Coding Agent

Baseline wrapping Princeton's mini-swe-agent v2.2.8 with Claude Sonnet 4.6 via LiteLLM.

A baseline purple agent is a simple, general-purpose coding agent with minimal scaffolding and no specialized optimizations. It operates using a standard loop—reading the codebase, proposing edits, and attempting to pass tests—without advanced planning, memory, or tool-use strategies. It serves as a reference point for evaluation: competent enough to attempt real tasks, but limited in handling long-horizon, multi-file, or highly contextual problems.

The Purple Coding Agent is a high-performance, autonomous software engineering agent optimized for repository-level reasoning and complex bug resolution in competitive environments like SWE-Bench Pro and AIMO2026. Operating on a stateful Phase 2 architecture, the agent moves beyond static code analysis by utilizing a live, execution-grounded environment. It autonomously explores codebases, reproduces issues within isolated Docker containers, and verifies its own repairs through a mechanical test gate to ensure production-grade reliability. Key Capabilities Stateful Bash REPL: Maintains a persistent, 50-turn interactive session that allows the agent to explore, edit, and verify code iteratively within a single unified context. Mechanical Ground Truth: Utilizes a Docker-out-of-Docker (DooD) bridge to spawn sibling containers, allowing it to run test suites natively and generate its own diagnostic logs. Inference-Time Scaling (GRPO): Employs group sampling strategies to generate and evaluate multiple diagnostic hypotheses simultaneously, prioritizing leads based on real-world execution feedback. Graph-Based RAG: Leverages Tree-Sitter for AST-based repository mapping, providing the agent with a structural "skeleton" of the codebase to prevent context wandering in large repositories. Relative Reward Verification: Implements a smarter QA gate that compares post-fix execution results against a baseline state to prevent regressions and ensure the core issue is resolved. Automated Tooling: Seamlessly integrates specialized models (e.g., DeepSeek-v4-flash) with local bash utilities to perform batched file reads and robust Python-based edits.

A coding agent for SWE-bench Pro that fixes real GitHub issues using mini-swe-agent in Docker sibling containers. Supports multiple LLMs via litellm.