Amazon Bedrock Agents helps you accelerate the development of GenAI applications by orchestrating multistep tasks. Agents uses the reasoning capability of foundation models (FMs) to break down user-requested tasks into steps. Amazon Bedrock Agents can perform the following tasks:
- Breakdown user requests into multiple smaller steps
- Collect additional information from a user through natural conversation
- Decide which APIs to call and provide the necessary parameters for calling the APIs
- Take actions to fulfill a customer's request calling provided APIs
- Augment performance and accuracy by querying integrated Knowledge Bases
An agent consists of the following components:
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Foundation model – You choose a foundation model that the agent invokes to interpret user input and subsequent prompts in its orchestration process, and to generate responses and follow-up steps in its process
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Instructions – You author instructions that describe what the agent is designed to do
- (Optional) With Advanced Prompts you can further customize instructions for the agent at every step of orchestration
- With customized Lambda Parser functions you can parse the output of each orchestration step
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(Optional) Action groups – You define the actions that the agent should carry out by providing the available APIs with
- Function Definition where you specify functions and define parameters as JSON objects that will be associated to the action group invocation or,
- API Schema file that defines the APIs that the agent can invoke to carry out its tasks resources
Additionally, you can define a Lambda function to execute API calls with the selected parameters
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(Optional) Knowledge bases – Associate knowledge bases with an agent to allow it to retrieve context to augment response generation and input into orchestration steps
This repository contains examples and use-cases to get you started with Amazon Bedrock Agents and its capabilities. It is organized in the following folders:
- Feature examples: Examples of how to use specific features of Agents for Bedrock. Those examples are feature focuses and highlight how to use the service itself.
- Use case examples: examples of Agents in specific use cases, including:
- Amazon Bedrock Agents Blueprint templates to create reusable and scalable agents using AWS CDK
- Test Agent Sample code to test your agent for latency and accuracy (based on LLM judges)
We welcome community contributions! Please ensure your sample aligns with AWS best practices, and please update the Contents section of this README file with a link to your sample, along with a description.