semvec/pypi-packages huggingface dataset:
intellibot 0.5
A CLI tool for interacting with intellibot API
Requires Python: >=3.6

# Intellibot

Intellibot is a terminal-based client for interacting with the ViewMo cloud platform. It allows users to connect to the platform using their credentials and chat with the bot through a command-line interface. And also this package let users to initialize there own RAG Agents and run them on ViewMo platform.

## Installation

To install Intellibot, run:

```sh
pip install intellibot
```

## Usage

### Connect to Intellibot

To connect to Intellibot, use the `connect` command with your username and password:

```sh 
intellibot connect --username <your-username> --password <your-password>
```

Example:

```sh 
intellibot connect --username jane@gmail.com --password pass
```

This command logs in to Intellibot and saves credentials to `credentials.json`.

### Chat with Intellibot

Once connected, you can start a chat session with the bot using the `chat` command:

```sh 
intellibot chat
```

Example:

```sh 
intellibot chat
```

This starts an interactive chat session where you can type messages and receive responses until you type "exit" or "quit".

### Initialize AI Agents

To initialize the AI agent system with a JSON configuration file, use the `initialize` command:

```sh 
intellibot initialize path/to/your/config.json
```

Example:

```sh 
intellibot initialize C:/intellihack_4.0/cli/ViewMo/config.json
```

### Check Available Projects

To list all available projects for the authenticated user, use the `projects` command:

```sh 
intellibot projects
```

Example:

```sh 
intellibot projects
```

### Execute a Project

To execute a specified project, use the `execute` command:

```sh 
intellibot execute project_name
```

Example:

```sh 
intellibot execute "Mental health chatbot researcher"
```

### View Active User Details

To display details of the authenticated user, use the `user_details` command:

```sh 
intellibot user_details
```

Example:

```sh 
intellibot user_details
```

## Development

To install the package locally for development, navigate to the root directory (where `setup.py` is located) and run:

```sh
pip install .
```

You can then use the `intellibot` CLI commands as described above to test the functionality.

## Project Structure

```sh
Intellibot/
â”œâ”€â”€ intellibot/
â”‚   â”œâ”€â”€ __init__.py
â”‚   â”œâ”€â”€ cli.py
â”‚   â””â”€â”€ api.py
â”œâ”€â”€ setup.py
â”œâ”€â”€ README.md
â”œâ”€â”€ requirements.txt
â””â”€â”€ MANIFEST.in
```

### API Module (`api.py`)

The `api.py` module contains the `IntelliBotAPI` class, which handles connection, chat, project management, and user details functionalities.

### CLI Module (`cli.py`)

The `cli.py` module defines the command-line interface using `click`. It includes commands for connecting to the backend, chatting with the bot, initializing agents, viewing projects, executing projects, and viewing user details.

## License

This project is licensed under the Apache 2.0 License.
maskgit 0.0.1.dev0
maskgit
Keywords: maskgit

# MaskGIT: Masked Generative Image Transformer
Official Jax Implementation of the CVPR 2022 Paper

[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/maskgit-masked-generative-image-transformer/image-generation-on-imagenet-512x512)](https://paperswithcode.com/sota/image-generation-on-imagenet-512x512?p=maskgit-masked-generative-image-transformer)
[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/maskgit-masked-generative-image-transformer/image-generation-on-imagenet-256x256)](https://paperswithcode.com/sota/image-generation-on-imagenet-256x256?p=maskgit-masked-generative-image-transformer)

[[Paper](https://arxiv.org/abs/2202.04200)] [[Project Page](https://masked-generative-image-transformer.github.io/)] [[Demo Colab](https://colab.research.google.com/github/google-research/maskgit/blob/main/MaskGIT_demo.ipynb)]

![teaser](imgs/teaser.png)

## Summary
MaskGIT is a novel image synthesis paradigm using a bidirectional transformer decoder. During training, MaskGIT learns to predict randomly masked tokens by attending to tokens in all directions. At inference time, the model begins with generating all tokens of an image simultaneously, and then refines the image iteratively conditioned on the previous generation. 

## Running pretrained models

Class conditional Image Genration models:

| Dataset  | Resolution | Model | Link | FID |
| ------------- | ------------- | ------------- | ------------- | ------------- |
| ImageNet  | 256 x 256 | Tokenizer | [checkpoint](https://storage.googleapis.com/maskgit-public/checkpoints/tokenizer_imagenet256_checkpoint)| 2.28 (reconstruction) |
| ImageNet  | 512 x 512 | Tokenizer | [checkpoint](https://storage.googleapis.com/maskgit-public/checkpoints/tokenizer_imagenet512_checkpoint)| 1.97 (reconstruction) |
| ImageNet  | 256 x 256 | MaskGIT Transformer |[checkpoint](https://storage.googleapis.com/maskgit-public/checkpoints/maskgit_imagenet256_checkpoint)| 6.06 (generation) |
| ImageNet  | 512 x 512 | MaskGIT Transformer | [checkpoint](https://storage.googleapis.com/maskgit-public/checkpoints/maskgit_imagenet512_checkpoint) | 7.32 (generation) |

You can run these models for class-conditional image **generation** and **editing** in the [demo Colab](https://colab.research.google.com/github/google-research/maskgit/blob/main/MaskGIT_demo.ipynb).

![teaser](imgs/class-conditional-teaser-small.png)

## Training
[Coming Soon]


## BibTeX

```
@InProceedings{chang2022maskgit,
  title = {MaskGIT: Masked Generative Image Transformer},
  author={Huiwen Chang and Han Zhang and Lu Jiang and Ce Liu and William T. Freeman},
  booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  month = {June},
  year = {2022}
}
```

## Disclaimer

This is not an officially supported Google product.
gif-generator 0.4.0
A package to convert images in folders to GIFs
Requires Python: >=3.6

# gif-generator
 
A Python package to convert images in folders to GIFs.

## Installation

You can install the package using pip:

```bash
pip install pip install gif-generator
```

## Usage

```python
from gifgenerator import convert_images_to_gif

image_folders = ['/path/to/folder1', '/path/to/folder2']
output_folder = '/path/to/output'
convert_images_to_gif(image_folders, output_folder)
```