semvec/pypi-packages huggingface dataset:
barrel.py 0.4
A simple Discord bot package.
License: MIT
Requires Python: >=3.7

# 🚀 **Introducing Barrel – The Ultimate Discord Bot Package!** 🚀

Barrel is a lightweight and powerful custom Discord bot package designed for simplicity and efficiency. With Barrel, you can easily manage commands, handle errors, and customize your bot's interactions with Discord's API.

## ✨ **Features**:

- **Custom Commands**: Easily add and manage commands for your bot.
- **Seamless Integration**: Connects smoothly with Discord’s API.
- **Error Handling**: Built-in error handling to ensure smooth operation.
- **Embed Support**: Create and send rich embeds for enhanced message formatting.
- **Latency Checking**: Built-in command to check the bot's latency.

## 📦 **Installation**

To install Barrel, use pip:

```bash
pip3 install barrel.py
```

## 🛠 **Usage Instructions**

### **1. Basic Setup**

**Create a new Python file for your bot, e.g., `main.py`.**

```python
# main.py
from barrel import Bot  # Importing the Bot class

# Initialize the bot (create an instance of the Bot class)
barrel_bot = Bot(command_prefix="!")  # Command prefix defaults to "!" if not provided

# Register a simple command
@barrel_bot.command()
async def greet(ctx):
    """Command to greet users with an embed."""
    title = "Greetings from BarrelBot!"
    description = "This is a message sent using an embed."
    await barrel_bot.send_embed(ctx, title, description)

@barrel_bot.command()
async def my_command(ctx):
    await ctx.send("This is a custom command!")

# Run the bot with your bot token
barrel_bot.run('YOUR_BOT_TOKEN_HERE')  # Replace with your actual bot token
```

### **2. Adding Custom Commands**

To add custom commands to your bot:

**Define a command using the `@barrel_bot.command()` decorator:**

```python
# main.py
@barrel_bot.command()
async def my_command(ctx, *args):
    """Your custom command description."""
    # Your command logic here
    await ctx.send("This is a custom command!")
```

### **3. Running the Bot**

To run your bot:

**Make sure your `main.py` includes:**

```python
# main.py
if __name__ == "__main__":
    barrel_bot.run('YOUR_BOT_TOKEN_HERE')  # Replace with your actual bot token
```

**Execute your script:**

```bash
python3 main.py
```

Feel free to replace `'YOUR_BOT_TOKEN_HERE'` with your actual bot token when running the bot.
fences-api 0.1.3
Fences is an LLM augmented OpenAPI interpreter with a visual interface to easily make requests
License: MIT
Requires Python: >=3.8

# Fences
<a href="https://pypi.org/project/fences-api" target="_blank">
  <img src="https://img.shields.io/pypi/v/fences-api?color=%2334D058&label=pypi%20package" alt="Package version">
</a>

An LLM augmented OpenAPI specification interpreter that provides a human-readable interactive representation of APIs, automatically generate requests and stores both requests and responses on your browser to improve AI-generated requests in future queries.

Fences operates similarly to SwaggerUI, but with a more human-friendly interface. It uses AI to create a visual diagram and categorize endpoints. After the initial parse Fences uses the OpenAPI specification to automatically generate request bodys for you, filling with it with sample data. It stores every single request and response data in your browser to better generate future requests. Data is only stored locally, the only third-party server it uses is Anthropic's API to access LLMs.

![alt text](documentation/home.png)

# Work in progress
Fences is still under construction and may break for some edge cases.
Please submit an issue with a reproducible example if you encounter any problems.

# Usage
```sh
pip install fences-api # Installation command
fences # You will be prompted for an anthropic api key and for the link to the openapi spec
```

You will be prompted to enter your anthropic key so that fences can make requests to an LLM model to parse the OpenAPI specification.

# How to contribute
PR's are welcome!

Please create an issue before opening a PR so that we can discuss the changes you want to make.

# How to setup your dev enviroment

```sh
pip install -r requirements.txt
cd ui && npm install && npm run build && cd..
python fences/cli.py
pip install -e . # To test package locally
```