This tutorial demonstrates how to create an AI agent that validates answers through code execution using Python. We will use Amazon Bedrock AgentCore Code Interpreter to run code that is generated by the LLM
This tutorial demonstrates how to use Amazon Bedrock AgentCore Code Interpreter to:
- Set up a sandbox environment
- Configure strands & langchain based agents that generated code based on the user query
- Execute code in a sandbox environment using Code Interpreter
- Display the results back to the user
| Information | Details |
|---|---|
| Tutorial type | Conversational |
| Agent type | Single |
| Agentic Framework | Langchain & Strands Agents |
| LLM model | Anthropic Claude Sonnet 3.5 & 3.7 |
| Tutorial components | Amazon Bedrock AgentCore Code Interpreter |
| Tutorial vertical | Cross-vertical |
| Example complexity | Easy |
| SDK used | Amazon BedrockAgentCore Python SDK and boto3 |
The code execution sandbox enables agents to safely process user queries by creating an isolated environment with a code interpreter, shell, and file system. After a Large Language Model helps with tool selection, code is executed within this session, before being returned to the user or agent for synthesis.
