PlanForge AI - Intelligent Project Manager

A modern, full-stack software project management studio with an integrated NVIDIA AI Agent that automatically analyzes specifications, generates software architecture execution plans, enforces sequential task completion dependencies, and adapts based on user feedback.

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Key Features

1. Clean, Minimal & Modern UI:
   • Designed with an ultra-clean white canvas, subtle borders, single indigo accent (#4f46e5), and Google Fonts Inter.
   • Powered by Lucide Icons.
2. AI Project Type & Archetype Detection:
   • Automatically classifies project type (Mobile App, Full-Stack Web, AI/ML System, API Backend, DevOps Infrastructure, etc.) from project name and description.
   • Allows inline manual editing at any time.
3. Split-View Planning Page:
   • LEFT: Markdown/Text execution plan editor with character counters, unsaved state tracking, and View/Edit mode toggling.
   • RIGHT: Interactive NVIDIA AI Agent chat with one-click "Generate Plan", "Ask Questions", and Auto-Sync to Editor.
4. Sequential Task Execution with Dependency Enforcement:
   • Strictly ordered tasks ($1^{\text{st}}, 2^{\text{nd}}, 3^{\text{rd}}\dots$).
   • Prerequisite validation: Tasks are locked if prior dependencies are incomplete.
   • Reorder tasks with Up / Down buttons, recalculating dependencies and order numbers.
   • Manual task creation and deletion.
5. PDF Specification Upload:
   • Drag-and-drop PRDs, technical specs, or architecture documents (.pdf).
   • Automatically extracts text using pypdf and merges it into the AI agent prompt context.
6. AI Persistent Learning & Feedback Loop:
   • Users can rate or provide feedback on AI responses, which are stored in user_feedback to adapt future generations.
7. In-App Notification Center:
   • Real-time activity alerts (plan synced, task completed, PDF parsed, reminders) with unread count badges and popover history.
8. Robust Multi-Database Engine:
   • Full MySQL compatibility with schema.sql (configured via phpMyAdmin or local MySQL server).
   • Zero-configuration automatic SQLite fallback (ai_project_manager.db) if MySQL is unavailable.

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Directory Structure

ai_project_manager/
├── backend/
│   ├── .env                  # Local environment variables
│   ├── .env.example          # Template environment file
│   ├── requirements.txt      # Python dependencies
│   ├── schema.sql            # MySQL schema for phpMyAdmin
│   ├── database.py           # DB engine with MySQL + SQLite fallback
│   ├── models.py             # SQLAlchemy models (Project, Task, UserFeedback, Notification)
│   ├── schemas.py            # Pydantic request/response schemas
│   ├── ai_agent.py           # NVIDIAAgent with exact prompts & fallback engine
│   ├── main.py               # REST API endpoints & dependency enforcement
│   └── test_api.py           # Automated test suite
├── frontend/
│   ├── index.html            # App entry point with Inter font
│   ├── package.json          # Node dependencies
│   ├── vite.config.ts        # Vite build configuration
│   └── src/
│       ├── types.ts          # Project, Task, AIResponse, Notification, Feedback interfaces
│       ├── api.ts            # Typed HTTP client
│       ├── context/
│       │   └── ProjectContext.tsx # Central reactive state & notifications
│       ├── components/
│       │   ├── Sidebar.tsx        # Project navigation & active status indicator
│       │   ├── Navbar.tsx         # Archetype badge & notification bell
│       │   ├── AIAgent.tsx        # Reusable AI Agent Chat (bubbles, auto-sync, feedback)
│       │   ├── PDFUpload.tsx      # PDF specification uploader
│       │   └── NotificationCenter.tsx # Notification popover drawer
│       ├── pages/
│       │   ├── ProjectCreatePage.tsx  # Name, description, auto type detection
│       │   ├── PlanningPage.tsx       # Split-view architecture editor & chat
│       │   └── TaskAssignmentPage.tsx # Sequential tasks & dependency enforcement
│       ├── index.css         # Minimal styling tokens
│       ├── App.tsx           # Top-level application layout & toast alerts
│       └── main.tsx
└── README.md

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Getting Started

1. Backend Setup

1. Open a terminal in backend/:

   cd backend

2. Install Python dependencies:

   python -m pip install -r requirements.txt

3. Configure .env:

   DB_HOST=localhost
   DB_PORT=3306
   DB_NAME=ai_project_manager
   DB_USER=root
   DB_PASSWORD=
   NVIDIA_API_KEY=your_nvidia_api_key_here

   (Note: If MySQL is not running, the backend will automatically use a local SQLite file ai_project_manager.db without crashing).

4. Run automated backend tests:

   python -m pytest -v test_api.py

5. Start the FastAPI server:

   python -m uvicorn main:app --reload --port 8000

   API will be live at http://127.0.0.1:8000. Interactive Swagger docs at http://127.0.0.1:8000/docs.

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2. Frontend Setup

1. Open a terminal in frontend/:

   cd frontend

2. Install dependencies:

   npm install

3. Start the Vite development server:

   npm run dev

4. Open your browser at http://127.0.0.1:5173.

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API Endpoints Overview

Method	Endpoint	Description
GET	/api/health	Service health status
GET	/api/projects	List all projects
POST	/api/projects	Create new project (with auto AI archetype detection)
GET	/api/projects/{id}	Get project details
PUT	/api/projects/{id}/plan	Save updated execution plan
PUT	/api/projects/{id}/type	Manually update project archetype
POST	/api/projects/{id}/upload-pdf	Upload and parse project PDF document
GET	/api/projects/{id}/progress	Calculate completion statistics
GET	/api/projects/{id}/tasks	Get sequential task list
POST	/api/projects/{id}/tasks	Create manual sequential task
PUT	/api/tasks/{id}/toggle	Toggle task (strictly enforces prior dependency completion)
PUT	/api/tasks/{id}/reorder	Move task up/down in sequential order
DELETE	/api/tasks/{id}	Delete task and re-sequence orders
POST	/api/projects/{id}/ai/questions	Ask 3–5 clarifying questions
POST	/api/projects/{id}/ai/plan	Generate full 8-section architecture plan
POST	/api/projects/{id}/ai/tasks	Extract ordered sequential tasks from plan
POST	/api/projects/{id}/ai/improvements	Suggest improvements based on progress
POST	/api/projects/{id}/feedback	Record user feedback to reinforce AI context
GET	/api/projects/{id}/notifications	Fetch activity notifications
POST	/api/notifications/{id}/read	Mark notification as read