semvec/pypi-packages huggingface dataset:
pvmlib 1.9.11
Python library for PVM
License: MIT
Requires Python: >=3.12

# Introduction 
TODO: Give a short introduction of your project. Let this section explain the objectives or the motivation behind this project. 

# Getting Started
TODO: Guide users through getting your code up and running on their own system. In this section you can talk about:
1.	Installation process
2.	Software dependencies
3.	Latest releases
4.	API references

# Build and Test
TODO: Describe and show how to build your code and run the tests. 

# Contribute
TODO: Explain how other users and developers can contribute to make your code better. 

If you want to learn more about creating good readme files then refer the following [guidelines](https://docs.microsoft.com/en-us/azure/devops/repos/git/create-a-readme?view=azure-devops). You can also seek inspiration from the below readme files:
- [ASP.NET Core](https://github.com/aspnet/Home)
- [Visual Studio Code](https://github.com/Microsoft/vscode)
- [Chakra Core](https://github.com/Microsoft/ChakraCore)
aiguard-sdk-python 0.1.0
AIGuard SDK for monitoring and logging AI model invocations
License: MIT
Requires Python: >=3.8
Keywords: ai, monitoring, logging, openai, llm

# AIGuard Python SDK

Python SDK for monitoring and logging AI model invocations with AIGuard.

## Installation

```bash
pip install aiguard
```

Or install from source:

```bash
pip install -e /path/to/python-sdk
```

## Usage

### Initialize the client

```python
from aiguard import AIGuard

guard = AIGuard(api_key="your-api-key")
```

### Direct API calls

```python
# Start an invocation
invocation = guard.start_invocation({
    "eventId": "unique-event-123",
    "event": "chat-completion",
    "userId": "user-456",
    "inputMessage": "Hello, how are you?",
    "model": "gpt-4",
    "convoId": "conversation-789",
    "properties": {"temperature": 0.7}
})

# ... make your AI call ...

# End the invocation
completed = guard.end_invocation({
    "eventId": "unique-event-123",
    "output": "I am doing well, thank you!"
})
```

### Manual logging

```python
guard.log({
    "model": "gpt-4",
    "input": [{"role": "user", "content": "Hello"}],
    "output": "Hi there!",
    "latency": 150,
    "tokens": {"prompt": 10, "completion": 5, "total": 15},
    "status": "success"
})
```

### Wrap OpenAI client (automatic logging)

```python
from openai import OpenAI
from aiguard import AIGuard

guard = AIGuard(api_key="your-api-key")
client = guard.wrap_openai(OpenAI())

# All chat completion calls are now automatically logged
response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello!"}]
)
```

## API Reference

### `AIGuard(api_key, base_url="http://localhost:5000/api")`

Initialize the AIGuard client.

### `start_invocation(data) -> dict`

Start tracking an invocation. Required fields: `eventId`, `event`, `userId`.

### `end_invocation(data) -> dict`

End an invocation. Required field: `eventId`.

### `log(data) -> None`

Fire-and-forget logging of a model call.

### `wrap_openai(client) -> client`

Wrap an OpenAI client for automatic logging.
aiguard-sdk 0.1.0
AIGuard SDK for monitoring and logging AI model invocations
License: MIT
Requires Python: >=3.8
Keywords: ai, monitoring, logging, openai, llm

# AIGuard Python SDK

Python SDK for monitoring and logging AI model invocations with AIGuard.

## Installation

```bash
pip install aiguard
```

Or install from source:

```bash
pip install -e /path/to/python-sdk
```

## Usage

### Initialize the client

```python
from aiguard import AIGuard

guard = AIGuard(api_key="your-api-key")
```

### Direct API calls

```python
# Start an invocation
invocation = guard.start_invocation({
    "eventId": "unique-event-123",
    "event": "chat-completion",
    "userId": "user-456",
    "inputMessage": "Hello, how are you?",
    "model": "gpt-4",
    "convoId": "conversation-789",
    "properties": {"temperature": 0.7}
})

# ... make your AI call ...

# End the invocation
completed = guard.end_invocation({
    "eventId": "unique-event-123",
    "output": "I am doing well, thank you!"
})
```

### Manual logging

```python
guard.log({
    "model": "gpt-4",
    "input": [{"role": "user", "content": "Hello"}],
    "output": "Hi there!",
    "latency": 150,
    "tokens": {"prompt": 10, "completion": 5, "total": 15},
    "status": "success"
})
```

### Wrap OpenAI client (automatic logging)

```python
from openai import OpenAI
from aiguard import AIGuard

guard = AIGuard(api_key="your-api-key")
client = guard.wrap_openai(OpenAI())

# All chat completion calls are now automatically logged
response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "Hello!"}]
)
```

## API Reference

### `AIGuard(api_key, base_url="http://localhost:5000/api")`

Initialize the AIGuard client.

### `start_invocation(data) -> dict`

Start tracking an invocation. Required fields: `eventId`, `event`, `userId`.

### `end_invocation(data) -> dict`

End an invocation. Required field: `eventId`.

### `log(data) -> None`

Fire-and-forget logging of a model call.

### `wrap_openai(client) -> client`

Wrap an OpenAI client for automatic logging.
adafruit-circuitpython-display-text 4.0.2
Displays text using CircuitPython's displayio.
License: MIT
Keywords: adafruit, blinka, circuitpython, micropython, bitmap, fonts, text, display, tft, lcd, displayio

Introduction
============

.. image:: https://readthedocs.org/projects/adafruit-circuitpython-display_text/badge/?version=latest
    :target: https://docs.circuitpython.org/projects/display_text/en/latest/
    :alt: Documentation Status

.. image:: https://raw.githubusercontent.com/adafruit/Adafruit_CircuitPython_Bundle/main/badges/adafruit_discord.svg
    :target: https://adafru.it/discord
    :alt: Discord

.. image:: https://github.com/adafruit/Adafruit_CircuitPython_Display_Text/workflows/Build%20CI/badge.svg
    :target: https://github.com/adafruit/Adafruit_CircuitPython_Display_Text/actions/
    :alt: Build Status

.. image:: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json
    :target: https://github.com/astral-sh/ruff
    :alt: Code Style: Ruff

Displays text using CircuitPython's displayio.

Dependencies
=============
This driver depends on:

* `Adafruit CircuitPython <https://github.com/adafruit/circuitpython>`_

Please ensure all dependencies are available on the CircuitPython filesystem.
This is easily achieved by downloading
`the Adafruit library and driver bundle <https://github.com/adafruit/Adafruit_CircuitPython_Bundle>`_.

Usage Example
=============

For a board with a built-in display.

.. code:: python

    import board
    import terminalio
    from adafruit_display_text import label


    text = "Hello world"
    text_area = label.Label(terminalio.FONT, text=text)
    text_area.x = 10
    text_area.y = 10
    board.DISPLAY.root_group = text_area
    while True:
        pass


Documentation
=============

API documentation for this library can be found on `Read the Docs <https://docs.circuitpython.org/projects/display_text/en/latest/>`_.

For information on building library documentation, please check out `this guide <https://learn.adafruit.com/creating-and-sharing-a-circuitpython-library/sharing-our-docs-on-readthedocs#sphinx-5-1>`_.

Contributing
============

Contributions are welcome! Please read our `Code of Conduct
<https://github.com/adafruit/Adafruit_CircuitPython_Display_Text/blob/main/CODE_OF_CONDUCT.md>`_
before contributing to help this project stay welcoming.