We made an AI SWE that solved 48.60% of issues on the SWE bench, 100% open-source.
We at Composio are building the tool infrastructure for AI agents. One of our users' biggest requests was toolkits for building custom coding agents that work. So, we created SWE-Kit, a starter template with all the toolkits for building AI coding agents.
These agents can run locally end-to-end to automate your coding workflows.
To test the efficiency of our tools, we built a comprehensive AI agent complete open-source using LangGraph and tested it on SWE-bench verified, and it got 48.60% and 41% on SWE-bench lite.
SWE-bench is a benchmark with over 2,200 real-world Python issues from repositories such as Django, Flask, Sklearn, SciPy, etc.
Check out the technical report for more: Tool design is all you need for SOTA AI agents
Complete code for the SWE agent: SWE-kit Agent
The tools you need for running the agent locally
- Code Analysis Tool: Intelligently retrieves relevant code snippets from the repository.
- File Tool: Facilitates navigation and updates to files.
- Shell Tool: Performs shell operations.
- Git Tool: Handles version control tasks.
- Composio Docker workspace for isolated code execution.
We optimized the tools for improved function calling accuracy.
What can you build with SWE-kit and Composio?
The code is open-source, and you can even modify it to add external integrations like GitHub, Jira, Linear, Slack, etc., using Composio to build a full-fledged AI software engineer.
You can automate many aspects of your Software development workflows with custom agents such as,
- Writing codes
- refactoring code bases
- testing
- documentation
- Project management with Linear or Jira, etc.
- Communication using Slack and Gmail.
For an architectural explanation of the SWE-Kit agent, check out the SWE-Kit agent blog published on LangChains’ blog.
I am not even kidding. Many companies have raised millions just from this.
Start building your custom local coding agent with SWE-kit now.