{"slug": "how-i-built-a-provider-agnostic-ai-architecture-that-automatically-switches-groq", "title": "How I built a provider-agnostic AI architecture that automatically switches between Groq, OpenRouter, Ollama, and Gemini.", "summary": "A developer built a provider-agnostic AI architecture for CVForbes that automatically switches between Groq, OpenRouter, Ollama, and Gemini without changing any service code. The system uses a router layer that handles failover and keeps the application decoupled from specific LLM providers.", "body_md": "*How I designed CVForbes to automatically switch between Groq, OpenRouter, Ollama, and Gemini without changing a single service.*\n\n```\n                    Client\n                       │\n                       ▼\n             FastAPI Endpoint\n                       │\n                       ▼\n             Dependency Injection\n                       │\n                       ▼\n               LLMRouter Service\n      ┌────────────┬──────────────┐\n      │            │              │\n      ▼            ▼              ▼\n  GroqProvider  OpenRouter   OllamaProvider\n      │            │              │\n      └────────────┴──────────────┘\n                 │\n            GeminiProvider\n                 │\n                 ▼\n          LangChain Models\n                 │\n                 ▼\n         Structured Output\n```\n\nWhen building ** CVForbes**, I quickly realized that depending on a single LLM provider wasn't a great long-term strategy.\n\nWhat if Groq goes down?\n\nWhat if another provider becomes cheaper or faster?\n\nWhat if I want to test a new model without touching every service in my application?\n\nInstead of tightly coupling my business logic to one provider, I designed a **provider-agnostic routing layer** that sits between my application and the LLMs.\n\nNow, every AI feature—resume tailoring, parsing, cover letter generation, and future modules—talks to a single router. The router decides which provider should handle the request, performs automatic failover when necessary, and keeps the rest of the application completely unaware of what's happening behind the scenes.\n\nThis article explains the architecture behind that system and the design decisions that made it scalable.\n\nA lot of AI projects start like this:\n\n```\nllm = ChatGroq(...)\nresponse = llm.invoke(prompt)\n```\n\nIt works.\n\nUntil it doesn't.\n\nOnce your application grows, changing providers means editing multiple services, updating imports, and introducing provider-specific logic across the codebase.\n\nI wanted to avoid that entirely.\n\nInstead of allowing services to communicate directly with an LLM provider, every request goes through a single router.\n\n```\n                    Client\n                       │\n                       ▼\n             FastAPI Endpoint\n                       │\n                       ▼\n             Dependency Injection\n                       │\n                       ▼\n               LLMRouter Service\n      ┌────────────┬──────────────┐\n      │            │              │\n      ▼            ▼              ▼\n  GroqProvider  OpenRouter   OllamaProvider\n      │            │              │\n      └────────────┴──────────────┘\n                 │\n            GeminiProvider\n                 │\n                 ▼\n          LangChain Models\n                 │\n                 ▼\n         Structured Output\n```\n\nEvery service simply asks for **\"an LLM.\"**\n\nThe router decides which one.\n\nThe router has one job:\n\nThat's it.\n\nEverything else stays where it belongs.\n\nThis keeps the application clean and makes providers interchangeable.\n\nEach provider follows the same interface.\n\n``` python\nclass BaseLLMProvider:\n    def get_llm(self):\n        ...\n```\n\nWhether it's Groq, Gemini, Ollama, or OpenRouter doesn't matter.\n\nThe router simply calls:\n\n```\nprovider.get_llm()\n```\n\nAdding a new provider later becomes incredibly straightforward.\n\nEvery AI request follows the same journey.\n\n```\nIncoming Request\n       │\n       ▼\nNeed LLM?\n       │\n       ▼\nRouter receives prompt\n       │\n       ▼\nIs Groq healthy?\n      / \\\n    Yes  No\n    │      │\n    ▼      ▼\n Use Groq  Try OpenRouter\n               │\n               ▼\n        Healthy?\n          / \\\n       Yes   No\n       │      │\n       ▼      ▼\nUse OpenRouter Try Ollama\n                     │\n                     ▼\n               Healthy?\n                  │\n                  ▼\n              Use Ollama\n                  │\n                  ▼\n              Last fallback\n                Gemini\n```\n\nNotice something missing?\n\nNowhere in the application do we reference Groq or Gemini directly.\n\nThat's intentional.\n\nOne of my biggest goals was resilience.\n\nInstead of immediately failing when a provider becomes unavailable, the router simply tries the next one.\n\n```\nGroq\n  │\n  ❌\n  ▼\nOpenRouter\n  │\n  ❌\n  ▼\nOllama\n  │\n  ✅\n  ▼\nReturn Response\n```\n\nThe user doesn't know a provider failed.\n\nAnd honestly, they shouldn't have to.\n\nTrying the same failed provider on every request wastes time.\n\nInstead, the router keeps lightweight health information.\n\n```\nGroq        ✅\nOpenRouter  ✅\nOllama      ❌\nGemini      ✅\n```\n\nIf a provider repeatedly fails, it's temporarily skipped until it becomes healthy again.\n\nThis reduces unnecessary delays during outages.\n\nAnother design choice was using FastAPI's dependency injection.\n\nInstead of creating providers inside every endpoint, a shared router instance is injected wherever it's needed.\n\n```\nEndpoint\n    │\nDepends()\n    │\nLLM Router\n    │\nProviders\n```\n\nThis keeps endpoints focused on business logic rather than infrastructure.\n\nThis approach gave [CVForbes](https://github.com/UsmanDevCraft/cvforbes-backend) several advantages:\n\nPerhaps my favorite part is that adding another provider requires almost no changes to the rest of the application.\n\nThe architecture grows without becoming more complicated.\n\nBuilding AI applications isn't just about choosing the best model.\n\nIt's about designing systems that continue working when models, providers, or APIs inevitably change.\n\nA small investment in abstraction early on saved me from coupling my entire application to a single vendor.\n\nLooking back, that decision has probably been one of the most valuable architectural choices in [CVForbes](https://github.com/UsmanDevCraft/cvforbes-backend).\n\nThe router already supports multiple providers with automatic failover, but there's plenty of room for future improvements:\n\nThe exciting part is that the architecture already supports these ideas without requiring a redesign.\n\nWhen people think about AI architecture, they often focus on **which model** to use.\n\nI think the better question is:\n\nHow easily can your application switch models tomorrow?\n\nDesigning around abstractions instead of vendors made [CVForbes](https://github.com/UsmanDevCraft/cvforbes-backend) significantly more maintainable, resilient, and scalable. Providers may change, APIs may evolve, and new models will continue to emerge—but the rest of the application won't need to know.\n\nThat's the kind of architecture I aim for: one that's built around software engineering principles rather than a single AI provider.\n\nThe complete implementation, including the router, providers, health management, and FastAPI integration, is available in the accompanying [GitHub repository](https://github.com/UsmanDevCraft/cvforbes-backend).\n\nFeel free to explore it, suggest improvements, or adapt the architecture for your own AI applications.", "url": "https://wpnews.pro/news/how-i-built-a-provider-agnostic-ai-architecture-that-automatically-switches-groq", "canonical_source": "https://dev.to/usman_awan/how-i-built-a-provider-agnostic-ai-architecture-that-automatically-switches-between-groq-790", "published_at": "2026-07-16 05:55:18+00:00", "updated_at": "2026-07-16 06:06:32.190885+00:00", "lang": "en", "topics": ["artificial-intelligence", "large-language-models", "ai-infrastructure", "ai-tools", "developer-tools"], "entities": ["CVForbes", "Groq", "OpenRouter", "Ollama", "Gemini", "LangChain", "FastAPI"], "alternates": {"html": "https://wpnews.pro/news/how-i-built-a-provider-agnostic-ai-architecture-that-automatically-switches-groq", "markdown": "https://wpnews.pro/news/how-i-built-a-provider-agnostic-ai-architecture-that-automatically-switches-groq.md", "text": "https://wpnews.pro/news/how-i-built-a-provider-agnostic-ai-architecture-that-automatically-switches-groq.txt", "jsonld": "https://wpnews.pro/news/how-i-built-a-provider-agnostic-ai-architecture-that-automatically-switches-groq.jsonld"}}