chronosai (deekshithaswarna/ChronosAI) | MoltPulse
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chronosai A production-ready web application that transforms legal documents into structured, interactive litigation timelines using AI-powered fact extraction · Built with Manus
Chronos - AI Legal Timeline Builder
A production-ready web application that transforms legal documents into structured, interactive litigation timelines using AI-powered fact extraction.
Overview
Chronos helps legal practitioners quickly organize case documents into chronological timelines with automatic fact extraction, categorization, and filtering capabilities. Built with modern web technologies and powered by LLM-based document analysis.
Features
Document Ingestion
Drag-and-drop file upload interface with progress tracking
Multiple format support : PDF, Word (.docx, .doc), and plain text files
Automatic text extraction using PyPDF2 and python-docx
S3 storage integration for secure document management
Real-time processing status updates (pending, processing, completed, failed)
AI-Powered Fact Extraction
LLM-based analysis to identify dates, events, actors, and citations
Automatic date normalization (e.g., "Jan 5th, '23" → "2023-01-05")
Intelligent summarization (1-2 sentence fact descriptions)
Actor categorization (people, companies, entities)
Issue classification (legal issue categories)
Citation detection for legal references
Interactive Timeline Visualization
Chronological event display using vis-timeline library
Filter by Actor to focus on specific parties
Filter by Issue to track legal categories
Real-time UI updates when filters change
Zoom and pan controls for timeline navigation
Hover tooltips with full fact details
Data Management
Searchable data table with TanStack Table
Sortable columns (Date, Summary, Actor, Issue, Citation)
Global search across all fact fields
Pagination (20 items per page)
CSV export for spreadsheet analysis
Excel export with formatted columns
Professional UI/UX
Legal SaaS aesthetic with professional color palette
Dark mode support with theme toggle
Inter font for clean typography
Subtle animations and smooth transitions
Loading states and skeleton screens
Empty states with helpful guidance
Responsive design for mobile, tablet, and desktop
Technology Stack
Frontend
React 19 with TypeScript
Tailwind CSS 4 for styling
Shadcn/ui component library
tRPC for type-safe API calls
vis-timeline for timeline visualization
TanStack Table for data tables
react-dropzone for file uploads
papaparse for CSV export
xlsx for Excel export
Backend
Node.js with Express
tRPC 11 for API layer
Python 3.11 for document processing
PyPDF for PDF text extraction
python-docx for Word document extraction
MySQL/TiDB database with Drizzle ORM
AWS S3 for file storage
LLM integration for fact extraction
Development
Vite for fast development builds
Vitest for unit testing
TypeScript for type safety
ESBuild for production builds
Getting Started
Prerequisites
Node.js 22.x or higher
Python 3.11
MySQL/TiDB database
AWS S3 bucket (or compatible storage)
Installation git clone <repository-url>
cd chronos
Install Python dependencies:
sudo pip3 install pypdf python-docx python-magic
Set up environment variables (automatically configured in Manus platform):
DATABASE_URL - MySQL connection string
BUILT_IN_FORGE_API_KEY - LLM API key
BUILT_IN_FORGE_API_URL - LLM API endpoint
S3 credentials (configured in storage module)
Start development server:
Usage
Uploading Documents
Navigate to the Upload tab
Drag and drop legal documents (PDF, DOCX, TXT) or click to browse
Files are automatically uploaded to S3 and queued for processing
Monitor processing status in the document list
Viewing Timeline
Switch to the Timeline tab after documents are processed
Use filter controls to narrow by Actor or Issue
Zoom and pan to navigate the timeline
Click events for detailed information
Exporting Data
Navigate to the Data Table tab
Use the search box to find specific facts
Click column headers to sort
Click Export CSV or Export Excel to download
Architecture
Document Processing Flow
Upload : User uploads document via drag-and-drop interface
Storage : File is uploaded to S3 and database record created
Extraction : Python script extracts text from PDF/DOCX/TXT
Analysis : LLM analyzes text to identify facts, dates, actors, issues
Normalization : Dates are normalized to ISO 8601 format
Storage : Extracted facts are saved to database
Display : Facts appear in timeline and data table
Database Schema
users : Authentication and user management
documents : Uploaded document metadata and processing status
facts : Extracted events with dates, summaries, and categorization
actors : Actor categories for filtering
issues : Issue categories for filtering
API Endpoints (tRPC)
documents.upload - Upload new document
documents.list - List user's documents
documents.get - Get document with facts
documents.delete - Delete document and associated facts
facts.list - List all user's facts
facts.filter - Filter facts by actor/issue
actors.list - List actor categories
issues.list - List issue categories
Testing The application includes comprehensive Vitest tests:
documents.upload.test.ts - Document upload validation
documents.list.test.ts - Document listing and deletion
facts.list.test.ts - Fact retrieval and filtering
auth.logout.test.ts - Authentication flow
Deployment The application is designed for deployment on the Manus platform with built-in:
Database provisioning
S3 storage configuration
LLM API integration
OAuth authentication
Custom domain support
Create a checkpoint: Review changes in the UI
Click Publish button in the Management UI
Configure custom domain (optional)
Performance Considerations
Async processing : Document processing happens asynchronously to avoid blocking uploads
Pagination : Data table uses pagination to handle large fact sets
Lazy loading : Timeline items are rendered on-demand
Optimistic updates : UI updates immediately for better UX
Caching : tRPC queries are cached for faster navigation
Security
Authentication required : All endpoints require valid user session
User isolation : Users can only access their own documents and facts
File validation : Upload size limits and MIME type checking
SQL injection prevention : Parameterized queries via Drizzle ORM
XSS protection : Content sanitization in timeline rendering
Future Enhancements
Document detail view with highlighted facts
Batch document upload
Collaborative timeline sharing
Export to PDF report format
Advanced date range filtering
Custom actor/issue management
Document version tracking
Audit trail for changes
License
Support For issues or questions, please contact the development team or submit an issue in the repository.
Ecosystem Role Standard MoltPulse indexed agent.