semvec/pypi-packages huggingface dataset:
langchain-gradientai 0.1.19
An integration package connecting Digitalocean and LangChain
License: MIT
Requires Python: <4.0,>=3.9

# langchain-gradientai

This package contains the LangChain integration with DigitalOcean

## Installation

```bash
pip install -U langchain-gradientai
```

And you should configure credentials by setting the `DIGITALOCEAN_INFERENCE_KEY` environment variable:

1. Log in to the DigitalOcean Cloud console
2. Go to the **GradienAI Platform** and navigate to **Serverless Inference**.
2. Click on **Create model access key**, enter a name, and create the key.
3. Use the generated key as your `DIGITALOCEAN_INFERENCE_KEY`:   


Create .env file with your access key:  
```DIGITALOCEAN_INFERENCE_KEY=your_access_key_here```

## Chat Models

`ChatGradientAI` class exposes chat models from langchain-gradientai.

### Invoke

```python
import os
from dotenv import load_dotenv
from langchain_gradientai import ChatGradientAI

load_dotenv()

llm = ChatGradientAI(
    model="llama3.3-70b-instruct",
    api_key=os.getenv("DIGITALOCEAN_INFERENCE_KEY")
)

result = llm.invoke("What is the capital of France?.")
print(result)
```

### Stream

```python
import os
from dotenv import load_dotenv
from langchain_gradientai import ChatGradientAI

load_dotenv()

llm = ChatGradientAI(
    model="llama3.3-70b-instruct",
    api_key=os.getenv("DIGITALOCEAN_INFERENCE_KEY")
)

for chunk in llm.stream("Tell me what happened to the Dinosaurs?"):
    print(chunk.content, end="", flush=True)
```

More features coming soon.
orappgen 0.2.1
Générateur d'applications Django structurées (modèles, vues, urls...)
License: MIT
Requires Python: >=3.7

# orappgen

`orappgen` est un générateur d’applications Django structuré, conçu pour remplacer `django-admin startapp` tout en appliquant une architecture modulaire dès la création.

## 🔧 Fonctionnalités

- Création d’une app Django avec :
  - Dossier `models/`.
  - Dossier `views/`.
  - Fichier `urls.py` prêt à l’emploi
  - Fichiers standards (`admin.py`, `apps.py`, `tests.py`, et autres...)
- Génération via une simple commande CLI :
  ```bash
  startcustomapp nom_de_l_app
FLImagingClrPy 6.8.5
FLImaging(R) CLR for Python
License: MIT
Requires Python: >=3.8.0

# FLImagingClrPy  
FLImaging CLR for Python  
---

**FLImagingClrPy** is a lightweight helper package that automatically sets up the initial environment to seamlessly import the **.NET CLR wrapper (FLImagingCLR.dll)**—built on top of the **commercial machine vision library FLImaging®**'s native C++ engine—directly into Python.  
It simplifies the use of `clr.AddReference()` through `pythonnet` (or `pythonnet_win64`), and minimizes common barriers to entry such as version or architecture mismatches, DLL search paths, and license dongle detection.

---

## 🖥️ Supported Environment

### 🧩 Operating System
* Supports **Windows 7 SP1** through **Windows 11 24H2** (both x86 and x64).  
  Linux is not supported at this time.  
  :contentReference[oaicite:0]{index=0}

### 🧪 Development Tools
* **Python 3.7 ~ 3.12** (64-bit recommended)  
* **.NET Framework 4.8** or **.NET 6/7 Runtime**  
* **Microsoft Visual C++ Redistributable 2015–2022** (required for native DLL execution)

---

## ⚡ Optional: Deep Learning Hardware Acceleration

To accelerate the **FLImaging® AI modules** with GPU, the following additional system requirements apply:

| Category | Minimum Specification | Recommended Specification |
|---------|------------------------|----------------------------|
| CPU     | x64 with 4+ cores      | x64 with 32+ cores         |
| RAM     | 32 GB for training / 16 GB for inference | 256 GB for training / 64 GB for inference |
| RAM Type | DDR4 or higher        | DDR5 or higher             |
| NVIDIA GPU | **Ampere** (e.g., RTX 3000, A100) | **Ada Lovelace** (e.g., RTX 4000/5000, H100) |
| NVIDIA Driver | Setup Package 572.61+, internal version 32.0.15.7261+ | Latest Game Ready / Studio Driver |
| OS | Windows 10 or higher | Windows 11 or higher |  
:contentReference[oaicite:1]{index=1}

> 💡 **TIP**: Even without a GPU, CPU-only inference is possible.  
> However, for large model training or real-time processing, the recommended specs are strongly advised.

---

## 🚀 Installation & Usage

1. Download the latest version of **FLImaging®** from  
   👉 [https://flimaging.fourthlogic.co.kr](https://flimaging.fourthlogic.co.kr)  
2. After installation, run the following command to install `FLImagingClrPy`:  
   ```bash
   pip install FLImagingClrPy
   ```
3. In your Python code, add the following at the top:  
   ```python
   from FLImagingClrPy import *
   ```
   Then, you're ready to begin developing software using the FLImaging® algorithms.