This is a full-stack cultivation world simulator game (xianxia RPG) with a Python backend (FastAPI + asyncio) and a Vue 3 + TypeScript + PixiJS frontend, supported by an optional Electron desktop shell for Epic Games Store distribution. The simulation engine runs a month-by-month tick system orchestrating ~29 phases (lifecycle, actions, social, war, world events, etc.) producing emergent narratives driven by LLM calls (OpenAI/Anthropic compatible) for character decisions, story generation, world lore rewriting, and roleplay interactions. The codebase is heavily data-driven with static game configurations (sects, techniques, items, regions) loaded from CSV files and multi-language localization via gettext PO files. It exposes a public REST API (query/command) and WebSocket for real-time state updates, supports save/load with JSON snapshots and SQLite event storage, and includes comprehensive test coverage (pytest, vitest, Playwright) and CI/CD workflows. While the architecture shows strong engineering patterns (effect system, action registry, single-choice decision framework, phased simulation pipeline), it carries risks from tight coupling of global singleton registries, LLM dependency, and use of `eval` in effect conditions.
Debug-gym is a framework for developing and evaluating AI agents that perform interactive debugging of software. It provides a Gymnasium-inspired environment where agents can use tools like a debugger (pdb), file viewer, editor, and shell to inspect and modify code in order to fix bugs. The framework supports multiple execution backends (local, Docker, Kubernetes) to ensure isolation and reproducibility, and integrates with various LLM providers through a unified interface. The system is designed around a loop of observation, action, and feedback: the agent observes the current state (e.g., code, test output), selects a tool to apply (e.g., set a breakpoint, edit a file), and receives the outcome from the environment. This enables the creation of agents that can learn to debug or be evaluated on debugging benchmarks such as SWE-Bench and Mini-Nightmare. The framework also includes analysis tools for visualizing agent trajectories and logging experiment results, supporting both development and research use cases. Key architectural features include a plugin-based tool system, abstract terminal and LLM interfaces, and a secure workspace for code manipulation. These components are designed to be modular and extensible, allowing researchers and developers to plug in new tools, environments, or language models with minimal changes to the core loop.
This repository is a fully functional, offline single-player space strategy game (OGame clone) built with Vue 3, TypeScript, Pinia, and shadcn-vue. It implements the complete OGame feature set: resource management, building, research, fleet combat, defense, diplomacy, NPC AI, achievements, campaigns, and a battle simulator. The architecture is a modern SPA with client-side persistence (localStorage encrypted via AES), optional WebDAV cloud sync, and multi-platform builds (web, desktop via Electron, Android via Capacitor, Docker). The game logic is organized into modular TypeScript files under `src/logic/`, with a centralized game loop in `App.vue` that processes resource production, construction queues, fleet missions, NPC behavior, and achievement checks every second. The UI uses a custom component library built on shadcn-vue and Reka UI, with full internationalization (8 languages). The repository also includes a Go-based static server for production deployment and a battle simulation Web Worker for offloading heavy computation. While the codebase is well-structured and demonstrates good use of modern frontend patterns, it is heavily coupled to game state and lacks automated tests, which limits reusability of most modules outside this project.