary Black Hole explorer (visualizations).
Keywords: black-holes gravitational-waves visualization

[![github](https://img.shields.io/badge/GitHub-binaryBHexp-blue.svg)](https://github.com/vijayvarma392/binaryBHexp)
[![PyPI version](https://badge.fury.io/py/binaryBHexp.svg)](https://pypi.org/project/binaryBHexp/)
[![license](https://img.shields.io/badge/license-MIT-blue.svg)](https://github.com/vijayvarma392/binaryBHexp/blob/master/LICENSE)
[![Build Status](https://github.com/vijayvarma392/binaryBHexp/actions/workflows/test.yml/badge.svg)](https://github.com/vijayvarma392/binaryBHexp/actions/workflows/test.yml)

# binaryBHexp
The binary Black Hole explorer.

<img src="https://raw.githubusercontent.com/vijayvarma392/binaryBHexp/master/animations/example.png" alt="snapshot" width="400px"/>

Generates visualizations of precessing binary black hole mergers and the final
remnant black holes.

See our [webpage](https://vijayvarma392.github.io/binaryBHexp/) for more details.
hmedia 1.0.0
Django本地存储的图片，前端调用通过参数生成缩略图与格式转换
Requires Python: >=3

# HMedia实现对本地化图片的丝滑般生成缩略图

我经常使用阿里云的oss服务，我最喜欢oss的功能就是通过简单的参数，就能实现图片的缩略图与格式转换。

但是，如果图片使用本地存储时候，就没办法使用oss的生成缩略图和格式转换功能了。

所以，借着一个项目必须本地化部署的背景，我写了一个模块，让前端方便进行对应渲染。

# 快速开始

## 安装

```bash
pip install hmedia
```

在url.py中增加以下代码

```python
from django.urls import re_path
from hmedia.views import hmedia

urlpatterns = [
    re_path(r'^media/(?P<path>.*)$', hmedia),
]
```

注意，示例中urlpatterns的内容，是增加在您原有内容里，不是覆盖。

另外，media目录是在settings里配置的静态文件目录。如果你不一样，请修改，我的settings内容如下：

```python
MEDIA_URL = 'media/'
MEDIA_ROOT = os.path.join(BASE_DIR, 'media/')
```

所以是media。

## 使用方式

前端调用时候，参考阿里云的oss语法规范，目前仅支持图片缩放、格式转换功能。

传送门：[阿里云oss图片处理](https://help.aliyun.com/zh/oss/user-guide/resize-images-4?spm=a2c4g.11186623.0.i1)

也可以在oss管理中的数据处理里，配置图片处理规则，参考其设定的前端调用代码。

# 版本历史

1.0.0 首次发布