semvec/pypi-packages huggingface dataset:
grammarchecking1 0.1.0
Grammar checking using Ai
Requires Python: >=3.6

# Grammar Check Tool

This is a web application built using Flask to check grammar errors in uploaded text files.

## Features

- Upload `.csv`, `.xlsx`, or `.txt` files.
- Process and check grammar.
- Download the corrected file with grammar fixes and explanations.

## Setup

1. Clone the repository.
2. Install dependencies:

```bash
pip install -r requirements.txt
authese 0.1.7
OpenID Connect JWT Token Snatcher
Requires Python: >=3.8

# Authese

### Authenticate through OpenID Connect and cache your JWT token in a file.

## Example
```
from authese import get_token, EnvConfig, Environment

token = get_token(EnvConfig.from_env(Environment.STAGING))
```

## Install
`pip install authese`

## Info
There are 3 possible environments.
- LOCAL
- STAGING
- PROD
#### Assuming STAGING
Create an EnvConfig object.
Call get_token() and provide it with the EnvConfig object.  
### EnvConfig
#### - Personal access token  
  `grant_type: ''`  *Identical to `grant_type: 'authorization_code'`*  
  This is the **default** authorization flow.  
  This will open a browser window where you can authenticate to the requested keycloak_url.  
  
#### - Server to server  
  Depending if you set the `grant_type: 'client_credentials'`.  
This will authenticate to the requested keycloak_url using the client credentials.  

### Cache

Once authenticated, your token will be cached at /tmp/authese-cache.dat  
Subsequent calls to get_token() will use the cached token.  
When the token expires it will be deleted and you must authenticate again.

To force reauthentication just remove the /tmp/authese-cache.dat file.

## Config
```
local:
staging:
  keycloak_url: 'https://<openid-host>/realms/<realm>/protocol/openid-connect'
  grant_type: '<authorization_code | client_credentials>'
  client_id: '<client_id>'
  client_secret: '<client_secret>'
  redirect_host: 'http://127.0.0.1'
  redirect_port: 9981
  scopes:
    - 'email'
    - 'profile'
prod:
  keycloak_url: 'https://<openid-host>/realms/<realm>/protocol/openid-connect'
  grant_type: '<authorization_code | client_credentials>'
  client_id: '<client_id>'
  client_secret: '<client_secret>'
  redirect_host: 'http://127.0.0.1'
  redirect_port: 9981
  scopes:
    - 'email'
    - 'profile'
```
eryonai 0.11.0
Eryon AI is an advanced language model designed for interactive tasks.
Requires Python: >=3.6

# EryonAI

EryonAI is a custom version of Llama architecture for interactive tasks, such as keyword detection, memory recall, and improved performance by Wikipedia search integration. It was trained on the same datasets used by Llama models, but it also contains extra custom datasets geared for all sorts of tasks.

## Features

* **Modified Llama Architecture**: EryonAI is based on the architecture of Llama but comprises personalized configurations, including external memory and keyword-based processing.
- **Wikipedia Search**: The model can search Wikipedia for relevant information to enhance its responses. This allows it to provide real-time insights on various topics, powered by the Wikipedia API.
- **Memory Recall**: The model can "remember" previous inputs and recall them to provide context to new queries.
- **Custom Datasets**: EryonAI was not only trained on Llama's publicly available datasets but also on custom datasets to improve performance in specific domains.

## Installation

To install the EryonAI package, you can use pip:

```bash
pip install eryonai
```

## Training

EryonAI was trained on Google Colab's GPU using the same datasets as Llama models but modified for memory and external internet search capabilities. This training was executed on custom datasets in order to adapt the model to specific uses.

## Special Thanks

- **Wikipedia**: This project would not have been possible without all the valuable data provided by the API, which runs the search within EryonAI.
- **Meta**: For creating the original Llama models, on which EryonAI was built.
oarepo-oidc-einfra-uvt 1.0.3
E-infra OIDC Auth backend for OARepo

# E-infra authentication and authorization module for InvenioRDM

This remote backend adds support for Czech e-infra AAI solution - login.e-infra.cz
allowing all members of czech academic community can use their home institution
credentials to log in.

## Installation

Add the module to your repository's pyproject.toml:

``` toml

dependencies = [
    "oarepo-oidc-einfra>=1.0.0",
    # ...
]
```

## Configuration

1. Register a new application with e-infra OIDC Provider at
   https://spadmin.e-infra.cz/. When registering the application
   ensure that the *Redirect URI* points to `https://<my_invenio_site>:5000/oauth/authorized/e-infra/`


![General parameters](docs/settings1.png)


![OIDC parameters](docs/settings2.png)

In OIDC parameters, you need to set at least the following scopes:
- openid
- profile
- email
- eduperson_entitlement
- isCesnetEligibleLastSeen
- organization


![Perun-specific parameters](docs/settings3.png)


2. Grab the *Client ID* and *Client Secret* after registering the application
   and add them to your ENVIRONMENT variables:
```python
INVENIO_EINFRA_CONSUMER_KEY=*Client ID*
INVENIO_EINFRA_CONSUMER_SECRET=*Client Secret*
```
3. Add the remote application to the site's `invenio.cfg`:

```python
from oarepo_oidc_einfra import EINFRA_LOGIN_APP

OAUTHCLIENT_REMOTE_APPS = {
    "e-infra": EINFRA_LOGIN_APP
}
```

4. Add the e-infra public key to your invenio.cfg or environment variables:
```python
EINFRA_RSA_KEY=b'-----BEGIN PUBLIC KEY-----\nMIIBIjANBgkqhkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEAmho5h/lz6USUUazQaVT3\nPHloIk/Ljs2vZl/RAaitkXDx6aqpl1kGpS44eYJOaer4oWc6/QNaMtynvlSlnkuW\nrG765adNKT9sgAWSrPb81xkojsQabrSNv4nIOWUQi0Tjh0WxXQmbV+bMxkVaElhd\nHNFzUfHv+XqI8Hkc82mIGtyeMQn+VAuZbYkVXnjyCwwa9RmPOSH+O4N4epDXKk1V\nK9dUxf/rEYbjMNZGDva30do0mrBkU8W3O1mDVJSSgHn4ejKdGNYMm0JKPAgCWyPW\nJDoL092ctPCFlUMBBZ/OP3omvgnw0GaWZXxqSqaSvxFJkqCHqLMwpxmWTTAgEvAb\nnwIDAQAB\n-----END PUBLIC KEY-----\n'
```

5. Add the VO, communities group, api url and others to your invenio.cfg or environment variables:

```python

EINFRA_SERVICE_USERNAME = "username"
"""Username of the service in the E-INFRA Perun."""

EINFRA_SERVICE_PASSWORD = "password"
"""Password of the service in the E-INFRA Perun."""

EINFRA_SERVICE_ID = 0
"""Internal ID of the service (whose username and password are above) in the E-INFRA Perun."""

EINFRA_REPOSITORY_VO_ID = 0
"""Internal ID of the VO in the E-INFRA Perun that represents the repository."""

EINFRA_COMMUNITIES_GROUP_ID = 0
"""Internal ID of the group in the E-INFRA Perun that represents the communities."""

EINFRA_REPOSITORY_FACILITY_ID = 0
"""Internal ID of the facility in the E-INFRA Perun that represents the repository."""

EINFRA_CAPABILITIES_ATTRIBUTE_ID = 0
"""Internal ID of the attribute in the E-INFRA Perun that represents the capabilities."""

EINFRA_SYNC_SERVICE_ID = 0
"""Internal ID of the service in the E-INFRA Perun that is responsible for synchronization
(creating and pushing dumps with resources and users)."""

```

6. Start the server and go to the login page https://127.0.0.1:5000/login/