Using Lingxi AI Plaza in Jan

Jan is an offline-first open-source AI desktop client that can run models locally and connect to OpenAI-compatible endpoints via Remote Engine. This article explains how to connect to Lingxi AI Plaza.

Application Process

To connect Lingxi AI Plaza in Jan, first go to the Lingxi AI Plaza Console to obtain your API Token for future use.

Get Lingxi AI Plaza API Key

If you are not logged in or registered, you will be automatically redirected to the login page inviting you to register and log in. After logging in or registering, you will be automatically returned to the current page.

There is a free quota available for first-time applicants, allowing you to experience Lingxi AI Plaza's model services for free.

Download Jan

Go to the Jan official website to download according to your platform (Windows, macOS, Linux). For Apple Silicon models, please download the arm64 package for optimal performance.

Configure Lingxi AI Plaza

Jan categorizes models into Local Engine (running locally) and Remote Engine (third-party API). Lingxi AI Plaza follows the OpenAI compatibility protocol and connects as a Remote Engine.

Open Jan, go to Settings → Model Providers, find the OpenAI card and edit:

Field Value Description
API Key Your Lingxi AI Plaza Token Token copied from the console
Base URL https://api.acedata.cloud/v1 Must end with /v1, do not include a trailing slash

The requirement for the Base URL to end with /v1 is a clear stipulation in Jan's official documentation. If you do not want to overwrite the original OpenAI configuration, you can create a new openai-compatible type Provider by clicking “+ Add Provider” and filling in the same content.

Jan will not automatically pull the model list from Lingxi AI Plaza; you need to click + Add Model at the bottom of the same editing page to fill in the model IDs one by one. After adding, the models will appear in the dropdown in the upper left corner, marked with a "Cloud" icon to distinguish between remote/local.

Select Model

The model directory will continue to be updated. Prefer using the model list automatically loaded by the client; if manual entry is needed, first request GET https://api.acedata.cloud/v1/models to get the current model IDs, then choose based on the context, image, and tool invocation capabilities supported by the client.

Verify Connection

If you are unsure whether the issue lies with Jan or the network, you can first verify the endpoint directly using curl (replace {token} with your Token):

curl -X POST 'https://api.acedata.cloud/v1/chat/completions' \
  -H 'Authorization: Bearer {token}' \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "MODEL_ID",
    "messages": [{"role": "user", "content": "ping"}]
  }'

If you receive an OpenAI-compatible chat.completion object, it indicates that both the Token and endpoint are ready; if you receive HTTP 403 used_up, it means the Token is valid but the balance is insufficient, and you can recharge at the console.

Advanced: Local + Cloud Hybrid

Jan has a built-in local OpenAI-compatible API Server that can be enabled (Settings → Local API Server). Once enabled, it listens on http://localhost:1337/v1/chat/completions, running the local models you downloaded. This allows you to point the Base URL to local for free debugging in frameworks like LangChain / LlamaIndex, and switch to Lingxi AI Plaza remote models for complex tasks. The conversation context will not be lost when switching models.

Frequently Asked Questions

Prompt Connection error or 404

This is usually due to the Base URL missing /v1. Change it to https://api.acedata.cloud/v1 (must end with /v1, and should not be written as .../openai/v1).

Prompt 401 Unauthorized

Please ensure that the API Key pasted is the Lingxi AI Plaza Token (without the Bearer prefix and no extra spaces), and that the balance of the associated application is sufficient.

Jan will not automatically call /v1/models; you must manually + Add Model to add the model IDs.

Can I upload images for the model to analyze?

Yes, but you need to select a model from the current model directory that explicitly supports visual input.

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