deairequest 0.0.20

A Decentralised AI library which allows to run remote AI jobs

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/"))