semvec/pypi-packages huggingface dataset:
fabler 0.0.6
Multimodal AI Story Teller, built with Stable Diffusion, GPT, and neural text-to-speech.
Requires Python: >=3.8
Keywords: GPT,TTS,language-model,multimodal AI,neural text-to-speech,stable diffusion,transformer

# Fabler

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[![PyPI Status Badge][pypi-badge]][pypi-url]
[![PyPI - Python Version][python-badge]][python-url]
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[![License: MIT][license-badge]][license-url]

---

A multi-model AI story teller, built with [Stable Diffusion](https://huggingface.co/spaces/stabilityai/stable-diffusion), GPT, and neural text-to-speech (TTS).

Given a prompt as an opening line of a story, GPT writes the rest of the plot; Stable Diffusion draws an image for each sentence; a TTS model narrates each line, resulting in a fully animated video of a short story, replete with audio and visuals.

![demo animation](https://user-images.githubusercontent.com/25360440/210071764-51ed5872-ba56-4ed0-919b-d9ce65110185.gif)


## Quickstart

### Check it out now [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/christopherwoodall/fabler/blob/main/notebooks/demo.ipynb) or follow the instructions below to install locally.


### Install from [PyPi](https://pypi.org/project/fabler/)
```bash
$ pip install fabler
```


### Install from Source
1. Clone the repository

```bash
$ git clone https://github.com/christopherwoodall/fabler.git
```

2. Install package requirements.

```bash
$ pip install --upgrade pip wheel
$ pip install -e ".[developer]"
```

3. Run the demo. The final video will be saved as `/out/out.mp4`, alongside other intermediate images, audio files, and subtitles.

```bash
$ fabler --scene=scene.yaml
```

4 Alternatively with make:

```bash
make install && make run
```

## Usage

1. Load the model with defaults.

```python
from fabler import Fabler

story_teller = Fabler.from_defaults()
story_teller.generate(...)
```

2. Alternatively, configure the model with custom settings.

```python
from fabler import Fabler, FablerConfig

config = FablerConfig(
    writer="gpt2-large",
    painter="CompVis/stable-diffusion-v1-4",
    max_new_tokens=100,
    diffusion_prompt_prefix="Van Gogh style",
)

story_teller = Fabler(config)
story_teller.generate(...)
```

## License

Released under the [MIT License](LICENSE).


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zesty.zbs-api-securonix-agent-baseurl-debug 2.0.2023.7.26.1690405274
Zesty Disk API

## Description
Zesty Disk API

## Installation
pip install zesty.zbs-api

## Usage
from zesty.zbs-api import *

## Alembic and Postgres Data Models.
For instructions on how to manage the Postgres data model as well as using Alembic to automatically prepare database migrations, please refer to the `README.md` in the `alembic` folder which is located at the root of this repository.

## SQLAlchemy Dependency
Some of the models within this package require SQLAlchemy to be imported. To keep this package light as it's used across many places in our code base, we do not install SQLAlchemy with this package. Thus, if you need to use any of the models that depend on SQLAlchemy, please install the Postgres-Utils package with your requirements.txt.