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Agentless
Overview :
Agentless is an agentless method for automatically resolving software development issues. It addresses each problem through three stages: localization, repair, and patch validation. Agentless utilizes a hierarchical process to locate failures down to specific files, related classes or functions, and fine-grained edit locations. It then samples multiple candidate patches based on these locations and selects regression tests to run, generating additional reproduction tests to replicate the original error. The results of these tests are used to re-rank all remaining patches to select a submission. Agentless is currently the top-performing open-source method on SWE-bench lite, with 82 fixes and a resolution rate of 27.3%, averaging a cost of $0.34 per problem.
Target Users :
The target audience includes software developers, programming enthusiasts, and teams requiring automated solutions for software issues. Agentless reduces the workload of manual debugging and fixing software problems through automation, enhancing development efficiency and lowering costs, especially for teams needing rapid iteration and maintenance of large codebases.
Use Cases
Example 1: On SWE-bench lite, Agentless achieved 82 fixes with a resolution rate of 27.3%.
Example 2: After integration with Claude 3.5 Sonnet, Agentless achieved resolution rates of 40.7% and 50.8% on SWE-bench lite and verified, respectively.
Example 3: The release of Agentless version 1.5 introduced enhanced capabilities for the automatic resolution of software issues.
Features
? Localization: Agentless uses a hierarchical approach to pinpoint failures in specific files, classes, or functions, along with fine-grained edit locations.
? Repair: Agentless samples multiple candidate patches based on edit locations, presenting them in a simple diff format.
? Patch Validation: Agentless selects regression tests and generates reproduction tests to replicate the original error, re-ranking all patches using test results to choose the best patch for submission.
? Integration with Claude 3.5 Sonnet: Agentless integrates with Claude 3.5 Sonnet to enhance resolution rates.
? Multi-file editing support: Agentless supports editing multiple files, enhancing its repair capabilities.
? Pre-commit hooks: Agentless supports pre-commit hooks to standardize code style.
? Simple environment setup: Easily create environments and install required dependencies through straightforward command-line operations.
How to Use
1. Clone the Agentless repository to your local machine: Run `git clone https://github.com/OpenAutoCoder/Agentless.git`.
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2. Navigate to the Agentless directory: Run `cd Agentless`.
3. Create and activate a Python virtual environment: Execute `conda create -n agentless python=3.11` and `conda activate agentless`.
4. Install dependencies: Run `pip install -r requirements.txt` to install the necessary dependencies.
5. Configure environment variables: Execute `export PYTHONPATH=$PYTHONPATH:$(pwd)`.
6. Install pre-commit hooks (if contributing code): Run `pre-commit install`.
7. Export the OpenAI API key: Set the environment variable `export OPENAI_API_KEY={key_here}`.
8. Run Agentless: Execute the appropriate command for the specific issue.
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