semvec/pypi-packages huggingface dataset:
alfreds 0.0.19
Alfreds CLI
Requires Python: >=3.8

# Alfreds CLI Tool
Alfreds (www.alfreds.ai) is the LLM platform for data teams. It enables data teams to create LLM agents that can be used
in different stages of data workflows.
Alfreds command-line tool allows data teams to install alfreds platform on their local machines and perform various tasks.

## Prerequisites

1. Python 3.6 or higher
2. Docker
3. Linux or macOS

## Installation

To install alfreds, run the following command:

```
pip install alfreds
```

## Usage

Alfreds can perform the following tasks:

1. Initialize alfreds:
   ```
   alfreds init --agent_path {agent_absolute_path} --working_dir {working_dir_absolute_path} --seed_dir {seeds_absolute_path(optional)}
   ```
   This command initializes alfreds with the specified agent, working directory, and seeds (optional). 
   <br>
   Example:
   ```
    alfreds init --agent_path /Users/subu/alfreds/agent --working_dir /Users/subu/alfreds/working_dir --seed_dir /Users/subu/alfreds/seeds
    ```
2. Update the agent:
   ```
   alfreds update_agent {agent_absolute_path}
   ```
   This command updates the agent with the specified absolute path.
   <br>
   Example:
    ```
    alfreds update_agent /Users/subu/alfreds/agent
    ```

3. Update the working directory:
   ```
   alfreds update_working_dir {working_dir_absolute_path}
   ```
   This command updates the working directory with the specified absolute path.

4. Seed the application:
   ```
   alfreds seed {seed dir/csv file absolute path}
   ```
   This command seeds the application with the specified seed directory or CSV file.

5. Stop alfreds:
   ```
   alfreds stop
   ```
   This command stops the alfreds application.

6. Start alfreds:
   ```
   alfreds start
   ```
   This command starts the alfreds application.

7. Refresh alfreds:
   ```
   alfreds refresh
   ```
   This command refreshes the alfreds application.

8. Alfreds Help:
   ```
   alfreds --help
   ```
   This command displays the help menu for alfreds.

Please note that you need to provide the absolute paths for the agent, working directory, and seeds when using the respective commands.

If you have any questions or need further assistance, please refer to the alfreds documentation or contact our support team.
odb2vtk 1.0.0
ODB2VTK converter
Requires Python: >=3.7

# odb2vtk

A python wrapper package for the [ODB2VTK](https://github.com/Arris-Composites/ODB2VTK) library.

## Installation

```sh
pip install odb2vtk
```

## Usage

Use the `odb2vtk` command to convert an ODB file to a VTK file.

```sh
$ odb2vtk --help

usage: odb2vtk.py [-h] [--header HEADER] [--instance [INSTANCE [INSTANCE ...]]]
                  [--step [STEP [STEP ...]]] [--writeHistory WRITEHISTORY]
                  --odbFile ODBFILE [--writePVD WRITEPVD] [--suffix SUFFIX]

optional arguments:
  -h, --help            show this help message and exit
  --header HEADER       if 1, extract header information and generate a .json
                        file. Otherwise, generate .vtu file. By default 0
  --instance [INSTANCE [INSTANCE ...]]
                        selected instance names which are separated by
                        whitespace, e.g. 'instanceName1' 'instanceName2'
  --step [STEP [STEP ...]]
                        selected step names and frames which are separated by
                        whitespace, e.g., 'step1:1,2,3' 'step2:2,3,4'. The
                        frames can be any valid Python expression that can be
                        evaluated to an integer iterable, e.g., 'range(1, 10)'
  --writeHistory WRITEHISTORY
                        if 1, write history output.
  --odbFile ODBFILE     selected odb file (full path name)
  --writePVD WRITEPVD   if 1 write a pvd file
  --suffix SUFFIX       string appended to the file
```

Use the `odb2vtk-multiprocess` command for the multiprocessing version.

```sh
$ odb2vtk-multiprocess --help

usage: odb2vtk-multiprocess [-h] [--header HEADER] [--instance [INSTANCE ...]]
                            [--step [STEP ...]] [--writeHistory WRITEHISTORY]
                            --odbFile ODBFILE [--suffix SUFFIX]

options:
  -h, --help            show this help message and exit
  --header HEADER       if 1, extract header information and generate a .json
                        file. Otherwise, generate .vtu file. By default 0
  --instance [INSTANCE ...]
                        selected instance names which are separated by
                        whitespace, e.g. 'instanceName1' 'instanceName2'
  --step [STEP ...]     selected step names and frames which are separated by
                        whitespace, e.g., 'step1:1,2,3' 'step2:2,3,4'. The
                        frames can be any valid Python expression that can be
                        evaluated to an integer iterable, e.g., 'range(1, 10)'
  --writeHistory WRITEHISTORY
                        if 1, write history output.
  --odbFile ODBFILE     selected odb file (full path name)
  --suffix SUFFIX       string appended to the file
```