TTA.dev

Legacy TTA Game Project Archive

This directory contains materials from the original “Therapeutic Text Adventure” (TTA) game project that was developed in this repository before the pivot to a general AI development toolkit.

Historical Context

The TTA project (approximately early 2024 - September 2024) was an ambitious text-based adventure game that:

• Used AI agents for narrative generation and game management
• Leveraged Neo4j knowledge graphs for game state
• Implemented dynamic agent generation with LangChain/LangGraph
• Aimed to provide therapeutic experiences through interactive storytelling

What’s Archived Here

Game Code

• core/ - Main game engine and logic
  • main.py - Game entry point
  • dynamic_game.py - Game state management
  • langgraph_engine.py - Agent orchestration

Documentation

• PRD.md - Product Requirements Document for the TTA game
• PLANNING.md - Development planning and architecture decisions
• Roadmap.md - Project phases and timeline
• TASKS.md - Specific implementation tasks
• User_Guide.md - Guide for players
• Agentic_RAG.md - RAG architecture for the game
• Neo4j_Schema.md - Knowledge graph schema
• DataModel.md - Game data structures
• TestingStrategy.md - Testing strategy

Tests

• test_basic.py - Basic import tests
• test_dynamic_agents.py - Agent system tests
• test_dynamic_tools.py - Tool system tests
• test_langgraph_engine.py - Workflow engine tests
• test_memory.py - Memory system tests

Pivot to AI Development Toolkit

In September 2024, the repository was refocused to become TTA.dev - AI Development Toolkit, a collection of reusable AI development tools, workflows, and primitives for building AI-native applications.

The new direction emphasizes:

• Production-ready, reusable components
• Workflow primitives and patterns
• MCP (Model Context Protocol) integration
• Development best practices
• General AI application development (not game-specific)

Why Archive Instead of Delete?

These materials represent significant development work and contain valuable insights about:

• Agentic system design
• LangChain/LangGraph patterns
• Knowledge graph integration
• AI-driven content generation
• Dynamic agent orchestration

While no longer the primary focus, they may provide reference material for future AI development work.

Using These Materials

Feel free to reference these materials for:

• Learning about agentic AI systems
• Understanding LangChain/LangGraph implementations
• Knowledge graph schema design
• AI game development concepts

However, be aware that:

• Code may reference non-existent dependencies
• Documentation reflects the old project scope
• Some approaches may be outdated

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Archived: October 2024 Original development period: ~Early 2024 - September 2024