Fynd AI Feedback System

Development Tasks

Phase 1: Project Setup & Backend Foundation

1. Backend Directory Structure - Create FastAPI backend with proper folder structure (app/, models/, schemas/, routers/, services/, database/)
2. Pydantic Schemas - Define request/response schemas with validation
3. Database Connection - Setup PostgreSQL connection with SQLAlchemy engine and session management
4. API Endpoints - Create RESTful endpoints: POST /api/reviews (submit), GET /api/reviews (fetch all), GET /api/health (health check), GET /api/analytics (dashboard stats)
5. AI Service Integration - Implement server-side LLM calls for sentiment analysis, review summarization, recommended actions, user responses
6. Error Handling - Implement comprehensive error handling and validation
7. CORS Configuration - Setup CORS middleware for frontend communication

Phase 2: Frontend - Landing Page

1. Landing Page Layout - Create hero section with Fynd branding, navigation header with logo, feature highlights section, call-to-action buttons
2. Navigation Component - Header with Fynd logo, links to User Dashboard and Admin Dashboard
3. Hero Section - Gradient background, compelling headline about AI feedback system, description of features, dual CTA buttons (Submit Feedback / Admin Login)
4. Features Section - Showcase key features: AI-powered analysis, Real-time insights, Sentiment detection, Actionable recommendations
5. Kaily Chatbot Integration - Embed Kaily widget on landing page

Phase 3: Frontend - User Dashboard

1. User Dashboard Layout - Clean, user-friendly interface with Fynd branding
2. Star Rating Component - Interactive 5-star rating selector with hover effects
3. Review Form - Text area for review input with character count, validation for empty/long reviews
4. Submit Button - Primary action button with loading states
5. Sentiment Indicator - Visual indicator (emoji/badge) showing detected sentiment
6. Success/Error States - Toast notifications and modal displays for submission results
7. Kaily Chatbot - Embed chatbot for user assistance

Phase 4: Frontend - Admin Dashboard

1. Admin Dashboard Layout - Professional analytics interface with sidebar navigation
2. Analytics Overview Cards - Display total reviews, average rating, sentiment distribution, recent activity
3. Review List Component - Table/card view showing all reviews with rating, review text, sentiment, AI summary, recommended actions, timestamp
4. Auto-Refresh Functionality - Implement polling or WebSocket for live updates (every 30 seconds)
5. Filter Controls - Dropdown filters for rating (1-5) and sentiment (positive/negative/neutral/sarcasm)
6. Search Functionality - Search bar to find reviews by text content
7. Sentiment Visualization - Pie chart showing sentiment distribution
8. Rating Distribution Chart - Bar chart showing rating counts (1-5 stars)
9. Trends Chart - Line chart showing review submissions over time
10. Export Functionality - Button to export data as CSV/JSON

Phase 5: Backend - AI Integration Details

1. Sentiment Analysis Service - Implement NLP-based sentiment detection (positive/negative/neutral/sarcasm)
2. Contextual Response Generator - Generate appropriate user-facing responses based on sentiment
3. Review Summarization - Create concise summaries for admin dashboard
4. Action Recommendations - Generate actionable business recommendations
5. Graceful Fallback - Handle LLM API failures with default responses

Phase 6: API Integration & State Management

1. API Client Setup - Create axios instance with base URL configuration
2. React Query Setup - Implement data fetching and caching with TanStack Query
3. Form State Management - Handle form submissions with proper validation
4. Error Boundary - Implement error boundaries for graceful error handling
5. Loading States - Add skeleton loaders and spinners for all async operations

Phase 7: Deployment Configuration

1. Backend Deployment (Render) - Create render.yaml for FastAPI service, setup environment variables (DATABASE_URL, LLM_API_KEY), configure build and start commands
2. Database Provisioning - Setup PostgreSQL database on Render
3. Frontend Deployment (Vercel/Render) - Configure build settings, setup environment variables (VITE_API_URL), optimize production build
4. Environment Variables - Document all required environment variables
5. Deployment Scripts - Create deployment documentation and scripts

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Technical Stack Summary

Frontend

• React 18 with TypeScript
• TailwindCSS for styling
• React Router for navigation
• Recharts for data visualization
• Axios for API calls

Backend

• FastAPI (Python)
• PostgreSQL database
• Pydantic for validation
• Server-side LLM integration
• CORS middleware

Deployment

• Frontend: Render
• Backend: Render
• Database: PostgreSQL on Render

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API Endpoints Schema

POST /api/reviews

Request:

{
  "rating": 5,
  "review_text": "Great experience!"
}

Response:

{
  "id": 1,
  "rating": 5,
  "review_text": "Great experience!",
  "sentiment": "positive",
  "ai_response": "Thank you for your wonderful feedback! We're thrilled to hear about your positive experience.",
  "ai_summary": "Customer expresses satisfaction with service",
  "recommended_actions": "Continue current service quality, share positive feedback with team",
  "created_at": "2026-01-07T10:30:00Z"
}

GET /api/reviews

Response:

{
  "reviews": [
    {
      "id": 1,
      "rating": 5,
      "review_text": "Great experience!",
      "sentiment": "positive",
      "ai_summary": "Customer expresses satisfaction",
      "recommended_actions": "Maintain service quality",
      "created_at": "2026-01-07T10:30:00Z"
    }
  ],
  "total": 1
}

GET /api/analytics

Response:

{
  "total_reviews": 150,
  "average_rating": 4.2,
  "sentiment_distribution": {
    "positive": 80,
    "neutral": 45,
    "negative": 20,
    "sarcasm": 5
  },
  "rating_distribution": {
    "1": 10,
    "2": 15,
    "3": 25,
    "4": 40,
    "5": 60
  }
}

Environment Variables

Backend (.env)

DATABASE_URL=postgresql://user:password@host:port/dbname
LLM_API_KEY=your_llm_api_key
CORS_ORIGINS=https://fynd-feedback-system.onrender.com

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Live : User : https://fynd-feedback-system.onrender.com

Admin: https://fynd-feedback-system.onrender.com/admin