semvec/pypi-packages huggingface dataset:
oarepo 14.1.1
CESNET, UCT Prague and NTK wrapper around Invenio v3.
License: MIT
Requires Python: <3.14,>=3.13
Keywords: oarepo, invenio

CESNET, UCT Prague and NTK wrapper around invenio v3
====================================================

This meta-package contains a curated and tested set of dependencies on Invenio and OArepo libraries.
It should be considered as a base building block for creating any OA repository applications.

Translations
------------

Note for RDM12:

This package also contains translations for all supported invenio languages,
as downloaded from Transifex server on June 20, 2025. 

If you want to make changes to translations, change them in the collected_translations
directory (use poedit to make tham as it will compile the .mo files for you).
If you need to change the javascript translations, add those directly 
to translation json files. Then create a PR to this repository with the changes.

During merge we'll make sure that these get propagated to RDM13 if approporiate.
langchain-moss 0.1.0
LangChain integration for Moss semantic search
License: MIT
Requires Python: >=3.11

# Moss LangChain Cookbook

This cookbook demonstrates how to integrate [Moss](https://moss.dev) with [LangChain](https://www.langchain.com/).

## Overview

Moss is a semantic search platform that allows you to build and query high-performance vector indices without managing infrastructure. This integration provides:

1.  **MossRetriever**: A LangChain-compatible retriever for semantic search.
2.  **MossSearchTool**: A tool for LangChain agents to search your knowledge base.

## Installation

Ensure you have the required packages installed:

```bash
pip install inferedge-moss langchain langchain-openai python-dotenv
```

## Setup

Create a `.env` file with your Moss credentials:

```env
MOSS_PROJECT_ID=your_project_id
MOSS_PROJECT_KEY=your_project_key
MOSS_INDEX_NAME=your_index_name
OPENAI_API_KEY=your_openai_api_key
```

## Usage

### Using the Retriever

The `MossRetriever` can be used in any LangChain chain.

```python
from moss_langchain import MossRetriever

retriever = MossRetriever(
    project_id="your_id",
    project_key="your_key",
    index_name="your_index",
    top_k=3,
    alpha=0
)

docs = retriever.invoke("What is the refund policy?")
```

### Using the Agent Tool

You can also use Moss as a tool for an agent.

```python
from moss_langchain import get_moss_tool

tool = get_moss_tool(
    project_id="your_id",
    project_key="your_key",
    index_name="your_index"
)

# Add to agent tools
tools = [tool]
```

## Examples

Check out the [moss_langchain.ipynb](moss_langchain.ipynb) notebook for complete examples including:

- Direct index querying
- Retrieval-Augmented Generation (RAG)
- ReAct Agent with Moss search
dsp-filter-design 0.1.0
An interactive Digital Signal Processing explorer for filter design and analysis.
License: MIT
Requires Python: >=3.9

# Digital Signal Processing Explorer

[![Launch App](https://img.shields.io/badge/Launch-App-success?style=for-the-badge&logo=rocket)](https://dsp-explorer.onrender.com)
An interactive tool for exploring Analog and Digital filters, poles, zeros, and stability.

## For Students
**[Click here to launch the app](https://dsp-explorer.onrender.com)**. No account or setup required.

## For Developers
If you want to host your own copy or modify the code:
[![Deploy to Render](https://render.com/images/deploy-to-render-button.svg)](https://render.com/deploy?repo=https://github.com/JWKennington/app-dsp-filter-design)

---

## Key Features

### 🎛️ Interactive Design
-   **Drag-and-Drop**: Move Poles and Zeros on the complex plane and watch the Bode and Impulse plots update instantly.
-   **Real-Time Feedback**: Immediate visualization of Magnitude, Phase, and Time-Domain response.

### 📈 Advanced Analysis
-   **Stability Visualization**: Toggle between **Causal** (standard) and **Anti-Causal** (stable reconstruction from unstable poles) modes.
-   **Two-Sided Impulse Response**:
    -   **Digital**: Moving poles outside $|z|=1$ generates left-sided sequences ($n < 0$).
    -   **Analog**: Moving poles to the Right Half Plane generates negative-time decay ($t < 0$).
-   **Bode Plot**: Logarithmic frequency application for Analog, Linear for Digital (normalized frequency).

### 🎨 Professional Branding
-   **LSC Branding**: Features a professional scientific color scheme (LSC Blue) and branding.
-   **Publication Ready**: Clean, compact layout suitable for demonstrations and teaching.

---

## Local Development

This project uses [uv](https://github.com/astral-sh/uv) for fast, reliable package management.

### Prerequisites
-   Python 3.9+
-   `uv` installed (`curl -LsSf https://astral.sh/uv/install.sh | sh`)

### Running the App

1.  **Clone the repository**:
    ```bash
    git clone https://github.com/JWKennington/app-dsp-filter-design.git
    cd app-dsp-filter-design
    ```

2.  **Sync dependencies**:
    ```bash
    uv sync
    ```

3.  **Run the application**:
    ```bash
    uv run dsp-fd
    ```
    Open [http://127.0.0.1:8050](http://127.0.0.1:8050) in your browser.

---

## Deployment

### Docker
A `Dockerfile` is included for containerized deployment.

```bash
docker build -t dsp-fd .
docker run -p 8050:8050 dsp-fd
```

### Render
This repository is configured for immediate deployment on Render.
1.  Click the **Deploy to Render** button above.
2.  Connect your GitHub account.
3.  Render will automatically build using the `Dockerfile` and deploy the service.

---

## License
MIT License. See `LICENSE` for details.

© 2026 James Kennington.