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chatarena

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Basic Information

ChatArena is a Python library and research framework for building and running multi-agent language game environments that study autonomous large language model (LLM) agents and their social interactions. The project provides abstractions based on Markov Decision Processes to define Arenas, Environments, Players and Language Backends, and includes example environments such as conversation-based games, a social-deduction Chameleon game, and PettingZoo-based chess and tic-tac-toe ports. It offers both a Web UI and a CLI for interactive play, a Python API to load arenas from config files and run interaction loops, and optional integrations with LLM providers through backends. The README notes that as of Aug 11, 2025 the project has been deprecated and will not receive further updates due to limited community uptake.

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App URL
https://github.com/Farama-Foundation/chatarena
Github Repository
https://github.com/Farama-Foundation/chatarena/blob/main/README.md

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App Details

Features
The repository supplies a flexible Arena abstraction that encapsulates an environment and a collection of players and drives the main game loop with HCI utilities like web UI, CLI, configuration loading and data storage. Environments implement game state, transition logic, rendering of natural language observations and terminal/reward logic. Language backends provide text-in/text-out model interfaces and optional integrations with providers such as OpenAI and other backends listed as optional dependencies. Developers can extend base classes to create custom environments, add new players or backends, and reuse provided examples and tutorials. The package supports pip installation and extra dependency groups for backends, environments and full functionality, and includes demo files and sample JSON configs for quick starts.
Use Cases
ChatArena helps researchers and developers prototype, benchmark and study multi-agent interactions driven by LLMs by offering ready-made environments, a clear abstraction layer and tools for customization. It lowers engineering effort by providing a main loop implementation, HCI interfaces, configuration-driven arena loading and example games to test emergent behaviors, cooperation, competition and moderation dynamics. The modular design makes it straightforward to swap or extend language backends, implement custom environment rules or run interactive CLI or Web UI demos. Provided tutorials and example configs enable reproducible experiments and serve as templates for porting external environments. Note that the project is deprecated and will not receive new updates, so users should consider stability and community support when planning adoption.

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