build-on-aws/bedrock-agents-infer-models
Use natural language to run inference on various LLMs via Bedrock agents
### Overview
This project demonstrates how to use natural language processing (NLP) to infer various Large Language Models (LLMs) via Amazon Bedrock agents. It showcases the potential of leveraging multiple models on Bedrock to create chained responses that adapt to diverse scenarios. The app supports generating text-based outputs and even creates and examines images using image generation and text-to-image models, enhancing its versatility for more creative and visual use cases.
### Key Features
- **Model Inference**: Inference on various LLMs using Bedrock agents.
- **Image Generation**: Creation and examination of images using image generation and text-to-image models.
- **Chained Responses**: Adaptation of responses based on input prompts.
- **Flexibility**: Infrastructure-as-Code (IaC) setup using AWS CloudFormation for manual deployment.
### Tech Stack
- **Python**: The primary programming language used for the application.
- **AWS**: Amazon Bedrock, S3, Lambda, and Serverless Application Model are utilized for the project setup and deployment.
### Why It Matters
This project provides a practical demonstration of how to integrate multiple models on Amazon Bedrock, showcasing the potential of using Bedrock agents to create versatile and adaptable NLP applications. The ability to handle both text-based and image-based tasks makes it suitable for a wide range of use cases, from generating text to creating and examining images.