cuopt-server-api-python

Deploy the cuOpt REST server and submit optimization tasks via Python or curl clients.

Updated Apr 16, 2026

Search Tags:#rest-api #server-deployment #milp #lp #pdp #vrp #cuopt

Ready to run

npx skills add https://github.com/sayalinvidia/sayali-skills-test --skill cuopt-server-api-python-sayalinvidia

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Please help me install this Agent Skill.
Skill: cuopt-server-api-python
Source: https://github.com/sayalinvidia/sayali-skills-test/tree/main/skills/cuopt-server-api-python
Command: npx skills add https://github.com/sayalinvidia/sayali-skills-test --skill cuopt-server-api-python-sayalinvidia

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

Deploy cuOpt REST server and provide Python/curl client examples to interact with it for submitting optimization tasks and retrieving results.

Core Features & Use Cases

Server deployment: Start the cuOpt REST server in development or production modes.
Client examples: Use Python requests or curl-based clients to submit requests and poll for solutions.
Supported problems: Vehicle routing (VRP/VRPTW), pickup-and-delivery (PDP), LP, and MILP workloads via REST endpoints.

Quick Start

Launch the cuOpt REST server locally and run the Python or curl client to submit a problem and fetch the solution.

Frequently Asked Questions about cuopt-server-api-python

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

FAQPage Schema

How do I deploy a cuOpt REST server for optimization workloads?▼

You can deploy the cuOpt REST server locally or in cloud environments using specific startup commands. It supports development and production modes, with health checks to verify the server is ready to accept optimization tasks.

Can I use Python or curl to submit VRP and MILP tasks to a cuOpt server?▼

Yes, you can use Python requests or curl clients to submit VRP, PDP, LP, and MILP optimization tasks to the cuOpt REST server. The clients submit problem payloads to REST endpoints and poll the server to retrieve the computed solutions.

What payload formats are needed to submit a pickup-and-delivery problem to the cuOpt REST API?▼

Submitting a pickup-and-delivery problem to the cuOpt REST API requires formatting the task data into specific payload structures. You send this payload to the REST endpoint and use the Python or curl client to poll for the returned solution.

Does the cuOpt REST server support both local development and cloud deployment?▼

Yes, the cuOpt REST server supports deployment in both local development and cloud environments. It specifies startup commands and health checks to ensure end-to-end deployment of optimization workloads across different infrastructure setups.

How do I retrieve optimization results after submitting a task to the cuOpt server?▼

You retrieve optimization results by using Python or curl clients to poll the cuOpt REST server. After submitting your VRP, PDP, LP, or MILP task to the endpoint, the client continuously checks until the computed solution is ready to fetch.