semvec/pypi-packages huggingface dataset:
research-task 0.1.7
LLM Research tool
License: MIT

# LLM Analyst
LLM Analyst leverages the power of LLMs to create research reports based on a Local Data Store of Reference Articles

## This code is a rewrite of `gpt-researcher`.

* If you are looking for a code base that is being actively developed
* Has a strong community following
* And provides an excellent foundation for Internet Research 
* __I recommend the original code base__
* https://github.com/assafelovic/gpt-researcher
rpca 0.1.6
Robust PCA using Accelerated Alternating Projection
License: MIT
Requires Python: <3.13,>=3.9

# AccAltProj for robust PCA

<p align="center">
  <a href="https://github.com/loiccoyle/RPCA/actions/workflows/ci.yml"><img src="https://github.com/loiccoyle/RPCA/actions/workflows/ci.yml/badge.svg"></a>
  <a href="https://pypi.org/project/rpca/"><img src="https://img.shields.io/pypi/v/rpca"></a>
  <a href="./LICENSE.md"><img src="https://img.shields.io/badge/license-MIT-blue.svg"></a>
  <img src="https://img.shields.io/badge/platform-linux%20%7C%20macOS%20%7C%20windows-informational">
</p>

> Port of the AccAltProj algorithm for robust PCA to python.

<div align="center">
  <image src="https://github.com/loiccoyle/RPCA/assets/33181239/dbccf187-740f-461f-8e05-78ad497b2d30" />
</div>

This is a python port of the [AccAltProj algorithm for robust PCA](https://github.com/caesarcai/AccAltProj_for_RPCA), described in this [paper](https://arxiv.org/abs/1711.05519).

This implementation follows `sklearn`'s `fit` & `transform` API.

## 📦 Installation

Requires python 3

In a terminal:

```sh
pip install rpca
```

As always, it is usually a good idea to use a [virtual environment](https://docs.python.org/3/library/venv.html).
terrajinja-sbp-vault 0.2.1
Terrajinja extension for automation using cdktf
License: MIT

# terrajinja-sbp-vault

This is an extension to the vault provider for the following modules.
The original documentation can be found [here](https://registry.terraform.io/providers/hashicorp/vault/latest/docs)

# SBP Specific implementations
Here is a list of supported resources and their modifications

## sbp.vault.kv_secret_v2
Original provider: [vault.kv_secret_v2](https://registry.terraform.io/providers/hashicorp/vault/latest/docs/resources/kv_secret_v2)

This custom provider adds the following:
- automaticly convert data to json as input for the resource
- automaticly create random passwords if requested

| old parameter | new parameter | description                                                           |
| ------ | ------ |-----------------------------------------------------------------------|
| data_json | data | the data field is automaticly converted to json                       |
| lifecycle | - | default is set to ignore all changes only if random passwords are used |

additional to the above the data structure expected is in the format:
```
{ 
    "key": "value",
    "key2": "value2",
}
```
if any of the values contains the word "random" then a rendomly generated password is created of 30 characters

example:
```
{
    "my_secret": "random"
}
```
will result in a random string being created as password for my_secret

### terrajinja-cli example
the following is a code snipet you can used in a terrajinja-cli template file.
This created both the hashicorp vault with the name `generic`, and adds a secret in it in the path `application` with key `admin` that contains a random password
```
terraform:
  resources:
    - task: vault-mount-generic
      module: vault.mount
      parameters:
        path: "generic"
        type: "kv"
        options:
            version: "2"

    - task: vault-application-password
      module: sbp.vault.kv_secret_v2
      parameters:
        mount: $vault-mount-generic.path
        name: "application"
        data:
          admin: "random"
```



History
-------

0.0.1 (14-03-2024)
---------------------

* First code creation