Using Lingxi AI Plaza in LibreChat

LibreChat is a highly configurable open-source AI client that describes providers, models, and routing rules using librechat.yaml. It supports custom OpenAI-compatible endpoints, allowing integration with Lingxi AI Plaza. This article outlines the configuration process.

Application Process

To integrate Lingxi AI Plaza into LibreChat, 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 to invite 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.

Deploying LibreChat

LibreChat is deployed using Docker Compose. First, prepare the directory and download the official configuration:

mkdir -p ~/librechat && cd ~/librechat
curl -O https://raw.githubusercontent.com/danny-avila/LibreChat/main/docker-compose.yml
curl -O https://raw.githubusercontent.com/danny-avila/LibreChat/main/.env.example
mv .env.example .env

In the .env file, generate JWT_SECRET, JWT_REFRESH_SECRET, CREDS_KEY, CREDS_IV, and other security keys using openssl rand -hex 32, and set ALLOW_REGISTRATION as needed.

Configuring Lingxi AI Plaza

Create librechat.yaml and set Lingxi AI Plaza as a custom OpenAI-compatible endpoint (for complete field descriptions, see the official Custom Endpoints documentation, replacing {token} with your Token):

version: 1.0.5
cache: true

endpoints:
  custom:
    - name: "Ace Data Cloud"
      apiKey: "{token}"
      baseURL: "https://api.acedata.cloud/v1"
      models:
        default:
          - "MODEL_ID"
        fetch: true
      titleConvo: true
      titleModel: "MODEL_ID"
      modelDisplayLabel: "Ace Data Cloud"

Mount this file into the api service in docker-compose.yml, then start with docker compose up -d:

    volumes:
      - type: bind
        source: ./librechat.yaml
        target: /app/librechat.yaml

Note the path rules for baseURL:

baseURL Actual Request Result
https://api.acedata.cloud/v1 https://api.acedata.cloud/v1/chat/completions Correct
https://api.acedata.cloud/openai https://api.acedata.cloud/openai/chat/completions Also available
https://api.acedata.cloud/openai/v1 https://api.acedata.cloud/openai/v1/chat/completions 404 (/openai does not have /v1)
https://api.acedata.cloud https://api.acedata.cloud/chat/completions 404 (missing /v1)

Selecting Models

The model directory will continue to update. 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 ID, then choose based on the context, image, and tool invocation capabilities supported by the client.

Verifying Integration

If you are unsure whether the issue lies with LibreChat 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"}]
  }'

Receiving an OpenAI-compatible chat.completion object 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: YAML Configuration Tips

librechat.yaml supports multiple endpoint groups, allowing you to use apiKey: "user_provided" so that each user can enter their own Key; titleModel specifies the model for generating conversation titles; dropParams can be used to uniformly remove parameters not supported by the target API. For more details, see librechat.yaml Configuration Explained.

Frequently Asked Questions

Cannot see Lingxi AI Plaza endpoint after starting

This is usually due to the yaml not being mounted into the container or indentation errors. Check the volumes in docker-compose.yml and verify the yaml indentation.

Getting a 404 error

The baseURL may have been written as .../openai/v1 or missing /v1. Change it to https://api.acedata.cloud/v1.

If fetch: true but /v1/models fails, change it to fetch: false and manually list default.

Changes to yaml do not take effect

You need to restart the container: docker compose restart api.

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