This section provides common issues and their solutions when working with the Agent Engine Code Execution.
Sandbox creation issues
Permissions error: If you encounter errors when creating a sandbox, ensure your Google Cloud project has the Vertex AI User
(roles/aiplatform.user)Identity and Access Management (IAM) role.Invalid Project ID or Location: Verify that the
PROJECT_IDandLOCATIONvariables used in your code are correct and supported. For a list of supported regions, see Supported regions.Agent Engine not created: Before creating a sandbox, confirm that the Agent Engine instance was successfully created. The
agent_engine.create()method must complete without errors.
Code execution issues
Code errors: Review the
stderroutput from theexecute_coderesponse to identify any syntax errors, runtime exceptions, or logical flaws in your code.File I/O issues:
File not found: Ensure that any input files specified in the
filesarray of yourinput_dataare correctly referenced within your code. Your code is executed in the same folder as the files and can't access other folders.Output file not generated: Check that your code is writing to the expected output filename and that there are no errors preventing file creation or writing.
Size limits: There is a 100MB size limit for files.
State persistence: If your code relies on previous state, verify that you are using the same
sandbox_namefor subsequent calls. Also, make sure that the sandbox has not expired.Timeout: Code execution times out after 300 seconds. Consider optimizing your code for performance or breaking down complex tasks into smaller, more manageable steps.
Sandbox management and cleanup
Sandbox not found for deletion: If you're unable to delete a sandbox, ensure that the
sandbox_nameyou are using is correct and that the sandbox still exists.Agent Engine not found for deletion: Similar to sandboxes, verify the
agent_engine_namewhen attempting to delete the Agent Engine.Resource quotas: If you are creating many sandboxes or performing frequent executions, you might encounter resource quota limits. Check your project's quotas for Vertex AI services and request increases if necessary. For a list of Agent Engine quotas, see Quotas.