Simplify Your Bedrock Converse API Integration with the bedrock-tools Python Library

Simplify Your Bedrock Converse API Integration with the bedrock-tools Python Library

A Python library that simplifies Amazon Bedrock Converse API tool use

John Ritsema
Amazon Employee
Published Oct 25, 2024
The Amazon Bedrock Converse API enables developers to build conversational AI applications and leverage custom tools and functions, enhancing their AI agents' capabilities. Integrating these tools with the API can be time-consuming due to boilerplate code.
bedrock-tools is a Python library that simplifies integrating native Python functions with the Bedrock Converse API, enabling conversational AI application development.

Key Features of bedrock-tools:

  1. Simple Integration: You can author AI tools as standard Python functions without the need for complex frameworks.
  2. Automatic Type Handling: The library generates the necessary JSON schema based on your functions' type annotations, handling various data types.
  3. Transparent Tool Invocation: When the Bedrock Converse API requests a tool, the library handles the invocation and exception handling, returning the result in the expected format.
Using bedrock-tools allows you to focus on building your application's core functionality while the library handles the integration details.
Here's an example of how to use the library. First, install the library.
Then, use it in your code.
The following is an example from the Bedrock Converse API documentation without and with the use of the library:
Code without and with the use of the library
Code without and with the use of the library
Code without and with the use of the library
Code without and with the use of the library
The bedrock-tools library simplifies the integration of custom Python functions with the Amazon Bedrock Converse API, enabling you to build more sophisticated conversational AI applications efficiently. Contributions to improve the library are welcome.
 

Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.

Comments