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SingTown AI Python Client

Project description

SingTown AI Python SDK

This SDK is designed to interact with SingTown AI Cloud Service or SingTown AI Standalone(self-hosted).

Installation

pip install singtown_ai

Usage

Login Configuration

  • SingTown AI Cloud Service: The host is "https://ai.singtown.com".
  • SingTown AI Standalone (self-hosted): The host is something like "http://127.0.0.1:8000".

You can obtain the token and task_id from Project -> Information.

Environment Variables:

export SINGTOWN_AI_HOST="https://ai.singtown.com"  # Or the cloud service URL
export SINGTOWN_AI_TOKEN="your token"            # Your token
export SINGTOWN_AI_TASK_ID="your id"             # Your task ID

Alternatively, set them directly in code:

SingTownAiClient(
  host="https://ai.singtown.com",  # Or the cloud service URL
  token="your token",            # Your token
  task_id="your id"              # Your task ID
)

Dry Run

python -m singtown_ai.dryrun --host=http://127.0.0.1:8000 --token=012345 --task_id=1
  • This command will simulate 10s train task.

Basic Usage

from singtown_ai import SingTownAiClient

with SingTownAiClient() as client:
    pass  # Insert your code here
  • This will periodically update the running status. After finished, it will post a "training succeeded" status. If an error occurs, it will post a "training failed" status.

Mock Usage

from singtown_ai import SingTownAiClient

with SingTownAiClient(mock=True) as client:
    pass  # Insert your code here
  • Set mock=True, Will mock demo task and dataset, this is useful for debugging.

Uploading Metrics

metrics = [
    {"epoch": 0, "accuracy": 0.8, "loss": 0.2},
    {"epoch": 1, "accuracy": 0.9, "loss": 0.1},
]
with SingTownAiClient() as client:
    client.upload_metrics(metrics)
  • The field names in metrics are not restricted, and they will appear on the Metrics page in SingTown AI.

Watching metrics.csv

with SingTownAiClient(metrics_file="metrics.csv") as client:
    pass  # Insert your code here
  • Every 3 seconds, the SDK will parse the metrics.csv and upload data.

Posting Logs

with SingTownAiClient() as client:
    import time
    for i in range(100):
        client.log(f"epoch: {i}")
        time.sleep(0.1)
  • This will upload log strings, posting them every 3 seconds.

Download Trained Files from Server

with SingTownAiClient() as client:
    client.download_trained_file("folder")
  • This method will download the trained file and automatically extract it into the specified folder.

Uploading Result Files

with SingTownAiClient() as client:
    client.upload_results_zip("your.zip")
  • This method uploads a .zip result file.

Run Subprocess Command

with SingTownAiClient() as client:
    client.run_subprocess("echo hello world!")
    client.run_subprocess("python3 train.py", ignore_stdout=True)
  • This method will run subprocess and log stdout and stderr.
  • If ignore_stdout=True , will not log stdout.

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