OVOPS API · BETA

OpenAI-compatible access for business AI systems

Use one managed endpoint for model access, project keys, usage visibility and controlled rollout across prototypes, internal tools and agent workflows.

Open API Platform See Quick Start

Available models, interfaces and pricing are subject to the live platform.

from openai import OpenAI
import os

client = OpenAI(
    api_key=os.environ["ORIGIN_VECTOR_API_KEY"],
    base_url="https://models.ovops.com/v1",
)

response = client.chat.completions.create(
    model="model-id-from-console",
    messages=[{"role": "user", "content": "Hello"}],
)

WHY OVOPS API

A cleaner path for sustained AI usage

For teams standardizing AI workloads, OVOPS API provides a stable gateway, project-level control and usage transparency without tying every workflow to a separate provider account.

Unified access

Use one gateway for available models.

Project-level keys

Issue separate keys for each project or client.

Usage visibility

Track requests, tokens and balance.

Model flexibility

Pick models by task, cost and quality.

QUICK START

Make your first call in three steps

Validate the connection, usage logs and cost path before scaling traffic.

Review the platform

Review models, interfaces and pricing in the console.

Create a project key

Create one key per project or workflow.

Run a test request

Test chat completions with a console model ID.

from openai import OpenAI
import os

client = OpenAI(
    api_key=os.environ["ORIGIN_VECTOR_API_KEY"],
    base_url="https://models.ovops.com/v1",
)

response = client.chat.completions.create(
    model="model-id-from-console",
    messages=[{"role": "user", "content": "Hello"}],
)

FAQ

Frequently Asked Questions

Which models are available?

The model catalog may change. Check the live model list for current status, interface type and pricing.

How is usage billed?

Billing follows the model price shown by the platform and actual usage. Balance and spend details are displayed in the console.

Can I use an existing SDK?

Yes. Use OpenAI-compatible clients with the OVOPS base URL, then validate model-specific parameters before launch.

Is it ready for production?

Start with controlled traffic, monitor logs and design fallbacks for timeouts, rate limits and upstream changes.

How can enterprise customers work with you?

What should I check before topping up?

Use a small amount to verify registration, key creation, the first request, logs and balance deduction before increasing usage.