semvec/pypi-packages huggingface dataset:
titli 0.0.11
A library for collection of IDS and tools for evaluating them
License: MIT
Requires Python: >=3.10
Keywords: ids, adversarial, network, nids

<img src="assets/images/ titli-logo.png" alt="Titli Logo" width="150" />


![PyPI - Python Version](https://img.shields.io/pypi/pyversions/titli)
![PyPI - Version](https://img.shields.io/pypi/v/titli)
![GitHub License](https://img.shields.io/github/license/spg-iitd/titli)
[![Documentation Status](https://readthedocs.org/projects/titli/badge/?version=latest)](https://titli.readthedocs.io/en/latest/?badge=latest)

A toolkit for hosting feature extraction, model training, model inference, and model evaluation of AI-based Intrusion Detection Systems
<p align="center">
	<img src="assets/images/pipeline-overview.jpg" alt="Pipeline Overview" width="800" />
</p>

## Documentation

📚 **[Read the full documentation](docs/)** to get started with Titli.

The documentation includes:
- Installation guide
- Quick start tutorial
- Detailed usage examples
- Complete API reference
- And more!

To build the documentation locally:
```bash
cd docs
pip install sphinx sphinx-rtd-theme sphinx-autodoc-typehints
make html
```

Then open `docs/build/html/index.html` in your web browser.

### Installation
```
pip install titli
```

### Usage
- Step 1: Copy the ```test_titli.ipynb``` file and run it locally.
- Step 2: Run both the files to train and test IDSs.

<!-- ### Todo (Developer Tasks)
- [ ] Check if RMSE is used for loss or just the difference.
- [ ] Put Kitsune code into the base IDS format.
- [ ] Write code to evaluate the model and calculate all the metrics.  

### TODO New:
- [ ] Resolve BaseSKLearn class infer function's TODO
- [ ] Make fit and predict function as private by putting "_" in the starting
- [ ] Similar to PyTorch, define __call__ function for SkLearn models too
- [ ] Investigate and modify the use of get_model in the Pytorch class.
- [ ] Make internal methods private
- [ ] Add docstrings in the class and functions

- Write where the model is saved in the print statement! -->
ui-setup 0.1.2
If you want to vibe code, at least do it properly.
License: MIT
Requires Python: >=3.7

![banner](images/banner.png)

# Ui Setup

> Create UI's that actually look beautiful.

## Requirements

- Python version 3.7 or higher
- pip
- minimum knowledge with programming OR vibe coding tools.

## Inspiration

This project is hugely inspired by this twitter [thread](https://x.com/jasonzhou1993/status/1985291755705835832) by [Jason Zhou](https://x.com/jasonzhou1993). The prompts are mostly stolen from his thread.

## Installation

`pip install ui-setup`

## Usage

Well, the idea here is quite simple:

### You:

```mermaid
---
config:
  theme: dark
  look: handDrawn
  layout: dagre
---
flowchart TD
    A["find a website that looks cool"] --> B["you give it the URL"]
    B --> C["the AI clones it"]
    C -- The cloning looks good --> D["AI creates a style.md file teaching your agents how to create pages in that exact same style"]
    D --> E["you make changes in the style.md file so it has your personality"]
    E --> F["🎉 Now your AI agents can generate consistently generate beautiful pages!"]
    C -- It looks ass --> G["you keep refining the prompt until it looks nice"]
    G -- It still doesn't look nice --> H["You either"]
    H --> I["try another website"] & J["cry"]
```
tsa-core 0.0.1
Temporal State Abstraction Core — The OS for AI Agents
License: MIT
Requires Python: >=3.8
Keywords: ai, temporal, agents, memory, tsa, state

# TSA-Core — Temporal State Abstraction for AI

**`pip install tsa-core`**

The missing temporal layer: diffs, trajectories, decay for agents.

→ `tsa.diff("24h")` → `tsa.trajectory("BTC")`

Open-core. Launching Q1 2026.

https://tsacore.ai  
https://github.com/tsa-core/tsa-core
autopyperf 0.1.0
A lightweight automatic Python performance analyzer and optimizer.
License: MIT
Requires Python: >=3.8
Keywords: performance, profiler, optimizer, python

# ⚡ autopyperf

**autopyperf** is a lightweight Python module that automatically profiles your code and suggests simple optimizations — no external data, no setup, just pure Python.

---

## 🚀 Features
- ⏱️ Function-level timing with `@profile_function`
- 🧮 Full-script performance analysis with `profile_script()`
- 💡 Simple static code suggestions with `suggest_optimizations()`
- 🧰 No dependencies — just plug and play

---

## 📦 Installation
Once published to PyPI:
```bash
pip install autopyperf