swekit 0.2.43

Tools for running a SWE agent using Composio platform

Production Ready Toolset for AI Agents

Build Software engineering Agents fast and easy!

SWEKIT Docs »

---

✨ Socials >> Discord | Youtube | Twitter | Linkedin

⛏️ Contribute >> Report Bugs | Request Feature | Contribute

📋 Table of contents

Table of Contents

• 📋 Table of contents
• Table of Contents
• Overview
• Dependencies
• Getting Started
  • Creating a new agent
  • Workspace Environment
  • Customising the workspace environment
  • Running the Benchmark

Overview

swekit is a framework for building SWE agents on by utilising composio tooling ecosystem. SWE Kit allows you to

• Scaffold agents which works out-of-the-box with choice of your agentic framework, crewai, llamaindex, etc...
• Tools to add or optimise your agent's abilities
• Benchmark your agents against SWE-bench

Dependencies

Before getting started, ensure you have the following set up:

1. Installation:

   pip install swekit composio-core
   

2. Install agentic framework of your choice and the Composio plugin for the same: Here we're using crewai for the example:

   pip install crewai composio-crewai
   

3. GitHub Access Token:

   The agent requires a github access token to work with your repositories, You can create one at https://github.com/settings/tokens with necessary permissions and export it as an environment variable using export GITHUB_ACCESS_TOKEN=<your_token>

4. LLM Configuration: You also need to setup API key for the LLM provider you're planning to use. By default the agents scaffolded by swekit uses openai client, so export OPENAI_API_KEY before running your agent

Getting Started

Creating a new agent

1. Scaffold your agent using:

   swekit scaffold <type> -f <framework> -o <path>
   

   • <type> can be swe or pr_review depending on the use-case
   • <framework> can be crewai or langgraph. Support for more frameworks coming soon!

   This creates a new agent in <path>/agent with four key files:

   • main.py: Entry point to run the agent on your issue
   • agent.py: Agent definition (edit this to customise behaviour)
   • prompts.py: Agent prompts
   • benchmark.py: SWE-Bench benchmark runner

2. Run the agent:

   cd agent
   python main.py
   

   You'll be prompted for the repository name and issue.

Workspace Environment

The SWE-agent runs in Docker by default for security and isolation. This sandboxes the agent's operations, protecting against unintended consequences of arbitrary code execution.

The composio toolset has support for different types of workspaces.

1. Host - This will run on the host machine.

from composio import ComposioToolSet, WorkspaceType

toolset = ComposioToolSet(
    workspace_config=WorkspaceType.Host()
)

2. Docker - This will run inside a docker container

from composio import ComposioToolSet, WorkspaceType

toolset = ComposioToolSet(
    workspace_config=WorkspaceType.Docker()
)

On the docker container you can configure and expose the port for development as per your requirements. You can also use workspace.as_prompt() method to generate a workspace description for setting up your agent.

from composio import ComposioToolSet, WorkspaceType

toolset = ComposioToolSet(
    workspace_config=WorkspaceType.Docker(
        ports={
            8001: 8001,
        }
    )
)

You can read more about configuring docker ports here.

3. E2B - This will run inside a E2B Sandbox

from composio import ComposioToolSet, WorkspaceType

toolset = ComposioToolSet(
    workspace_config=WorkspaceType.E2B(),
)

4. FlyIO - This will run inside a FlyIO machine

from composio import ComposioToolSet, WorkspaceType

toolset = ComposioToolSet(
    workspace_config=WorkspaceType.FlyIO(),
)

FlyIO also allows for configuring ports for development/deployment.

from composio import ComposioToolSet, WorkspaceType

composio_toolset = ComposioToolSet(
    workspace_config=WorkspaceType.FlyIO(
        image="composio/composio",
        ports=[
            {
                "ports": [
                    {"port": 443, "handlers": ["tls", "http"]},
                ],
                "internal_port": 80,
                "protocol": "tcp",
            }
        ],
    )
)

You can read more abour configuring network ports on flyio machine here

Customising the workspace environment

The workspace environment contains following environment variables by default

• COMPOSIO_API_KEY: The composio API key for interacting with composio API.
• COMPOSIO_BASE_URL: Base URL for composio API server.
• GITHUB_ACCESS_TOKEN: Github access token for the agent.
• ACCESS_TOKEN: Access token for composio tooling server.

If you want to provide additional environment configuration you can use environment argument when creating a workspace configuration.

composio_toolset = ComposioToolSet(
    workspace_config=WorkspaceType.Docker(
        environment={
            "SOME_API_TOKEN": "<SOME_API_TOKEN>",
        }
    )
)

Running the Benchmark

SWE-Bench is a comprehensive benchmark designed to evaluate the performance of software engineering agents. It comprises a diverse collection of real-world issues from popular Python open-source projects, providing a robust testing environment.

To run the benchmark:

1. Ensure Docker is installed and running on your system.
2. Execute the following command:

   cd agent
   python benchmark.py --test-split=<test_split>
   

   • By default, python benchmark.py runs only 1 test instance.
   • Specify a test split ratio to run more tests, e.g., --test-split=1:300 runs 300 tests.

To run the benchmarks in E2B or FlyIO sandbox, you can set the workspace_env in the evaluate function call in benchmark.py

from composio import WorkspaceType

(...)

    evaluate(
        bench,
        dry_run=False,
        test_range=test_range,
        test_instance_ids=test_instance_ids_list,
        workspace_env=WorkspaceType.E2B
    )

To use E2B or FlyIO sandboxes you'll require API key for respective platforms, to use E2B export your API key as E2B_API_KEY and to use FlyIO export your API token as FLY_API_TOKEN.

Note: We utilize SWE-Bench-Docker to ensure each test instance runs in an isolated container with its specific environment and Python version.

To extend the functionality of the SWE agent by adding new tools or extending existing ones, refer to the Development Guide.