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Welcome

Create an API Key​

  1. Log in to the Turing Portal
  2. Click your avatar in the upper-right corner and select API Key Management
  3. On the API Key Management page, click Create API Key
  4. Copy the generated API Key (save it now — it cannot be viewed again later)
  5. Start building your AI application

Request a Quota Increase​

  1. Log in to the Turing Portal
  2. Click your avatar in the upper-right corner and select API Key Management
  3. In the Usage Management panel, click Request Quota Increase
info

The Turing Platform integrates a variety of mainstream model types. Visit the Model List to choose the model that best fits your use case. For your first API call, refer to Quick Start.

Environment Configuration​

Before using the SDK, you need to configure the required environment variables. We recommend the following best practices for managing your configuration:

Security Notice

Do not hardcode your API Key directly in source code. Doing so can lead to:

  • Security risks from exposing sensitive credentials
  • Maintenance difficulties when switching between environments

Use environment variables or a configuration management system to manage your API Key.

API Endpoint​

The Turing Platform provides multiple regional endpoints. Select the one that best suits your business needs:

China Region (Default)​

TURING_API_BASE=https://live-turing.cn.llm.tcljd.com/api/v1

Europe Region​

TURING_API_BASE=https://live-turing.eu.llm.tcljd.com/api/v1

North America Region​

TURING_API_BASE=https://live-turing.us.llm.tcljd.com/api/v1

Asia Pacific (Singapore) Region​

TURING_API_BASE=https://live-turing.sg.llm.tcljd.com/api/v1

Other Regions

Local Development Configuration​

We recommend using a .env file to manage environment variables:

# .env example (China region)
TURING_API_BASE=https://live-turing.cn.llm.tcljd.com/api/v1
TURING_API_KEY=your-api-key

Best practices:

  • Add the .env file to .gitignore to prevent sensitive information from being committed to your repository
  • Use a .env.example file as a template for team members
  • Use separate .env files for different environments (development, testing, production)

Python Environment Configuration​

For Python projects, you can use the python-dotenv package to automatically load your .env file:

pip install python-dotenv
from dotenv import load_dotenv
import os

# Load environment variables from the .env file
load_dotenv()

# Retrieve environment variables via os.getenv
api_key = os.getenv("TURING_API_KEY")
api_base = os.getenv("TURING_API_BASE")

Docker Environment Configuration​

In a Docker environment, you can manage environment variables in the following ways:

  1. Pass them as docker run command-line arguments:
docker run -e TURING_API_KEY=your-api-key -e TURING_API_BASE=https://live-turing.cn.llm.tcljd.com/api/v1 your-image
  1. Use an environment variable file:
docker run --env-file .env your-image

Docker Compose Configuration​

Recommended project structure:

your-project/
├── .env                  # Local development environment variables (not committed to git)
├── .env.example          # Environment variable template (committed to git)
├── docker-compose.yml    # Development environment configuration
├── docker-compose.prod.yml # Production environment configuration
└── Dockerfile

Development environment example (docker-compose.yml):

version: "3.8"
services:
  app:
    build: .
    env_file:
      - .env
    environment:
      - NODE_ENV=development
    volumes:
      - .:/app
      - /app/node_modules
    ports:
      - "3000:3000"

Production environment example (docker-compose.prod.yml):

version: "3.8"
services:
  app:
    image: your-registry/your-image:latest
    env_file:
      - .env.prod
    environment:
      - NODE_ENV=production
    deploy:
      replicas: 3
      restart_policy:
        condition: any
    secrets:
      - turing_api_key

secrets:
  turing_api_key:
    external: true

Usage:

# Development environment
docker compose up

# Production environment
docker compose -f docker-compose.yml -f docker-compose.prod.yml up

Production Environment Configuration​

In production environments, we recommend:

  • Using an environment variable management system (e.g., Kubernetes Secrets, AWS Secret Manager, Nacos, etc.)
  • Using separate API Keys for different application scenarios to simplify management and access control

Once you have selected the appropriate SDK or API integration method and completed your configuration, you are ready to start exploring the Turing large model service.

Next Steps​

  • Overview: Platform capabilities and integration options
  • API Reference: View the detailed API documentation