cli-batches

Automate batch inference job submission and monitoring via the NexRoute CLI.

Updated Jun 6, 2026
One-click install
npx skills add https://github.com/DevMHOne/nextroute --skill cli-batches
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: cli-batches
Source: https://github.com/DevMHOne/nextroute/tree/main/skills/cli-batches
Command: npx skills add https://github.com/DevMHOne/nextroute --skill cli-batches

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Submit and monitor batch inference jobs from the CLI, enabling scalable batch workflows across ML deployments.

Core Features & Use Cases

  • Upload and manage batch files, configure endpoints and metadata, and monitor progress.
  • Retrieve results and errors to integrate batch pipelines with CI/CD and data processing workflows.
  • Use Case: Orchestrate multiple batches from scripts to streamline ML model inference at scale.

Quick Start

Install the nextroute CLI and run the batches commands to create and manage a batch job.

Frequently Asked Questions about cli-batches

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate batch inference jobs from the command line?

You can automate batch inference jobs by using the CLI to upload files, configure endpoints and metadata, and track progress until completion. This allows scalable batch workflows directly within your scripts.

Can I submit and monitor batch inference jobs in a CI/CD pipeline?

Yes, batch inference jobs can be integrated into CI/CD pipelines. The CLI handles command-group parsing and flag configurations, allowing automated submission and progress tracking within data processing workflows.

How do I retrieve results and errors after a batch inference job completes?

After a batch inference job completes, you retrieve results and errors by monitoring the job progress through the CLI. This integrates the batch pipeline outputs directly into your data processing systems.

What do I need to configure before submitting a batch processing job via the CLI?

Before submitting a batch processing job, you need to configure the endpoint, wait parameters, metadata, and output flags. You also need the input files uploaded and the CLI installed.

Does this CLI approach work for orchestrating multiple ML batches at scale?

Yes, this approach works for orchestrating multiple ML batches at scale. You can orchestrate multiple batches from scripts to streamline model inference and manage large volumes of files efficiently.