


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.
Get Started with SWE-kit
The above is the detailed content of We made an AI SWE that solved of issues on the SWE bench, % open-source.. For more information, please follow other related articles on the PHP Chinese website!

Pythonarrayssupportvariousoperations:1)Slicingextractssubsets,2)Appending/Extendingaddselements,3)Insertingplaceselementsatspecificpositions,4)Removingdeleteselements,5)Sorting/Reversingchangesorder,and6)Listcomprehensionscreatenewlistsbasedonexistin

NumPyarraysareessentialforapplicationsrequiringefficientnumericalcomputationsanddatamanipulation.Theyarecrucialindatascience,machinelearning,physics,engineering,andfinanceduetotheirabilitytohandlelarge-scaledataefficiently.Forexample,infinancialanaly

Useanarray.arrayoveralistinPythonwhendealingwithhomogeneousdata,performance-criticalcode,orinterfacingwithCcode.1)HomogeneousData:Arrayssavememorywithtypedelements.2)Performance-CriticalCode:Arraysofferbetterperformancefornumericaloperations.3)Interf

No,notalllistoperationsaresupportedbyarrays,andviceversa.1)Arraysdonotsupportdynamicoperationslikeappendorinsertwithoutresizing,whichimpactsperformance.2)Listsdonotguaranteeconstanttimecomplexityfordirectaccesslikearraysdo.

ToaccesselementsinaPythonlist,useindexing,negativeindexing,slicing,oriteration.1)Indexingstartsat0.2)Negativeindexingaccessesfromtheend.3)Slicingextractsportions.4)Iterationusesforloopsorenumerate.AlwayschecklistlengthtoavoidIndexError.

ArraysinPython,especiallyviaNumPy,arecrucialinscientificcomputingfortheirefficiencyandversatility.1)Theyareusedfornumericaloperations,dataanalysis,andmachinelearning.2)NumPy'simplementationinCensuresfasteroperationsthanPythonlists.3)Arraysenablequick

You can manage different Python versions by using pyenv, venv and Anaconda. 1) Use pyenv to manage multiple Python versions: install pyenv, set global and local versions. 2) Use venv to create a virtual environment to isolate project dependencies. 3) Use Anaconda to manage Python versions in your data science project. 4) Keep the system Python for system-level tasks. Through these tools and strategies, you can effectively manage different versions of Python to ensure the smooth running of the project.

NumPyarrayshaveseveraladvantagesoverstandardPythonarrays:1)TheyaremuchfasterduetoC-basedimplementation,2)Theyaremorememory-efficient,especiallywithlargedatasets,and3)Theyofferoptimized,vectorizedfunctionsformathematicalandstatisticaloperations,making


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

MinGW - Minimalist GNU for Windows
This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

PhpStorm Mac version
The latest (2018.2.1) professional PHP integrated development tool

SublimeText3 Chinese version
Chinese version, very easy to use

Notepad++7.3.1
Easy-to-use and free code editor
