semvec/pypi-packages huggingface dataset:
fabsdk 0.0.2
SDK Python pour accéder à l’API MovieLens (Data Analysts/Data Scientists friendly)
Requires Python: >=3.12

# MovieLens SDK - `fabsdk`

Un SDK Python simple pour interagir avec l’API REST MovieLens. Il est conçu pour les **Data Analysts** et **Data Scientists**, avec une prise en charge native de **Pydantic**, **dictionnaires** et **DataFrames Pandas**.

[![PyPI version](https://badge.fury.io/py/moviesdk.svg)](https://badge.fury.io/py/moviesdk)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/licenses/MIT)

---

## Installation

```bash
pip install fabsdk
```

---

## Configuration

```python
from fabsdk import MovieClient, MovieConfig

# Configuration avec l’URL de votre API (Render ou locale)
config = MovieConfig(movie_base_url="https://movie-api-9x1n.onrender.com")
client = MovieClient(config=config)
```

---

## Tester le SDK

### 1. Health check

```python
client.health_check()
# Retourne : {"status": "ok"}
```

### 2. Récupérer un film

```python
movie = client.get_movie(1)
print(movie.title)
```

### 3. Liste de films au format DataFrame

```python
df = client.list_movies(limit=5, output_format="pandas")
print(df.head())
```

---

## Modes de sortie disponibles

Toutes les méthodes de liste (`list_movies`, `list_ratings`, etc.) peuvent retourner :

- des objets **Pydantic** (défaut)
- des **dictionnaires**
- des **DataFrames Pandas**

Exemple :

```python
client.list_movies(limit=10, output_format="dict")
client.list_ratings(limit=10, output_format="pandas")
```

---

## Tester en local

Vous pouvez aussi utiliser une API locale :

```python
config = MovieConfig(movie_base_url="http://localhost:8000")
client = MovieClient(config=config)
```

---

## Public cible

- Data Analysts
- Data Scientists
- Étudiants et curieux en Data
- Développeurs Python

---

## Licence

MIT License

---

## Liens utiles

- API Render : [https://movie-api-9x1n.onrender.com](https://movie-api-9x1n.onrender.com)
- PyPI : [https://pypi.org/project/fabsdk/](https://pypi.org/project/fabsdk/)
arthaLM 0.1.0
Plug-and-play pipeline for Artha LLM
Requires Python: >=3.7

# Artha Language Model (ArthaLM)

## World's First & Most Affordable Custom LLM â€“ Built by a Teen

**Artha-1** is the **world's first Liquid Neural Network-powered language model pipeline** trained and deployed end-to-end by an independent teen researcher. Unlike traditional LLMs that require millions of dollars, proprietary infrastructure, and industrial compute clusters, **Artha-1 was built in under 3 days using accessible tools and mid-range hardware.**

### What Makes It a World First?

-  **LNN-Based Reasoning Core:**  
  This is the **first open-source LLM** to integrate a **Liquid Neural Network (LNN)** core for deep, dynamic reasoning inside compressed latent space.

-  **Built With ~Zero Budget:**  
  Trained using just local GPUs and open datasets, **no enterprise backing or funding** was involved. This makes Artha-1 arguably the **cheapest working LLM** architecture available to the public.

-  **Created by a Teen Researcher:**  
  From architecture design and training to deployment and packaging, every step was executed by an **independent teen developer**, proving that **you donâ€™t need a PhD or billion-dollar lab** to innovate in AI.