LLM Personal Productivity Platform - Design Specification

1. Project Overview

1.1 Purpose

A personal productivity platform that combines LLM chat capabilities with visual workflow design, enabling users to create, manage, and execute AI-powered automation workflows for personal tasks.

1.2 Core Features

  • LLM Chat Interface: Direct conversation with AI models
  • Workflow Designer: Visual drag-and-drop workflow builder
  • Task Automation: Execute workflows automatically or on-demand
  • Personal Dashboard: Overview of workflows, chat history, and productivity metrics

1.3 Target User

Individual users seeking to enhance personal productivity through AI automation and assistance.

2. Technical Architecture

2.1 Frontend Stack

  • Framework: React 18+ with TypeScript
  • UI Library: Tailwind CSS + Headless UI
  • State Management: Zustand (lightweight, perfect for personal apps)
  • Routing: React Router v6
  • HTTP Client: Axios
  • Workflow Visualization: React Flow
  • Icons: Lucide React
  • Forms: React Hook Form + Zod validation

2.2 Backend Stack

  • Framework: FastAPI (Python)
  • Database: PostgreSQL with SQLAlchemy ORM
  • Authentication: JWT tokens
  • LLM Integration: OpenAI Python SDK
  • Task Queue: Celery with Redis
  • API Documentation: Automatic with FastAPI
  • Environment: Pydantic for settings management

2.3 System Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   React Frontend │    │  FastAPI Backend │    │   OpenAI API    │
│                 │◄──►│                 │◄──►│                 │
│ - Chat UI       │    │ - API Endpoints │    │ - GPT Models    │
│ - Workflow UI   │    │ - Workflow Exec │    │ - Embeddings    │
│ - Dashboard     │    │ - Auth          │    │                 │
└─────────────────┘    └─────────────────┘    └─────────────────┘
                                │
                                ▼
                       ┌─────────────────┐
                       │   PostgreSQL    │
                       │                 │
                       │ - Users         │
                       │ - Workflows     │
                       │ - Chat History  │
                       │ - Executions    │
                       └─────────────────┘

3. Core Components

3.1 Chat Interface

Purpose: Direct interaction with LLM models

Features:

  • Real-time chat with OpenAI GPT models
  • Message history persistence
  • Conversation threads/sessions
  • Message export capabilities
  • Prompt templates library

Components:

  • ChatContainer: Main chat interface
  • MessageList: Chat message display
  • MessageInput: Text input with send functionality
  • ConversationSidebar: Chat history navigation
  • PromptTemplates: Reusable prompt library

3.2 Workflow Designer

Purpose: Visual workflow creation and management

Features:

  • Drag-and-drop node-based editor
  • Pre-built workflow templates
  • Custom node types (LLM, API, Logic, etc.)
  • Workflow validation and testing
  • Version control for workflows

Node Types:

  • LLM Node: Send prompts to OpenAI
  • Input Node: Accept user input
  • Output Node: Display results
  • Logic Node: Conditional branching
  • API Node: External API calls
  • Timer Node: Scheduled execution
  • File Node: File operations

Components:

  • WorkflowCanvas: React Flow workspace
  • NodePalette: Available node types
  • NodeEditor: Configure selected nodes
  • WorkflowControls: Save, run, test actions
  • WorkflowList: Manage saved workflows

3.3 Dashboard

Purpose: Overview and management interface

Features:

  • Workflow execution status
  • Chat statistics and analytics
  • Quick actions panel
  • Recent activity feed
  • Personal productivity metrics

Components:

  • DashboardGrid: Layout container
  • StatsCards: Key metrics display
  • RecentActivity: Activity timeline
  • QuickActions: Common workflow triggers
  • WorkflowStatus: Execution monitoring

4. Data Models

4.1 User Model

class User:
    id: UUID
    email: str
    name: str
    created_at: datetime
    updated_at: datetime
    openai_api_key: str (encrypted)

4.2 Workflow Model

class Workflow:
    id: UUID
    user_id: UUID
    name: str
    description: str
    nodes: List[WorkflowNode]
    edges: List[WorkflowEdge]
    is_active: bool
    created_at: datetime
    updated_at: datetime

4.3 Chat Model

class ChatSession:
    id: UUID
    user_id: UUID
    title: str
    created_at: datetime
    updated_at: datetime

class ChatMessage:
    id: UUID
    session_id: UUID
    role: str  # 'user' | 'assistant'
    content: str
    timestamp: datetime

4.4 Workflow Execution Model

class WorkflowExecution:
    id: UUID
    workflow_id: UUID
    status: str  # 'pending' | 'running' | 'completed' | 'failed'
    input_data: dict
    output_data: dict
    error_message: str
    started_at: datetime
    completed_at: datetime

5. API Endpoints

5.1 Authentication

  • POST /auth/login - User login
  • POST /auth/register - User registration
  • POST /auth/refresh - Refresh token
  • POST /auth/logout - User logout

5.2 Chat API

  • GET /chat/sessions - List chat sessions
  • POST /chat/sessions - Create new session
  • GET /chat/sessions/{id}/messages - Get messages
  • POST /chat/sessions/{id}/messages - Send message
  • DELETE /chat/sessions/{id} - Delete session

5.3 Workflow API

  • GET /workflows - List user workflows
  • POST /workflows - Create workflow
  • GET /workflows/{id} - Get workflow details
  • PUT /workflows/{id} - Update workflow
  • DELETE /workflows/{id} - Delete workflow
  • POST /workflows/{id}/execute - Execute workflow
  • GET /workflows/{id}/executions - Get execution history

5.4 Dashboard API

  • GET /dashboard/stats - Get user statistics
  • GET /dashboard/recent - Recent activity
  • GET /dashboard/executions - Recent executions

6. User Interface Design

6.1 Layout Structure

┌─────────────────────────────────────────────────────────────┐
│                    Header (Navigation)                     │
├─────────────────────────────────────────────────────────────┤
│           │                                                 │
│  Sidebar  │               Main Content Area                 │
│           │                                                 │
│ - Chat    │  ┌─────────────────────────────────────────┐   │
│ - Flows   │  │                                         │   │
│ - Dash    │  │         Dynamic Content                 │   │
│           │  │      (Chat/Workflow/Dashboard)          │   │
│           │  │                                         │   │
│           │  └─────────────────────────────────────────┘   │
└─────────────────────────────────────────────────────────────┘

6.2 Color Scheme

  • Primary: Blue (#3B82F6) - Actions, links
  • Secondary: Gray (#6B7280) - Text, borders
  • Success: Green (#10B981) - Completed states
  • Warning: Amber (#F59E0B) - Pending states
  • Error: Red (#EF4444) - Error states
  • Background: White/Gray-50 - Main areas

6.3 Typography

  • Headers: Inter font, various weights
  • Body: Inter font, regular weight
  • Code: JetBrains Mono, monospace

7. Security Considerations

7.1 Authentication & Authorization

  • JWT-based authentication
  • API key encryption at rest
  • Role-based access (future expansion)
  • Session timeout management

7.2 Data Protection

  • Encrypt sensitive data (API keys)
  • Secure HTTP-only cookies
  • Input validation and sanitization
  • Rate limiting on API endpoints

7.3 API Security

  • CORS configuration
  • Request size limits
  • API key rotation support
  • Audit logging

8. Development Phases

Phase 1: Core Infrastructure (Weeks 1-2)

  • Set up React + TypeScript project
  • FastAPI backend with basic auth
  • Database setup and models
  • Basic chat interface

Phase 2: Chat Functionality (Weeks 3-4)

  • Complete chat interface
  • OpenAI integration
  • Message persistence
  • Conversation management

Phase 3: Workflow Designer (Weeks 5-7)

  • React Flow integration
  • Basic node types
  • Workflow persistence
  • Simple execution engine

Phase 4: Dashboard & Polish (Weeks 8-9)

  • Dashboard implementation
  • UI/UX improvements
  • Testing and bug fixes
  • Documentation

Phase 5: Advanced Features (Weeks 10+)

  • Advanced node types
  • Workflow scheduling
  • Analytics and reporting
  • Performance optimization

9. File Structure

9.1 Frontend Structure

src/
├── components/
│   ├── chat/
│   ├── workflow/
│   ├── dashboard/
│   └── ui/
├── hooks/
├── stores/
├── types/
├── utils/
├── pages/
└── api/

9.2 Backend Structure

app/
├── api/
│   ├── auth/
│   ├── chat/
│   ├── workflow/
│   └── dashboard/
├── models/
├── services/
├── utils/
├── core/
└── tests/

10. Next Steps

  1. Environment Setup: Configure development environment
  2. Repository Setup: Initialize Git repository with proper structure
  3. Basic Authentication: Implement user registration/login
  4. MVP Chat: Build basic chat interface with OpenAI integration
  5. Workflow Foundation: Create basic workflow designer
  6. Iterative Development: Add features incrementally based on usage

11. Success Metrics

  • User Engagement: Daily active usage of chat interface
  • Workflow Adoption: Number of workflows created and executed
  • Task Completion: Successful workflow executions
  • User Satisfaction: Feedback and feature requests
  • Performance: Response times and system reliability

This specification provides a comprehensive foundation for building your LLM personal productivity platform. Each section can be expanded based on specific requirements and user feedback during development.