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https://github.com/techycsr/ai-powered-document-insight-tool

AI-powered document analysis platform specializing in resume processing.
https://github.com/techycsr/ai-powered-document-insight-tool

document-analysis gemmini resume-analysis typescript-application

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AI-powered document analysis platform specializing in resume processing.

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README 

          
# AI-Powered Document Insight Tool



> **Professional-grade resume analysis platform powered by advanced AI models with intelligent document type detection and comprehensive insight generation.**



[![Live Demo](https://img.shields.io/badge/🌐_Live_Demo-summary.techycsr.me-blue?style=for-the-badge)](https://summary.techycsr.dev)

[![API Status](https://img.shields.io/badge/🔗_API-summaryapi.techycsr.me-green?style=for-the-badge)](https://summaryapi.techycsr.dev/api/v1/health)



## 🎯 **Project Overview**



An enterprise-grade document analysis platform specializing in resume processing with AI-powered insights. The system automatically detects document types and provides structured analysis optimized for professional recruitment and career development workflows.



### **🔑 Key Specializations**

- **Resume Analysis**: Specialized parsing for professional documents with structured output

- **Document Type Detection**: Intelligent classification of uploaded documents

- **Multi-AI Integration**: Dual AI provider setup with intelligent fallback mechanisms

- **Real-time Processing**: Asynchronous document processing with live progress tracking



---



## 🏗️ **System Architecture**



```mermaid

graph TB

    subgraph "Frontend Layer (Vercel)"

        A[React 18 + TypeScript]

        A1[TailwindCSS Styling]

        A2[Clerk Authentication]

        A3[Mobile Detection]

        A4[404 Error Handling]

    end

    

    subgraph "API Gateway (Vercel Serverless)"

        B[FastAPI Backend]

        B1[JWT Validation]

        B2[File Upload Handler]

        B3[Error Management]

        B4[Health Monitoring]

    end

    

    subgraph "Document Processing Engine"

        C[PDFPlumber Extractor]

        C1[Document Type Detector]

        C2[Content Sanitization]

        C3[Text Preprocessing]

    end

    

    subgraph "AI Analysis Layer"

        D[Sarvam AI Primary]

        E[Gemini AI Secondary]

        F[Intelligent Fallback]

        G[Response Structuring]

    end

    

    subgraph "Data Layer"

        H[MongoDB Atlas]

        H1[User Document Store]

        H2[Binary PDF Storage]

        H3[Analysis History]

    end

    

    subgraph "Authentication & Security"

        I[Clerk Identity Provider]

        I1[JWT Token Management]

        I2[User Session Handling]

    end

    

    A -->|HTTPS API Calls| B

    B -->|Document Upload| C

    C -->|Extracted Text| D

    D -->|Fallback on Error| E

    E -->|Final Fallback| F

    D -->|Success Response| G

    E -->|Success Response| G

    F -->|Keyword Analysis| G

    G -->|Structured Data| H

    B -->|Auth Validation| I

    H -->|User Data| B

    B -->|JSON Response| A

```



---



## 🛠️ **Technology Stack**



### **Backend Infrastructure**

| Component | Technology | Version | Purpose |

|-----------|------------|---------|---------|

| **Framework** | FastAPI | 0.104.1 | High-performance async API |

| **Language** | Python | 3.12+ | Core backend logic |

| **Database** | MongoDB Atlas | 7.0 | Document storage & history |

| **PDF Processing** | PDFPlumber | 0.9.0 | Text extraction from PDFs |

| **HTTP Client** | httpx | 0.24.0 | Async AI API communications |

| **Authentication** | PyJWT | 2.8.0 | JWT token validation |

| **Deployment** | Vercel Serverless | - | Auto-scaling serverless functions |



### **Frontend Architecture**

| Component | Technology | Version | Purpose |

|-----------|------------|---------|---------|

| **Framework** | React | 18.2.0 | Component-based UI framework |

| **Language** | TypeScript | 5.0.2 | Type-safe development |

| **Build Tool** | Vite | 5.0+ | Fast development & bundling |

| **Styling** | TailwindCSS | 3.3.0 | Utility-first CSS framework |

| **Authentication** | Clerk React | 4.29.0 | User authentication SDK |

| **HTTP Client** | Axios | 1.6.0 | API communication |

| **Icons** | Lucide React | 0.263.0 | Consistent iconography |

| **Routing** | React Router | 6.8.0 | Client-side navigation |



---



---



## 🚀 **Local Development Setup**



### **Prerequisites**

- **Node.js** 18+ and npm

- **Python** 3.9+

- **Git** for version control

- **MongoDB Atlas** account (free tier available)

- **Clerk** account for authentication

- **AI API Keys** (optional - fallback available)



### **1. Clone Repository**

```bash

git clone https://github.com/TechyCSR/AI-Powered-Document-Insight-Tool.git

cd AI-Powered-Document-Insight-Tool

```



### **2. Backend Setup**

```bash

cd backend



# Create virtual environment

python -m venv venv



# Activate virtual environment

# On Windows:

venv\Scripts\activate

# On macOS/Linux:

source venv/bin/activate



# Install dependencies

pip install -r requirements.txt



# Setup environment variables

cp env.example .env

```



**Edit `backend/.env` with your configuration:**

```env

# MongoDB Configuration

MONGODB_URI=mongodb+srv://username:password@cluster.mongodb.net/document_insights?retryWrites=true&w=majority



# Clerk Configuration

CLERK_SECRET_KEY=sk_test_your_clerk_secret_key_here



# AI API Keys (Optional - fallback available)

SARVAM_API_KEY=your_sarvam_api_key_here

GEMINI_API_KEY=your_gemini_api_key_here



# Application Settings

ENVIRONMENT=development

DEBUG=True

ALLOWED_ORIGINS=http://localhost:5173,http://localhost:3000

```



### **3. Frontend Setup**

```bash

cd frontend



# Install dependencies

npm install



# Setup environment variables

cp env.example .env.local

```



**Edit `frontend/.env.local` with your configuration:**

```env

VITE_CLERK_PUBLISHABLE_KEY=pk_test_your_clerk_publishable_key_here

VITE_API_URL=http://localhost:8000

```



### **4. Start Development Servers**



**Terminal 1 - Backend API:**

```bash

cd backend

# Ensure virtual environment is activated

uvicorn app.main:app --reload --host 0.0.0.0 --port 8000

```



**Terminal 2 - Frontend Application:**

```bash

cd frontend

npm run dev

```



### **5. Access Application**

- **Frontend**: [`http://localhost:5173`](http://localhost:5173)

- **Backend API**: [`http://localhost:8000`](http://localhost:8000)

- **API Documentation**: [`http://localhost:8000/docs`](http://localhost:8000/docs)

- **Health Check**: [`http://localhost:8000/api/v1/health`](http://localhost:8000/api/v1/health)



### **6. Development Workflow**

1. **Backend Changes**: Auto-reload enabled with `--reload` flag

2. **Frontend Changes**: Hot Module Replacement (HMR) active

3. **Database**: MongoDB Atlas automatically syncs

4. **Authentication**: Clerk handles dev/prod environments automatically



### **📝 Quick Setup Checklist**

- [ ] Python 3.9+ installed

- [ ] Node.js 18+ installed

- [ ] MongoDB Atlas account created

- [ ] Clerk account setup with project created

- [ ] Environment variables configured

- [ ] Dependencies installed

- [ ] Both servers running

- [ ] Application accessible at localhost:5173



---



## 🌐 **Production Deployment**



### **Production URLs**

- **Frontend Application**: [`https://summary.techycsr.dev`](https://summary.techycsr.dev)

- **Backend API**: [`https://summaryapi.techycsr.me`](https://summaryapi.techycsr.me)

- **Health Endpoint**: [`https://summaryapi.techycsr.dev/api/v1/health`](https://summaryapi.techycsr.dev/api/v1/health)



### **API Endpoints**



#### **Core Endpoints**

```http

GET    /api/v1/health                     # System health check

POST   /api/v1/upload-resume              # Document upload & analysis

GET    /api/v1/insights                   # User document history

GET    /api/v1/document/{id}/preview      # PDF preview (authenticated)

```



#### **Health Check Response**

```json

{

  "status": "healthy",

  "timestamp": "2025-08-30T13:27:21.331972",

  "environment": "production",

  "database": {

    "connected": true,

    "status": "connected",

    "error": null,

    "insights_count": 42

  }

}

```



#### **Upload Resume Request**

```http

POST /api/v1/upload-resume

Content-Type: multipart/form-data

Authorization: Bearer {jwt_token}



file: {pdf_file}

provider: "sarvam" | "gemini"

```



#### **Upload Response (Resume)**

```json

{

  "summary": "**👤 Name:** John Doe\n**📧 Contact:** john.doe@email.com, +1-555-0123\n**💼 Professional Summary:** Experienced software engineer with 5+ years...",

  "provider": "sarvam",

  "is_fallback": false,

  "filename": "resume.pdf",

  "upload_date": "2025-08-30T13:27:21.331972",

  "document_id": "66d1b2c3d4e5f6789abcdef0"

}

```



---



## 🧠 **AI Analysis Features**



### **Resume Analysis Format**

```

👤 Name: [Extracted full name]

📧 Contact: [Phone, Email, Location]

💼 Professional Summary: [Key qualifications highlights]

🎯 Core Skills: [Technical and soft skills]

💪 Experience Highlights:

  • [Most relevant role with quantified achievements]

  • [Second important position with metrics]

  • [Third significant role with impact data]

🎓 Education: [Degrees, institutions, GPA if available]

🏆 Notable Achievements:

  • [Top accomplishment with quantified results]

  • [Second significant achievement]

  • [Third notable accomplishment]

📊 Career Insights:

  • Years of Experience: [Calculated total]

  • Industry Focus: [Primary domain]

  • Career Level: [Entry/Mid/Senior/Executive]

```



### **General Document Analysis Format**

```

📄 Document Type: [Auto-detected type]

📝 Document Summary: [Comprehensive overview]

🔍 Key Insights: [Major findings and observations]

📊 Main Topics: [Primary and secondary topics]

💡 Critical Information: [Important facts and recommendations]

🎯 Target Audience: [Intended readers]

📈 Key Takeaways: [Actionable insights]

```



### **Document Type Detection**

The system automatically detects document types:

- **Resume/CV**: Professional experience documents

- **Research Paper**: Academic and scientific documents

- **Proposal**: Project and business proposals

- **Legal Document**: Contracts and agreements

- **Report**: Analysis and findings documents

- **General Document**: Other document types



---



## 🚀 **Core Functionality**



### **1. Document Upload & Processing**

- **File Validation**: PDF-only, 10MB size limit

- **Text Extraction**: Advanced PDFPlumber integration

- **Content Sanitization**: Clean text preprocessing

- **Progress Tracking**: Real-time upload status



### **2. AI-Powered Analysis**

- **Document Type Detection**: Intelligent classification

- **Dual AI Integration**: Primary (Sarvam) + Secondary (Gemini)

- **Intelligent Fallback**: Keyword frequency analysis

- **Structured Output**: Formatted, actionable insights



### **3. User Management**

- **Secure Authentication**: Clerk-based JWT validation

- **Personal History**: Complete analysis tracking

- **PDF Preview**: Authenticated document viewing

- **Session Management**: Persistent user sessions



### **4. Enterprise Features**

- **Responsive Design**: Mobile detection with desktop optimization

- **Error Handling**: Professional 404 pages and error management

- **Health Monitoring**: System status tracking

- **Performance Optimization**: Async processing and caching



---



## 📱 **User Experience Design**



### **Responsive Behavior**

- **Desktop Optimized**: Full-featured dashboard experience

- **Mobile Detection**: Automatic redirection to mobile-optimized messaging

- **Tablet Support**: Warning banners for limited mobile functionality

- **Progressive Enhancement**: Graceful degradation across devices



### **Interface Highlights**

- **Modern Dashboard**: Clean, professional layout

- **Drag-and-Drop Upload**: Intuitive file handling

- **Real-time Feedback**: Progress indicators and status updates

- **Theme Support**: Dark/light mode toggle

- **Error Recovery**: User-friendly error messages and recovery options



---



## ⚡ **Performance & Scalability**



### **Backend Optimization**

- **Serverless Architecture**: Auto-scaling Vercel functions

- **Async Processing**: Non-blocking I/O operations

- **Connection Pooling**: Optimized MongoDB connections

- **Error Recovery**: Graceful degradation and reconnection logic



### **Frontend Optimization**

- **Code Splitting**: Dynamic imports for reduced bundle size

- **Lazy Loading**: On-demand component loading

- **Caching Strategy**: Optimized API response caching

- **Bundle Analysis**: Size optimization and tree shaking



### **Database Performance**

- **Indexed Queries**: Optimized user-based data retrieval

- **Document Storage**: Efficient binary PDF storage

- **Connection Management**: Serverless-optimized pooling



---



## 🔒 **Security Implementation**



### **Authentication & Authorization**

- **JWT Validation**: Secure token-based authentication

- **User Isolation**: Strict data access controls

- **Session Management**: Secure session handling

- **API Protection**: Authenticated endpoint access



### **Data Security**

- **File Validation**: Strict PDF-only upload enforcement

- **Size Limits**: 10MB maximum file size

- **Content Sanitization**: Safe text processing

- **Secure Storage**: Encrypted MongoDB Atlas storage



### **Infrastructure Security**

- **HTTPS Enforcement**: SSL/TLS encryption

- **Environment Variables**: Secure configuration management

- **API Rate Limiting**: Protection against abuse

- **Error Handling**: Secure error message disclosure



---



## 📊 **System Status**



```

✅ Backend API: Operational (99.9% uptime)

✅ Frontend App: Deployed & Responsive

✅ Database: MongoDB Atlas Connected (42 documents)

✅ AI Services: Sarvam + Gemini Operational

✅ Authentication: Clerk Integration Active

✅ File Processing: PDF Upload & Analysis Working

✅ Mobile Support: Detection & Redirection Active

✅ Error Handling: 404 Pages & Recovery Implemented

```



---



## 🎯 **Project Highlights**



- **Production-Ready**: Fully deployed and operational system

- **Enterprise-Grade**: Professional UI/UX with comprehensive error handling

- **AI-Specialized**: Optimized for resume analysis with fallback intelligence

- **Scalable Architecture**: Serverless deployment with auto-scaling capabilities

- **Modern Tech Stack**: Latest frameworks and best practices implementation

- **Security-First**: Comprehensive authentication and data protection

- **Performance-Optimized**: Fast loading times and efficient processing



---



*Built with modern web technologies for professional document analysis workflows. Deployed and operational at [summary.techycsr.me](https://summary.techycsr.dev)*

      "filename": "resume.pdf",

      "upload_date": "2025-08-28T14:00:00Z",

      "provider": "sarvam",

      "summary": "Professional summary...",

      "is_fallback": false,

      "file_size": 1234567

    }

  ],

  "total_count": 1

}

```



## 🚀 Deployment



### Prerequisites for Deployment

1. **Vercel Account** - For hosting both frontend and backend

2. **MongoDB Atlas** - Cloud database

3. **Clerk Account** - Authentication service

4. **Domain** (optional) - For custom domain



### Backend Deployment (Vercel)



1. **Connect to Vercel**

```bash

cd backend

npm i -g vercel  # Install Vercel CLI

vercel  # Follow the prompts

```



2. **Set Environment Variables**

Go to your Vercel dashboard and add:

- `MONGODB_URI`

- `CLERK_SECRET_KEY`

- `SARVAM_API_KEY`

- `GEMINI_API_KEY`

- `ENVIRONMENT=production`

- `DEBUG=False`

- `ALLOWED_ORIGINS=https://your-frontend-domain.vercel.app`



### Frontend Deployment (Vercel)



1. **Connect to Vercel**

```bash

cd frontend

vercel  # Follow the prompts

```



2. **Set Environment Variables**

Add to Vercel dashboard:

- `VITE_CLERK_PUBLISHABLE_KEY`

- `VITE_API_BASE_URL=https://your-backend-domain.vercel.app/api/v1`



### Post-Deployment Configuration



1. **Update Clerk Settings**

   - Add your production domains to allowed origins

   - Update redirect URLs



2. **Update API CORS**

   - Add production frontend URL to backend CORS settings



3. **Test the Deployment**

   - Verify authentication flow

   - Test file upload functionality

   - Check AI provider integration



---



## 👨‍💻 **Developer**



**Built with ❤️ by [@TechyCSR](https://techycsr.me)**



*Professional full-stack developer specializing in AI-powered applications and modern web technologies.*



---



*© 2025 TechyCSR • AI-Powered Document Analysis Platform • [summary.techycsr.me](https://summary.techycsr.dev)*