semvec/pypi-packages huggingface dataset:
baicai-tutor 0.1.0
AI tutor for Everyone
License: MIT
Requires Python: <3.12,>=3.10
Keywords: python, agent, AI, machine learning, LLM

# Baicai Tutor

An AI-powered tutoring system designed to provide personalized learning experiences for everyone.

## Overview

Baicai Tutor is an intelligent tutoring system that leverages advanced AI technologies to create adaptive and engaging learning experiences. It's built on top of the Baicai Base framework and aims to make quality education accessible to all.

## Features

- AI-powered personalized tutoring
- Adaptive learning paths
- Interactive learning experiences
- Comprehensive knowledge base
- Real-time feedback and assessment

## Requirements

- Python 3.10 or higher (but less than 3.12)
- Poetry for dependency management

## Installation

1. Clone the repository:

```bash
git clone https://github.com/yourusername/baicai_tutor.git
cd baicai_tutor
```

2. Install dependencies using Poetry:

```bash
poetry install
```

3. Activate the virtual environment:

```bash
poetry shell
```

## Usage

The project provides a command-line interface:

```bash
baicai-tutor
```

## Development

### Project Structure

```
baicai_tutor/
├── baicai_tutor/    # Main package directory
├── docs/            # Documentation
├── tests/           # Test files
└── pyproject.toml   # Project configuration
```

### Development Tools

- **Testing**: pytest (>=8.0.0)
- **Type Checking**: mypy (>=1.5.0)
- **Code Formatting**: ruff (^0.11.6)
- **Documentation**: mkdocs (optional)

### Running Tests

```bash
poetry run pytest
```

### Code Quality

The project uses several tools to maintain code quality:

- **Type Checking**:

```bash
poetry run mypy .
```

- **Code Formatting**:

```bash
poetry run ruff format .
```

- **Linting**:

```bash
poetry run ruff check .
```

## Documentation

Documentation is available in the `docs/` directory and can be built using MkDocs:

```bash
poetry run mkdocs build
```

## Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

## License

This project is licensed under the [GPL-3.0](https://www.gnu.org/licenses/gpl-3.0.en.html) License.

## Authors

- Zhaoyang tech <gengyabc@aliyun.com>

## Acknowledgments

- Built on top of the Baicai Base framework
- Uses various open-source libraries and tools
xyra-auth 1.0.1
Termux Authentication System - Sistem Autentikasi dengan OTP Email
License: MIT
Requires Python: >=3.8
Keywords: termux, auth, authentication, otp, email, security

# XYRA Auth

Termux Authentication System - Sistem Autentikasi dengan OTP Email untuk Termux

## Fitur

- Signup dengan verifikasi OTP email
- Login dengan Supabase
- Template email OTP yang keren
- Kode OTP berlaku 5 menit
- 3x percobaan input OTP
- Auto-install dependensi
- Konfigurasi terenkripsi (aman)

## Instalasi

```bash
pip install xyra-auth
```

## Penggunaan

### Sebagai Command Line

```bash
xyra-auth
```

### Sebagai Module Python

```python
from xyra_auth import main
main()
```

### Menjalankan sebagai Module

```bash
python -m xyra_auth
```

## Persyaratan

Pastikan Anda memiliki file-file berikut di direktori kerja:

- `termux_auth_lib*.so` - Binary module (minta dari developer)
- `config.enc` - File konfigurasi terenkripsi

## Instalasi di Termux

```bash
# Update Termux
pkg update && pkg upgrade

# Install Python
pkg install python

# Install xyra-auth
pip install xyra-auth

# Jalankan
xyra-auth
```

## Menu Utama

1. **Signup** - Daftar akun baru
2. **Login** - Masuk ke akun
3. **Resend** - Kirim ulang OTP
4. **Reset** - Lupa password
5. **Exit** - Keluar

## Troubleshooting

### "File .so tidak cocok dengan device"
File .so harus sesuai arsitektur (ARM untuk Termux). Minta file .so versi ARM dari developer.

### "File .so tidak ditemukan"
Pastikan file `termux_auth_lib*.so` ada di folder yang sama.

### "File config tidak ditemukan"
Pastikan `config.enc` ada di folder yang sama.

### "OTP expired"
Kode hanya berlaku 5 menit, kirim ulang OTP.

## Kontak

Email: xyraofficialsup@gmail.com

## Lisensi

MIT License
baicai-dev 0.1.0
Development package for Baicai
License: MIT
Requires Python: <3.12,>=3.10
Keywords: python, agent, AI, machine learning, LLM

# Baicai Dev

A (not) powerful Python package for AI workflow development, built on top of LangChain and LangGraph frameworks.

## Overview

Baicai Dev is a development toolkit designed to streamline the creation and management of AI workflows. It provides a flexible framework for building, testing, and deploying AI-powered applications using LangChain and LangGraph.

## Features

- Workflow development and management
- Integration with LangChain and LangGraph
- Support for multiple LLM providers
- Development and testing utilities
- Code quality and type checking tools

## Requirements

- Python 3.10 or higher (but less than 3.12)
- Poetry for dependency management

## Installation

1. Clone the repository:

```bash
git clone [repository-url]
cd baicai-dev
```

2. Install dependencies using Poetry:


> MacOs
    > 1. The torchvision package is trying to use the lzma module. The lzma module depends on the _lzma C extension. To fix this, you need to install the XZ development libraries, which provide the required LZMA support, you can install this using Homebrew: `brew install xz`
    > 2. libomp.dylib for lightgbm, solve by `brew install libomp`

```bash
poetry install
```

## Development Setup

1. Create and activate a virtual environment:

```bash
poetry shell
```

2. Install development dependencies:

```bash
poetry install --with dev
```

## Project Structure

```
baicai-dev/
├── baicai_dev/     # Main package directory
├── tests/          # Test files
├── pyproject.toml  # Project configuration
└── README.md       # This file
```

## Development Tools

The project uses several development tools to maintain code quality:

- **pytest**: For testing
- **mypy**: For static type checking
- **ruff**: For linting and code formatting

## Code Style

The project follows strict code style guidelines:

- Line length: 120 characters
- Indentation: 4 spaces
- Quote style: Double quotes
- Type hints are required

## Testing

Run tests using pytest:

```bash
pytest
```

## License

This project is licensed under the [GPL-3.0](https://www.gnu.org/licenses/gpl-3.0.en.html) License.

## Authors

- Zhaoyang tech <gengyabc@aliyun.com>

## Contributing

1. Fork the repository
2. Create your feature branch
3. Commit your changes
4. Push to the branch
5. Create a new Pull Request

## Keywords

- Python
- AI
- Workflow
- LangChain
- LangGraph

## Example data

- Fisher, R. (1936). Iris [Dataset]. UCI Machine Learning Repository. <https://doi.org/10.24432/C56C76>.
- This dataset was obtained from the StatLib repository. <https://www.dcc.fc.up.pt/~ltorgo/Regression/cal_housing.html>
- seaborn-data/titanic.csv <https://github.com/mwaskom/seaborn-data/blob/master/titanic.csv>
- Productivity Prediction of Garment Employees [Dataset]. (2020). UCI Machine Learning Repository. <https://doi.org/10.24432/C51S6D>.
cleon 0.1.15
A Genetic Dynasty of Agentic Clones for Jupyter Notebooks
License: MIT
Requires Python: >=3.9
Keywords: codex, cleon, ipython

[![PyPI version](https://img.shields.io/pypi/v/cleon.svg)](https://pypi.org/project/cleon/)
[![PyPI downloads](https://img.shields.io/pypi/dm/cleon.svg)](https://pypistats.org/packages/cleon)
[![Python versions](https://img.shields.io/pypi/pyversions/cleon.svg)](https://pypi.org/project/cleon/)
[![License](https://img.shields.io/pypi/l/cleon.svg)](https://pypi.org/project/cleon/)

# Cleon

<img src="img/cleon.jpg" alt="Cleon logo" style="max-height:300px;">

Cleon brings the magic of LLM Agents to Jupyter notebooks.
Have interactive conversations about your notebook and even have agents augment and run cells using the Jupyter extension.

Bring your own tokens via Codex, Claude or Gemini subscriptions or standard token apis.

## Features
- invocation is as low friction as typing a single configurable prefix in a code cell
- run code at the same time while waiting for agents to respond
- queue agent prompts and approve actions just like cli agents

## Default Prefixes
`: hi codex`  
`~ hi claude`  
`> hi gemini` <- currently slow  

## Installation

### Default (extension included, no Jupyter)
`pip install cleon`

This installs the Python magics and backend plus the prebuilt Cleon extension package, but does not pull in JupyterLab itself (so it won’t reinstall Jupyter if you already have it).

Launch with the bundled helper (creates/uses `~/.cache/cleon/jupyter-env`):

```
cleon jupyter lab
```

You can also run `cleon jupyter notebook` if you prefer the classic UI.

The launcher will install JupyterLab + the Cleon extension into its managed env if they’re missing. If you install the Cleon Jupyter extension while Jupyter is running, restart Jupyter (and refresh the browser) so the extension loads.

### Full install into your current env
`pip install "cleon[jupyter]"`

This pulls in JupyterLab 4+ and the prebuilt Cleon extension into your active environment.

### Minimal install
Need to skip Jupyter/extension? Install without deps and add only what you want:

```
pip install --no-deps cleon
```

There is a placeholder extra `cleon[no-jupyter]`, but it’s a no-op; use `--no-deps` for a truly lean install.

![Cleon install](img/install.jpg)  


## Usage
![Cleon in use](img/use.jpg) 


## Codex
- Make sure your codex is already authed, or copy your `~/.codex/auth.json` from another machine.

## Claude Code
- Install `npm install -g @mariozechner/pi-coding-agent`  
- Run `cleon.login()`  
- Complete auth token flow

## Sessions
- Currently supports `codex` sessions, try `cleon.stop()` and `cleon.resume()`

## Options
- cleon.status()
- cleon.sessions()
- cleon.resume()
- cleon.stop()
- cleon.mode("learn")
- cleon.mode("do")

## Bugs or Feedback
- Twitter/X: [x.com/madhavajay](https://x.com/madhavajay)
- Blog: [madhavajay.com](https://madhavajay.com)