semvec/pypi-packages huggingface dataset:
ironaai 0.0.4
IronaAI Python SDK
Requires Python: <4.0,>=3.9



### API vs SDK
* Client side LLM invocation.
  - Our API endpoint of model-router, only recommends the model to use.
  - The sdk invokes the "recommended model" for the given prompt, gets the response back.

SDK also provides the following features which API endpoint doesn't via a common interface.
##### Features:
- Model routing functionality using the IronaAI API endpoints
- [] Support for async & sync requests of LLM-invocation.
- Function calling,
- Tool binding using LiteLLM's function calling capabilities
- Error handling and retries
- Support for streaming, 
- and JSON mode (i.e. structured output)
- [] Detailed latency tracking and reporting - TBD
- [] Creation of preference IDs - TBD


* Retry logic (invocation or model-router)
* Unified Interface
* Tool binding



Export keys for provider you will use:

```
IRONAAI_API_KEY = "OUR_IRONAI_API_KEY"
OPENAI_API_KEY = "YOUR_OPENAI_API_KEY"
ANTHROPIC_API_KEY = "YOUR_ANTHROPIC_API_KEY"
```

To use this client, you would initialize it like this:

```
client = IronaAI(
    model_list=["openai/gpt-3.5-turbo", "openai/gpt-4", "anthropic/claude-2"],
)
```

You can then use it for completions, function calling, and tool binding:


```
# Regular completion
response = client.completions.create(
    messages=[{"role": "user", "content": "Hello, how are you?"}],
    model_list=["openai/gpt-3.5-turbo", "openai/gpt-4", "anthropic/claude-2"],)

# Function calling
def get_current_weather(location: str, unit: str = "fahrenheit"):
    """Get the current weather in a given location"""
    # Implementation here
    return f"The weather in {location} is 72°F."

tools = [
    {
        "name": "get_current_weather",
        "description": "Get the current weather in a given location",
        "parameters": {
            "type": "object",
            "properties": {
                "location": {"type": "string"},
                "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
            },
            "required": ["location"],
        },
    }
]

messages = [{"role": "user", "content": "What's the weather like in San Francisco?"}]

# Call the model
response = client.completions.create( messages=messages, tools=tools, tool_choice="auto",)

```


### Install Instructions

```
poetry install .
```

### Push this to PyPi

```
poetry build
poetry publish
```


Then users can simply install the package using pip:

```
pip install ironaai
```
pyarccli 0.0.7
Paquetage Python pour generer des blocs de code pour faciliter la creation d'application
Requires Python: >=3.7

# README

**pyarccli** est un paquetage Python de **PYARCCORE** pour generer des blocs de code pour faciliter la creation d'application.

## Builder le projet

### Installations prÃ©alables

* **windows** : python -m pip install sdist bdist_wheel
* **linux** : sudo -H pip3 install sdist bdist_wheel

### Builder le projet

* **windows** : python setup.py sdist bdist_wheel
* **linux** : sudo py setup.py sdist bdist_wheel

### Deployer le projet sur pip

* **windows** : python -m twine upload dist/*
* **linux** : sudo twine upload dist/*

## Git

### Cloner le projet

git init && git remote add origin https://[username]@bitbucket.org/[username]/pypyarc.git && git config user.email [email] && git checkout -b [branche] && git pull origin [branche]

### Pousser le projet

git checkout [branche] && git add -A && git fetch && git merge [branche] && git commit -am "[le message commit]" && git push -u origin [branche]

## Tests

* **windows** : cls && python test.py --generate-module="module-cstm" --destination="E:\conserver\projects\mix-app\hivienv\pyarc-demo"
* **linux** : clear && python test.py -h lorem1 bilong ntouba -prename2 custom --prename cÃ©lestin --config=conf.json --name="title 2"

## Docstring

### Installations prÃ©alables

* **windows** : python -m pip install pdoc3
* **linux** : sudo -H pip3 install pdoc3

### Au prÃ©alable

Documenter aux prÃ©alables son code.

### Generer une documentation

* **windows** : python -m pdoc [projet]
* **linux** : sudo pdoc [projet]

### Exemple d'utilisation

#### Generer le module

```cmd 
python pyarccli --generate-module="module-cstm" --destination="E:\conserver\projects\mix-app\hivienv\pyarc-demo"
```

#### Aide

```cmd 
python pyarccli -h
```

```python 
###
```
shippingtracker 0.1.2
Korean shipping tracker MCP server using SweetTracker API
Requires Python: >=3.13

# ShippingTracker MCP Server

한국 택배 추적을 위한 MCP (Model Context Protocol) 서버입니다. SweetTracker API를 사용하여 배송 추적 기능을 제공합니다.

## 기능

- `get_company_list()`: 지원하는 택배회사 목록 조회
- `track_shipping(company_code, tracking_invoice)`: 택배 추적

## 사전 요구사항

- [SweetTracker (스마트택배)](https://www.sweettracker.co.kr/) API 키

## 로컬 개발

### 1. 저장소 클론

```bash
git clone https://github.com/gws8820/shippingtracker.git
cd shippingtracker
```

### 2. 환경변수 설정

```bash
echo "SWEETTRACKER_API_KEY=YOUR_API_KEY" > .env
```

### 3. 실행

```bash
uv run python -m shippingtracker.main

# 또는 uvx로 실행
uvx --from . shippingtracker
```

## Claude Desktop과 연결

Claude Desktop의 설정 파일(`claude_desktop_config.json`)을 다음과 같이 설정해 주세요.

```json
{
  "mcpServers": {
    "shippingtracker": {
      "command": "uvx",
      "args": ["shippingtracker"],
      "env": {
        "SWEETTRACKER_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}
```

## 라이선스

이 프로젝트는 [MIT 라이선스](LICENSE)하에 배포됩니다.