semvec/pypi-packages huggingface dataset:
interfaceagent 0.0.1
Interface Agent: Addressing Tasks by Controlling Interfaces
Requires Python: >=3.10

# Interface Agent: Addressing Tasks by Controlling Interfaces

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Written as part of the book "Multi-Agent Systems with AutoGen" by Victor Dibia.

Interface Agent package demonstrates how to build an agent that can accomplish tasks by driving interfaces (web browser). It combines the capabilities of large language models with web browsing to accomplish complex tasks autonomously.

## Installation

```bash
pip install interfaceagent
```

Or install the latest version from the source code:

```bash
cd interfaceagent
pip install -e .
```

## Components

1. **WebBrowser**: A wrapper around Playwright for browser control
2. **WebBrowserManager**: Manages multiple browser sessions
3. **Planner**: Uses OpenAI models to plan and execute tasks
4. **Web Api**: Provides a RESTful API to interact with the agent based on FastAPI

## Usage

```python

from interfaceagent import WebBrowser, Planner , OpenAIPlannerModel

browser = WebBrowser(start_url="http://google.com/",headless=False)
model = OpenAIPlannerModel(model="gpt-4o-mini-2024-07-18")
task = "What is the website for the Manning Book - Multi-Agent Systems with AutoGen. Navigate to the book website and find the author of the book."
planner = Planner(model=model, web_browser=browser, task=task)
result = await planner.run(task=task)

```
pyviber 0.2
Python package for developing Viber Bots

# PyViber

PyViber is a powerful asynchronous Python library for interacting with Viber Bot API.

## Installation

```bash
pip install pyviber
```

## Usage

### Initializing the Bot

```python
from pyviber.bot import Bot
from pyviber.event_type import EventType
import asyncio

# Initialize the bot with your Viber Bot token
bot = Bot("your_viber_bot_token")
```

### Setting and Unsetting Webhook

```python
# Set webhook URL to receive callbacks
webhook_url = "https://your-webhook-url.com/viber"
event_types = [EventType.MESSAGE, EventType.SUBSCRIBED]

async def set_webhook():
    await bot.set_webhook(webhook_url, event_types)

async def unset_webhook():
    await bot.unset_webhook()
```

### Sending Messages

```python
from pyviber.messages import TextMessage
from pyviber.sender import Sender

async def send_message_example():
    sender = Sender(name="Your Bot Name", avatar="https://your-avatar-url.com/avatar.png")
    message = TextMessage(text="Hello from your Viber Bot!")
    receiver_id = "user_viber_id"

    await bot.send_message(receiver_id, message, sender)
```

### Getting Account Information

```python
from pyviber.bot_info import BotInfo

async def get_account_info_example():
    account_info = await bot.get_account_info()
    print(account_info.name)
    print(account_info.uri)
```

### Handling Events

```python
@bot.event("message")
async def handle_message_event(event):
    # Handle incoming message event
    if event.type == EventType.MESSAGE:
        print("Received message:", event.message)

async def handle_events():
    # Simulate receiving an event (should come from Viber)
    event = {"event": "message", "message": "Test message"}
    await bot.handle_event(event)
```

## Error Handling

Exceptions are raised for API errors, ensuring robust error handling for operations like sending messages or retrieving information.

## References

- [Viber Public Account API Documentation](https://developers.viber.com/docs/api/rest-bot-api/)
pyprogress-elunico 0.1.6
A terminal progress printing utility
Requires Python: >=3.6
Keywords: progress bar terminal

# PyProgress

## General Use

A simple interface for terminal based progress updates

Begin by creating an instance with the starting and ending value

```python
import os

files = os.listdir('.')
bar = ProgressBar(0, len(files))
for file in files:
    bar.iterbegin('Processing file: {}'.format(file))
    process(file)
    bar.iterdone()
bar.done()
```

Manually call `ProgressBar.iterbegin([message])` before an iteration starts 
and call `ProgressBar.iterend()` when it completes or `ProgressBar.iterfail()` 
if it fails 

When all items complete use `ProgressBar.done()` to print a summary

## Alternative Use – Context Manager

ProgressBar instances can also be used as context managers

use a with statement on every iteration

```python
import os

files = os.listdir('.')
bar = ProgressBar(0, len(files), supress_exc=True)
for file in files:
    with bar:
        process(file)
bar.done()
```

Using the `supress_exc=True` argument will report statistic for failures
from raised exceptions but not raise the exception itself 

This is not necessary to use bar as a Context Manager but you must use it as a Context Manager to get the exception suppressing behavior
kumar 5.4.0
`kumar` is a Python package that provides two high-level features.
Keywords: python, transformer, chat-GPT Transformer




[![Build Status](https://github.com/raimon49/pip-licenses/workflows/Python%20package/badge.svg)](https://github.com/ProgramerSalar/kumar) [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pip-licenses.svg)](https://www.python.org/downloads/) [![PyPI version](https://badge.fury.io/py/pip-licenses.svg)](https://pypi.org/project/kumar/) [![GitHub Release](https://img.shields.io/github/release/raimon49/pip-licenses.svg)](https://pypi.org/project/kumar/#history)  [![MIT License](http://img.shields.io/badge/license-MIT-green.svg)](https://github.com/ProgramerSalar/kumar/blob/master/LICENSE) [![PyPI - Downloads](https://img.shields.io/pypi/dm/pip-licenses)]()





Dump the software license list of Python packages installed with pip.



## Table of Contents



* [Description](#description)

* [Installation](#installation)

* [License](#license)

* [Dependencies](#Dependencies)

* [Reference](https://github.com/ProgramerSalar/kumar/blob/master/Readme_File/REFERENCE.md)

* [Uninstallation](#uninstallation)

* [Contributing](#contributing)

* [CHANGELOG](#CHANGELOG)







## Description



`kumar` is a Python package that provides two high-level features.





## installation

```

pip install kumar==<version>



            OR



pip install kumar

```













## license 

[MIT Licence](https://github.com/ProgramerSalar/kumar/blob/master/LICENSE)



## Dependencies 

- ```torch``` 

- ```tqdm ``` this is progress bar library

- ```datasets ```  this is dataset libarary by huggingface

- ```tokenizers ```  this is tokenizers libary by huggingface

- ```tensorboard ```  TensorBoard is a visualization toolkit for machine learning experimentation. TensorBoard allows tracking and visualizing metrics such as loss and accuracy, visualizing the model graph, viewing histograms, displaying images and much more. In this tutorial we are going to cover TensorBoard installation, basic usage with PyTorch, and how to visualize data you logged in TensorBoard UI.





# Uninstallation

Uninstall package and dependent package with ```pip``` command .

```

pip uninstall kumar torch tqdm datasets tokenizers tensorboard

```



# Contributing 

See [contribution guidelines](https://github.com/ProgramerSalar/kumar/blob/master/CONTRIBUTING.md) .





# CHANGELOG



## 1.0.0



- First Implemention version

    - Add a function 



        - ```BilingualDataset()```

        - ```build_transformer()```





## 2.0.0

- solve some Error, I will Get the package error 







## 3.0.0

- Improve document

    - Update the README document

    - Add the Licence 

    - some Required Things 





## 4.0.0 

- Update the Libarary 

    - add the Diffusion model function 

    - update the Readme document





## 5.0.0

- update the library

    - update the Readme file





## 5.4.0 

- stable version of this library