AI_Diplomacy/README.md

AI Diplomacy

AI-Powered Diplomacy with LLMs

This repository extends the original Diplomacy project to create a completely LLM-powered version of the classic board game Diplomacy. Each power is controlled by an LLM that can negotiate, form alliances, and plan strategies across multiple game phases.

Features

• Strategic LLM Agents: Each country is controlled by an LLM with specialized prompting tailored to their unique geopolitical position
• Multi-Turn Negotiations: Powers engage in diplomatic exchanges through global and private messages
• Automatic Order Generation: Each power autonomously determines orders based on game state and diplomatic history
• Context Management: Intelligent summarization of game state and message history to optimize context windows
• Enhanced Logging: Structured, detailed logging for analysis of AI reasoning and decision-making
• Multi-Model Support: Compatible with OpenAI, Anthropic Claude, Gemini, and DeepSeek models
• Power-Specific Strategy: Country-specific system prompts that provide strategic guidance based on historical Diplomacy strategy

Getting Started

# Clone the repository
git clone https://github.com/username/AI_Diplomacy.git
cd AI_Diplomacy

# Install dependencies 
pip install -r requirements.txt

# Run a game
python lm_game.py --max_year 1910 --summary_model "gpt-4o-mini" --num_negotiation_rounds 3

Command Line Options

The main game script supports various configuration options:

python lm_game.py [options]

Options:
  --max_year INTEGER        Maximum year to simulate (default: 1910)
  --summary_model STRING    Model to use for phase summarization (default: "gpt-4o-mini")
  --num_negotiation_rounds  Number of message rounds per phase (default: 3)
  --models STRING           Comma-separated list of models to use for each power
  --log_full_prompts        Log complete prompts sent to models
  --log_full_responses      Log complete responses from models
  --verbose                 Enable verbose logging including connection details
  --log_level STRING        Set logging level (DEBUG, INFO, WARNING, ERROR)

How It Works

1. Game Initialization

   • Creates a standard Diplomacy game and assigns an LLM to each power
   • Initializes logging and context management systems

2. Diplomacy Phases

   • For each movement phase, powers engage in negotiation rounds
   • Each power analyzes game state, diplomatic history, and strategic position
   • Powers autonomously generate orders through concurrent execution

3. Context Management

   • Game history and diplomatic exchanges are intelligently summarized
   • Recursive summarization optimizes context windows while preserving crucial information
   • System provides each power with relevant, concise context to make decisions

4. Order Processing

   • Orders from all powers are collected and processed by the game engine
   • Phase summaries are generated to capture key events
   • Results are saved and the game advances to the next phase

Project Structure

• ai_diplomacy/: Core extension code

  • clients.py: Model client implementations for different LLM providers
  • game_history.py: Tracks and manages game history for LLM context
  • long_story_short.py: Context optimization and summarization
  • negotiations.py: Handles diplomatic exchanges between powers
  • prompts/: Templates for system instructions, orders, and negotiations
  • utils.py: Helper functions for game state analysis and formatting

• lm_game.py: Main game runner script

• diplomacy/: Original game engine (with minor extensions)

Recent Improvements

• Enhanced Structured Logging: Added structured logging with context tags for better debugging and analysis
• Optimized Context Management: Rewrote the recursive summarization system to handle model context more efficiently
• Improved Power-Specific Prompts: Updated all country-specific system prompts with more strategic guidance
• Better Convoy and Threat Analysis: Enhanced convoy path detection and threat assessment
• Command Line Options: Added configuration options for logging verbosity and model selection

---

Documentation

The complete documentation is available at diplomacy.readthedocs.io.

Getting Started

Installation

The latest version of the package can be installed with:

pip install diplomacy

The package is compatible with Python 3.5, 3.6, and 3.7.

Running a game

The following script plays a game locally by submitting random valid orders until the game is completed.

import random
from diplomacy import Game
from diplomacy.utils.export import to_saved_game_format

# Creating a game
# Alternatively, a map_name can be specified as an argument. e.g. Game(map_name='pure')
game = Game()
while not game.is_game_done:

    # Getting the list of possible orders for all locations
    possible_orders = game.get_all_possible_orders()

    # For each power, randomly sampling a valid order
    for power_name, power in game.powers.items():
        power_orders = [random.choice(possible_orders[loc]) for loc in game.get_orderable_locations(power_name)
                        if possible_orders[loc]]
        game.set_orders(power_name, power_orders)

    # Messages can be sent locally with game.add_message
    # e.g. game.add_message(Message(sender='FRANCE',
    #                               recipient='ENGLAND',
    #                               message='This is a message',
    #                               phase=self.get_current_phase(),
    #                               time_sent=int(time.time())))

    # Processing the game to move to the next phase
    game.process()

# Exporting the game to disk to visualize (game is appended to file)
# Alternatively, we can do >> file.write(json.dumps(to_saved_game_format(game)))
to_saved_game_format(game, output_path='game.json')

Web interface

It is also possible to install a web interface in React to play against bots and/or other humans and to visualize games.

The web interface can be installed with:

# Install NVM
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.34.0/install.sh | bash

# Clone repo
git clone https://github.com/diplomacy/diplomacy.git

# Install package locally
# You may want to install it in a conda or virtualenv environment
cd diplomacy/
pip install -r requirements_dev.txt

# Build node modules
cd diplomacy/web
npm install .
npm install . --only=dev

# In a terminal window or tab - Launch React server
npm start

# In another terminal window or tab - Launch diplomacy server
python -m diplomacy.server.run

The web interface will be accessible at http://localhost:3000.

To login, users can use admin/password or username/password. Additional users can be created by logging in with a username that does not exist in the database.

Visualizing a game

It is possible to visualize a game by using the "Load a game from disk" menu on the top-right corner of the web interface.

Network Game

It is possible to join a game remotely over a network using websockets. The script below plays a game over a network.

Note. The server must be started with python -m diplomacy.server.run for the script to work.

import asyncio
import random
from diplomacy.client.connection import connect
from diplomacy.utils import exceptions

POWERS = ['AUSTRIA', 'ENGLAND', 'FRANCE', 'GERMANY', 'ITALY', 'RUSSIA', 'TURKEY']

async def create_game(game_id, hostname='localhost', port=8432):
    """ Creates a game on the server """
    connection = await connect(hostname, port)
    channel = await connection.authenticate('random_user', 'password')
    await channel.create_game(game_id=game_id, rules={'REAL_TIME', 'NO_DEADLINE', 'POWER_CHOICE'})

async def play(game_id, power_name, hostname='localhost', port=8432):
    """ Play as the specified power """
    connection = await connect(hostname, port)
    channel = await connection.authenticate('user_' + power_name, 'password')

    # Waiting for the game, then joining it
    while not (await channel.list_games(game_id=game_id)):
        await asyncio.sleep(1.)
    game = await channel.join_game(game_id=game_id, power_name=power_name)

    # Playing game
    while not game.is_game_done:
        current_phase = game.get_current_phase()

        # Submitting orders
        if game.get_orderable_locations(power_name):
            possible_orders = game.get_all_possible_orders()
            orders = [random.choice(possible_orders[loc]) for loc in game.get_orderable_locations(power_name)
                      if possible_orders[loc]]
            print('[%s/%s] - Submitted: %s' % (power_name, game.get_current_phase(), orders))
            await game.set_orders(power_name=power_name, orders=orders, wait=False)

        # Messages can be sent with game.send_message
        # await game.send_game_message(message=game.new_power_message('FRANCE', 'This is the message'))

        # Waiting for game to be processed
        while current_phase == game.get_current_phase():
            await asyncio.sleep(0.1)

    # A local copy of the game can be saved with to_saved_game_format
    # To download a copy of the game with messages from all powers, you need to export the game as an admin
    # by logging in as 'admin' / 'password'

async def launch(game_id):
    """ Creates and plays a network game """
    await create_game(game_id)
    await asyncio.gather(*[play(game_id, power_name) for power_name in POWERS])

if __name__ == '__main__':
    asyncio.run(launch(game_id=str(random.randint(1, 1000))))

## License

This project is licensed under the APGLv3 License - see the [LICENSE](LICENSE) file for details