What is the benefit of using the Converse API over the native API?

The Converse API provides a model-agnostic, unified interface that works consistently across different model providers in Bedrock, making it easier to switch models without rewriting your code.

Can I use this skill for real-time applications?

Yes, the skill includes patterns for streaming responses, which reduces perceived latency by sending tokens to the client as they are generated.

How does it handle AI safety?

The skill integrates with Amazon Bedrock Guardrails, allowing you to implement runtime content filtering and safety policies directly within your inference calls.

Does this skill help with AWS cost management?

Yes, it includes token counting capabilities to estimate costs before inference and supports inference profiles for cost and performance optimization.

Which models are supported by the bedrock-inference skill?

It supports all models available via Amazon Bedrock Runtime, including Anthropic Claude (Opus, Sonnet, Haiku), Amazon Nova, Amazon Titan, and third-party models from Meta, Cohere, and AI21.

Amazon Bedrock Inference

Name: Amazon Bedrock Inference
Author: adaptationio

byadaptationio

Ciencia de Datos y ML

Integrates Amazon Bedrock Runtime APIs for unified model inference, streaming, and safety guardrails across multiple foundation models.

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This skill provides a robust framework for interacting with the Amazon Bedrock Runtime, enabling developers to invoke foundation models like Anthropic Claude, Amazon Nova, and Amazon Titan via a unified interface. It covers essential production patterns including synchronous and asynchronous inference, real-time token streaming for low-latency applications, and the versatile Converse API for multi-turn dialogues. By incorporating token counting for cost estimation and runtime guardrails for content safety, this skill ensures that AI-driven applications are not only powerful but also secure, cost-effective, and highly available through global inference profiles.

Características Principales

Runtime Bedrock Guardrails for safety and content filtering
Real-time token streaming for low-latency conversational UX
Precise token counting for cost estimation and quota management
Asynchronous invocation support for long-running AI tasks up to 24 hours
Unified model interaction via the Amazon Bedrock Converse API
0 GitHub stars

Casos de Uso

Optimizing AI costs and availability using cross-region inference profiles
Building production-grade conversational AI with multi-turn history
Implementing real-time streaming responses in web and mobile applications

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Características Principales

Runtime Bedrock Guardrails for safety and content filtering
Real-time token streaming for low-latency conversational UX
Precise token counting for cost estimation and quota management
Asynchronous invocation support for long-running AI tasks up to 24 hours
Unified model interaction via the Amazon Bedrock Converse API
0 GitHub stars

Casos de Uso

Optimizing AI costs and availability using cross-region inference profiles
Building production-grade conversational AI with multi-turn history
Implementing real-time streaming responses in web and mobile applications