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AlphaEvolveWriting

⭐ 114 stars English by tamassimonds

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AlphaEvolve Writing

AlphaEvolve Writing Process

You can find the full explanation here

You can find a sample story submitted to a writing competition here

A modern, evolutionary writing system that uses AI models to generate, evaluate, and evolve creative stories or general writing pieces through iterative competitions. Built with clean, modular Python architecture following modern design principles.

✨ Features

🚀 Quick Start

Installation

# Clone the repository
git clone https://github.com/your-org/alphaevolve-writing
cd alphaevolve-writing

Install with uv (recommended)

uv sync

Or install with pip

pip install -e .

Configure your API keys (see Configuration section below)

Run Evolution

# Run 5 evolution iterations
python evolve.py 5

Fresh start with 3 iterations

python evolve.py 3 --fresh

Use general writing mode

python evolve.py 5 --general

Show help

python evolve.py --help

🏗️ Architecture

The system follows modern Python design principles with clean separation of concerns:

├── src/
│   ├── core/           # Pipeline orchestration
│   │   └── pipeline.py # Main EvolutionPipeline class
│   ├── generators/     # Story generation logic
│   │   ├── story_generator.py      # Initial & next batch generators
│   │   ├── generate_response.py    # Creative writing generation
│   │   ├── generate_response_general.py # General writing generation
│   │   └── judge_response.py       # AI judging system
│   ├── rankers/        # ELO ranking system
│   │   ├── elo_rank.py            # Core ELO algorithm
│   │   └── tournament_runner.py    # Tournament management
│   └── utils/          # Utility functions
│       └── inference.py           # Multi-provider LLM interface
├── evolve.py           # Clean CLI entry point
├── pyproject.toml      # Modern Python packaging
├── config.json         # Configuration
└── web_interface/      # Web UI for validation

Key Components

📖 How It Works

The system follows a three-stage evolution cycle:

1. Generate Initial Batch

2. Run ELO Tournament

3. Generate Next Batch

This iterative process evolves increasingly better writing over time.

⚙️ Configuration

Basic Setup

Edit these key files:

API Keys Setup

The system supports multiple AI providers configured through config.json. The configuration maps models to providers and specifies which environment variables contain the API keys:

{
  "llm_providers": {
    "openai": {
      "type": "openai",
      "base_url": "https://api.openai.com/v1",
      "api_key_env": "OPENAI_API_KEY"
    },
    "anthropic": {
      "type": "anthropic", 
      "api_key_env": "ANTHROPIC_API_KEY"
    },
    "deepinfra": {
      "type": "openai_compatible",
      "base_url": "https://api.deepinfra.com/v1/openai",
      "api_key_env": "DEEPINFRA_API_KEY"
    },
    "deepseek": {
      "type": "openai_compatible",
      "base_url": "https://api.deepseek.com/v1",
      "api_key_env": "DEEPSEEK_API_KEY"
    },
    "gemini": {
      "type": "openai_compatible",
      "api_key_env": "GEMINI_API_KEY",
      "base_url": "https://generativelanguage.googleapis.com/v1beta/openai/"
    }
  },
  "model_provider_mapping": {
    "gpt-4": "openai",
    "gpt-3.5-turbo": "openai", 
    "claude-3-sonnet-20240229": "anthropic",
    "meta-llama/Meta-Llama-3-70B-Instruct": "deepinfra",
    "deepseek-chat": "deepseek",
    "gemini-2.5-flash": "gemini"
  }
}
Then set your API keys as environment variables:

export OPENAI_API_KEY="your-openai-key"        # For GPT models
export ANTHROPIC_API_KEY="your-anthropic-key"  # For Claude models  
export DEEPINFRA_API_KEY="your-deepinfra-key"  # For Llama models
export DEEPSEEK_API_KEY="your-deepseek-key"    # For DeepSeek models
export GEMINI_API_KEY="your-gemini-key"          # For Gemini models
You only need to set keys for the providers you plan to use. The system automatically routes model requests to the correct provider based on the configuration.

Configuration Options

The config.json file controls all system behavior:

{
  "batch_generation": {
    "num_stories": 10,
    "model": "gpt-4",
    "initial_elo": 1500
  },
  "elo_ranking": {
    "tournament_rounds": 50,
    "judge_model": "claude-3-sonnet-20240229",
    "k_factor": 32
  },
  "next_batch_generation": {
    "top_stories_to_select": 3,
    "variants_per_story": 2,
    "include_original_stories": true
  },
  "evolution_pipeline": {
    "max_iterations": 5,
    "auto_continue_from_existing": true
  }
}

🎭 Writing Modes

Creative Writing Mode (Default)

General Writing Mode (--general)

🔧 Advanced Configuration

Customizing Generation Strategies

For advanced users, you can customize the generation prompts, author styles, and mission sets by editing the files in the src/generators/ directory:

#### Creative Writing Customization (src/generators/generate_response.py)

Mission Sets - Define creative approaches and goals:

mission_sets = {
    "emotional_depth": [
        "Focus on the psychological depth of characters",
        "Explore complex emotional landscapes", 
        "Create moments of genuine human connection"
    ],
    "narrative_craft": [
        "Experiment with unique narrative structures",
        "Use vivid, sensory descriptions",
        "Create compelling story arcs"
    ],
    "dialogue_mastery": [
        "Write authentic, character-specific dialogue",
        "Use subtext and implied meaning",
        "Balance dialogue with action and description"
    ]
}
Author Styles - Emulate different writing approaches:

author_styles = [
    "Write with the psychological insight of Virginia Woolf",
    "Adopt the sparse, powerful prose of Ernest Hemingway", 
    "Use the magical realism style of Gabriel García Márquez",
    "Employ the detailed world-building of Tolkien"
]
#### General Writing Customization (src/generators/generate_response_general.py)

Academic Focus Areas - Target specific writing domains:

academic_focuses = [
    "Rigorous analytical argument development",
    "Clear thesis statement and supporting evidence",
    "Proper academic citation and source integration",
    "Logical flow and coherent structure"
]
Writing Approaches - Define analytical strategies:

writing_approaches = [
    "Comparative analysis with multiple perspectives",
    "Problem-solution framework with evidence",
    "Cause-and-effect reasoning with examples",
    "Critical evaluation with balanced arguments"
]

Customizing Judge Criteria (src/generators/judge_response.py)

You can modify the judging criteria and evaluation prompts to focus on specific aspects of writing quality:

# Edit the judge_responses function to customize evaluation criteria
evaluation_criteria = [
    "Technical writing proficiency",
    "Creative originality and innovation", 
    "Emotional impact and reader engagement",
    "Structural coherence and flow",
    "Character development and authenticity"
]

Tips for Advanced Configuration

This modular approach allows you to fine-tune the evolution process for your specific writing goals and domains.

🌐 Web Interface

Validate your evolution results with the built-in web interface:

cd web_interface
pip install -r requirements.txt
python app.py
Open http://localhost:5000 to access:

```

--- Tranlated By Open Ai Tx | Last indexed: 2025-07-18 ---