https://github.com/255bits/personas

Create Private AI characters
https://github.com/255bits/personas

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Create Private AI characters

• Host: GitHub
• URL: https://github.com/255bits/personas
• Owner: 255BITS
• Created: 2024-02-23T18:53:20.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2024-05-30T21:35:26.000Z (7 months ago)
• Last Synced: 2024-05-31T00:03:40.122Z (7 months ago)
• Language: Python
• Size: 66.4 KB
• Stars: 1
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Personas

Personas is an entry into the Backdrop Build v3 program.

In this entry we also introduce `MLQ Pipelines`

# MLQ Pipelines

MLQ Pipelines is a Python library that provides a flexible and intuitive way to build and execute machine learning inference pipelines(DAGs). It allows you to define tasks, compose them into pipelines, and execute them efficiently using asynchronous programming.

## Features

- Define tasks as simple Python functions or coroutines

- Compose tasks into pipelines using intuitive operators (`>>` for sequential composition, `|` for parallel composition)

- Execute pipelines asynchronously using `asyncio`

- Built-in support for setting and retrieving task outputs

- Validation of pipeline structure to ensure proper usage of `set_output` and `get_output`

- Extensible architecture to accommodate custom task types and behaviors

## Installation

You can install MLQ Pipelines using pip:

```

pip install mlq-pipelines #TODO

```

## Usage

Here's a simple example of how to use ML Inference Pipeline:

```python

from mlq_pipelines import task, Pipeline

@task

async def task1(x):

    return x * 2

@task

async def task2(x):

    return x + 1

@task

async def task3(x, y):

    return x + y

pipeline = Pipeline(

    (task1 | task2) >> task3

)

result = await pipeline(5)

print(result)  # Output: 21

```

## Documentation

For detailed documentation and more examples, please refer to the [ML Inference Pipeline Documentation](link-to-documentation).

## Contributing

Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request on the [GitHub repository](link-to-repository).

## License

ML Inference Pipeline is released under the [MIT License](link-to-license).

## Acknowledgements

We would like to thank the open-source community for their valuable contributions and inspiration.