- Added new contracts for intent interpretation, including InterpreterOutput and ResolverMode.
- Implemented deterministic intent resolver with clarity checks for ambiguous references and empty input.
- Developed LLM intent resolver that communicates with an external model, handling JSON responses and fallback clarifications.
- Created an interpretTurn function to manage intent resolution based on the selected resolver mode.
- Introduced validation for interpreter output to ensure integrity before processing actions.
- Established a turn manager to orchestrate turn processing, including action validation and world state mutation.
- Added integration tests to verify the functionality of the new intent resolution system.
Co-authored-by: Copilot <copilot@github.com>
- Added a new SceneRulebook system to manage data-driven validation rules for actions.
- Introduced rule checks for actions like "take", "open", "move", "introduce", and "describe".
- Created a rulebook engine to evaluate conditions and enforce rules during action validation.
- Enhanced action handling with support for scene entry and character descriptions.
- Updated the architecture documentation to reflect the new rule-based validation approach.
- Added new endpoints and improved the persistence layer for rulebooks.
refactor: remove legacy types.ts file and update frontend to use new contracts
feat: add applyActions function to manage action application and world state mutation
chore: remove empty .gitkeep file from sqlite data directory
refactor: update frontend App component to align with new API contracts and improve UX
docs: revise project.md to reflect updated architecture and system requirements
docs: update thoughts.md with current status, architecture decisions, and remaining checks
- Add Fastify server in `app/src/index.ts` with health check and API routes for game state and turn processing.
- Create `latentEntities.ts` to handle personal item plausibility and promote beliefs to facts based on actor context.
- Introduce `llmAdapter.ts` for action extraction from prose input.
- Develop `truthEngine.ts` for pure validation logic, handling all verbs with explicit rejection reasons.
- Define new types in `types.ts` for facts, affordances, and latent entity requests/resolutions.
- Update `docker-compose.yml` for improved service structure and volume management.
- Create frontend structure with React, including Dockerfile, Vite configuration, and initial components for state inspection.
- Implement basic styles and HTML structure for the frontend application.
- Document current status and next steps in `thoughts.md`.
