chat-notifier 0.1.3

Google Chat notifier for MLflow and Ray jobs

Chat Notifier

A lightweight Python library for sending Google Chat notifications from ML workflows. It helps monitor MLflow experiments and Ray jobs and send alerts to your team automatically.

Useful for ML engineers and MLOps pipelines running long training jobs.

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Features

• Send notifications to Google Chat via webhook
• Monitor MLflow experiments for new best metrics
• Send completion/failure notifications for Ray jobs
• Lightweight and easy to integrate

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Installation

Install with pip:

pip install chat-notifier

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MLflow Experiment Notification

This example checks if a new best metric is produced in an MLflow experiment and sends a notification.

from notifier import MLflowNotifier

nn = MLflowNotifier(
    webhook_url="YOUR_GOOGLE_CHAT_WEBHOOK",
    tracking_uri="http://mlflow.server",
    metric_mode="max",
    metric_name="mAP50"
)

nn.check_new_best(
    "ppe-detection",
    "228f5a2e084040d4aadc16cd22f6c12c"
)

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Ray Job Notification

Send a notification when a training job starts, finishes, or fails.

from notifier import RayJobNotifier
from datetime import datetime

ray_obj = RayJobNotifier(
    webhook_url="YOUR_GOOGLE_CHAT_WEBHOOK",
    server="gtx-1080",
    model_name="yolo11",
    max_chars=2000
)

ray_obj.send_notification(
    status=1,
    start_time=datetime.utcnow(),
    end_time=datetime.utcnow(),
    logs="training finished successfully"
)

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Status Codes

Code	Meaning
0	Job Failed
1	Job Completed Successfully
2	Job Running

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Example Use Cases

• Notify when a new best MLflow experiment result appears
• Send alerts when Ray training jobs complete
• Monitor long-running ML pipelines
• Inform teams about experiment progress via Google Chat

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License

MIT License