Full life-cycle management process for tasks
1. Mandate creation
- Log in and go to the "Task Management" screen.
- Fill in task metadata (name/description/label)
- Key Parameter Configuration:
- Select processing mode (batch/real-time)
- Setting priorities and resource caps
- Define input and output formats
2. Implementation monitoring
- Live view:
- Heat map of resource utilization
- Percentage of progress
- Cost per token change curve
- Setting alarm thresholds (e.g., delay overruns)
3. Dynamic adjustments
Supports online adjustments without interruption of service:
- Modify the concurrency parameter
- Switching Calculation Accuracy
- Resizing the batch
4. Access to results
- Automatic generation of processing reports (with quality assessment indicators)
- Support S3/GCS and other cloud storage direct transfer
- Provide Python/Javascript result parsing SDK
All operations are open to the public through the REST API for easy CI/CD integration.
This answer comes from the articleKluster.ai: low-cost AI inference platform, sends 100$ DeepSeek-R1 credits, ~167 million tokens!The
May not be reproduced without permission:AI productivity tools " What is the complete process for creating and managing AI tasks on the Kluster.ai platform?
