Building a self-service LLM gateway with Amazon Bedrock and LiteLLM | Amazon Web Services
Developers want AI coding assistants with minimal setup. With a large language model (LLM) gateway and LiteLLM, they can quickly access foundation models (FMs) available on Amazon Bedrock while you gain visibility and usage control. Platform teams need to monitor latency and errors, finance teams need to attribute inference costs to teams and projects, and security teams need consistent access controls. An LLM gateway can help address these needs by providing a centrally managed access point to the models that power coding assistants.
In this post, we show how to build a self-service LLM gateway using Amazon Bedrock Application Inference Profiles with LiteLLM running on AWS Fargate to abstract Amazon Bedrockbehind an OpenAI-compatible API. With this pattern, developers can access foundation models through a single API with a dedicated key while you gain per-user cost controls and model performance observability. By the end, you will understand the pattern well...
Copyright of this story solely belongs to aws.amazon.com. To see the full text click HERE
