semvec/pypi-packages huggingface dataset:
byteify 2
Turns files into bytes, useful for specific uses

 # Byteify
- This turns files into bytes or filestreams.
- Example code:
```python
import byteify
print(byteify.return_bytes("filename")) # this returns bytes, made for file specific tasks
print(byteify.return_filestream("filename")) # this returns a file object, with the file name, metadata and content on it. like opening a file
```
To install,
```bash
pip install byteify
```
corvic-engine 0.3.0rc155
Seamless embedding generation and retrieval.
Requires Python: <3.14,>=3.12

# Corvic Engine [![CI](https://github.com/corvicai/corvic-engine/actions/workflows/ci.yaml/badge.svg)](https://github.com/corvicai/corvic-engine/actions/workflows/ci.yaml) [![Python Version](https://img.shields.io/badge/python-3.12-blue)](https://www.python.org/downloads/release/python-3120/)
leilao-ai-common 1.0.2
Common utilities shared across leilao-ai projects
Requires Python: >=3.10

# leilao-ai-common

Common utilities shared across Leilao AI projects.

## Modules
- `leilao_ai_common.preprocess`: Image preprocessing transforms (ImageNet mean/std). Use `build_transform(image_size)`.
- `leilao_ai_common.config`: Helpers to resolve `classes` and `image_size` from training YAML or checkpoints.

## Install (editable)
```bash
pip install -e ./leilao-ai-common
```

## Usage
```python
from leilao_ai_common.preprocess import build_transform
from leilao_ai_common.config import resolve_classification_settings

# Build transform
transform = build_transform(448)

# Resolve classes and image size
classes, image_size = resolve_classification_settings(
    yaml_path="leilao-ai-damage-classifier/configs/train.yaml",
    checkpoint_path="leilao-ai-damage-classifier/outputs/training/run_resnet18_5/best_model.pt",
)
```
agentforge-cli 0.2.0
Registry and trust layer for AI agent skills
Requires Python: >=3.10

# agentforge (CLI: forge)

Registry and trust layer for AI agent skills. This package provides the **forge** command so you can create, inspect, publish, and install skills from the terminal.

## Install

```bash
pip install agentforge-cli
```

**If you need `forge auth login`** (GitHub login for publish) and your installed version doesn’t list an `auth` command, install from the repo so you get the latest CLI:

```bash
cd /path/to/AgentForge
pip install -e ./cli
forge auth login -r https://agentforgeprivate-production.up.railway.app
```

You can pass the registry URL with or without `https://` (e.g. `-r agentforgeprivate-production.up.railway.app` is normalized to `https://...`).

## Use

From any directory:

```bash
forge init              # scaffold a skill (skill.yaml + example code)
forge inspect           # show permissions and risk for the skill here
forge auth login -r URL # log in with GitHub (required before publish)
forge auth logout -r URL # clear saved login for a registry
forge publish -r URL   # publish to the registry (must be logged in)
forge search -r URL    # list skills
forge install <slug> -r URL  # record an install
```

**Publish requires GitHub login**  
Every skill is attached to a user. You must log in with GitHub once per registry:

```bash
forge auth login -r https://agentforgeprivate-production.up.railway.app
# Browser opens → authorize with GitHub → token is saved
forge publish -r https://your-backend.railway.app
```

**Registry URL (what `-r` is for)**  
The **registry** is the backend API that stores and serves skills. When you deploy the AgentForge backend (e.g. on Render or Railway), you get a URL like `https://agentforge-api.onrender.com`. That URL is your **registry URL**.

- **`forge publish`** sends your skill to that API so it appears on the website (explore skills + skill detail page) and in `forge search`. You must run **`forge auth login -r <URL>`** first.
- **`forge search`** and **`forge install`** read from that same API (no login required).

If you don't pass `-r`, the CLI defaults to `http://localhost:8000` (your own API running on your machine). For the **public** registry, pass its URL:

```bash
forge auth login -r https://agentforgeprivate-production.up.railway.app
forge publish -r https://agentforgeprivate-production.up.railway.app
forge search -r https://agentforgeprivate-production.up.railway.app
forge install send-email -r https://agentforgeprivate-production.up.railway.app
```

The registry for this project is **https://agentforgeprivate-production.up.railway.app** (Railway backend).

## Releasing a new version to PyPI

1. Bump **version** in `cli/pyproject.toml` (e.g. `0.2.0` → `0.2.1`).
2. From the repo root:
   ```bash
   pip install build twine
   cd cli && python -m build && python -m twine upload dist/*
   ```
3. Users get the update with `pip install --upgrade agentforge-cli`.

See the main repo **docs/DEPLOYMENT.md** (Part 1) for full steps and Test PyPI.

## Links

- [AgentForge](https://github.com/vince13/AgentForge) — repo and docs
stsci.skypac 1.0.12
Sky matching on image mosaic
Requires Python: >=3.10

# stsci.skypac

[![Documentation Status](https://readthedocs.org/projects/stsci-skypac/badge/?version=latest)](http://stsci-skypac.readthedocs.io/en/latest/?badge=latest)
[![build](https://github.com/spacetelescope/stsci.skypac/actions/workflows/publish-to-pypi.yml/badge.svg)](https://github.com/spacetelescope/stsci.skypac/actions/workflows/publish-to-pypi.yml)
[![PyPI Status](https://img.shields.io/pypi/v/stsci.skypac.svg)](https://pypi.org/project/stsci.skypac/)
[![Powered by Astropy Badge](http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat)](http://www.astropy.org/)

Sky matching for image mosaic.
stsci.tools 4.3.0
Collection of STScI utility functions
Requires Python: >=3.10
Keywords: astronomy, astrophysics, utility

# stsci.tools

[![Documentation Status](https://readthedocs.org/projects/stscitools/badge/?version=latest)](http://stscitools.readthedocs.io/en/latest/?badge=latest)
[![Github Actions CI Status](https://github.com/spacetelescope/stsci.tools/workflows/CI/badge.svg)](https://github.com/spacetelescope/stsci.tools/actions?query=workflow%3ACI)

STScI utility functions.