semvec/pypi-packages huggingface dataset:
tibet 0.4.2
TIBET - Transparency, Intent, Behavior, Evidence, Trust. AI provenance and security framework. Alias for tibet-audit.
Requires Python: >=3.10
Keywords: ai-security, audit, humotica, provenance, tibet, transparency, trust

# TIBET

**Transparency, Intent, Behavior, Evidence, Trust**

This is an alias package for [`tibet-audit`](https://pypi.org/project/tibet-audit/).

## Installation

```bash
pip install tibet
```

This automatically installs `tibet-audit` with all features:
- AI action provenance tracking
- Trust scoring (FIR/A model)
- Security auditing for AI systems
- ERIN/ERAAN/EROMHEEN/ERACHTER framework

## The TIBET Philosophy

Every AI action has four dimensions:
- **ERIN**: What's IN the action (the content)
- **ERAAN**: What's attached (dependencies, references)
- **EROMHEEN**: Context around it (environment, state)
- **ERACHTER**: Intent behind it (why this action)

## Usage

CLI tool:
```bash
tibet-audit scan /path/to/project
tibet-audit fix /path/to/project
```

Python API:
```python
from tibet import *
```

## Part of HumoticaOS

TIBET is part of the [HumoticaOS](https://humotica.com) ecosystem - AI and human in symbiosis.

One love, one fAmIly!
rabel 0.3.2
RABEL - Recidive Active Brain Environment Layer. Alias package for mcp-server-rabel.
Requires Python: >=3.10
Keywords: ai, humotica, knowledge-graph, mcp, memory, rabel, semantic-search

# RABEL

**Recidive Active Brain Environment Layer**

This is an alias package for [`mcp-server-rabel`](https://pypi.org/project/mcp-server-rabel/).

## Installation

```bash
pip install rabel
```

This automatically installs `mcp-server-rabel` with all features:
- Local-first AI memory with semantic search
- Graph relations between memories
- Soft pipelines for data processing
- Remote Mode for cross-machine AI communication
- I-Poll integration for AI-to-AI messaging

## Usage

For MCP server:
```bash
mcp-server-rabel
```

For Python API:
```python
from rabel import *
```

## Part of HumoticaOS

RABEL is part of the [HumoticaOS](https://humotica.com) ecosystem - AI and human in symbiosis.

One love, one fAmIly!
semantido 0.1.2
Semantic layer for SQLAlchemy models that auto-generates LLM-ready schema with rich semantic metadata for text-to-SQL systems and LLM-powered database interactions
Requires Python: >=3.11

# Semantido

[![PyPI - Version](https://img.shields.io/pypi/v/semantido.svg)](https://pypi.org/project/semantido)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/semantido.svg)](https://pypi.org/project/semantido)

-----

Table of Contents
-----

- [About](#about)
- [Installation](#installation)
- [Contributing](#contributing)
- [License](#license)

About
-----
In the world of GenAI, providing a reliable semantic layer foundations for a reliable RAG and agentic systems becomes the real differentiator. 
The value is in your data and workflows. `semantido` handles the semantic layer plumbing so you can focus on what makes your system unique.

-----

```console
pip install semantido
```

Contributing
-----
Contributions to this library are welcomed and highly encouraged.
See [CONTRIBUTING.md](https://github.com/hikarilabs/semantido/blob/main/CONTRIBUTING.md) for more information on how to get started.

License
-----
`semantido` is distributed under the terms of the [Apache License 2.0](https://spdx.org/licenses/Apache-2.0.html) license.