open-swe/README.md

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  <h1>Open SWE - An Open-Source Asynchronous Coding Agent</h1>
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Open SWE is an open-source cloud-based asynchronous coding agent built with [LangGraph](https://docs.langchain.com/oss/javascript/langgraph/overview). It autonomously understands codebases, plans solutions, and executes code changes across entire repositories—from initial planning to opening pull requests.

>
> **Note: you're required to set your own LLM API keys to use the demo.**

> [!NOTE]
> 💬 Read the **announcement blog post [here](https://blog.langchain.com/introducing-open-swe-an-open-source-asynchronous-coding-agent/)**

# Features

![UI Screenshot](./static/ui-screenshot.png)

- 🔗 **Trigger from Linear, Slack, or GitHub** — mention `@openswe` in a Linear comment, Slack thread, or GitHub PR comment to kick off a task
- 👀 **Instant acknowledgement** — reacts with 👀 the moment it picks up your message so you know it's on it
- 💬 **Message it while it's running** — send follow-up messages mid-task and it'll pick them up before its next step
- 🔀 **Run multiple tasks in parallel** — each task runs in its own isolated cloud sandbox, no queuing
- 🔐 **GitHub OAuth built-in** — authenticates with your GitHub account automatically, no token setup needed
- 🚀 **Opens PRs automatically** — commits changes and opens a draft PR when done, linked back to your Linear ticket


## Installation

### Prerequisites

- Python 3.11+
- [uv](https://docs.astral.sh/uv/) package manager
- [LangGraph CLI](https://langchain-ai.github.io/langgraph/cloud/reference/cli/)
- [ngrok](https://ngrok.com/) (for exposing local webhooks)

### 1. Clone the repo

```bash
git clone https://github.com/langchain-ai/open-swe.git
cd open-swe/apps/agent
```

### 2. Install dependencies

```bash
uv sync
```

### 3. Set up the Linear webhook

In a terminal, start ngrok to get your public URL:

```bash
ngrok http 8000
# e.g. https://xxxx.ngrok.io
```

Then in Linear:

1. Go to **Settings** → **API** → **Webhooks** → **New webhook**
2. Fill in:
   - **Label**: `open-swe`
   - **URL**: `https://xxxx.ngrok.io/webhooks/linear`
   - **Secret**: generate a random string — copy it, you'll need it for `LINEAR_WEBHOOK_SECRET`
3. Under **Data change events**, enable **Comments** → `Create` only
4. Click **Create webhook**

To get your `LINEAR_API_KEY`:

1. Go to **Settings** → **API** → **Personal API keys** → **New API key**
2. Name it `open-swe` and copy the key

### 4. Set environment variables

Create a `.env` file in `apps/agent/` with the following:

```bash
# LangSmith
LANGSMITH_API_KEY_PROD=""           # Your LangSmith API key
LANGCHAIN_TRACING_V2="true"
LANGCHAIN_PROJECT=""

# LLM
ANTHROPIC_API_KEY=""                # Anthropic API key (recommended default provider)

# GitHub OAuth (via LangSmith agent auth)
GITHUB_OAUTH_PROVIDER_ID=""         # GitHub OAuth provider ID from LangSmith
X_SERVICE_AUTH_JWT_SECRET=""        # Secret for service JWT tokens

# GitHub App (Bot)
GITHUB_APP_ID=""                    # GitHub App ID
GITHUB_APP_PRIVATE_KEY="-----BEGIN RSA PRIVATE KEY-----
...
-----END RSA PRIVATE KEY-----
"
GITHUB_APP_INSTALLATION_ID=""       # GitHub App installation ID

# GitHub Webhook
GITHUB_WEBHOOK_SECRET=""            # Secret for verifying GitHub webhooks

# Linear
LINEAR_API_KEY=""                   # Linear API key (from step 3)
LINEAR_WEBHOOK_SECRET=""            # Secret you set when creating the webhook (from step 3)

# Slack (optional)
SLACK_BOT_TOKEN=""
SLACK_BOT_USER_ID=""
SLACK_BOT_USERNAME=""
SLACK_SIGNING_SECRET=""

# Sandbox
DEFAULT_SANDBOX_TEMPLATE_NAME=""    # LangSmith sandbox template name (uses default if not set)

# Token encryption
TOKEN_ENCRYPTION_KEY=""             # 32-byte url-safe base64 key for encrypting GitHub tokens
```

### 5. Run the agent

In one terminal, start the LangGraph dev server:

```bash
uv run langgraph dev --no-browser
```

In a second terminal, start the webhook server:

```bash
make run
```

The LangGraph server runs on `http://localhost:2024` and the webhook server on `http://localhost:8000`.

### 6. Verify it works

Comment `@openswe` on any Linear issue. You should see:
- A 👀 reaction on your comment within a few seconds
- A new run appear in your LangSmith project

---

## Usage

Open SWE can be used in multiple ways:

- 📋 **From Linear**. Mention `@openswe` in a comment on any Linear issue and describe the task you want it to perform (e.g. `@openswe fix the login bug described above`). The agent will pick up the issue context along with your instructions and start working on it.
- 🐙 **GitHub (for Open SWE-generated PRs)**. Once Open SWE completes implementation, it pushes changes to a branch `open-swe/<thread-id>` and opens a **draft pull request** linking back to the originating Linear issue. From there, you can review the code, request changes, and merge when ready.