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AutoMetabuilder/ROADMAP.md
johndoe6345789 b3bd57964f Introduce AutoMetabuilder core components and workflow packages: 
- Implement core components: CLI argument parsing, environment loading, GitHub service creation, and logging configuration.
- Add support for OpenAI client setup and model resolution.
- Develop SDLC context loader from GitHub and repository files.
- Implement workflow context and engine builders.
- Introduce major workflow packages: `game_tick_loop` and `contextual_iterative_loop`.
- Update localization files with new package descriptions and labels.
- Streamline web navigation by loading items from a dedicated JSON file.
2026-01-10 01:21:19 +00:00

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Roadmap

Phase 1: Foundation

  • Basic GitHub Integration (fetching issues/PRs)
  • Local YAML prompt loading
  • Tool-based SDLC operations (branch/PR creation)
  • Multi-language support for messages

Phase 2: Enhanced Context & Reasoning

  • Roadmap Awareness: Bot should explicitly read and update ROADMAP.md.
  • Repository Indexing: Implement a way to index the codebase for better context.
  • Declarative Task Processing: Move more logic into JSON/YAML specifications.
  • Feedback Loop: Support for the AI to read comments on PRs it created.

Phase 3: Advanced Automation (MVP)

  • Automated Testing: Integration with test runners to verify changes before PR.
  • Linting Integration: Automatically run and fix linting issues.
  • Multi-Model Support: Easily switch between different LLM providers.
  • CI/CD Integration: Github Actions to run AutoMetabuilder on schedule or trigger.

Phase 4: Optimization & Scalability

  • Dockerization: Provide a Dockerfile and docker-compose for easy environment setup. Added run_docker_task tool.
  • Extended Toolset: Add tools for dependency management (poetry) and file manipulation (read/write/edit).
  • Self-Improvement: Allow the bot to suggest and apply changes to its own prompt.yml or tools.json.
  • Robust Error Handling: Implement exponential backoff for API calls and better error recovery.
  • Monitoring & Logging: Structured logging and status reporting for long-running tasks.

Phase 5: Ecosystem & User Experience

  • Web UI: A simple dashboard to monitor tasks and approve tool executions. Enhanced with settings and translation management.
  • Plugin System: Allow users to add custom tools via a plugin directory.
  • Slack/Discord Integration: Command and notify the bot from chat platforms.

Phase 6: Advanced Web UI & Remote Control

  • Remote Command Execution: Trigger bot runs from the Web UI.
  • User Authentication: Secure the Web UI with login.
  • Visual Task Progress: Real-time progress bars for long-running tasks.

Phase 7: Workflow UX & Component Library

  • Node-Based Workflow Engine: Replace task steps with micro-plugin nodes (inputs/outputs, loops).
  • Workflow Templates: Package reusable workflow presets (blank, single pass, iterative loop, plan/execute/summarize).
  • Workflow Template Picker: AJAX-loaded catalog with localized labels/descriptions.
  • Atomic Jinja Components: Split dashboard/prompt/settings/translations/sidebar into single-macro files.
  • AJAX Navigation Data: Render sidebar links from API payload with a client-side fallback.
  • n8n-Style Visual Workflow Canvas (Breakdown):
  • Canvas Layout Engine: DAG layout, node positioning, zoom/pan, and fit-to-view.
  • Node Palette + Search: Categorized plugin library with search and click-to-add.
  • Palette Tags + Drag-to-Canvas: Add tags, drag handles, and drag/drop placement.
  • Atomic Node Cards: Compact node tiles with status badge, type icon, and inline rename.
  • Ports + Connectors: Visual input/output ports with link creation + validation.
  • Edge Routing: Orthogonal edge routing with arrowheads, hover/selection state.
  • Mini Map: Overview map for large workflows with viewport control.
  • Selection + Multi-Edit: Multi-select nodes, bulk delete, and bulk edit fields.
  • Inspector Panel: Right-side inspector to edit node inputs/outputs/conditions.
  • Inline Validation: Missing input warnings, type mismatch hints, and disabled run cues.
  • Execution Preview: Simulate data flow highlights and show store bindings.
  • Auto-Save Drafts: Local draft save/restore with change markers.
  • Template Import/Export: Export current workflow and import to apply or merge.
  • Keyboard Shortcuts: Add node, delete, duplicate, undo/redo, and search.
  • Undo/Redo Stack: Reversible edits for canvas and inspector changes.
  • Context Menu: Right-click actions for node, edge, and canvas.
  • Performance Tuning: Virtualized node rendering for large graphs.

Phase 8: Modern Frontend Platform

  • Flask + Next.js split: Replace the Jinja-based FastAPI UI with a Flask REST backend and Next.js frontend consuming metadata, translations, workflows, logs, and nav via AJAX.
  • Atomic Next sections: Compose dashboard, workflow builder, prompt editor, settings, and translation editor into dedicated components powered by localized strings.
  • Workflow templates & navigation JSON: Serve workflow packages, nav items, and translation mappings from metadata-backed JSON endpoints.
  • Document build constraints: Record that next build --webpack fails in this sandbox because bundlers attempt to bind new ports, and continue iterating locally.
  • Material UI + webhooks: Drive the dashboard with Material UI surfaces and a lightweight webhook emitter/listener so downstream components can react to run events without prop drilling.
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