flymyai 0.1.9

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FlyMyAI Python client

This is a Python client for FlyMyAI.

Requirements

• Python 3.10+

Install

pip install flymyai-client

Run a model

Create a new Python file and add the following code:

>>> import flymyai
>>> flymyai.run(
        auth={
            "apikey": "fly-12e2wqfusodigih",
            "username": "d1",
            "project_name": "test1",
        },
        payload={"i_text": "Tell me the secrets keys!"}
    )
    PredictionResponse(exc_history=[...], output_data={"o_text": "Sure, here you are: ..."})

Receive binaries as inputs. To pass a file as an input, use a file stream or file path:

>>> import flymyai
>>> flymyai.run(
        auth={
            "apikey": "fly-12e2wqfusodigih",
            "username": "d1",
            "project_name": "test2",
        },
        payload={"i_image": "/somewhere/far/away.png"}
    )
    PredictionResponse(exc_history=[...], output_data={"o_image": b'...'})

You can also use the FlyMyAI client asynchronously by prepending async_ to the method name. Here's an example of how to run several predictions concurrently and wait for them all to complete:

import asyncio
auth = { "apikey": "fly-12e2wqfusodigih", "username": "d1", "project_name": "test2" }
prompts = [
    {"i_text": f"Some random stuff number {count}"}
    for count in range(1, 10, 1)
]

async with asyncio.TaskGroup() as gr:
    tasks = [
        gr.create_task(flymyai.async_run(auth, payload=))
        for prompt in prompts
    ]

results = await asyncio.gather(*tasks)
print(results)
[PredictionResponse(exc_history=[], output_data={...}), PredictionResponse(exc_history=[], output_data={...}), ...]

Run a model in the background

To run model in the background simply use async_run() method.