semvec/pypi-packages huggingface dataset:
orionac-ai 0.2.1
Python client for Orionac AI API
Requires Python: >=3.10

# Orionac GenAI Python SDK Documentation

---

## Installation

Install via PyPI:

```bash
pip install orionac_ai
```

Or install locally:

```bash
pip install ./dist/orionac_ai-0.2.1-py3-none-any.whl
```

---

## Quick Start

```python
from orionac_genai.client import Theta

client = Theta(api_key="YOUR_API_KEY_HERE", base_url="http:///v1")

# Non-streaming generation
response = client.generate("Hello EC2!", stream=False)
print(response.text)

# Streaming generation
stream_gen = client.generate("Hello EC2!", stream=True)
for chunk in stream_gen:
    print(chunk, end="")
```

---

## Features

1. Non-streaming generation: Returns a full `APIResponse` object.
2. Streaming generation: Returns a generator yielding chunks of text.
3. Custom parameters: Supports `model`, `temperature`, `max_tokens`, etc.
4. Automatic error handling with `AuthenticationError` and `APIError`.
5. Stateless: Each request is independent.

---

## API Reference

### Class: `Theta`

```python
Theta(api_key: str, base_url: str = "")
```

* `api_key`: Your API key for authentication.
* `base_url`: URL of the Orionac GenAI server.

### Method: `generate`

```python
generate(prompt: str, stream: bool = False, **kwargs) -> APIResponse | generator
```

* `prompt`: Text to generate from.
* `stream`: If True, returns a generator.
* `kwargs`: Additional parameters like `model`, `max_tokens`, `temperature`, etc.

Returns `APIResponse` for non-streaming, or generator for streaming.

### Class: `APIResponse`

```python
APIResponse._data
APIResponse.text
APIResponse.model_used
APIResponse.prompt_tokens
APIResponse.completion_tokens
APIResponse.total_tokens
```

---

## Error Handling

```python
from orionac_genai.client import Theta, AuthenticationError, APIError

try:
    client = Theta(api_key="YOUR_API_KEY")
    response = client.generate("Hello!")
except AuthenticationError as e:
    print("Invalid API key:", e)
except APIError as e:
    print("API request failed:", e, e.status_code)
```

---

## Example Use Cases

1. Chatbots
2. Email drafting

```python
resp = client.generate(
    "Draft a follow-up email to a prospect we spoke with.",
    context={"prospect_name": "Jane Doe"}
)
print(resp.text)
```

3. Streaming terminal applications

```python
for chunk in client.generate("Explain AWS EC2 to a beginner.", stream=True):
    print(chunk, end="")
```

---

## Notes

* Ensure EC2 security group allows inbound traffic on port `8000`.
* Supports HTTP and HTTPS.
* Fully stateless.
mongodb-url-checker 0.1.0
A simple MongoDB URL validator
Requires Python: >=3.8

📦 mongodb-url-checker

Validate your MongoDB connection URL easily and safely.


---

🚀 Installation

Install the package from PyPI:

```pip install mongodb-url-checker```


---

🖥️ Usage

If the CLI command mongodb-url-checker doesn’t work in your terminal, you can use the included runner file.

1. Create a file called mongodb_checker.py with this content:



```from mongodb_url_checker import main

if __name__ == "__main__":
    main()```

2. Run it with:



```python mongodb_checker.py```


---

📌 Example

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
MongoDB URL Validator
Made by Syntax Development | https://discord.gg/vMTDMVYE74
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Enter your MongoDB URL to check: xxxxxxxxxxxx
[✓] MongoDB URL is valid and connected successfully!

If invalid:

Enter your MongoDB URL to check: xxxxxxxxxxxx
[✗] Invalid MongoDB URL or connection failed!
Error: ...


---

⚡ Features

Works with standard MongoDB URIs and MongoDB Atlas URIs

Shows clear ✅ valid / ❌ invalid messages

Lightweight (only depends on pymongo)

Cross-platform (Windows, macOS, Linux)



---

🔗 Links

PyPI: mongodb-url-checker

Discord Support: [Syntax Development](https://discord.gg/vMTDMVYE74)



---
chembl-gen-check 0.1.1
Simple package that performs basic molecular structural sanity checks
Requires Python: >=3.10

# chembl_gen_check

chembl_gen_check is a Python library that uses lightweight [MolBloom](https://github.com/whitead/molbloom) filters for rapid verification of the existence of scaffolds, generic scaffolds or ring systems in ChEMBL structures. The library can also indicate whether a compound has uncommon bonds according to the [LACAN](https://github.com/dehaenw/lacan) algorithm, or that a compound triggers a structural alert. Taken together, these checks provide rapid assessment of the reasonableness of ring systems and scaffolds, as well as ensuring that atom and bond environments have precedent.

## Installation

```
pip install chembl-gen-check
```

## Usage example

```python
from chembl_gen_check import Checker

checker = Checker()

smiles = "CCN(CC)C(=O)C[C@H]1C[C@@H]1c1ccccc1"
checker.load_smiles(smiles)

# Murcko scaffold found in ChEMBL (True/False)
checker.check_scaffold()

# Generic Murcko scaffold found in ChEMBL (True/False)
checker.check_skeleton()

# All molecule ring systems found in ChEMBL (True/False)
checker.check_ring_systems()

# Number of structural alerts using the ChEMBL set (integer)
checker.check_structural_alerts()

# LACAN score > 0.5 (True/False)
checker.check_lacan() > 0.5
```

Code to extract ring systems adapted from: W Patrick Walters. [useful_rdkit_utils](https://github.com/PatWalters/useful_rdkit_utils/blob/master/useful_rdkit_utils/ring_systems.py)

Code to calculate LACAN scores adapted from: Dehaen, W. LACAN. https://github.com/dehaenw/lacan/
petrel-chicks 0.7.2
A module to petrel_chicks
Requires Python: >=3.9

<a href="https://www.islas.org.mx/"><img src="https://www.islas.org.mx/img/logo.svg" align="right" width="256" /></a>
# Dummy Transformations

Para usar este repo como plantilla debemos hacer lo siguiente:

1. Presiona el botón verde que dice _Use this template_
1. Selecciona como dueño a la organización IslasGECI
1. Agrega el nombre del nuevo módulo de python
1. Presiona el botón _Create repository from template_
1. Reemplaza `dummy_transformations` por el nombre del nuevo módulo en:
    - `Makefile`
    - `pyproject.toml`
    - `tests\test_transformations.py`
1. Renombra el archivo `dummy_transformations\transformations.py` al nombre del primer archivo del
   nuevo módulo
1. Cambia la descripción del archivo `dummy_transformations\__init__.py`
1. Renombra el directorio `dummy_transformations` al nombre del nuevo módulo
1. Cambia el `codecov_token` del archivo `Makefile`

Los archivos del nuevo módulo los agregarás en la carpeta que antes se llamaba
`dummy_transformations` y las pruebas en la carpeta `tests`.