semvec/pypi-packages huggingface dataset:
enki-runtime 0.1.0
Python bindings for Enki agent runtime with memory, tools, and HTTP server
Requires Python: >=3.8
Keywords: ai, agent, runtime, llm, chatbot, memory, tools

# Enki Runtime

Python bindings for the Enki agent runtime, providing a powerful framework for building AI agents with memory, tools, and HTTP server capabilities.

## Features

- **Agent Runtime**: Run and manage AI agents with built-in lifecycle management
- **Memory System**: Pluggable memory stores with in-memory and custom implementations
- **Tool System**: Decorator-based tool registration for agent capabilities
- **HTTP Server**: Built-in HTTP API server for agent interactions
- **Multi-Agent Support**: Run multiple agents concurrently with dynamic registration

## Installation

```bash
pip install enki-runtime
```

## Quick Start

### Basic Agent

```python
from enki_sdk import Agent, tool
import enki_runtime

@Agent
class MyAgent:
    """A simple agent example"""
    
    @tool
    def greet(self, name: str) -> str:
        """Greet someone by name"""
        return f"Hello, {name}!"

# Create and run agent
config = enki_runtime.AgentConfig(
    name="my-agent",
    model="gpt-4",
    system_prompt="You are a helpful assistant."
)

agent = MyAgent(config)
response = agent.chat("Say hello to Alice")
print(response)
```

### Memory Store

```python
from enki_sdk import InMemoryStore

# Use built-in memory store
memory = InMemoryStore()
memory.save("key", "value")
value = memory.get("key")
```

### HTTP Server

```python
from enki_runtime import EnkiRuntime

# Start runtime with HTTP server
runtime = EnkiRuntime()
runtime.start_server("0.0.0.0", 8000)

# Register agents dynamically
runtime.register_agent("agent-1", agent_config)
```

## Documentation

For more examples and detailed documentation, see the [examples](examples/) directory.

## Requirements

- Python >= 3.8
- Rust (for building from source)

## License

MIT License - see LICENSE file for details.

## Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.
harmonized-landsat-sentinel 2.3.0
Harmonized Landsat Sentinel (HLS) search and download utility
Requires Python: >=3.10

# Harmonized Landsat Sentinel (HLS) Python Search and Download Utility

[![CI](https://github.com/STARS-Data-Fusion/harmonized-landsat-sentinel/actions/workflows/ci.yml/badge.svg)](https://github.com/STARS-Data-Fusion/harmonized-landsat-sentinel/actions/workflows/ci.yml)

[Gregory H. Halverson](https://github.com/gregory-halverson-jpl) (they/them)<br>
[gregory.h.halverson@jpl.nasa.gov](mailto:gregory.h.halverson@jpl.nasa.gov)<br>
NASA Jet Propulsion Laboratory 329G

[Evan Davis](https://github.com/evandjpl) (he/him)<br>
[evan.w.davis@jpl.nasa.gov](mailto:evan.w.davis@jpl.nasa.gov)<br>
NASA Jet Propulsion Laboratory 397K

## Installation

This package is available on PyPi: [https://pypi.org/project/harmonized-landsat-sentinel](https://pypi.org/project/harmonized-landsat-sentinel)

```
pip install harmonized-landsat-sentinel
```

## References

If you use this package to access or analyze the Harmonized Landsat Sentinel (HLS) dataset, please cite the following datasets and research articles:

### Data Citations

- **HLS v2.0 (L30 and S30)**:  
  NASA Goddard Space Flight Center; U.S. Geological Survey. (2022). Harmonized Landsat Sentinel-2 (HLS) Product, Version 2.0 [Dataset]. NASA LP DAAC. https://doi.org/10.5067/HLS/HLS.020

### Peer-Reviewed Articles

1. **Roy, D. P., Li, J., Zhang, H. K., & Yan, L. (2016)**. *The Harmonized Landsat and Sentinel-2 (HLS) Product: An Analytical Framework for Characterizing Land Cover Using Satellite Remote Sensing*. Remote Sensing of Environment, 176, 152-171. https://doi.org/10.1016/j.rse.2015.12.024  
   This foundational article presents the analytical framework for harmonizing Landsat and Sentinel-2 data, discussing challenges in land cover characterization and product development.

2. **Claverie, M., Ju, J., Masek, J. G., Dungan, J. L., Vermote, E. F., Roger, J. C., Skakun, S., & Justice, C. O. (2018)**. *Harmonized Landsat-8 Sentinel-2 Products for Land Monitoring*. Remote Sensing of Environment, 219, 145-161. https://doi.org/10.1016/j.rse.2018.09.002  
   This article describes the harmonization process, atmospheric correction, and band alignment used in generating the HLS products.

3. **Feng, M., Vermote, E. F., & Masek, J. G. (2020)**. *Harmonized Landsat Sentinel-2 Data for Monitoring Global Agriculture*. Remote Sensing, 12(22), 3684. https://doi.org/10.3390/rs12223684  
   This paper highlights applications of HLS in agricultural monitoring, with validation studies that underscore its importance for tracking global agricultural patterns.
osqp 1.1.1
OSQP: The Operator Splitting QP Solver
Requires Python: >=3.8

[![PyPI version](https://badge.fury.io/py/osqp.svg)](https://badge.fury.io/py/osqp)
[![Python 3.8‒3.14](https://img.shields.io/badge/python-3.8%E2%80%923.14-blue)](https://www.python.org)
[![Build](https://github.com/osqp/osqp-python/actions/workflows/build_default.yml/badge.svg)](https://github.com/osqp/osqp-python/actions/workflows/build_default.yml)

# OSQP Python
Python wrapper for [OSQP](https://osqp.org): The Operator Splitting QP solver.

The OSQP (Operator Splitting Quadratic Program) solver is a numerical
optimization package for solving problems in the form

$$\begin{array}{ll}
    \mbox{minimize} & \frac{1}{2} x^T P x + q^T x \\
    \mbox{subject to} & l \le A x \le u
\end{array}
$$

where $\( x \in \mathbf{R}^n \)$ is the optimization variable and $\( P \in \mathbf{S}^{n}_{+} \)$ is a positive semidefinite matrix.

## Installation
To install `osqp` for python, make sure that you're using a recent version of `pip` (`pip install --upgrade pip`)
and then use ``pip install osqp``.

To install `osqp` from source, clone the repository (`git clone https://github.com/osqp/osqp-python`)
and run `pip install .` from inside the cloned folder.

## Documentation
The interface is documented [here](https://osqp.org/docs/interfaces/python.html).