semvec/pypi-packages huggingface dataset:
jupyter-deploy-test 0.1.0a1
CLI based tool to deploy Jupyter application that integrates with infrastructure as code frameworks.
Requires Python: >=3.12

# JupyterDeploy

Jupyter deploy provides a command line interface tool (CLI) that you can
use to deploy a Jupyter Server container to a remote compute provided by a Cloud provider.

### Install Terraform

Terraform from HashiCorp is the default deployment engine. To use it, you must set it up in your system.
Refer to Terraform installation [guide](https://developer.hashicorp.com/terraform/tutorials/aws-get-started/install-cli).

Verify installation by running
```bash
terraform --version
```

## Install jupyter-deploy dependencies

From the repository root, run:

```bash
# Sync all dependencies
uv sync
```

## The CLI

To get started, open a terminal, cd to the repository root, and run:

```bash
uv run jupyter-deploy --help
```

## Templates

To use a template to initialize a new project, first create a new project directory:

```bash
mkdir my-jupyter-deployment
cd my-jupyter-deployment
```

Then, run the `init` command.

```bash
uv run jupyter-deploy init -E terraform -P aws -I ec2 -T traefik .
```
edidio-control 0.0.1
Python library for controlling the Control Freak eDIDIO S10 device.
Requires Python: >=3.9

# Edidio Control Plugin

A Python library for communicating with and controlling the Control Freak eDIDIO S10 device.

## Features

- Asynchronous TCP communication with eDIDIO controllers.
- Support for DMX and DALI (including DALI DT8 CCT) message creation.
- Connection management including keep-alive and auto-reconnect.

## Installation

This plugin can be installed via pip:

```bash
pip install edidio_control
llamka 0.0.5
llamka - Attempt to make Second Brain - Simple stand alone UI for RAG loader pipline/chatbot/api
Requires Python: <4.0,>=3.11

# llamka
 
[![CI](https://github.com/walnutgeek/llamka/actions/workflows/ci.yml/badge.svg)](https://github.com/walnutgeek/llamka/actions/workflows/ci.yml)

MLOps for building second brain

There is few principles we want to build llamka around


| Principle | Because |
| :-- | :-- |
| Standardize interface for different model vendors | Ability to substitute and store conversations uniformly |
| Automation of pipelines | Consistency  |
| Maintain teargeted conversation datasets | Capture requirements and provide data for finetuining and evaluation |
| Model evaluation and management | Informed decision making about trade off between open and closed models |
| Preference to open weight models and self hosting | Ability to finetune, privacy and lower cost |



## Architecture

* llore - (llamka-core) Tornado App that keep everything running. llore provides api and all other services built on top of it
    * MVP
        - [x] provide abstraction interface over LLM providers (local: ollama;  remote: openai,  claude;)
        - [x] maintain external document locations/versions and rebuild vector db collections on changes
        - [ ] augmentation pipelines and chatbot config
        - [x] completion api to interact with configured models and chatbots
    * later
        - [ ] store chatbot interactions in oumi conversation format per user if instructed
        - [ ] maintain chatbot library (includes: system prompt, finetuning and augmentation pipelines, data dependencies, and build schedule)
        - [ ] maintain conversation datasets and use them for tuning, RAG and testing
        - [ ] schedule and run pipelines: finetuning, RAG, chatbot evaluation 
        - [ ] monitor and run services: databases, queues, proxies, ui (llit)

* llit - streamlit UI 
    * MVP
        - [x] Chatbot interaction 
    * later
        - [ ] Inspect previous conversations or from library
        - [ ] Inspect data: sql, document db, vector db
        - [ ] Inspect logs from pipelines
        - [ ] Configuration: models, chatbot, pipelines


Got API and streamlit endpoints working, almost MVP!!!

![Screenshot_2025-06-08](Screenshot_2025-06-08.png)



* * *

## Project Docs

For how to install uv and Python, see [installation.md](installation.md).

For development workflows, see [development.md](development.md).

For instructions on publishing to PyPI, see [publishing.md](publishing.md).

* * *

*This project was built from
[simple-modern-uv](https://github.com/jlevy/simple-modern-uv).*