semvec/pypi-packages huggingface dataset:
deepsearchkit 1.0.1
A small, fast, and easy package for semantic searching using artificial intelligence.

Note: This project is still a work-in-progress. It works, but it doesn't have many features yet. Please suggest features, report problems (bugs should go in Issues), or just say hi in Discussions!

![PyPI - Downloads](https://img.shields.io/pypi/dm/deepsearchkit)

# :mag: DeepSearchKit

A small, fast, and easy package that allows easy semantic searching using :brain: artificial intelligence. It is based on and similar to the closed-source DeepSearch system.

## :computer: Installation

You can install the latest stable version from the registry:

```
pip3 install deepsearchkit
```

You can install the very latest version directly from the Git repository, however certain features may not work:

```
pip3 install git+https://github.com/fakerybakery/deepsearchkit
```

## :white_check_mark: Features

 * CPU, CUDA, and MPS support (enhanced GPU acceleration)!
 * Simple usage

## :newspaper: Usage

Documentation is available [here](DOCUMENTATION.md).

## :thought_balloon: Todo

- [ ] Integrate DeepSearch into DeepSearchKit
  - [ ] Open-source DeepSearch
- [ ] Add Web Interface (from DeepSearch)
- [ ] Add document search demo
  - [ ] Add document chat demo
- [ ] Add upsert feature ([txtai#251](https://github.com/neuml/txtai/issues/251))
- [ ] Add more data support, e.g. parquet, MySQL/hosted DBs
- [ ] Custom prompt/data format for multiple columns in JSON
- [ ] Custom progress callback for indexing
- [ ] Make some example projects
  - [ ] Chat with a folder using open-sourced conversational models
  - [ ] Search an entire directory
- [ ] Allow easy publishing with a `.dskpkg` file - compressed DeepSearchKit package that includes the index, the data, and some attributes (name, author, license, etc)
  - [ ] Maybe in the future: "DSK Hub" - hub for DSK packages

## :memo: Credits

We would like to thank the authors of the following open source projects:

 * [sentence-transformers](https://github.com/UKPLab/sentence-transformers)
 * [txtai](https://github.com/neuml/txtai)

## :briefcase: Disclaimer/Agreement (Read BEFORE you contribute!)

In every new issue/PR, make sure to include "I agree to the disclaimer!"

By using/contributing to this software, you agree to the [agreement](DISCLAIMER.md).
mkdocs-code-validator 0.2.0
Checks Markdown code blocks in a MkDocs site against user-defined actions
Requires Python: >=3.7
Keywords: mkdocs,mkdocs-plugin

# mkdocs-code-validator

**Checks Markdown code blocks in a [MkDocs][] site against user-defined actions**

[![PyPI](https://img.shields.io/pypi/v/mkdocs-code-validator)](https://pypi.org/project/mkdocs-code-validator/)
[![License](https://img.shields.io/github/license/oprypin/mkdocs-code-validator)](https://github.com/oprypin/mkdocs-code-validator/blob/master/LICENSE.md)
[![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/oprypin/mkdocs-code-validator/ci.yml.svg)](https://github.com/oprypin/mkdocs-code-validator/actions?query=event%3Apush+branch%3Amaster)

```shell
pip install mkdocs-code-validator
```

## Usage

Activate the plugin in **mkdocs.yml**. The `identifiers` config is mandatory. And the plugin **doesn't work without [pymdownx.superfences][]**:

```yaml
plugins:
  - search
  - code-validator:
      identifiers:
        bash:
          validators:
            - grep a
markdown_extensions:
  - pymdownx.superfences
```

The above contrived config checks that every <code>```bash</code> code block in the Markdown files of this MkDocs site must contain the letter "a", otherwise a warning will appear.

The content of each code block is piped as stdin to the command. The exit code of the command is what's checked: a non-zero code will produce a warning (which in MkDocs you can make fatal with the `--strict` flag). The output of the command is not used in any way, only preserved on the screen as part of a warning.

You can add any number of identifiers, and within them any number of `validators` commands, each of them has the ability to produce a warning.

If stdin is not usable with your command, the input can be passed as a temporary file instead -- that is done if the command contains the exact argument `$<` (which is then replaced with a file path). For the above example, changing the command to `grep a $<` would be equivalent (other than technicalities).

The commands do *not* allow freeform shell syntax, it's just one subprocess to call with its arguments. To explicitly opt into a shell, just run it as (e.g.) `sh -c 'if grep a; then exit 1; fi'`. Or, with a temporary file: `sh -c 'if grep a "$1"; then exit 1; fi' $<`.

The definition of what a code block is is all according to the [pymdownx.superfences][] extension. It must be enabled; the plugin won't do anything without it.


[mkdocs]: https://www.mkdocs.org/
[documentation site]: https://oprypin.github.io/mkdocs-code-validator
[pymdownx.superfences]: https://facelessuser.github.io/pymdown-extensions/extensions/superfences/
choose-your-own-adventure 0.4.0
Choose Your Own Adventure (CYOA) stories using the Language Model LLM.
Requires Python: >=3.10

# Choose Your Own Adventure !
Choose Your Own Adventure (CYOA) stories using the Language Model LLM.

## Description

This repository contains code that enables users to create and explore Choose Your Own Adventure (CYOA) stories using the Language Model LLM. With this code, users can craft their own interactive narratives, where the reader/player can make decisions that impact the progression and outcome of the story.

The Language Model LLM provides a powerful tool for generating text that is consistent and coherent. By leveraging LLM, this code enables the creation of dynamic narratives that adapt to user choices, resulting in a personalized and engaging reading experience.

The repository includes a user-friendly interface that allows authors to input their story structure, define decision points, and specify branching paths. The code then uses LLM to generate subsequent story sections based on user-selected options.

The CYOA functionality provided by this code allows users to immerse themselves in stories that cater to their preferences, fostering creativity and imagination in both authors and readers. Whether you are an aspiring writer looking to craft interactive narratives or a reader seeking an innovative storytelling experience, this repository offers an exciting platform to explore the world of Choose Your Own Adventure stories using the power of LLM.

## Installation

```bash
pip install choose-your-own-adventure
```

## Play 
```bash
cyoa
```
kartezio 1.0.0a1
A CGP Framework for Image Processing
Keywords: Machine Learning,Cartesian Genetic Programming,Computer Vision

<h2 align="center"> Kartezio </h2>
<h5 align="center"> A Darwinian Designer of Explainable Algorithms for Biomedical Image Segmentation </h5>

## Package Description
[TODO]

## Installation

Tested on Windows, Ubuntu 18.04, Ubuntu 22.04.

Tested with different versions of Python3: 3.7, 3.8, 3.9 and 3.10.


### Creation of a virtualenv is recommanded:

```bash
python3 -m pip install virtualenv
python3 -m venv <path/to/venv/venv_name>
source <path/to/venv/venv_name>/bin/activate
pip install --upgrade pip
```

### Installation from Pypi

```bash
(venv_name)$ pip install kartezio
```

### Local installation using pip

```bash
(venv_name)$ git clone [TODO] 
(venv_name)$ cd kartezio
(venv_name)$ python -m pip install -e .
```
## First steps
[TODO]

## Reported Results
Kartezio was compared on the Cell Image Library dataset against the reported performance of Cellpose/Stardist/MRCNN (December, 2022) as reported in Stringer et al, Nature Methods, 2021 and published in Cortacero et al, Nature Communnications, 2023:

|                  | Kartezio | Kartezio | Kartezio | Cellpose | Stardist | MRCNN |
|------------------|----------|----------|----------|----------|----------|-------|
| Training images  | 8        | 50       | 89       | 89       | 89       | 89    |
| AP50 on test set | 0.838 (mean)| 0.849 (mean)| 0.858 (mean) | 0.91 (max)   | 0.76 (max)     | 0.80 (max |

An additional, but not published, comparison was performed against the reported performance of CPP-Net, on BBBC006v1 dataset reported in Chen et al, 2023 (July, 2023):

|                  | Kartezio-s1 | Kartezio-s2 | CPP-Net | Stardist | 
|------------------|-------------|-------------|---------|----------|
| Training images  | 20          | 20          | 538     |   538    | 
| AP50 on test set | 0.822       | 0.879       | 0.9811  | 0.9757   |

## References and Citation
[TODO .bibtex]


## Licensing
The Software must be used for Non-Commercial Research only, under the terms and conditions set out in the License file, and You may not use the Software except in compliance with the License.
The Software distributed under the License is distributed on an "as is" basis, without warranties or conditions of any kind, either express or implied.
See the License file for the specific language governing permissions and limitations under the License.