OpenMAIC LLM Backends: Complete Supported Provider Guide

OpenMAIC supports six categories of LLM backends through the Vercel AI SDK, including native OpenAI, Anthropic Claude, Amazon Bedrock, Google Gemini, Anthropic-compatible MiniMax, and any OpenAI-compatible provider such as DeepSeek, Qwen, and Kimi.

OpenMAIC is an open-source AI framework developed by THU-MAIC that leverages the Vercel AI SDK to provide unified access to multiple large language model providers. The platform's provider architecture is defined in lib/ai/providers.ts, which implements adapters for both native APIs and generic compatibility layers. This extensibility allows developers to switch between cloud and custom endpoints without modifying application logic.

Native Cloud Provider Support

OpenMAIC implements first-party adapters for four major cloud AI platforms. These providers are initialized through dedicated factory functions that handle authentication and request formatting, as documented in the comment block at lines 4-10 of lib/ai/providers.ts.

OpenAI

The OpenAI provider serves as the default backend, supporting models including GPT-5.6, GPT-5.5, and GPT-4-o. The adapter is created via createOpenAI and referenced by the provider ID 'openai'.

Anthropic Claude

Native Anthropic integration supports Claude models such as claude-3-5-sonnet-20240620. This backend uses the createAnthropic factory function with the provider ID 'anthropic'.

Amazon Bedrock

OpenMAIC includes native support for Amazon Bedrock LLMs through the createAmazonBedrock adapter, enabling access to AWS-hosted foundation models without intermediate translation layers.

Google Gemini

Google Gemini models are supported via the createGoogleGenerativeAI function, allowing direct integration with Google's Generative AI platform using native SDK patterns.

Anthropic-Compatible Providers

MiniMax

MiniMax implements the Anthropic API specification and is supported as a first-class provider within OpenMAIC. This allows MiniMax service endpoints to utilize the same adapter patterns as native Anthropic Claude, referenced by the provider ID 'minimax'.

Generic OpenAI-Compatible Providers

Beyond native integrations, OpenMAIC supports any provider implementing the OpenAI-compatible REST API through a generic adapter. This extensible approach enables integration with numerous Chinese and international model providers without requiring dedicated code changes.

Supported OpenAI-compatible providers include:

• DeepSeek
• Qwen
• Kimi
• GLM
• SiliconFlow
• Doubao
• Tencent
• Xiaomi
• Lemonade

These providers are configured using standard OpenAI SDK patterns with custom base URLs and API keys, referenced by their respective provider IDs in the PROVIDERS registry.

Provider Resolution Architecture

The central registry in lib/ai/providers.ts defines the PROVIDERS constant that maps provider IDs to their respective adapter factories (lines 29-34). When executing an inference request, the callLLM function in lib/ai/llm.ts resolves the appropriate client based on the providerId parameter and injects configured API keys or base URLs from the application's settings store.

import { callLLM } from '@/lib/ai/llm';

// Example: use OpenAI (default)
await callLLM({
  providerId: 'openai',
  modelId: 'gpt-5.6',
  prompt: 'Summarize the latest research on transformer architectures.',
});

// Example: switch to Anthropic Claude
await callLLM({
  providerId: 'anthropic',
  modelId: 'claude-3-5-sonnet-20240620',
  prompt: 'Explain the concept of chain-of-thought prompting.',
});

// Example: use a custom OpenAI-compatible endpoint (e.g., DeepSeek)
await callLLM({
  providerId: 'deepseek',
  modelId: 'deepseek-chat',
  prompt: 'Write a short poem about autumn.',
});

Model Capabilities and Configuration

OpenMAIC enriches provider definitions with capability metadata through lib/ai/model-metadata.ts, which tracks features like streaming, tool use, vision support, and reasoning capabilities. The lib/ai/thinking-config.ts module manages chain-of-thought ("thinking") configurations for models that support explicit reasoning parameters. For preserving reasoning across Server-Sent Events streams, lib/ai/reasoning-sse.ts provides middleware that maintains stateful reasoning context.

Summary

• OpenMAIC supports six distinct provider categories through the Vercel AI SDK architecture
• Native adapters exist for OpenAI, Anthropic Claude, Amazon Bedrock, and Google Gemini in lib/ai/providers.ts
• MiniMax integrates via Anthropic-compatible API patterns as a specialized provider
• Generic OpenAI-compatible support enables DeepSeek, Qwen, Kimi, GLM, SiliconFlow, and others without code changes
• Provider resolution occurs through the PROVIDERS registry (lines 29-34) which maps IDs to adapter factories like createOpenAI and createAnthropic
• The callLLM function in lib/ai/llm.ts handles backend abstraction, request routing, and credential injection

Frequently Asked Questions

How do I configure a custom OpenAI-compatible endpoint in OpenMAIC?

Configure the base URL and API key in your application's settings store, then reference the custom provider ID in your callLLM invocation. The generic adapter in lib/ai/providers.ts automatically handles OpenAI-compatible REST API formatting for any endpoint you specify.

Does OpenMAIC support local or self-hosted LLMs?

Yes. Any self-hosted model exposing an OpenAI-compatible API—such as those served by vLLM, Ollama, or Text Generation Inference—can be integrated using the generic OpenAI-compatible adapter. No native code changes are required if the endpoint adheres to OpenAI's REST specification.

Which file determines available model capabilities like tool use or vision?

Model capabilities including streaming, tool use, vision support, and reasoning modes are defined in lib/ai/model-metadata.ts. This file enriches provider definitions with metadata that determines which features are exposed for each LLM backend supported by OpenMAIC.

Can I switch between providers without changing my application code?

Yes. The callLLM function abstracts provider-specific implementation details. Changing only the providerId and modelId parameters is sufficient to switch between any registered backend, including transitions from native OpenAI to Anthropic-compatible or generic OpenAI-compatible endpoints.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}