semvec/pypi-packages huggingface dataset:
agi-med-ai-chat-manager 1.11.6
Ai chat managers for agi-med team
Requires Python: >=3.11

# agi-med-ai-chat-manager

Реализация подключения к разным ai чатам, таким как разным llm сервисам

## Ответственный разработчик

@shaposhnikov

## Общая информация

- Yandex_GPT
- Gigachat
- OpenRouter
- AiriServer

## Тесты

- `sudo docker compose up --build`
pyconfigue 0.0.2
A library that let's you manage your python app configuration easily
Requires Python: >=3.10
Keywords: config, configue, pyconfigue, configuration

# PyConFigue



## Features

This library provides you an easy way to properly manage your python application configuration easily.

The key features are:

- Multiple configuration sources support using configuration providers
- Sources priority managment using a layer based model
- Typed configuration
- Autocomplete from IDEs
- Support of objects configurations using [Pydantic](https://docs.pydantic.dev/latest/)

## Installation

```bash
pip install pyconfigue
```

## Usage

### 1 - Define your ConFigue Model

```python
from pyconfigue import ConFigueModel
from pydantic import BaseModel

class MyPydanticModel(BaseModel):
    key1: dict[str, str]
    key2: float

class MyConFigueModel(ConFigueModel):
    CONFIG_KEY: str
    CONFIG_KEY_2: int
    CONFIG_KEY_3: list[str]
    CONFIG_KEY_4: MyPydanticModel
```

### 2 - Define your Providers

```python
from pyconfigue.providers import StaticFileProvider,EnvProvider,DefaultProvider

# File Provider


file_provider = StaticFileProvider( ["my_file.yaml","my_file_2.yaml"])

# Environment Provider
env_provider=EnvProvider()

# Default Provider
class DefaultConFigue(MyConFigueModel):
    CONFIG_KEY = "test_value"
    CONFIG_KEY_2= 2
    CONFIG_KEY_3 = ["1", "2"]
    CONFIG_KEY_4 = MyPydanticModel(key1={"k1": "1", "k2": "2"}, key2=1.2)

default_provider = DefaultProvider(DefaultConFigue())

```

### 3 - Define your ConFigue Manager

```python
from pyconfigue import ConFigueManager
class MyAppConFigueManager(ConFigueManager, MyConFigueModel):
    pass

CONFIG=MyAppConFigueManager([env_provider, file_provider, default_provider])
```

### 4 - Use your ConFigue

```python
from .app_config import CONFIG

print("CONFIG VALUE of CONFIG_KEY",CONFIG.CONFIG_KEY)
```

## Documentation

See our [wiki](https://github.com/AlexiDN/pyconfigue/wiki) if you need more details about how the project works.

## License 

The project is under the MIT License.

## Requirements

The project requires:
- python = ">=3.10"
- pydantic = "^2.11.4"
- pyyaml = "^6.0.2"
- toml = "^0.10.2"

## Project Status

> **NOTE** <br>
> The project is currently in development phase. If you have any remark or question feel free to open an Issue
exopie 1.2.3
A package for finding exoplanet interiors
Requires Python: >=3.6

# exopie
Find exoplanet interior structure error (exopie), given mass and radius of the planet.

The methodology is described in Plotnykov & Valencia (2024) and is based on the SUPEREARTH interior structure model developed by Valencia et al. [(2006)](https://www.sciencedirect.com/science/article/abs/pii/S0019103505004574?via%3Dihub) and 
updated in Plotnykov & Valencia [(2020)](https://academic.oup.com/mnras/article/499/1/932/5899063). 

## Features
* Find the core mass fraction (CMF) of a rocky planet.
* Find the water mass fraction (WMF) of a temperate water world (Teq=300K).
* Find the atmospheric mass fraction (AMF) of a H_2/He dominated sub-Neptune (beta).

## Installation

```ssh
pip install exopie
```

## Citation
Please cite Plotnykov & Valencia (2024) if you use this code or parts of SUPEREARTH.
liotel 0.2b1
A resilient, minimal HTTP client for the Liotel API with retries, caching, and CLI support.
Requires Python: >=3.6

# Liotel v0.2b1

**English** | [فارسی](#-فارسی)

A resilient, lightweight Python client for the **Liotel API** with:

- **Automatic retries** (with exponential backoff & jitter) to handle network errors  
- **Safe timeouts** to prevent hanging requests  
- **Token-based authentication** for secure communication  
- **Simple CLI (`liotel`)** for quick tests and automation  
- **In-memory caching (optional)** for GET requests to improve performance  

---

## Installation

```bash
pip install liotel==0.2b1
resinkit-api-python 0.1.4
Service for interacting with Resinkit
Requires Python: >=3.11


# Running the service

```bash
nohup uvicorn resinkit_api.main:app --host 0.0.0.0 --port 8602 > /opt/resinkit/api/resinkit_api.log 2>&1 &
```


## Connect to MCP

```json
{
  "mcpServers": {
    "rsk": {
      "type": "http",
      "url": "http://localhost:8603/mcp-server/mcp"
    }
  }
}
```