semvec/pypi-packages huggingface dataset:
tropass-sdk 0.1.7
Tropass SDK helps you develop and manage your models for Tropass platform
Requires Python: <4,>=3.10
Keywords: python, ai, tropass, models, ai-model, ai-sdk, python-sdk, llm

<p align="center">
    <img src="https://raw.githubusercontent.com/tropass-ai/tropass-sdk/main/logo.svg" width="350">
</p>
<br>
<p align="center">
    <a href="https://codecov.io/gh/tropass-ai/tropass-sdk" target="_blank"><img src="https://codecov.io/gh/tropass-ai/tropass-sdk/branch/main/graph/badge.svg"></a>
    <a href="https://pypi.org/project/tropass-sdk/" target="_blank"><img src="https://img.shields.io/pypi/pyversions/tropass-sdk"></a>
    <a href="https://pypi.org/project/tropass-sdk/" target="_blank"><img src="https://img.shields.io/pypi/v/tropass-sdk"></a>
    <a href="https://pypistats.org/packages/tropass-sdk" target="_blank"><img src="https://img.shields.io/pypi/dm/tropass-sdk"></a>
</p>

**tropass-sdk** — это инструмент для разработки и управления ML-моделями на платформе Тропасс.

---

## 📦 Установка


```bash
# Для pip
pip install tropass-sdk[server]

# Для uv
uv add tropass-sdk[server]

# Для poetry
poetry add tropass-sdk[server]

```

---

## 🛠 Подготовка приложения

Для инициализации сервера достаточно передать функцию предсказания в класс `ModelServer`.

### Ключевые требования:
* Функция предсказания обязана принимать схему запроса модели `MLModelRequestSchema`.
* Функция предсказания обязана возвращать схему ответа модели `MLModelResponseSchema`.
* Инстанс `ModelServer` обязан находиться в файле `main.py` в корне проекта.

```python
from tropass_sdk.server import ModelServer
from tropass_sdk.schemas.model_contract_schema import MLModelRequestSchema, MLModelResponseSchema

def predict_handler(data: MLModelRequestSchema) -> MLModelResponseSchema:
    # Логика инференса модели
    return MLModelResponseSchema(panel_items=[])

server = ModelServer(
    model_func=predict_handler,
    model_name="my_model",
    model_description="Production model description",
    model_version="1.0.0",
    debug=False
)

```

---

## ⚡ Варианты запуска

Для запуска создайте экземпляр приложения c помощью метода `build_application`. Важно! Имя приложения обязательно должно быть `application`:

```python
application = server.build_application()

```

Запуск: `uvicorn main:application --host 0.0.0.0 --port 8000 --workers 4`

---

## 🔍 Мониторинг и наблюдаемость

Благодаря интеграции с [microbootstrap](https://github.com/community-of-python/microbootstrap), сервис из коробки поддерживает:

* **Метрики:** Доступны по эндпоинту `/metrics` в формате Prometheus.
* **Health Checks:** Проверка состояния сервиса доступна по пути `/health`.
* **Логирование:** Структурированные логи готовы к сбору в ELK/Loki.

---
adi-doctools 0.4.37
ADI's sphinx extensions and theme
Requires Python: >=3.8

# Analog Devices Doctools

[Analog Devices Inc.](http://www.analog.com/en/index.html)
central repository to host tooling for automated documentation builds.
It includes Sphinx extensions, themes, and tools for multiple repositories in
the organization.

All tools, directives and roles are documented in this repository documentation.

Guarantee to work with Python newer than 3.8 and distros released on or after 20H1
(e.g. Ubuntu 20.04 LTS).

## Release install

Ensure pip is newer than 23.0 [1]:
```
pip install pip --upgrade
```
Install the documentation tools, which will fetch this repository release:
```
(cd docs ; pip install -r requirements.txt)
```
Build the documentation with Sphinx:
```
(cd docs ; make html)
```
The generated documentation will be available at `docs/_build/html` and it
provides information about the `adoc` command line tool and general documentation
guidelines.

In summary, the `serve` allows to live reload the documentation when editing
the docs, and `aggregate` to generate an aggregated documentation of the multiple
repositories.

[1] There is a [known bug](https://github.com/pypa/setuptools/issues/3269)
with pip shipped with Ubuntu 22.04

### Using a Python virtual environment

Installing packages at user level through pip is not always recommended, instead,
consider using a Python virtual environment (``python3-venv`` on ubuntu 22.04).
To create and activate the environment, do before the previous instructions:
```
python3 -m venv ./venv
source ./venv/bin/activate
```
Use ``deactivate`` to exit the virtual environment.

For next builds, just activate the virtual environment:
```
source ./venv/bin/activate
```

## Development install

Development mode allows to edit the source code and apply the changes without
reinstalling.
Also extends Author Mode to watch changes on the webpage source code
(use `--dev`/`-r` option to enable this).

### Install the web compiler

If you care about the web scripts (`js modules`) and style sheets (`sass`),
install `npm` first, if not, just skip this section.

> **_NOTE:_** If the ``npm`` provided by your package manager is too old and
> updating with `npm install npm -g` fails, consider installing with
> [NodeSource](https://github.com/nodesource/distributions).

At the repository root, install the `npm` dependencies locally:
```
npm install rollup \
    @rollup/plugin-terser \
    sass \
    --save-dev
```

### Fetch third-party resources

Fetch third-party fonts:
```
./ci/fetch-fonts.sh
```

### Install the repository

Finally, do a symbolic install of this repo:
```
pip install -e . --upgrade
```

## Removing

To remove, either release or development, do:
```
pip uninstall adi-doctools
```
openlayer-guardrails 0.2.0
Guardrails that can be used to check inputs and outputs of functions and works well with Openlayer tracing.
Requires Python: >=3.10

# Openlayer Guardrails

Open source guardrail implementations that work with Openlayer tracing.

## Installation

```bash
pip install openlayer-guardrails
```

## Usage

### Standalone Usage

```python
from openlayer_guardrails import PIIGuardrail

# Create guardrail
pii_guard = PIIGuardrail(
    block_entities={"CREDIT_CARD", "US_SSN"},
    redact_entities={"EMAIL_ADDRESS", "PHONE_NUMBER"}
)

# Check inputs manually
data = {"message": "My email is john@example.com and SSN is 123-45-6789"}
result = pii_guard.check_input(data)

if result.action.value == "block":
    print(f"Blocked: {result.reason}")
elif result.action.value == "modify":
    print(f"Modified data: {result.modified_data}")
```

### With Openlayer Tracing

```python
from openlayer_guardrails import PIIGuardrail
from openlayer.lib.tracing import trace

# Create guardrail
pii_guard = PIIGuardrail()

# Apply to traced functions
@trace(guardrails=[pii_guard])
def process_user_data(user_input: str):
    return f"Processed: {user_input}"

# PII is automatically handled
result = process_user_data("My email is john@example.com")
# Output: "Processed: My email is [EMAIL-REDACTED]"
```
fabric-cicd 0.2.0
Microsoft Fabric CI/CD
Requires Python: <3.13,>=3.9

# Fabric CICD

[![Language](https://img.shields.io/badge/language-Python-blue.svg)](https://www.python.org/)
[![PyPi version](https://badgen.net/pypi/v/fabric-cicd/)](https://pypi.org/project/fabric-cicd)
[![Python version](https://img.shields.io/pypi/pyversions/fabric-cicd)](https://pypi.org/project/fabric-cicd)
[![Code style: ruff](https://img.shields.io/badge/code%20style-ruff-000000.svg)](https://github.com/charliermarsh/ruff)
[![Tests](https://img.shields.io/github/actions/workflow/status/microsoft/fabric-cicd/test.yml?logo=github&label=tests&branch=main)](https://github.com/microsoft/fabric-cicd/actions/workflows/test.yml)

---

## Project Overview

fabric-cicd is a Python library designed for use with [Microsoft Fabric](https://learn.microsoft.com/en-us/fabric/) workspaces. This library supports code-first Continuous Integration / Continuous Deployment (CI/CD) automations to seamlessly integrate Source Controlled workspaces into a deployment framework. The goal is to assist CI/CD developers who prefer not to interact directly with the Microsoft Fabric APIs.

## Documentation

All documentation is hosted on our [fabric-cicd](https://microsoft.github.io/fabric-cicd/) GitHub Pages

Section Overview:

-   [Home](https://microsoft.github.io/fabric-cicd/latest/)
-   [How To](https://microsoft.github.io/fabric-cicd/latest/how_to/)
-   [Examples](https://microsoft.github.io/fabric-cicd/latest/example/)
-   [Contribution](https://microsoft.github.io/fabric-cicd/latest/contribution/)
-   [Changelog](https://microsoft.github.io/fabric-cicd/latest/changelog/)
-   [About](https://microsoft.github.io/fabric-cicd/latest/help/) - Inclusive of Support & Security Policies

## Installation

To install fabric-cicd, run:

```bash
pip install fabric-cicd
```

## Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow [Microsoft's Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general). Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.