> ## Documentation Index
> Fetch the complete documentation index at: https://composio-27-feat-docs-revamp.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# SWE Development Kit

> Build Software Engineering agents locally with frameworks and tools of your choice

## Overview

SWE Development Kit (swekit) is a powerful framework for building Software Engineering agents using Composio's tooling ecosystem.
It provides tools like Github, Repo Indexing, Repo Search, File Manager, Shell Manager, and more.

## Key Features

* **Agent Scaffolding**: Quickly create Devin like agents that work out-of-the-box with popular agentic frameworks like CrewAI, LlamaIndex, and more.
* **Flexible Workspace Environments**: Operate your agents within a variety of secure and isolated environments including Docker, E2B, and FlyIO for security and isolation.
* **Customizable Tools**: Add or optimize your agent's abilities with a variety of tools.
* **Benchmarking**: Evaluate your agents against the SWE-bench, a comprehensive benchmark for software engineering tasks.

## Introduction to Key Concepts

* **Workspace Environments**: These are isolated and secure execution contexts where agents can be run. They ensure that agents operate in a controlled setting, which can be tailored for specific security or resource needs. Examples include containerized environments like Docker, virtualized environments like E2B, and cloud-based platforms like FlyIO.
* **Custom Tools**: These are specialized utilities or enhancements that can be integrated into your agent to extend its functionality or improve its performance. They can range from simple scripts to complex software packages.
* **Benchmarks**: Benchmarks are standardized tests that measure the performance and effectiveness of your agents. They provide a way to compare different agents and track improvements over time.

## Getting Started

<Steps>
  <Step title="Installation">
    Begin by installing the core packages:

    <CodeGroup>
      ```bash Installing SweKit
      pip install swekit composio-core
      ```
    </CodeGroup>

    For additional functionality, install packages for your preferred framework (e.g., CrewAI):

    <CodeGroup>
      ```bash Installing CrewAI and Composio CrewAI Plugin
      pip install crewai composio-crewai
      ```
    </CodeGroup>
  </Step>

  <Step title="Connect your Github Account">
    To utilize Github Issues as a task source, link your Github account as follows:

    <Tabs>
      <Tab title="Composio CLI">
        <CodeGroup>
          ```bash Use Composio CLI
          composio add github
          ```
        </CodeGroup>
      </Tab>

      <Tab title="Locally using Github Auth Token">
        <CodeGroup>
          ```bash Use Github Auth Token
          export GITHUB_ACCESS_TOKEN=<your_token>
          ```
        </CodeGroup>
      </Tab>
    </Tabs>

    <Note>
      There are two ways to provide the GitHub access token for git clone:

      1. Set the environment variable `GITHUB_ACCESS_TOKEN='<git_access_token>'`.
      2. Use the GitHub account connected to your toolset entity. However, this method has limitations:
         * The agent won't be able to push or create PRs.
         * You need to set `export ALLOW_CLONE_WITHOUT_REPO='true'`.

      Option 1 is recommended for full functionality.
    </Note>
  </Step>

  <Step title="Create a New Agent">
    Generate your agent's scaffolding:

    <CodeGroup>
      ```bash Create a new Folder with basic SWE agent code
      swekit scaffold swe -f crewai -o swe_agent
      ```
    </CodeGroup>

    | Argument | Description                                   | Accepted Values          |
    | -------- | --------------------------------------------- | ------------------------ |
    | `-f`     | Specifies the framework to use                | `crewai`, `langgraph`    |
    | `-o`     | Sets the output directory for generated files | Any valid directory path |

    <Note>
      Scaffold support for other frameworks coming soon!
    </Note>

    This process will establish a new agent at `swe_agent` with essential files:

    * `main.py`: The main script to execute the agent
    * `agent.py`: The agent's core definition
    * `prompts.py`: Prompts to guide the agent's actions
    * `benchmark.py`: A runner for the SWE-Bench benchmarks
    * `input.py`: A helper file to take inputs from the user
    * `custom_tools.py`: A file to add custom tools to the agent
  </Step>

  <Step title="Start Docker Server">
    <Warning>
      To use Docker as the default workspace environment, ensure your Docker server is running
    </Warning>

    If you prefer to run the agent locally without Docker (**Unsafe**), modify the workspace configuration in `agent.py` by setting the `WorkspaceType.Docker()` to `WorkspaceType.Host()`.
  </Step>

  <Step title="Run the Agent">
    To activate the agent, proceed to its directory and execute:

    <CodeGroup>
      ```bash Run the agent
      cd swe_agent/agent
      python main.py
      ```
    </CodeGroup>

    You will be prompted to specify the repository and issue for the agent to address.
  </Step>
</Steps>