An open-source software factory built on Deep Agents by LangChain.
Open SWE turns engineering work into a repeatable system. Give it a code-change task from the dashboard, GitHub, Slack, or Linear—or run one on a schedule—and it works in an isolated environment to understand the codebase, make changes, validate them, and deliver a pull request.
It goes beyond code generation. Open SWE can review pull requests, learn a repository's review style, monitor CI, and respond to feedback. It is open source, deployable in your infrastructure, and designed to be adapted to your team's repositories, tools, policies, and workflows.
[!NOTE]
Open SWE is under active development. APIs, setup, and product surfaces may continue to evolve.
The software factory loop
flowchart LR
A[Issues, conversations, PRs, schedules] --> B[Plan and investigate]
B --> C[Implement in an isolated sandbox]
C --> D[Validate and deliver a PR]
D --> E[Review, CI, and feedback]
E -->|Follow-up work| B
Each cloud coding thread is bound to its own persistent sandbox, so the agent can continue from prior work when you reply. A thread is a durable conversation and work context. It can contain multiple invocations, each an agent execution triggered by a message or automation. An initial request and a follow-up belong to one thread and produce two invocations, each with its own usage. Independent threads run in parallel, and the same thread carries context from request through delivery and follow-up. Read-only PR chat does not need a sandbox, while desktop work can run directly against an allowlisted local project.
What Open SWE does
Build
- Investigates repositories, plans work, edits code, and runs focused validation
- Commits and pushes changes, then opens or updates pull requests
- Uses subagents to parallelize research and independent work
- Supports reusable skills, repository instructions, and custom environments
Review
- Runs read-only pull request reviews on demand or automatically
- Learns repository-specific review preferences from historical feedback
- Supports read-only PR chat for investigating a change without modifying it
- Keeps findings grounded in the diff and publishes them back to GitHub
Operate
- Runs tasks from the web dashboard, GitHub, Slack, and Linear
- Schedules recurring work through deterministic automations
- Monitors opted-in pull requests with
/baby-sit, diagnoses CI failures, and reruns only evidence-backed flaky jobs
- Routes follow-up messages to the original thread and sandbox
Customize
- Choose the models and reasoning effort available to agents and reviewers
- Configure supported integrations and extend the curated toolset without forking Deep Agents
- Define personal and repository coding instructions plus organization-wide review guidelines
- Swap sandbox providers, middleware, skills, triggers, and delivery policies
API contract
swagger.json is the generated OpenAPI 3.1 contract for the custom FastAPI backend (agent.webapp:app). Import it into an OpenAPI 3.1-compatible viewer, or run make run and open http://localhost:8000/docs for interactive API documentation (/openapi.json serves the live schema).
Regenerate the file with make swagger after changing backend routes or models. It reflects the current route declarations: some request/response schemas and authentication requirements are not yet documented. LangGraph runtime endpoints (such as /runs, /threads, and /assistants) are not included.
How it works
Deep Agents is the harness
Open SWE composes the agent with Deep Agents. Deep Agents provides the planning, file operations, shell access, skills, state, and subagent primitives; Open SWE adds the software-engineering tools, prompts, middleware, integrations, authorization, and product surfaces needed for end-to-end engineering work.
This composition keeps the system extensible while allowing it to inherit improvements from the underlying LangChain agent stack.
LangGraph is the runtime
LangGraph provides durable execution and thread state. Each Open SWE invocation executes as a LangGraph run within a thread. Open SWE currently ships five graph entrypoints:
| Graph |
Role |
| Agent |
Plans, implements, validates, and delivers software changes |
| Reviewer |
Performs read-only pull request reviews |
| Analyzer |
Learns repository-specific review style |
| Chat |
Answers questions about pull requests without changing code |
| Scheduler |
Dispatches recurring tasks and CI monitoring work |
Sandboxes contain the work
Cloud work runs in isolated Linux sandboxes with the development tooling supplied by the configured environment or snapshot. A sandbox persists with its thread, but an unreachable coding sandbox is not silently replaced—Open SWE fails safely rather than risk discarding uncommitted work.
LangSmith is the default sandbox and tracing provider. Open SWE also supports Modal, Daytona, Runloop, E2B, and local execution, with a pluggable interface for additional providers.
Deep Agents supplies the core filesystem, shell, and subagent tools. Open SWE adds focused capabilities for GitHub delivery, Linear, Slack, thread management, web research, browser-based application verification, planning, review, CI monitoring, and connected services. Personal integrations load using the user's connections. Admin-configured workspace MCP tools are available to all coding-agent users.
Work where your team works
- Dashboard — Start and continue tasks, inspect work, manage pull requests, and configure user or team settings.
- GitHub — Start tasks from issues, request changes from pull request conversations, run reviews, and continue work on the same branch.
- Slack — Start from a channel, thread, or code channel and receive progress and delivery updates in context.
- Linear — Invoke Open SWE from an issue and post results back to the issue.
- Desktop (experimental) — Run the same agent against local projects. Packaged releases currently target macOS; source builds also support Windows and Linux.
Control and safety
A useful software factory needs both autonomy and boundaries. Open SWE includes:
- Per-thread sandbox isolation and persistent workspaces for cloud coding tasks
- GitHub App installation boundaries and optional per-user OAuth
- Organization and repository allowlists with actor authorization checks
- Credentials kept in the server process or injected through a sandbox proxy
- Human approval before pushing workflow-file changes
- Read-only reviewer and PR chat agents
- Plan mode for reviewing an implementation approach before code changes
- Opt-in automatic review and CI monitoring
Sandboxes can have network access and powerful tools. Deployments should use least-privilege credentials, restrict enabled repositories and integrations, and tailor approval rules to their environment.
Getting started
Open SWE includes a LangGraph backend, a web dashboard, and an experimental desktop client.
- Installation Guide — Deploy Open SWE for a team: LangGraph Platform or Docker, the GitHub and Slack apps, model providers, environment variables, and the optional Linear trigger
- Development Guide — Run it on your machine, with hot reload for the dashboard and an ngrok tunnel for webhooks
- Customization Guide — Change models, sandboxes, tools, skills, prompts, triggers, and middleware
- Open SWE Enhancement Proposals — Review consequential product, architecture, security, and process decisions
One deployment serves the API, the webhooks, and the dashboard from a single URL. Locally:
git clone https://github.com/langchain-ai/open-swe.git
cd open-swe
uv venv
source .venv/bin/activate
uv sync --all-extras
make build-dashboard # pnpm install + Vite build of the dashboard
make dev # http://localhost:2024 serves the API and the dashboard
Create a GitHub App and a Slack app for your machine and fill in .env as described in the development guide, then sign in at http://localhost:2024. For UI work, make dev-ui starts Vite and the backend fronting it, so the same URL hot-reloads. GitHub and Slack deliver to a public webhook URL: locally the static domain of a free ngrok account (make tunnel NGROK_DOMAIN=<name>.ngrok-free.dev, which exposes only /webhooks/*, since the dev server's LangGraph API has no authentication), on LangGraph Platform the deployment URL.
Production self-hosting uses the standalone LangGraph Agent Server and requires its license key.
Project status
Open SWE is built in the open by LangChain and is evolving quickly. The original internal coding-agent framework announcement is available on the LangChain blog; the project has since expanded considerably.
License
Open SWE is licensed under the MIT License.
Open SWE 是一个开源的异步编程智能体，也就是一座“软件工厂”，基于 LangChain 的 Deep Agents 构建。它可以接收来自控制面板、GitHub、Slack、Linear 或定时计划的代码修改任务，在隔离的沙箱中理解代码库、做出修改、验证结果，最后提交一个 PR。