Can Open SWE Refactor Existing Codebases? A Deep Dive into Automated Code Transformation

Yes, Open SWE can refactor existing codebases by combining a strict system prompt, precision file-editing tools, and automated PR workflows to safely transform code from discovery to review.

Open SWE, developed by LangChain AI, is an open-source agentic framework explicitly built to automate code-change tasks within existing repositories. Whether you need to migrate legacy patterns, enforce new style guides, or restructure entire packages, Open SWE provides the architectural foundation to refactor existing codebases reliably and reviewably.

Core Architecture for Refactoring Existing Codebases

The ability to safely transform production code stems from three integrated components: a disciplined system prompt, a precision toolset, and mandatory review workflows.

System Prompt: The Refactoring Philosophy

In agent/prompt.py, the system prompt establishes strict ground rules that govern how the agent approaches modifications. Lines 13-21 instruct the agent to "Read files before modifying them" and to "Fix root causes, not symptoms" while preserving the existing code style. This constraint prevents superficial changes and ensures refactoring addresses architectural debt rather than masking it.

Deep Agents Toolset: Precision Editing

Open SWE imports the Deep Agents toolset automatically, exposing functions that allow surgical code manipulation:

• read_file: Inspects current implementation before changes.
• edit_file: Modifies specific line ranges without rewriting entire files.
• write_file: Creates new modules when restructuring requires new files.

These tools operate within sandboxed environments, ensuring the agent can experiment with transformations without risking production stability.

The Four-Stage Refactoring Workflow

Open SWE executes refactoring through a deterministic pipeline that mirrors professional software engineering practices.

Stage 1: Discovery and Analysis

The agent begins by exploring the codebase to identify refactoring targets. Using execute to run grep, find, or repository-specific scripts, the agent maps dependencies and locates legacy patterns. This discovery phase ensures the agent understands the full scope of changes before modifying any files.

Stage 2: Applying Code Transformations

With targets identified, the agent invokes edit_file or write_file to apply transformations. For example, converting legacy classes to @dataclass decorators or migrating callback-based code to async/await patterns. The system prompt constraints ensure these changes maintain existing style conventions and do not introduce unrelated modifications.

Stage 3: Validation with Linters and Tests

Before finalizing, the agent validates changes within the sandbox environment. The execute tool runs formatters like Black or isort, followed by the repository's test suite. This validation step catches syntax errors or regressions introduced during the automated refactor, ensuring only working code reaches review.

Stage 4: Committing and Opening Pull Requests

Once validation passes, the agent calls commit_and_open_pr from agent/tools/commit_and_open_pr.py. This tool:

1. Stages all modified files.
2. Creates a commit with a descriptive message.
3. Pushes to a dedicated branch named open-swe/<thread_id>.
4. Opens a GitHub PR using the repository's required template conventions (lines 27-36 and 42-55).

Additionally, the open_pr middleware in agent/middleware/open_pr.py acts as a safety net, automatically triggering the PR creation if the LLM neglects to call the tool explicitly (lines 1-20).

Sandbox Environments for Safe Refactoring

Open SWE supports multiple sandbox backends that provide isolated Linux environments for refactoring operations. According to the README (lines 52-57), supported platforms include:

• Modal
• Daytona
• Runloop
• LangSmith

These sandboxes allow the agent to run destructive operations—such as mass find-and-replace scripts or dependency upgrades—without affecting the production repository. The isolated environment ensures that refactoring experiments remain contained until explicitly committed and pushed via the PR workflow.

Practical Examples: Refactoring Code with Open SWE

Example 1: Triggering Refactor via Slack Integration

You can initiate a refactoring task through natural language commands:

@openswe Please refactor the `utils` package to use type‑annotated dataclasses.

The agent executes the following sequence:

1. execute to search for class definitions in the utils directory.
2. edit_file to replace legacy classes with @dataclass decorators and type annotations.
3. execute to run black . && isort . for formatting.
4. commit_and_open_pr to create a reviewable pull request.

Example 2: Programmatic Refactoring with the Python API

For automated pipelines, invoke the commit_and_open_pr tool directly:

from openswe.agent.tools import commit_and_open_pr

result = commit_and_open_pr(
    title="refactor: convert utils to dataclasses [closes PROJ-123]",
    body="""

## Description

Converted legacy utility classes to `@dataclass` for clearer type contracts.

## Test Plan

- [ ] Run the existing unit‑test suite (passes) 
""",
    commit_message="refactor utils to dataclasses"
)

if result["success"]:
    print("PR opened:", result["pr_url"])
else:
    print("Error:", result["error"])

This function handles all git operations, pushes to the open-swe/<thread_id> branch, and creates the PR using GitHub's API according to the template conventions defined in agent/tools/commit_and_open_pr.py (lines 84-100).

Example 3: Validating Refactors with Linters

Before submitting changes, validate code quality within the sandbox:

# The agent executes formatting and linting

execute("black . && isort .")

After confirming clean output, the agent proceeds to commit_and_open_pr, ensuring that only properly formatted code reaches the pull request.

Summary

Open SWE provides a complete, automated solution to refactor existing codebases through:

• Disciplined system prompts in agent/prompt.py that enforce root-cause fixes and style preservation.
• Precision editing tools (edit_file, write_file, read_file) that enable surgical code transformations.
• Automated validation via sandboxed execution of linters and test suites.
• Guaranteed review workflows through commit_and_open_pr and open_pr middleware that ensure every refactor becomes a pull request.

Whether modernizing legacy patterns or restructuring entire packages, Open SWE executes refactoring tasks with the rigor of a senior engineer while maintaining full auditability through GitHub's standard review process.

Frequently Asked Questions

Can Open SWE handle large-scale refactoring across multiple packages?

Yes. Open SWE uses the execute tool with grep and find to map dependencies across packages, then applies changes incrementally using edit_file. The sandbox environment supports running repository-wide scripts, and the commit_and_open_pr tool captures all modifications in a single, reviewable pull request regardless of scope.

How does Open SWE ensure code style consistency during refactoring?

The system prompt in agent/prompt.py explicitly instructs the agent to preserve existing code style and fix root causes rather than symptoms. Additionally, the agent runs formatters like Black and isort via the execute tool before committing, ensuring all refactored code matches the repository's formatting standards.

What happens if the agent forgets to open a pull request after refactoring?

The open_pr middleware in agent/middleware/open_pr.py acts as a safety mechanism. If the LLM completes the refactoring workflow without explicitly calling commit_and_open_pr, this middleware automatically triggers the PR creation, ensuring that no code changes are lost and every refactor remains visible for human review.

Is it safe to run Open SWE on production repositories?

Yes, because Open SWE operates entirely within sandboxed environments provided by backends like Modal, Daytona, Runloop, or LangSmith. The agent cannot directly modify production branches; instead, it creates isolated branches (prefixed open-swe/<thread_id>) and opens pull requests, requiring standard human approval before any changes reach production.

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