This tutorial demonstrates how to create an AI agent that performs advanced data analysis through code execution using Python. We use Amazon Bedrock AgentCore Code Interpreter to run code that is generated by the LLM.
This tutorial demonstrates how to use AgentCore Bedrock Code Interpreter to:
- Set up a sandbox environment
- Configure trands & langchain based agents that performs advanced data analysis by generating 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 | AmazonBedrock 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.
