Our main use case for LLM Gateway is that our company has partnerships with multiple LLM providers including OpenAI, Claude, and Gemini. LLM Gateway acts as an interface between all three providers. I would describe it as a router that functions as middleware between our application and the AI providers so that we do not need to give or share API keys to each team. Our team calls LLM Gateway from their application, and all the keys and routing configurations are present in LLM Gateway. Its responsibility is to connect with Claude, OpenAI, or Gemini based on the request we receive. We have an application in which users can ask anything. For example, if a user is asking a general question, we call LLM Gateway and pass the model name as ChatGPT. It internally uses ChatGPT itself. If the question is related to the application we created, it internally uses RAG and goes to Claude. LLM Gateway is responsible for redirecting the request based on context. LLM Gateway also has an additional feature where if one of the models is unavailable at a time, it automatically redirects the request to another model, so there is no downtime in the application. The automatic failover feature ensures that if one model is not available, LLM Gateway redirects the request to another model.
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Our main use case for LLM Gateway is that our company has partnerships with multiple LLM providers including OpenAI, Claude, and Gemini. LLM Gateway acts as an interface between all three providers. I would describe it as a router that functions as middleware between our application and the AI providers so that we do not need to give or share API keys to each team. Our team calls LLM Gateway from their application, and all the keys and routing configurations are present in LLM Gateway. Its responsibility is to connect with Claude, OpenAI, or Gemini based on the request we receive. We have an application in which users can ask anything. For example, if a user is asking a general question, we call LLM Gateway and pass the model name as ChatGPT. It internally uses ChatGPT itself. If the question is related to the application we created, it internally uses RAG and goes to Claude. LLM Gateway is responsible for redirecting the request based on context. LLM Gateway also has an additional feature where if one of the models is unavailable at a time, it automatically redirects the request to another model, so there is no downtime in the application. The automatic failover feature ensures that if one model is not available, LLM Gateway redirects the request to another model.