AI Provider Configuration

This guide explains how to configure different AI model providers for next-ai-draw-io.

Quick Start

Copy .env.example to .env.local
Set your API key for your chosen provider
Set AI_MODEL to your desired model
Run npm run dev

Supported Providers

Doubao (ByteDance Volcengine)

Free tokens: Register on the Volcengine ARK platform to get 500K free tokens for all models!

bash

DOUBAO_API_KEY=your_api_key
AI_MODEL=doubao-seed-1-8-251215  # or other Doubao model

Google Gemini

bash

GOOGLE_GENERATIVE_AI_API_KEY=your_api_key
AI_MODEL=gemini-2.0-flash

Optional custom endpoint:

bash

GOOGLE_BASE_URL=https://your-custom-endpoint

Google Vertex AI (Enterprise GCP)

Google Vertex AI offers enterprise-grade features and data residency. Express Mode allows for simple API key authentication, making it compatible with edge runtimes like Vercel and Cloudflare.

bash

GOOGLE_VERTEX_API_KEY=your_api_key
AI_MODEL=gemini-2.0-flash

Optional custom endpoint:

bash

GOOGLE_VERTEX_BASE_URL=https://your-custom-endpoint

OpenAI

bash

OPENAI_API_KEY=your_api_key
AI_MODEL=gpt-4o

Optional custom endpoint (for OpenAI-compatible services):

bash

OPENAI_BASE_URL=https://your-custom-endpoint/v1

Anthropic

bash

ANTHROPIC_API_KEY=your_api_key
AI_MODEL=claude-sonnet-4-5-20250514

Optional custom endpoint:

bash

ANTHROPIC_BASE_URL=https://your-custom-endpoint

DeepSeek

bash

DEEPSEEK_API_KEY=your_api_key
AI_MODEL=deepseek-chat

Optional custom endpoint:

bash

DEEPSEEK_BASE_URL=https://your-custom-endpoint

SiliconFlow (OpenAI-compatible)

bash

SILICONFLOW_API_KEY=your_api_key
AI_MODEL=deepseek-ai/DeepSeek-V3  # example; use any SiliconFlow model id

Optional custom endpoint (defaults to the recommended domain):

bash

SILICONFLOW_BASE_URL=https://api.siliconflow.com/v1  # or https://api.siliconflow.cn/v1

SGLang

bash

SGLANG_API_KEY=your_api_key
AI_MODEL=your_model_id

Optional custom endpoint:

bash

SGLANG_BASE_URL=https://your-custom-endpoint/v1

Azure OpenAI

bash

AZURE_API_KEY=your_api_key
AZURE_RESOURCE_NAME=your-resource-name  # Required: your Azure resource name
AI_MODEL=your-deployment-name

Or use a custom endpoint instead of resource name:

bash

AZURE_API_KEY=your_api_key
AZURE_BASE_URL=https://your-resource.openai.azure.com  # Alternative to AZURE_RESOURCE_NAME
AI_MODEL=your-deployment-name

Optional reasoning configuration:

bash

AZURE_REASONING_EFFORT=low      # Optional: low, medium, high
AZURE_REASONING_SUMMARY=detailed  # Optional: none, brief, detailed

AWS Bedrock

bash

AWS_REGION=us-west-2
AWS_ACCESS_KEY_ID=your_access_key_id
AWS_SECRET_ACCESS_KEY=your_secret_access_key
AI_MODEL=anthropic.claude-sonnet-4-5-20250514-v1:0

Note: On AWS (Lambda, EC2 with IAM role), credentials are automatically obtained from the IAM role.

OpenRouter

bash

OPENROUTER_API_KEY=your_api_key
AI_MODEL=anthropic/claude-sonnet-4

Optional custom endpoint:

bash

OPENROUTER_BASE_URL=https://your-custom-endpoint

Ollama (Local)

bash

AI_PROVIDER=ollama
AI_MODEL=llama3.2

Optional custom URL:

bash

OLLAMA_BASE_URL=http://localhost:11434

ModelScope

bash

MODELSCOPE_API_KEY=your_api_key
AI_MODEL=Qwen/Qwen3-235B-A22B-Instruct-2507

Optional custom endpoint:

bash

MODELSCOPE_BASE_URL=https://your-custom-endpoint

Vercel AI Gateway

Vercel AI Gateway provides unified access to multiple AI providers through a single API key. This simplifies authentication and allows you to switch between providers without managing multiple API keys.

Basic Usage (Vercel-hosted Gateway):

bash

AI_GATEWAY_API_KEY=your_gateway_api_key
AI_MODEL=openai/gpt-4o

Custom Gateway URL (for local development or self-hosted Gateway):

bash

AI_GATEWAY_API_KEY=your_custom_api_key
AI_GATEWAY_BASE_URL=https://your-custom-gateway.com/v1/ai
AI_MODEL=openai/gpt-4o

Model format uses provider/model syntax:

openai/gpt-4o - OpenAI GPT-4o
anthropic/claude-sonnet-4-5 - Anthropic Claude Sonnet 4.5
google/gemini-2.0-flash - Google Gemini 2.0 Flash

Configuration notes:

If AI_GATEWAY_BASE_URL is not set, the default Vercel Gateway URL (https://ai-gateway.vercel.sh/v1/ai) is used
Custom base URL is useful for:
- Local development with a custom Gateway instance
- Self-hosted AI Gateway deployments
- Enterprise proxy configurations
When using a custom base URL, you must also provide AI_GATEWAY_API_KEY

Get your API key from the Vercel AI Gateway dashboard.

MiniMax

MiniMax supports two API formats:

Anthropic-compatible (/anthropic endpoint) — recommended, supports interleaved thinking
OpenAI-compatible (/v1 endpoint) — standard OpenAI chat completions format

bash

MINIMAX_API_KEY=your_api_key
AI_MODEL=MiniMax-M2.7

Optional configuration:

bash

# China mainland, Anthropic-compatible (default)
MINIMAX_BASE_URL=https://api.minimaxi.com/anthropic

# China mainland, OpenAI-compatible
MINIMAX_BASE_URL=https://api.minimaxi.com/v1

# International, Anthropic-compatible
MINIMAX_BASE_URL=https://api.minimax.io/anthropic

# International, OpenAI-compatible
MINIMAX_BASE_URL=https://api.minimax.io/v1

GLM (Zhipu AI)

bash

GLM_API_KEY=your_api_key
AI_MODEL=glm-4

Optional custom endpoint:

bash

GLM_BASE_URL=https://your-custom-endpoint

Qwen (Alibaba Cloud)

bash

QWEN_API_KEY=your_api_key
AI_MODEL=qwen-turbo

Optional custom endpoint:

bash

QWEN_BASE_URL=https://your-custom-endpoint

Kimi (Moonshot AI)

bash

KIMI_API_KEY=your_api_key
AI_MODEL=kimi-latest

Optional custom endpoint:

bash

KIMI_BASE_URL=https://your-custom-endpoint

Qiniu (Qiniu Cloud)

bash

QINIU_API_KEY=your_api_key
AI_MODEL=your_model_id

Optional custom endpoint:

bash

QINIU_BASE_URL=https://your-custom-endpoint

Auto-Detection

If you only configure one provider's API key, the system will automatically detect and use that provider. No need to set AI_PROVIDER.

If you configure multiple API keys, you must explicitly set AI_PROVIDER:

bash

AI_PROVIDER=google  # or: openai, anthropic, deepseek, siliconflow, doubao, azure, bedrock, openrouter, ollama, gateway, sglang, modelscope, minimax, glm, qwen, kimi, qiniu

Server-Side Multi-Model Configuration

Administrators can configure multiple server-side models that are available to all users without requiring personal API keys.

Configuration Methods

Option 1: Environment Variable (recommended for cloud deployments)

Set AI_MODELS_CONFIG as a JSON string:

bash

AI_MODELS_CONFIG='{"providers":[{"name":"OpenAI","provider":"openai","models":["gpt-4o"],"default":true}]}'

Option 2: Config File

Create an ai-models.json file in the project root (or set AI_MODELS_CONFIG_PATH to a custom location).

Example Configuration

json

{
  "providers": [
    {
      "name": "OpenAI Production",
      "provider": "openai",
      "models": ["gpt-4o", "gpt-4o-mini"],
      "default": true
    },
    {
      "name": "Custom DeepSeek",
      "provider": "deepseek",
      "models": ["deepseek-chat"],
      "apiKeyEnv": "MY_DEEPSEEK_KEY",
      "baseUrlEnv": "MY_DEEPSEEK_URL"
    }
  ]
}

Field Reference

Field	Required	Description
`name`	Yes	Display name (supports multiple configs for same provider)
`provider`	Yes	Provider type (`openai`, `anthropic`, `google`, `bedrock`, etc.)
`models`	Yes	List of model IDs
`default`	No	Set to `true` to auto-select this provider's first model as default
`apiKeyEnv`	No	Custom API key env var name (defaults to provider's standard var like `OPENAI_API_KEY`)
`baseUrlEnv`	No	Custom base URL env var name

Notes

API keys and credentials are provided via environment variables. By default, standard var names are used (e.g., OPENAI_API_KEY), but you can specify custom var names with apiKeyEnv.
The name field allows multiple configurations for the same provider (e.g., "OpenAI Production" and "OpenAI Staging" both using provider: "openai" but with different apiKeyEnv values).
If config is not present, the app falls back to AI_PROVIDER/AI_MODEL environment variable configuration.

Model Capability Requirements

This task requires exceptionally strong model capabilities, as it involves generating long-form text with strict formatting constraints (draw.io XML).

Recommended models:

Claude Sonnet 4.5 / Opus 4.5

Note on Ollama: While Ollama is supported as a provider, it's generally not practical for this use case unless you're running high-capability models like DeepSeek R1 or Qwen3-235B locally.

Temperature Setting

You can optionally configure the temperature via environment variable:

bash

TEMPERATURE=0  # More deterministic output (recommended for diagrams)

Important: Leave TEMPERATURE unset for models that don't support temperature settings, such as:

GPT-5.1 and other reasoning models
Some specialized models

When unset, the model uses its default behavior.

Recommendations

Best experience: Use models with vision support (GPT-4o, Claude, Gemini) for image-to-diagram features
Budget-friendly: DeepSeek offers competitive pricing
Privacy: Use Ollama for fully local, offline operation (requires powerful hardware)
Flexibility: OpenRouter provides access to many models through a single API