semvec/pypi-packages huggingface dataset:
rule34html 0.1.1
Feature-rich HTML parser for rule34.xxx (no API). Search posts, autocomplete tags, get random images.
Requires Python: >=3.9

# rule34html

A friendly, zero-API HTML parser for **rule34.xxx** built in Python.
It scrapes the website’s public HTML (no API calls) to provide:

- Search posts by tags
- Get a single random post from tags
- Get multiple random posts from tags
- Tag autocomplete
- Get full-size image/file URL
- Download images
- Both sync and async clients with context manager support (`with`/`async with`)
- Polite rate-limiting + retries
- Handy CLI: `r34`

> ⚠️ For adults and legal use only. This package just parses public HTML from rule34.xxx.
> It does **not** use the site's JSON/XML API endpoints.

## Quick start

```bash
pip install rule34html
```

### Synchronous Client

```python
from rule34html import Rule34Client

# Use the client as a context manager to ensure it's closed properly
with Rule34Client() as client:
    # Search for posts
    posts = client.search_posts(["blue_eyes", "1girl"], page=0)
    print(f"Found post: {posts[0].id}, Image URL: {posts[0].image_url}")

    # Get a single random post
    post = client.random_post(["blue_eyes"])
    print(f"Random post: {post.id}, Image URL: {post.image_url}")

    # Get 5 random posts
    random_posts = client.random_posts(["solo"], count=5)
    print(f"Got {len(random_posts)} random posts.")
    for p in random_posts:
        print(f" - Post {p.id}")
```

### Asynchronous Client

```python
import asyncio
from rule34html import AsyncRule34Client

async def main():
    async with AsyncRule34Client() as client:
        # Get 5 random posts concurrently
        random_posts = await client.random_posts(["solo"], count=5)
        print(f"Got {len(random_posts)} random posts asynchronously.")
        for p in random_posts:
            print(f" - Post {p.id}, Image URL: {p.image_url}")

if __name__ == "__main__":
    asyncio.run(main())
```

### CLI

```bash
# Search posts
r34 search "blue_eyes 1girl" --page 0 --limit 10

# Random post by tags
r34 random "blue_eyes" --open

# Autocomplete tags
r34 autocomplete blu --limit 15

# Download a post by id
r34 download --id 1234567 --out ./downloads
```
catchmeifyoucan 0.0.1
PLACEHOLDER: Google Cloud Fraud Detection SDK - Coming Soon
Requires Python: >=3.8

# Catch Me If You Can - Google Cloud Fraud Detection SDK

**⚠️ PLACEHOLDER PACKAGE - ACTUAL SDK COMING SOON**

This package name is reserved for the official Google Cloud fraud detection SDK.

The full SDK is currently under internal review and will be released soon with:
- Multi-agent orchestration for fraud detection
- Real-time transaction validation
- Hybrid rules + AI processing
- Automatic pattern learning
- Support for multiple domains (payment, invoice, expense)

For more information, please contact the development team.

**Note**: This is a name reservation only. The actual SDK will be published after internal approvals.
ola-maps-mcp-server 0.2.4
MCP server for Ola Maps
Requires Python: >=3.10
Keywords: Maps, Ola, llm, mcp

# Ola Maps MCP Server

## Features

* `get_geocode`
    - Provides probable geographic coordinates and detailed location information, including a formatted address, for the given address as input.

* `reverse_geocode`
    - Converts geographic coordinates back into readable addresses or place names.

* `get_elevation`
    - Retrieves elevation data for a single location.

* `get_placeDetails`
    - Provides Place Details of a particular Place/POI whose Ola place_id necessarily needs to be given as an input.

* `nearbysearch`
    - Provides nearby places of a particular category/type based on the given location.

* `textsearch`
    - Provides a list of places based on textual search without the need for actual location coordinates.

* `get_directions`
    - Provides a routable path between two places.

* `distancematrix`
    - Calculates travel distance between multiple origins and destinations.

* `get_route_optimizer`
    - Optimizes the route between multiple locations based on minimum ETA.

* `search_along_the_route`
    - Searches for POIs (e.g., hospital, school) along a specified route.

* `get_photo`
    - Fetches the photo URL and metadata for a given photo reference ID from Ola's Places Photo API.

* `show_map_html_for_route`
    - Returns HTML code to display an interactive map with a route polyline.

* `show_markers_map_html`
    - Returns HTML code to display an interactive map with markers and popups for POIs.

* `avoid_highways_or_tolls_routes`
    - Returns routes avoiding highways or tolls based on user preferences.

* `get_future_departure_route`
    - Returns the route and ETA for a future departure time, considering traffic conditions.

* `get_shortest_route`
    - Returns the shortest route by distance between two points, automatically considering multiple alternatives.

## Configuring mcp-ola-maps Server

### Steps to Configure:

1. Open the Claude Desktop Configuration File
    - On macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
    - On Windows: `%APPDATA%/Claude/claude_desktop_config.json`

2. Add the Following Configuration:
```json
{
  "mcpServers": {
    "mcp-ola-maps": {
      "command": "uvx",
      "args": ["ola-maps-mcp-server"],
      "env": {
        "OLA_MAPS_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}
```

3. Locate the command entry for `uvx` and replace it with the absolute path to the `uvx` executable. This ensures that the correct version of `uvx` is used when starting the server. On macOS, you can find this path using: `which uvx`.

4. Restart Claude Desktop to apply the changes.
aegis-redteam-framework 1.0.6
An Open-Source LLM Red Teaming & Evaluation Framework
Requires Python: >=3.9

# 🛡️ Aegis: An Open-Source LLM Red Teaming & Evaluation Framework

Aegis is a comprehensive, Python-based toolkit for systematically evaluating the security posture and ethical alignment of Large Language Models (LLMs) through adversarial testing and vulnerability assessment.

## Key Features

- **🤖 LLM-Powered Analysis**: Uses a powerful LLM to intelligently classify model responses.
- **🔌 Multi-Provider Support**: Test models from Gemini, OpenRouter, and any custom API endpoint.
- **🚀 Batch Evaluation**: Run entire categories of adversarial prompts against a model at once.
- **📊 Comprehensive Reporting**: Generate detailed PDF, JSON, and CSV reports for analysis.
- **💻 Interactive Web UI**: A Streamlit-based sandbox for live testing and a dashboard for visualizing results.

## 🚀 Quick Start

### Installation

Clone the repository and install dependencies:

```bash
git clone https://github.com/ruchirk22/aegis.git
cd aegis-framework
pip install -r requirements.txt
```

> **Note:** Once published to PyPI, you will be able to install with:

 ```bash
 pip install aegis-framework
 ```

### Set Up API Keys

Set your API keys as environment variables before running evaluations:

```bash
export GEMINI_API_KEY=your_gemini_api_key
export OPENROUTER_API_KEY=your_openrouter_api_key
```

Or create a `.env` file in the project root:

``` bash
GEMINI_API_KEY=your_gemini_api_key
OPENROUTER_API_KEY=your_openrouter_api_key
```

### Run an Evaluation from the CLI

1. **Run a single prompt evaluation:**

    ```bash
    python -m aegis evaluate --model "openrouter/google/gemma-2-9b-it:free" --prompt-id "JBR_001"
    ```

2. **Run a batch evaluation by category:**

    ```bash
    python -m aegis batch-evaluate --category "Jailbreaking_Role-Playing" --model "gemini-1.5-flash-latest" --output-json jailbreak_report.json
    ```

### Launch the Web Interface

Start the Streamlit web UI for interactive testing and dashboards:

```bash
streamlit run aegis/web_interface/Aegis.py
```

To view the Security Dashboard:

```bash
streamlit run aegis/web_interface/pages/1_Security_Dashboard.py
```

## 📚 Documentation

Full usage guides and API references are coming soon. For now, see the example commands above and explore the [aegis/core](aegis/core/) and [aegis/web_interface](aegis/web_interface/) directories for implementation details.

## 🤝 Contributing

We welcome contributions! Please open issues or submit pull requests on [GitHub](https://github.com/ruchirk22/aegis). For setup instructions and contribution guidelines, see `CONTRIBUTING.md` (to be added).

## 📜 License

Aegis is licensed under the [Apache 2.0 License](LICENSE.txt)