Code Editing - AG2

GPT-5.1 Apply Patch Tool: Automated Code Editing in AG2

AG2 now supports the apply_patch tool (from GPT-5.1 onward) through OpenAI's Responses API, enabling agents to create, update, and delete files using structured diffs. This integration brings precise, controlled file operations directly into your agent workflows.

This article explores how to use apply_patch in AG2, with practical examples for automated code editing, project scaffolding, and multi-file refactoring.

What is Apply Patch?

The apply_patch tool is a built-in capability in GPT-5.1 and above models that enables agents to perform structured file operations using unified diff format. Unlike traditional code generation approaches where agents output raw code blocks that you must manually integrate, apply_patch provides a standardized interface for file modifications that can be directly applied to your codebase.

The tool handles three core operations:

• create_file: Generate new files with specified content
• update_file: Modify existing files using unified diff format
• delete_file: Remove files from the workspace

Why Apply Patch Matters:

Traditional agent-based code generation often requires manual intervention—you receive code blocks, review them, and manually integrate changes. Apply patch transforms this workflow by enabling agents to:

• Make precise, targeted changes using diff format
• Handle multi-file operations in a single interaction
• Provide structured, reviewable changes before application
• Support iterative refinement through feedback loops

When to use Apply Patch:

Use apply_patch when you need:

• Multi-file refactoring: Renaming symbols, extracting helpers, or reorganizing modules across multiple files
• Project scaffolding: Generating complete project structures with multiple files and directories
• Iterative code improvement: Making incremental changes based on feedback or test results
• Automated code fixes: Applying structured fixes to codebases based on linter output or error messages
• Documentation and test generation: Creating test files, fixtures, and documentation alongside code changes

Don't use apply_patch for simple, single-file code generation where direct code output is sufficient—standard AG2 code generation patterns are more efficient for that.

Note: AG2's apply_patch implementation integrates with OpenAI's Responses API. For protocol-level details, see OpenAI's Apply Patch documentation.