Are you keeping up with the evolution of Large Language Models (LLMs)? New models are emerging rapidly, including Amazon Nova, Anthropic Claude, DeepSeek, Grok and others.
Amazon Bedrock is a great way to use these LLMs because it allows you to select models seamlessly without impacting the consuming application or chatbot integrated with them.
While you previously had the option to manually select from multiple LLMs, AWS introduced a new feature at re:Invent 2024: Intelligent Prompt Routing. With this feature, you provide the ARN of a model family, and Bedrock intelligently routes the request to the most suitable model based on the prompt.
For example, if you specify the Anthropic model family ARN, Amazon Bedrock will automatically route the request to Anthropic Haiku or Anthropic Sonnet, depending on the complexity of the prompt.
Please keep in consideration that this feature is not GA yet and in preview allowing routing with Claude Sonnet 3.5 and Claude Haiku, or between Llama 3.1 8B and Llama 3.1 70B.
In this article, I will implement Amazon Bedrock's intelligent prompt routing feature using anthropic family of models. Rather than providing a specific model id like Anthropic Haiku or Anthropic Sonnet, I will use a model family ARN and Bedrock will select the appropriate model based on the prompt.
As Large Language Models (LLMs) continue to evolve, selecting the optimal model for your specific use case becomes increasingly important. Amazon Bedrock addresses this challenge by enabling dynamic model selection without requiring changes to your application code.
Let's look at the architecture diagram!
Introduction to Amazon Bedrock
Amazon Bedrock is a fully managed service that provides access to a variety of foundation models, including Anthropic Claude, AI21 Jurassic-2, Stability AI, Amazon Titan, and others.
As a serverless offering from Amazon, Bedrock enables seamless integration with popular foundation models. It also allows you to privately customize these models with your own data using AWS tools, eliminating the need to manage any infrastructure.
Additionally, Bedrock supports the import of custom models.
With Bedrock, you have choice of foundation models.
Before model can be used, you need to request the access to the model.
For Amazon Models, typically it takes few mins to get access.
Introduction to Amazon Bedrock Intelligent Prompt Routing
At AWS re:Invent 2024, AWS introduced an exciting new feature: Intelligent Prompt Routing.
This Bedrock feature automates model selection within a model family. Instead of manually choosing specific models like Anthropic Haiku or Anthropic Sonnet, you simply provide a model family ARN. Bedrock then analyzes your prompt and routes it to the most appropriate model.
For instance, with the Anthropic model family ARN, Bedrock automatically directs:
- Simple queries to Anthropic Haiku for fast, efficient responses
- Complex requests to Anthropic Sonnet for detailed, comprehensive answers
Using Intelligent Prompt Routing in Amazon Bedrock Playground
In this part, I will use Amazon Bedrock Playground to use intelligent prompt routing feature.
Let's sign in to AWS Management console and navigate to Amazon Bedrock service.
You will see prompt routers for Anthropic and Meta LLMs.
Select Anthropic Prompt Router.
I will select Playground from the navigation panel
Validate the feature using few simple and complex prompts and observe which LLM is being selected for each response.
Prompt: Please suggest 3 places to visit in NYC in the bullet point format. I just need the name of the places and no additional description.
Result: Here are 3 places to visit in NYC:
- Central Park
- Metropolitan Museum of Art
- Brooklyn Bridge
Model Selected: Anthropic Haiku
Prompt: Write a python function that takes a word and print it in reverse.
Result: Here's a Python function that takes a word as input and prints it in reverse:
def print_reverse(word):
reversed_word = word[::-1]
print(reversed_word)
Model Selected: Anthropic Sonnet 3.5
Conclusion
In this article, I demonstrated Amazon Bedrock’s Intelligent Prompt Routing using the Anthropic model family. Instead of specifying a fixed model, I leveraged Bedrock’s intelligence to dynamically select the best model based on the prompt’s complexity.
I used the AWS Management Console and Bedrock Playground to perform these steps. In the next part, I will use the AWS SDK to demonstrate similar functionality by integrating with Lambda and API Gateway.
I hope you found this article both helpful and informative!
Thank you for reading!
Watch the video here:
https://www.youtube.com/watch?v=QXVTiseIfgQ
𝒢𝒾𝓇𝒾𝓈𝒽 ℬ𝒽𝒶𝓉𝒾𝒶
𝘈𝘞𝘚 𝘊𝘦𝘳𝘵𝘪𝘧𝘪𝘦𝘥 𝘚𝘰𝘭𝘶𝘵𝘪𝘰𝘯 𝘈𝘳𝘤𝘩𝘪𝘵𝘦𝘤𝘵 & 𝘋𝘦𝘷𝘦𝘭𝘰𝘱𝘦𝘳 𝘈𝘴𝘴𝘰𝘤𝘪𝘢𝘵𝘦
𝘊𝘭𝘰𝘶𝘥 𝘛𝘦𝘤𝘩𝘯𝘰𝘭𝘰𝘨𝘺 𝘌𝘯𝘵𝘩𝘶𝘴𝘪𝘢𝘴𝘵
Top comments (0)