ThinkLM

Chat with Your Documents & Data

Transform your documents into an intelligent, searchable knowledge base powered by advanced AI

Live Demo • Report Bug • Request Feature

Overview

ThinkLM is a powerful AI-powered document analysis and chat platform that transforms your documents, websites, and multimedia content into an intelligent, searchable knowledge base. Built with modern web technologies and advanced AI capabilities, ThinkLM enables users to upload various content types and interact with them through natural language queries.

Key Capabilities

Multi-Source Data Ingestion: Support for PDFs, websites, YouTube videos, and text input
Advanced AI Processing: Powered by OpenAI's GPT-4.1 and text-embedding-3-large models
Semantic Search: Vector-based similarity search using Qdrant vector database
Intelligent Chat Interface: Natural language queries with source citations
Organized Workspace: Notebook-based organization system
Real-time Processing: Lightning-fast document processing and response generation

Features

Core Features

Multiple Data Sources
- PDF document upload and processing
- Website content extraction and analysis
- YouTube video transcription and analysis
- Direct text input and processing
- Support for multiple content formats (PDFs, text files, markdown, web pages, YouTube videos)
AI-Powered Chat Interface
- Natural language question answering
- Source citation and reference tracking
- Context-aware responses
- Multi-document query capabilities
Advanced Search Capabilities
- Semantic vector search
- Cross-document information retrieval
- Relevance scoring and ranking
- Intelligent content matching
Organized Workspace
- Unlimited notebook creation
- Project-based content organization
- User-specific content isolation
- Hierarchical content management
Security & Privacy
- User authentication and authorization
- Encrypted data storage
- Private content isolation
- Secure API endpoints
Usage Tracking & Analytics
- Credit-based usage system (1 credit ≈ 1,000 tokens)
- Real-time usage statistics and monitoring
- Performance metrics and efficiency insights
- Account activity monitoring and logs
- Personalized usage recommendations and tips
- Credit consumption tracking per query

Technical Features

Modern Architecture
- RESTful API design
- Microservices-ready structure
- Scalable database design
- Real-time processing capabilities
Performance Optimizations
- Efficient document chunking
- Optimized vector embeddings
- Caching mechanisms
- Background processing

Screenshots

Landing Page

Modern, responsive landing page featuring the hero section with gradient backgrounds and animated elements

Dashboard

Clean dashboard interface showing user notebooks, recent activity, and quick access to features

Statistics Page

Comprehensive statistics page showing credit usage, data sources, performance metrics, and account activity

Notebook Interface

Interactive notebook interface with chat panel, document sources, and content management tools

Chat Interface

AI-powered chat interface displaying intelligent responses with source citations and references

Document Upload

Multi-source document upload interface supporting PDFs, URLs, YouTube videos, and text input

Authentication

Secure authentication system with login, registration, and password recovery functionality

Architecture

System Architecture

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Frontend      │    │    Backend      │    │   External      │
│   (React)       │◄──►│   (Express)     │◄──►│   Services      │
│                 │    │                 │    │                 │
│ • React Router  │    │ • REST API      │    │ • OpenAI API    │
│ • Zustand Store │    │ • JWT Auth      │    │ • Qdrant DB     │
│ • Tailwind CSS  │    │ • LangChain     │    │ • MongoDB       │
│ • Vite Build    │    │ • File Upload   │    │ • Email Service │
└─────────────────┘    └─────────────────┘    └─────────────────┘

Backend Architecture

src/
├── app.js                 # Main application entry point
├── controller/            # Request handlers
│   ├── chat.controller.js
│   ├── content.controller.js
│   ├── notebook.controller.js
│   └── user.controller.js
├── middleware/            # Custom middleware
│   ├── auth.middleware.js    # JWT authentication
│   └── upload.middleware.js  # File upload handling
├── model/                 # Database models
│   ├── Content.model.js
│   ├── Notebook.model.js
│   └── User.model.js
├── routes/                # API routes
│   ├── chat.routes.js
│   ├── content.routes.js
│   ├── notebook.routes.js
│   └── user.routes.js
├── services/              # Business logic
│   ├── chat.service.js
│   ├── document.processor.service.js
│   ├── embeddings.service.js
│   ├── qdrant.service.js
│   └── web.service.js
└── utils/                 # Utility functions
    └── db.js

Frontend Architecture

src/
├── App.jsx                # Main application component
├── components/            # Reusable components
│   ├── auth/              # Authentication components
│   ├── landing/           # Landing page components
│   ├── layout/            # Layout components
│   ├── notebook/          # Notebook-specific components
│   └── ui/                # UI component library
├── pages/                 # Page components
│   ├── auth/              # Authentication pages
│   │   ├── LoginPage.jsx
│   │   ├── RegisterPage.jsx
│   │   ├── VerifyPage.jsx
│   │   ├── ForgotPasswordPage.jsx
│   │   └── ResetPasswordPage.jsx
│   ├── DashboardPage.jsx
│   ├── NotebookPage.jsx
│   ├── ProfilePage.jsx
│   └── StatsPage.jsx
├── stores/                # State management
│   ├── authStore.js
│   ├── chatStore.js
│   └── notebookStore.js
└── lib/                   # Utility libraries
    └── utils.js

Frontend Routes

/ - Landing page with features and pricing
/login - User login page
/register - User registration page
/verify/:token - Email verification page
/forgot-password - Password reset request page
/reset-password/:token - Password reset page
/app/dashboard - User dashboard (protected)
/app/notebook/:id - Notebook interface (protected)
/app/profile - User profile page (protected)
/app/stats - Usage statistics page (protected)

Application Flow

System Interaction Overview

ThinkLM follows a sophisticated multi-layered architecture where each component plays a crucial role in the document processing and AI-powered chat experience.

┌─────────────────────────────────────────────────────────────────────────────────┐
│                                USER INTERFACE                                   │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐             │
│  │   Landing   │  │   Auth      │  │  Dashboard  │  │  Notebook   │             │
│  │    Page     │  │   Pages     │  │    Page     │  │   Interface │             │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────────┘             │
└─────────────────────────────────────────────────────────────────────────────────┘
                                        │
                                        ▼
┌─────────────────────────────────────────────────────────────────────────────────┐
│                              FRONTEND LAYER                                     │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐             │
│  │   React     │  │   Zustand   │  │   Axios     │  │   Router    │             │
│  │ Components  │  │   Store     │  │   Client    │  │   Handler   │             │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────────┘             │
└─────────────────────────────────────────────────────────────────────────────────┘
                                        │
                                        ▼
┌─────────────────────────────────────────────────────────────────────────────────┐
│                              API GATEWAY                                        │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐             │
│  │   Express   │  │   CORS      │  │   JWT       │  │   Multer    │             │
│  │   Server    │  │   Handler   │  │   Auth      │  │   Upload    │             │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────────┘             │
└─────────────────────────────────────────────────────────────────────────────────┘
                                        │
                                        ▼
┌─────────────────────────────────────────────────────────────────────────────────┐
│                            BUSINESS LOGIC LAYER                                 │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐             │
│  │   User      │  │  Notebook   │  │  Content    │  │    Chat     │             │
│  │ Controller  │  │ Controller  │  │ Controller  │  │ Controller  │             │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────────┘             │
└─────────────────────────────────────────────────────────────────────────────────┘
                                        │
                                        ▼
┌─────────────────────────────────────────────────────────────────────────────────┐
│                              SERVICE LAYER                                      │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐             │
│  │ Document    │  │ Embeddings  │  │   Qdrant    │  │    Web      │             │
│  │ Processor   │  │  Service    │  │  Service    │  │  Service    │             │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────────┘             │
└─────────────────────────────────────────────────────────────────────────────────┘
                                        │
                                        ▼
┌─────────────────────────────────────────────────────────────────────────────────┐
│                              DATA LAYER                                         │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐             │
│  │   MongoDB   │  │   Qdrant    │  │   OpenAI    │  │   Email     │             │
│  │  Database   │  │   Vector    │  │    API      │  │  Service    │             │
│  │             │  │   Database  │  │             │  │             │             │
│  └─────────────┘  └─────────────┘  └─────────────┘  └─────────────┘             │
└─────────────────────────────────────────────────────────────────────────────────┘

Detailed Application Flow

1. User Authentication Flow

User Registration/Login
         │
         ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Frontend      │───▶│   Backend       │───▶│   MongoDB       │
│   Auth Form     │    │   Auth Route    │    │   User Model    │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   JWT Token     │◀───│   JWT Sign      │◀───│   User Created  │
│   Storage       │    │   & Hash        │    │   & Verified    │
└─────────────────┘    └─────────────────┘    └─────────────────┘

2. Document Upload & Processing Flow

Document Upload
         │
         ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Frontend      │───▶│   Backend       │───▶│   File Storage  │
│   Upload UI     │    │   Multer        │    │   (Local/Cloud) │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Progress      │◀───│   Document      │───▶│   Text          │
│   Indicator     │    │   Processor     │    │   Extraction    │
└─────────────────┘    └─────────────────┘    └─────────────────┘
                                │                       │
                                ▼                       ▼
                       ┌─────────────────┐    ┌─────────────────┐
                       │   Text          │───▶│   OpenAI        │
                       │   Chunking      │    │   Embeddings    │
                       └─────────────────┘    └─────────────────┘
                                │                       │
                                ▼                       ▼
                       ┌─────────────────┐    ┌─────────────────┐
                       │   Vector        │◀───│   Embeddings    │
                       │   Storage       │    │   Generation    │
                       │   (Qdrant)      │    │                 │
                       └─────────────────┘    └─────────────────┘

3. Chat Query Processing Flow

User Query
         │
         ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Frontend      │───▶│   Backend       │───▶│   Qdrant        │
│   Chat Input    │    │   Chat Route    │    │   Vector Search │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Loading       │◀───│   Similarity    │───▶│   Relevant      │
│   State         │    │   Search        │    │   Documents     │
└─────────────────┘    └─────────────────┘    └─────────────────┘
                                │                       │
                                ▼                       ▼
                       ┌─────────────────┐    ┌─────────────────┐
                       │   Context       │───▶│   OpenAI        │
                       │   Assembly      │    │   GPT-4.1       │
                       └─────────────────┘    └─────────────────┘
                                │                       │
                                ▼                       ▼
                       ┌─────────────────┐    ┌─────────────────┐
                       │   AI Response   │◀───│   Response      │
                       │   with Sources  │    │   Generation    │
                       └─────────────────┘    └─────────────────┘

4. Multi-Source Content Integration Flow

Content Sources
         │
         ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   PDF Files     │    │   Web URLs      │    │   YouTube       │
│   Upload        │    │   Scraping      │    │   Videos        │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   PDF-Parse     │    │   Cheerio       │    │   YouTube       │
│   Processing    │    │   Web Scraping  │    │   Transcript    │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         ▼                       ▼                       ▼
                       ┌─────────────────┐
                       │   Unified       │
                       │   Text          │
                       │   Processing    │
                       └─────────────────┘
                                │
                                ▼
                       ┌─────────────────┐
                       │   Vector        │
                       │   Embeddings    │
                       │   & Storage     │
                       └─────────────────┘

5. Credit System & Usage Tracking Flow

User Action
         │
         ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Frontend      │───▶│   Backend       │───▶│   Credit        │
│   Action        │    │   Service       │    │   Calculation   │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Usage         │◀───│   Token         │───▶│   MongoDB       │
│   Update        │    │   Estimation    │    │   User Stats    │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Real-time     │    │   Usage         │    │   Analytics     │
│   Statistics    │    │   Tracking      │    │   & Reports     │
└─────────────────┘    └─────────────────┘    └─────────────────┘

Component Interaction Details

Frontend to Backend Communication

Authentication Flow
- User submits login/register form
- Frontend sends credentials via Axios
- Backend validates and returns JWT token
- Frontend stores token in Zustand store
- All subsequent requests include JWT in headers
Document Upload Flow
- User selects file via React Dropzone
- Frontend sends multipart form data via Axios
- Backend processes file with Multer middleware
- Real-time progress updates via WebSocket (if implemented)
Chat Interaction Flow
- User types query in chat interface
- Frontend sends query with selected content IDs
- Backend processes query through LangChain
- Response streamed back to frontend
- Chat history stored in Zustand store

Backend Service Interactions

Document Processing Pipeline

File Upload → Text Extraction → Chunking → Embedding → Vector Storage

Query Processing Pipeline

User Query → Vector Search → Context Retrieval → AI Generation → Response

Database Operations
- MongoDB: User data, notebooks, content metadata
- Qdrant: Vector embeddings for semantic search
- File System: Uploaded documents storage

External Service Integration

OpenAI API Integration
- Embeddings: text-embedding-3-large for vector generation
- Chat: GPT-4.1 for response generation
- Rate Limiting: Implemented to manage API costs
Email Service Integration
- Nodemailer: User verification and password reset
- SMTP Configuration: Mailtrap for development
Vector Database Integration
- Qdrant: High-performance vector similarity search
- Collection Management: Per-content collections for isolation

Error Handling & Recovery

Error Occurrence
         │
         ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Frontend      │───▶│   Backend       │───▶│   Error         │
│   Error         │    │   Error         │    │   Logging       │
│   Boundary      │    │   Middleware    │    │   & Monitoring  │
└─────────────────┘    └─────────────────┘    └─────────────────┘
         │                       │                       │
         ▼                       ▼                       ▼
┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   User          │    │   Graceful      │    │   Error         │
│   Notification  │    │   Degradation   │    │   Recovery      │
└─────────────────┘    └─────────────────┘    └─────────────────┘

Performance Optimization Flow

Caching Strategy
- Frontend: Zustand store for state management
- Backend: Response caching for frequent queries
- Database: Indexed queries for fast retrieval
Lazy Loading
- Component-based code splitting
- Dynamic imports for heavy components
- Progressive image loading
Background Processing
- Document processing in background
- Vector embedding generation
- Email sending queue

This comprehensive flow ensures that ThinkLM provides a seamless, efficient, and scalable document analysis and chat experience.

Technology Stack

Backend Technologies

Technology	Version	Purpose
Node.js	18+	Runtime environment
Express.js	5.1.0	Web framework
MongoDB	Latest	Primary database
Mongoose	8.17.2	ODM for MongoDB
LangChain	0.3.31	AI/ML framework
OpenAI	Latest	AI model integration
Qdrant	Latest	Vector database
JWT	9.0.2	Authentication
Multer	2.0.2	File upload handling
Cheerio	1.1.2	Web scraping and HTML parsing
PDF-Parse	1.1.1	PDF document processing
YouTube-Transcript	1.2.1	YouTube video transcription
YouTubei.js	15.0.1	YouTube API integration
Nodemailer	7.0.5	Email services
Bcryptjs	3.0.2	Password hashing
Cookie Parser	1.4.7	Cookie handling
CORS	2.8.5	Cross-origin resource sharing
Dotenv	17.2.1	Environment variable management
Nodemon	3.1.10	Development server auto-restart
LangChain Community	0.3.53	Community integrations
LangChain Core	0.3.72	Core LangChain functionality
LangChain OpenAI	0.6.9	OpenAI integration for LangChain
LangChain Qdrant	0.1.3	Qdrant integration for LangChain
LangChain Text Splitters	0.1.0	Text chunking utilities
LangChain	0.3.31	Main LangChain framework
Express	5.1.0	Web application framework
MongoDB	Latest	NoSQL database
Qdrant	Latest	Vector database for embeddings
OpenAI	Latest	AI model integration
JWT	9.0.2	JSON Web Token authentication
Multer	2.0.2	File upload middleware
Cheerio	1.1.2	HTML parsing and web scraping
PDF-Parse	1.1.1	PDF document processing
YouTube-Transcript	1.2.1	YouTube video transcription

Frontend Technologies

Technology	Version	Purpose
React	19.1.1	UI framework
Vite	7.1.2	Build tool
Tailwind CSS	4.1.12	Styling framework
React Router	7.8.2	Client-side routing
Zustand	5.0.8	State management
Axios	1.11.0	HTTP client
Radix UI	Latest	Component primitives
Lucide React	0.541.0	Icon library
React Hook Form	7.62.0	Form handling
React Dropzone	14.3.8	File upload UI
Sonner	2.0.7	Toast notifications
Next Themes	0.4.6	Theme management
Zod	4.1.1	Schema validation
Class Variance Authority	0.7.1	Component styling
Tailwind Merge	3.3.1	Tailwind CSS utility merging
CLSX	2.1.1	Conditional class names
Hookform Resolvers	5.2.1	Form validation resolvers
ESLint	9.33.0	Code linting and formatting
Vite Plugin React	5.0.0	React plugin for Vite
TypeScript Types	Latest	TypeScript type definitions
Tailwind Animate CSS	1.3.7	Animation utilities for Tailwind
Globals	16.3.0	Global ESLint configuration
React Hooks ESLint Plugin	5.2.0	ESLint rules for React hooks
React Refresh ESLint Plugin	0.4.20	ESLint rules for React refresh
ESLint JS	9.33.0	ESLint JavaScript configuration
Tailwind CSS Vite	4.1.12	Tailwind CSS integration for Vite
Vite	7.1.2	Build tool and development server
React	19.1.1	UI framework
React DOM	19.1.1	React DOM rendering
React Router DOM	7.8.2	Client-side routing

External Services

OpenAI API: GPT-4.1 for chat, text-embedding-3-large for embeddings
Qdrant: Vector database for semantic search
MongoDB Atlas: Cloud database hosting
Email Service: Nodemailer with SMTP configuration

Credit System

ThinkLM uses a credit-based system to manage usage and costs:

1 Credit ≈ 1,000 tokens processed
Document upload: 2-10 credits (depending on size)
Chat query: 1-3 credits (depending on complexity)
Unused credits roll over to the next month
Real-time tracking of credit consumption
Usage analytics and efficiency recommendations

Prerequisites

Before running ThinkLM, ensure you have the following installed:

Node.js (v18.0.0 or higher)
npm (v8.0.0 or higher) or yarn
MongoDB (local installation or MongoDB Atlas account)
Git (for cloning the repository)

Optional Prerequisites

Docker (for containerized deployment)
Docker Compose (for multi-service orchestration)

Installation

1. Clone the Repository

git clone https://github.com/milindkusahu/ThinkLM.git
cd ThinkLM

2. Backend Setup

# Navigate to backend directory
cd backend

# Install dependencies
npm install

# Create environment file
cp .env.example .env

# Edit environment variables (see Environment Variables section)
nano .env

3. Frontend Setup

# Navigate to frontend directory (from project root)
cd frontend

# Install dependencies
npm install

# Create environment file
cp .env.example .env

# Edit environment variables
nano .env

4. Database Setup

Option A: Local MongoDB

# Install MongoDB locally
# macOS (using Homebrew)
brew install mongodb-community

# Ubuntu/Debian
sudo apt-get install mongodb

# Start MongoDB service
sudo systemctl start mongod

Option B: MongoDB Atlas (Recommended)

Create a free account at MongoDB Atlas
Create a new cluster
Get your connection string
Add the connection string to your .env file

5. Vector Database Setup

Using Docker (Recommended)

# From the backend directory
docker-compose up -d qdrant

Manual Installation

# Install Qdrant locally
# Follow instructions at: https://qdrant.tech/documentation/quick-start/

6. Start the Application

Development Mode

# Terminal 1: Start backend
cd backend
npm run dev

# Terminal 2: Start frontend
cd frontend
npm run dev

Production Mode

# Build frontend
cd frontend
npm run build

# Start backend
cd backend
npm start

The application will be available at:

Frontend: http://localhost:5173
Backend API: http://localhost:3000

Environment Variables

Backend Environment Variables

Create a .env file in the backend directory with the following variables:

# Server Configuration
PORT=3000
NODE_ENV=development
FRONTEND_URL=http://localhost:5173

# Database Configuration
MONGO_URI=mongodb://localhost:27017/thinklm
# For MongoDB Atlas: mongodb+srv://username:password@cluster.mongodb.net/thinklm

# JWT Configuration
JWT_SECRET=your-super-secret-jwt-key-here
JWT_EXPIRY=7d

# OpenAI Configuration
OPENAI_API_KEY=sk-your-openai-api-key-here

# Qdrant Configuration
QDRANT_HOST=localhost
QDRANT_PORT=6333
QDRANT_API_KEY=your-qdrant-api-key-optional

# Email Configuration (for user verification)
MAILTRAP_HOST=smtp.mailtrap.io
MAILTRAP_PORT=2525
MAILTRAP_USERNAME=your-mailtrap-username
MAILTRAP_PASSWORD=your-mailtrap-password
MAILTRAP_SENDEREMAIL=noreply@thinklm.com

# Credit System Configuration
CHARACTERS_PER_TOKEN=4
TOKENS_PER_CREDIT=1000

Frontend Environment Variables

Create a .env file in the frontend directory:

# API Configuration
VITE_API_URL=http://localhost:3000/api/v1

# Application Configuration
VITE_APP_NAME=ThinkLM
VITE_APP_VERSION=1.0.0

Environment Variable Descriptions

Variable	Description	Required	Default
`PORT`	Backend server port	No	3000
`MONGO_URI`	MongoDB connection string	Yes	-
`JWT_SECRET`	Secret key for JWT tokens	Yes	-
`OPENAI_API_KEY`	OpenAI API key for AI features	Yes	-
`QDRANT_HOST`	Qdrant vector database host	No	localhost
`QDRANT_PORT`	Qdrant vector database port	No	6333
`MAILTRAP_HOST`	SMTP server host for emails	Yes	-
`MAILTRAP_USERNAME`	SMTP username	Yes	-
`MAILTRAP_PASSWORD`	SMTP password	Yes	-
`CHARACTERS_PER_TOKEN`	Characters per token estimate	No	4
`TOKENS_PER_CREDIT`	Tokens per credit conversion	No	1000

Usage

Getting Started

Create an Account
- Visit the application URL
- Click "Get Started Free"
- Complete the registration process
- Verify your email address
Create Your First Notebook
- Log in to your dashboard
- Click "Create New Notebook"
- Give your notebook a name and description
- Click "Create Notebook"
Add Content
- Open your notebook
- Click "Add Content"
- Choose your content type:
  - Upload PDF: Drag and drop or select PDF files
  - Add Website: Enter a URL to extract content
  - YouTube Video: Paste a YouTube URL for transcription
  - Text Input: Paste or type text directly
Chat with Your Content
- Wait for content processing to complete
- Use the chat interface to ask questions
- Get intelligent answers with source citations
Monitor Your Usage
- Visit the Statistics page to track your usage
- Monitor credit consumption and data source limits
- View performance metrics and get usage insights

Advanced Features

Multi-Source Queries

Select multiple content sources for comprehensive answers
Cross-reference information across different documents
Get aggregated insights from multiple sources

Content Organization

Create multiple notebooks for different projects
Organize content by topic, subject, or project
Manage content permissions and sharing

Export and Sharing

Export chat conversations
Share notebooks with team members
Generate reports from your content

Usage Analytics

Track credit consumption in real-time
Monitor data source usage and limits
View performance metrics and efficiency scores
Get personalized usage recommendations
Access detailed account activity logs

API Documentation

Authentication

All API endpoints (except registration and login) require authentication via JWT tokens.

# Login to get token
curl -X POST http://localhost:3000/api/v1/users/login \
  -H "Content-Type: application/json" \
  -d '{"email": "user@example.com", "password": "password"}'

# Use token in subsequent requests
curl -X GET http://localhost:3000/api/v1/notebooks \
  -H "Authorization: Bearer YOUR_JWT_TOKEN"

Core Endpoints

User Management

POST /api/v1/users/register - User registration
GET /api/v1/users/verify/:token - Verify user email
POST /api/v1/users/login - User login
GET /api/v1/users/logout - User logout
GET /api/v1/users/profile - Get user profile
PUT /api/v1/users/profile - Update user profile
GET /api/v1/users/stats - Get user statistics
POST /api/v1/users/forgot-password - Request password reset
POST /api/v1/users/reset-password/:token - Reset password with token
POST /api/v1/users/change-password - Change password (authenticated)
DELETE /api/v1/users/delete-account - Delete user account

Notebook Management

GET /api/v1/notebooks - Get user notebooks
POST /api/v1/notebooks - Create new notebook
GET /api/v1/notebooks/:id - Get specific notebook
PUT /api/v1/notebooks/:id - Update notebook
DELETE /api/v1/notebooks/:id - Delete notebook

Content Management

POST /api/v1/content/upload - Upload PDF file
POST /api/v1/content/text - Add text content
POST /api/v1/content/url - Add website content from URL
POST /api/v1/content/youtube - Add YouTube video content
GET /api/v1/content/:id - Get specific content details
PUT /api/v1/content/:id - Update content (title only)
DELETE /api/v1/content/:id - Delete content

Chat Interface

POST /api/v1/chat/query - Send chat query

System Health

GET /api/health - API health check

Response Format

All API responses follow a consistent format:

{
  "success": true,
  "message": "Operation completed successfully",
  "data": {
    // Response data here
  }
}

Error Handling

Error responses include detailed information:

{
  "success": false,
  "message": "Error description",
  "error": {
    "code": "ERROR_CODE",
    "details": "Additional error details"
  }
}

Contributing

We welcome contributions to ThinkLM! Please follow these guidelines:

Development Setup

Fork the repository
Create a feature branch: git checkout -b feature/amazing-feature
Make your changes
Add tests for new functionality
Ensure all tests pass: npm test
Commit your changes: git commit -m 'Add amazing feature'
Push to the branch: git push origin feature/amazing-feature
Open a Pull Request

Code Style

Follow ESLint configuration
Use Prettier for code formatting
Write meaningful commit messages
Add JSDoc comments for functions
Follow React best practices

Pull Request Process

Update documentation for new features
Add or update tests as needed
Ensure the build passes
Request review from maintainers
Address any feedback promptly

License

This project is licensed under the ISC License - see the LICENSE file for details.

Contact

Milind Kumar Sahu - @milindkusahu

Project Link: https://github.com/milindkusahu/ThinkLM

Built with ❤️ using modern web technologies

Transform your documents into intelligent conversations

Name		Name	Last commit message	Last commit date
Latest commit History 41 Commits
.github/workflows		.github/workflows
client		client
images		images
server		server
.gitignore		.gitignore
README.md		README.md
commands.md		commands.md
docker-compose.yml		docker-compose.yml

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ThinkLM

Table of Contents

Overview

Key Capabilities

Features

Core Features

Technical Features

Screenshots

Landing Page

Dashboard

Statistics Page

Notebook Interface

Chat Interface

Document Upload

Authentication

Architecture

System Architecture

Backend Architecture

Frontend Architecture

Frontend Routes

Application Flow

System Interaction Overview

Detailed Application Flow

1. User Authentication Flow

2. Document Upload & Processing Flow

3. Chat Query Processing Flow

4. Multi-Source Content Integration Flow

5. Credit System & Usage Tracking Flow

Component Interaction Details

Frontend to Backend Communication

Backend Service Interactions

External Service Integration

Error Handling & Recovery

Performance Optimization Flow

Technology Stack

Backend Technologies

Frontend Technologies

External Services

Credit System

Prerequisites

Optional Prerequisites

Installation

1. Clone the Repository

2. Backend Setup

3. Frontend Setup

4. Database Setup

Option A: Local MongoDB

Option B: MongoDB Atlas (Recommended)

5. Vector Database Setup

Using Docker (Recommended)

Manual Installation

6. Start the Application

Development Mode

Production Mode

Environment Variables

Backend Environment Variables

Frontend Environment Variables

Environment Variable Descriptions

Usage

Getting Started

Advanced Features

Multi-Source Queries

Content Organization

Export and Sharing

Usage Analytics

API Documentation

Authentication

Core Endpoints

User Management

Notebook Management

Content Management

Chat Interface

System Health

Response Format

Error Handling

Packages