Write files to a session - Amazon Bedrock AgentCore

Amazon Bedrock AgentCore is in preview release and is subject to change.

Write files to a session

You can use the Code Interpreter to read and write files in the sandbox environment. This allows you to upload data files, process them with code, and retrieve the results.

Install dependencies

Run the following command to install the required package:

pip install bedrock-agentcore
Upload Code and Data using the file tool

The following Python code shows how to upload files to the Code Interpreter session and execute code that processes those files. The files that are required are data.csv and stats.py that are available in this package.

# file_mgmt_ci_agent.py from bedrock_agentcore.tools.code_interpreter_client import CodeInterpreter import json from typing import Dict, Any, List #Configure and Start the code interpreter session code_client = CodeInterpreter('<Region>') code_client.start() #read the content of the sample data file data_file = "data.csv" try: with open(data_file, 'r', encoding='utf-8') as data_file_content: data_file_content = data_file_content.read() #print(data_file_content) except FileNotFoundError: print(f"Error: The file '{data_file}' was not found.") except Exception as e: print(f"An error occurred: {e}") #read the content of the python script to analyze the sample file code_file = "stats.py" try: with open(code_file, 'r', encoding='utf-8') as code_file_content: code_file_content = code_file_content.read() #print(code_file_content) except FileNotFoundError: print(f"Error: The file '{code_file}' was not found.") except Exception as e: print(f"An error occurred: {e}") files_to_create = [ { "path": "data.csv", "text": data_file_content }, { "path": "stats.py", "text": code_file_content }] #define the method to call the invoke API def call_tool(tool_name: str, arguments: Dict[str, Any]) -> Dict[str, Any]: response = code_client.invoke(tool_name, arguments) for event in response["stream"]: return json.dumps(event["result"], indent=2) #write the sample data and analysis script into the code interpreter session writing_files = call_tool("writeFiles", {"content": files_to_create}) print(f"writing files: {writing_files}") #List and validate that the files were written successfully listing_files = call_tool("listFiles", {"path": ""}) print(f"listing files: {listing_files}") #Run the python script to analyze the sample data file execute_code = call_tool("executeCode", { "code": files_to_create[1]['text'], "language": "python", "clearContext": True}) print(f"code execution result: {execute_code}") #Clean up and stop the code interpreter session code_client.stop()