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Project description
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.
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