Multi-Provider LLM

Configure and switch between OpenAI, Z.ai, OpenRouter, Gemini, and local fallback providers.

Updated Apr 26, 2026
One-click install
npx skills add https://github.com/Renzo-Tognella/UniversalThingsForMyAgents --skill multi-provider-llm
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Multi-Provider LLM
Source: https://github.com/Renzo-Tognella/UniversalThingsForMyAgents/tree/main/skills/40_multi_provider_llm
Command: npx skills add https://github.com/Renzo-Tognella/UniversalThingsForMyAgents --skill multi-provider-llm

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openai, z.ai, openrouter, gemini, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

The Multi-Provider LLM Skill solves the challenge of configuring and switching between multiple LLM providers, including OpenAI, Z.ai, OpenRouter, Gemini, and local fallbacks. It streamlines the process of using different providers and models.

Core Features & Use Cases

  • Provider Switching: Allows easy switching between different language model providers for various use cases.
  • Configuration Flexibility: Provides flexibility to select the desired model and dimensions, along with base URLs for different providers.
  • Fallback Mechanism: Ensures continuous operation with a local fallback if providers are unavailable.

Quick Start

To set up Multi-Provider LLM with OpenAI as the primary provider, configure the environment variables:

export LLM_PROVIDER=openai
export LLM_API_KEY='your-openai-api-key'

Frequently Asked Questions about Multi-Provider LLM

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I configure and switch between multiple LLM providers like OpenAI and Gemini?

To configure LLM providers, set environment variables such as LLM_PROVIDER and LLM_API_KEY. Switching between OpenAI, Z.ai, OpenRouter, and Gemini is facilitated by changing these variables to select the desired model and base URLs.

What is a fallback mechanism for LLM providers and when do I need it?

A fallback mechanism ensures continuous operation by using a local model if primary providers are unavailable. You need this mechanism to maintain application uptime when external API providers experience downtime or connectivity issues.

Does this provider switching approach support configuring base URLs for OpenRouter and Z.ai?

Yes, provider switching supports configuration flexibility for base URLs. You can specify desired model dimensions and base URLs for different providers including OpenRouter and Z.ai through environment variable configuration.

What's the best way to ensure continuous operation if my primary language model provider is unavailable?

The best way to ensure continuous operation is implementing a local fallback mechanism. If configured external providers become unavailable, the system automatically transitions to a local model to maintain processing.

How do I set up environment variables to start using multiple language model providers?

To set up multiple language model providers, export environment variables like LLM_PROVIDER=openai and LLM_API_KEY='your-openai-api-key'. This configuration enables seamless switching between different providers and models.

Can I use a local fallback with OpenAI and Gemini API configurations simultaneously?

Yes, you can use a local fallback alongside OpenAI and Gemini configurations. The system facilitates seamless provider switching while ensuring continuous operation through a local fallback if external providers are unavailable.