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A Decentralised AI library which allows to run remote AI jobs

Project description

The Decentralised AI Request

Enable for any AI python code to be executed on decentralised AI compute.

Supported AI compute:
Bacalhau

Required: Have a working IPFS Desktop App running on the same machine. You can download it here.

Commands:
python -m build # build the project
python -m unittest # run all unit tests

Usage:
from deairequest import DeProtocolSelector as selector
bp = selector.DeProtocolSelector("Bacalhau")
bp.get_docker_images()
if a user wants a custom image
bp.add_docker_image("custom_images")
For each request you need to set the docker image to use
bp.set_docker_image("the docker image to use")

To add datasets of type URL:
bp.add_dataset(bp.get_url_data_type(),"https://www...")
Of type File:
bp.add_dataset(bp.get_file_data_type(),"/path/to/file/name.csv")
Of type Directory:
bp.add_dataset(bp.get_directory_data_type(),"/path/to/directory/")
Of type IPFS:
bp.add_dataset(bp.get_ipfs_data_type(),"AW233dfD23dsds32323sdds") # The IPFS CID
To get all the datasets:
bp.get_datasets()
output: [{"url":"https://www..."},{"file":"/path/to/file/name.csv"},{"directory":"/path/to/directory/"},{"ipfs":"AW233dfD23dsds32323sdds"}]

Afterwards you can submit a job
job = bp.submit_job(Path("/path/to/notebook.jpynb"))
get the logs
state = bp.get_state(job)
and when the job is finished and the state changes from "InProgress" to either "Complete" or "Error"
result = bp.get_results(job,Path("/path/to/output/directory/"))

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