semvec/pypi-packages huggingface dataset:
tema-ai 0.17.0
A connector to the Tema AI APIs
Requires Python: <3.13,>=3.8

<p align="center">
 <img width="300px" src="https://github.com/tema-ai/.github/blob/production/profile/images/WorldLoop.gif?raw=true" align="center" alt="GitHub Readme Stats" />
 <h2 align="center">Tema AI</h2>
 <p align="center">A library to connect to Tema AI data</p>
</p>


<p align="center">
  <img src="https://img.shields.io/badge/python-3.8|3.9|3.10|3.11|3.12-navy.svg" />
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    <img src="https://api.codeclimate.com/v1/badges/7f59c6625078be938fff/maintainability">
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    <img src="https://api.codeclimate.com/v1/badges/7f59c6625078be938fff/test_coverage">
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</p>
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  <a href="https://github.com/tema-ai/tema_ai_connect/actions/workflows/black.yml">
    <img alt="Black" src="https://github.com/tema-ai/tema_ai_connect/actions/workflows/black.yml/badge.svg" />
  </a>
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    <img alt="release" src="https://github.com/tema-ai/tema_ai_connect/actions/workflows/publish-to-pypi.yml/badge.svg?event=release"/>
  </a>
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    <img alt="typing" src="https://github.com/tema-ai/tema_ai_connect/actions/workflows/mypy.yml/badge.svg"/>
  </a>
</p>

### Setting up the connection

You will need access to Tema AI API in order to use this library. Please generate the appropriate API client id and secret as well as the connection. Once you have those 3 values in addition to the sharing host you can configure the library to connect to the systems. Refer to the provided documentation to know how to generate those values if you don't already have them. Test

### Setting up the environment

You have two options to provide the access variables:

1. Provide them as environment variables and the code will automatically pick them up.

    ```bash
    export TEMA_AI_CONNECTION=connector_name
    export TEMA_AI_HOST=https://provided-host.ai
    export TEMA_AI_CLIENT_ID=HCD35....HAm34
    export TEMA_AI_CLIENT_SECRET=n...ryA
    ```

    or provide them in an environment file

    ```bash
    #.env

    TEMA_AI_CONNECTION=connector_name
    TEMA_AI_HOST=https://provided-host.ai
    TEMA_AI_CLIENT_ID=HCD35....HAm34
    TEMA_AI_CLIENT_SECRET=n...ryA
    ```

    ```python
    from tema_ai.connect import TemaAIShareAPI

    connection = TemaAIShareAPI()
    ```

2. Or simply provide them on runtime

    ```python
    from tema_ai.connect import TemaAIShareAPI

    connection = TemaAIShareAPI(
        connection_name="connector_name",
        host="https://provided-host.ai",
        client_id="HCD35....HAm34"
        client_secret="n...ryA"
    )

    ```

3. Alternatively you can mix and match and provide some of the variables through the environment and some directly to the class.
actor-rtc 0.1.0
Actor RTC bindings for Python
Requires Python: >=3.8
Keywords: actor, web-rtc, signaling

# actor-rtc python binding

## 简介
actor-rtc-py 是一个将 Rust 编写的 actor-rtc 库包装为 Python 模块的项目，使用 PyO3 框架创建高性能 Python 绑定。
它基于 Actor 模型实现 WebRTC 点对点通信，为 Python 应用提供简单高效的实时通信功能。


## 特性

- Actor 模型：采用 Actor 编程模型，每个参与者（Actor）拥有独立的状态和行为，通过消息传递进行通信
- WebRTC 通信：尽量利用 WebRTC 技术实现点对点通信，无需中心服务器中转数据
- 高性能：核心逻辑由 Rust 实现，提供卓越的性能和内存安全
- 类型支持：自动生成 .pyi 文件，提供完整的类型提示
- 错误处理：Rust 错误被优雅地转换为 Python 异常

## 安装

```shell
pip install actor_rtc
```

## 构建项目

使用示例：[examples/main.py](examples/main.py)
生成 pyi 文件：actor-rtc-py 目录下，执行 `cargo run --bin stub_gen`

```shell
python -m venv .env
source .env/bin/activate
pip install maturin
maturin develop
python examples/main.py
```