From c6b8c4bbd8f93db304780ead967c9cb1ec077129 Mon Sep 17 00:00:00 2001 From: LanWeiFRJ <101687185+LanWeiFRJ@users.noreply.github.com> Date: Wed, 29 Oct 2025 13:58:40 +0800 Subject: [PATCH] readme --- README.md | 158 ++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 158 insertions(+) create mode 100644 README.md diff --git a/README.md b/README.md new file mode 100644 index 0000000..d9abfc7 --- /dev/null +++ b/README.md @@ -0,0 +1,158 @@ +# InfCode + +[![Python 3.12+](https://img.shields.io/badge/python-3.12+-blue.svg)](https://www.python.org/downloads/) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) + + +**InfCode** is an intelligent Code Agent System developed by [Tokfinity](https://www.tokfinity.com)'s Code Research team, which uses LLMs to automatically analyze and fix Code Repo issues. + +**Project Status:** InfCode has achieved **79.4%** solution rate on the SWE-Bench Verified split, demonstrating the **latest SOTA** performance. + + +## 🌟 System Architecture + +framework + + +### Core Modules + +The InfCode adopts a generate-select architectural pattern. Its core modules include the **Patch Generator** and the **Patch Selector**, which are responsible for generating candidate patches and selecting the optimal patch, respectively. + +- **Patch Generator**: Register multiple groups of generators, where each generator is configured with a separate container to generate and repair multiple candidate patches in parallel. Can interact with `File Editor`, `File Search`, `Bash Executor`, `Result Submitter` tools. The Patch Generator runs up to $5$ attempts and gathers all produced patches. +- **Patch Selector**: Select the best patch from all the candidate patches. Can interact with `File Editor`, `File Search`, `Bash Executor` tools. + + +### Other Modules + +In addition to the core modules, InfCode includes several other modules, such as the **Image Builder**, **Tool Executor**, and **LLM API Manager**, which handle image construction, tool execution, and API management, respectively. These modules complement the core modules and enhance the overall system functionality. + +- **Image Builder**: This component is responsible for generating dedicated container images for each example in the benchmark suite. The images are stored locally and reused across iterative runs to improve efficiency. +- **Tool Executor**: This module is responsible for receiving tool-level instructions, executing the specified commands within the containerized environment, collecting the execution outputs, and transmitting the results back to the tool layer. +- **LLM API Manager**: Unified LLM API manager. It invokes the LLM API through the completion endpoint to retrieve model-generated responses. It supports integration with OpenAI, OpenRouter, and DeepSeek clients, as well as self-hosted (privately deployed) LLM instances. + + + +## ✨ Tools Support + +To enable interaction with code repositories, the InfCode is equipped with the following tools: + +- **File Editor**: + - File Preview (view): Retrieve the content of a specified line range from a file within the container. + - File Creation (create): Create a new file within the container and populate it with the specified content. + - File Modification (str_replace): Modify specific portions of a given file within the container by replacing designated content. + - File Insertion (insert): Insert specified content into a designated position within a target file in the container. + +- **File Searcher**: + - The LLM outputs a search pattern, which the tool uses to perform file searches within the container. + - The tool then parses and returns the results from the container. + + > This module is implemented based on `ripgrep`, a high-performance file search utility that outperforms traditional `grep` in speed and supports fuzzy matching for enhanced search flexibility. + + +- **Bash Executor**: + - Execute Bash commands generated by the LLM within the container environment. + - Parse and return the execution results from the container. + + +- **Result Submitter**: + - After the LLM completes patch generation and testing, it triggers this tool and provides patch generation details. + - The tool executes `git diff` within the container to obtain and return the patch content. + + + +## 📖 Quick Start + +### 1. Environment Setup + +- Create a `.env` file in the project root directory and configure the necessary environment variables: + +```bash +# LLM API configuration +OPENROUTER_API_KEY=your_openrouter_api_key +``` + + +- Install the pip dependencies, Python 3.12 is recommended. +```bash +pip install -r requirements.txt +``` + + +### 2. Run the System + +#### Batch Execution + +```bash +python _batch_run.py -c config/batch.yaml --name first -i config/list_all.txt -p 2 --clean +``` + +Explanation: + +- `-c` specifies the batch configuration file (currently minimal) +- `-name` assigns a name to this batch run +- `-i` specifies the issue list file +- `-p` sets concurrency (default 20) +- `-clean` clears the output directory before running (useful when reusing the same name) +- `-o` sets the output directory (default: ./batch_out/) +- `-h` prints help + + +#### Evaluation + +```bash +./eval.sh +``` + +Explanation: + +- `run_id` — required parameter identifying this evaluation run +- The script automatically reads dataset and prediction paths from `config/config.yaml`. +Since batch_run results are redirected, you may need to manually copy the preds.json file to the path specified in the config. +- Uses the official SWE-bench evaluation tool to verify generated patches +- Supports multi-process parallel evaluation (default: 20 workers) +- Results will be saved in the specified directory, including pass rates, failure reasons, and detailed logs + + +### 3. Configuration Files + +The main configurations are in `config/config.yaml`: +- `providers`: LLM provider settings +- `runner`: runner settings (concurrency, number of iterations, etc.) +- `builder`: Docker image build settings +- `log`: logging settings + + +### Notes + +- Ensure Docker is installed and running correctly. +- Check logs for detailed execution steps. +- Supports multiple LLM providers, tool formats are auto-selected based on configuration. + + +## Contact + +research@tokfinity.com + + + +## Core Team + +- [Pete Wong](https://petewongggg.github.io/) + +- [Shihao Zheng](https://github.com/kirito41dd) + +- [Hengzhi Zhang](https://henryzhang11.github.io) + +- [Kefan Li](https://lbaf23.github.io) + +- [Qingao Dong](https://qadong.github.io) + + + +## 📄 License + +This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. + +## 🙏 Acknowledgments +We thank Anthropic for building the [anthropic-quickstart](https://github.com/anthropics/claude-quickstarts) project and bytedance for building the [trae-agent](https://github.com/bytedance/trae-agent) project that served as valuable references for the tool building. + +