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PROJECT_STATE.md

Project: AI Algorithm Visualizer

Date: January 8, 2026

Current Status: Implementation Phase - Multi-Pattern Support Complete

Implemented Components:

  1. Project Planning

    • Created detailed implementation plan in PLAN.md

  2. Backend Structure

    • Initialized backend directory with proper subdirectories:
      • controllers/
      • services/
      • schemas/
      • middleware/
      • routes/
    • Created server.js with basic Express setup
    • Created algorithmRoutes.js for API endpoints
    • Created package.json with dependencies

  3. Frontend Structure

    • Initialized frontend directory with proper subdirectories:
      • components/
      • services/
      • utils/
    • Created package.json with React dependencies
    • Created Vite configuration with backend proxy
    • Created basic HTML template and React entry point

  4. LLM Integration

    • Created LLMAdapterInterface as abstract base class
    • Implemented comprehensive OllamaAdapter with extensive examples for multiple algorithm patterns (trees, stacks, queues, arrays, etc.)
    • Implemented GeminiAdapter placeholder for production use
    • Created LLMService that uses configured adapter (default: ollama)

  5. Data Validation

    • Created Zod schema (llmOutputSchema.js) for validating LLM output
    • Schema enforces algorithm patterns: Brute Force, Sliding Window, Two Pointers, Prefix Sum, Binary Search, Min/Max tracking, Frequency Map, Greedy

  6. Backend Services

    • Created UniversalNormalizer to convert LLM output to entity+action based frames
    • Created comprehensive Executors system with deterministic implementations for multiple algorithm patterns
    • Implemented pattern-specific executors for binary search, linear search, sliding window, stack operations, queue operations, and multiple sorting algorithms
    • Created algorithmController.js with validation and processing pipeline

  7. API Implementation

    • /api/classify endpoint that processes problem statements
    • Complete validation pipeline: LLM output → Schema validation → Universal normalization → Frame generation

  8. Frontend Components

    • Created comprehensive App.jsx with routing for landing page, visualizer, and about pages
    • Created LandingPage.jsx with hero section, features, live demo, and example problems
    • Created ProblemInput.jsx for user problem input with example suggestions
    • Created FrameVisualizer.jsx for displaying algorithm frames with playback controls
    • Created VisualCanvas.jsx for rendering multiple entity types (arrays, trees, stacks, queues, etc.)
    • Created specialized entity components: ArrayEntity, TreeEntity, StackEntity, QueueEntity, LinkedListEntity, DPTableEntity, MatrixEntity
    • Created InfoPanel.jsx for displaying frame information
    • Added comprehensive styling with Tailwind CSS and custom CSS

File Paths Added/Changed in This Session:

  • backend/src/services/ollamaAdapter.js - Extensive implementation with examples for multiple algorithm patterns
  • backend/src/services/universalNormalizer.js - Comprehensive normalizer for converting LLM output to entity+action frames
  • backend/src/services/executors.js - Deterministic executors for multiple algorithm patterns with fallback implementations, enhanced BST validation to fix multi-operation issues, fixed traversal consistency where results match actual tree structure, added path generation for search/insert/remove operations
  • frontend/src/components/landing/LandingPage.jsx - Complete landing page with multiple sections
  • frontend/src/components/entities/ArrayEntity.jsx, TreeEntity.jsx, StackEntity.jsx, QueueEntity.jsx, etc. - Specialized visualization components
  • frontend/src/components/VisualCanvas.jsx - Entity renderer for multiple data structures
  • frontend/src/pages/VisualizerPage.jsx - Main visualization page with comprehensive UI
  • frontend/src/components/ProblemInput.jsx - Enhanced input component with example functionality
  • frontend/src/components/entities/TreeEntity.jsx - Updated with animated path highlighting from root to target node for search/insert/remove operations, refined animation timing for better visual flow, slowed down animation speed to VisuAlgo-like pace
  • frontend/src/components/entities/TreeEntity.css - Updated with clean path/node highlighting animations, removed expanding/circle contrast effects

Pending TODOs:

  1. Add unit tests for backend services
  2. Implement additional visualization controls (speed adjustment, step-by-step highlighting)
  3. Add more comprehensive error handling for edge cases
  4. Extend to support additional algorithm patterns as needed
  5. Add export functionality for visualizations

Architectural Decisions:

  1. Adapter Pattern: Used for LLM integration to allow easy switching between local (Ollama) and cloud (Gemini) providers
  2. Schema Validation: Strict Zod validation enforces the exact JSON structure from LLMs
  3. Deterministic Processing: Backend processes LLM output deterministically through normalization and frame generation engines
  4. Separation of Concerns: Clear separation between LLM service, validation, normalization, and frame generation
  5. Environment-based Configuration: LLM provider can be switched via environment variables
  6. Entity-Action Architecture: Frames consist of entities and actions for flexible visualization
  7. Executor System: Deterministic fallback implementations ensure reliable visualizations even when LLM output is imperfect

Current Capabilities:

  • 14+ Algorithm Patterns: Sliding Window, Two Pointers, Binary Search, Stack, Queue, Hashmap, Tree BFS/DFS, Two Heaps, Subsets, Top K Elements, K-way Merge, Merge Intervals, Topological Sort, Cyclic Sort
  • Multiple Data Structures: Arrays, Trees (BST operations), Stacks, Queues, Linked Lists, DP Tables, Matrices
  • Interactive Visualization: Play/pause, next/previous, keyboard navigation (arrow keys, spacebar)
  • Educational Animations: Subtle, clean animations similar to VisuAlgo for better learning experience
  • BST Integrity: Enhanced BST validation ensures tree properties are maintained during multi-operation sequences
  • Traversal Consistency: Results of tree traversals now match the actual tree structure, preventing phantom nodes
  • Animated Path Highlighting: Smooth path animations from root to target node for search, insert, and remove operations
  • VisuAlgo-like Speed: Slower, educational-focused animation speed for better understanding
  • Path Generation: Automatic path calculation for tree operations when not provided by LLM
  • Comprehensive Examples: Built-in examples for each algorithm pattern in the Ollama adapter
  • Deterministic Fallbacks: Executor system provides reliable visualizations when LLM output is insufficient

Current Status:

  • LLM correctly identifies and generates visualizations for multiple algorithm patterns
  • Comprehensive visualization system for multiple data structures
  • Frontend with rich interactive controls and navigation
  • Deterministic fallback implementations for reliability
  • Complete end-to-end flow from problem input to visualization
  • Landing page with live demo and example problems